Unified treatment algorithm for the management of crotaline snakebite in the United States: results of an evidence-informed consensus workshop

PubMed Central

2011-01-01

Background Envenomation by crotaline snakes (rattlesnake, cottonmouth, copperhead) is a complex, potentially lethal condition affecting thousands of people in the United States each year. Treatment of crotaline envenomation is not standardized, and significant variation in practice exists. Methods A geographically diverse panel of experts was convened for the purpose of deriving an evidence-informed unified treatment algorithm. Research staff analyzed the extant medical literature and performed targeted analyses of existing databases to inform specific clinical decisions. A trained external facilitator used modified Delphi and structured consensus methodology to achieve consensus on the final treatment algorithm. Results A unified treatment algorithm was produced and endorsed by all nine expert panel members. This algorithm provides guidance about clinical and laboratory observations, indications for and dosing of antivenom, adjunctive therapies, post-stabilization care, and management of complications from envenomation and therapy. Conclusions Clinical manifestations and ideal treatment of crotaline snakebite differ greatly, and can result in severe complications. Using a modified Delphi method, we provide evidence-informed treatment guidelines in an attempt to reduce variation in care and possibly improve clinical outcomes. PMID:21291549

Use of electronic data and existing screening tools to identify clinically significant obstructive sleep apnea.

PubMed

Severson, Carl A; Pendharkar, Sachin R; Ronksley, Paul E; Tsai, Willis H

2015-01-01

To assess the ability of electronic health data and existing screening tools to identify clinically significant obstructive sleep apnea (OSA), as defined by symptomatic or severe OSA. The present retrospective cohort study of 1041 patients referred for sleep diagnostic testing was undertaken at a tertiary sleep centre in Calgary, Alberta. A diagnosis of clinically significant OSA or an alternative sleep diagnosis was assigned to each patient through blinded independent chart review by two sleep physicians. Predictive variables were identified from online questionnaire data, and diagnostic algorithms were developed. The performance of electronically derived algorithms for identifying patients with clinically significant OSA was determined. Diagnostic performance of these algorithms was compared with versions of the STOP-Bang questionnaire and adjusted neck circumference score (ANC) derived from electronic data. Electronic questionnaire data were highly sensitive (>95%) at identifying clinically significant OSA, but not specific. Sleep diagnostic testing-determined respiratory disturbance index was very specific (specificity ≥95%) for clinically relevant disease, but not sensitive (<35%). Derived algorithms had similar accuracy to the STOP-Bang or ANC, but required fewer questions and calculations. These data suggest that a two-step process using a small number of clinical variables (maximizing sensitivity) and objective diagnostic testing (maximizing specificity) is required to identify clinically significant OSA. When used in an online setting, simple algorithms can identify clinically relevant OSA with similar performance to existing decision rules such as the STOP-Bang or ANC.

Algorithms for the diagnosis and treatment of restless legs syndrome in primary care

PubMed Central

2011-01-01

Background Restless legs syndrome (RLS) is a neurological disorder with a lifetime prevalence of 3-10%. in European studies. However, the diagnosis of RLS in primary care remains low and mistreatment is common. Methods The current article reports on the considerations of RLS diagnosis and management that were made during a European Restless Legs Syndrome Study Group (EURLSSG)-sponsored task force consisting of experts and primary care practioners. The task force sought to develop a better understanding of barriers to diagnosis in primary care practice and overcome these barriers with diagnostic and treatment algorithms. Results The barriers to diagnosis identified by the task force include the presentation of symptoms, the language used to describe them, the actual term "restless legs syndrome" and difficulties in the differential diagnosis of RLS. Conclusion The EURLSSG task force reached a consensus and agreed on the diagnostic and treatment algorithms published here. PMID:21352569

Gliomatosis cerebri: A consensus summary report from the First International Gliomatosis cerebri Group Meeting, March 26-27, 2015, Paris, France.

PubMed

Greenfield, Jeffrey P; Castañeda Heredia, Alicia; George, Emilie; Kieran, Mark W; Morales La Madrid, Andres

2016-12-01

Gliomatosis cerebri (GC) is a universally fatal extensive and diffuse infiltration of brain parenchyma by a glial tumor. Many aspects of this phenomenon remain unknown. The First International Gliomatosis cerebri Group Meeting had the following goals: refine the clinical and radiologic diagnostic criteria for GC, suggest appropriate diagnostic procedures, standardize tissue manipulation for histologic and molecular characterization, and prioritize relevant preclinical projects. Also, general treatment recommendations were outlined for the pediatric population. Importantly, this meeting was the starting point for meaningful collaborative international research projects. This review is a consensus summary of discussions shared and conclusions derived from this meeting. © 2016 Wiley Periodicals, Inc.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

A hematology consensus agreement on antifungal strategies for neutropenic patients with hematological malignancies and stem cell transplant recipients. Gruppo Italiano Malattie Ematologiche dell'Adulto, Gruppo Italiano Trapianto di Midollo Osseo, Associazione Italiana Ematologia ed Oncologia Pediatrica, Invasive Fungal Infections Cooperative Group of the European Organization for Research and Treatment of Cancer and Sorveglianza Epidemiologica delle Infezioni Fungine nelle Emopatie Maligne.

PubMed

Girmenia, Corrado; Aversa, Franco; Busca, Alessandro; Candoni, Anna; Cesaro, Simone; Luppi, Mario; Pagano, Livio; Rossi, Giuseppe; Venditti, Adriano; Nosari, Anna Maria

2013-09-01

In the attempt to establish key therapy definitions and provide shared approaches to invasive fungal diseases in neutropenic patients, trials of empiric, preeemptive and targeted antifungal therapy (EAT, PAT and TAT) were reviewed, and a Consensus Development Conference Project was convened. The Expert-Panel concurred that all antifungal treatments, including EAT, should always follow an adequate diagnostic strategy and that the standard definition of PAT may be misleading: being PAT guided by the results of a diagnostic work-up, it should better be termed diagnostic-driven antifungal therapy (DDAT). The Expert-Panel agreed that radiological findings alone are insufficient for the choice of a TAT and that the identification of the etiologic pathogen is needed. The Consensus Agreement proceeded identifying which clinical and microbiological findings were sufficient to start a DDAT and which were not. Finally, an algorithm to rationalize the choice of antifungal drugs on the basis of clinical manifestations, antifungal prophylaxis, instrumental and laboratory findings was drawn up. Copyright © 2012 John Wiley & Sons, Ltd.

Kyoto global consensus report on Helicobacter pylori gastritis

PubMed Central

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-01-01

Objective To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Design Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. Results All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. Conclusions A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. PMID:26187502

Problems in shortening the time to confirmation of ALS diagnosis: lessons from the 1st Consensus Conference, Chicago, May 1998.

PubMed

Brooks, B R

2000-03-01

The 2nd Consensus Conference (Versailles) on the early diagnosis of amyotrophic lateral sclerosis (ALS) developed themes identified at the 1st Consensus Conference (Chicago) on defining optimal management in ALS. These themes included describing the problems and limitations in current diagnostic practices, identifying consequences of early diagnosis on patient management, establishing recommendations to help healthcare personnel achieve the early diagnosis and proposing solutions to facilitate early diagnosis of ALS. Lessons from the ISIS Survey and the 1st Consensus Conference focused on the variability of the first-contact physician, supply factors for specialists and variability of application of medical techniques. The recently introduced concept of 'ALS health states or stages' was reviewed in terms of ongoing and potential prospective studies. The relative contribution of neuroimaging or clinical neurophysiological investigations to accelerating the diagnosis of ALS in clinical practice was debated. The role of a common ALS knowledge-base among patients, initial healthcare providers, diagnosing neurologists and confirming neurologists was critically appraised with regard to simplified 'ALS diagnostic algorithm', 'ten aphorisms in the diagnosis of ALS' and 'ALS axioms of referral'. Refining this ALS knowledge-base is required to identify a minimum dataset required for the evaluation and diagnosis of ALS.

Kyoto global consensus report on Helicobacter pylori gastritis.

PubMed

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-09-01

To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Interdisciplinary consensus on management of premenstrual disorders in Switzerland.

PubMed

Stute, Petra; Bodmer, Christine; Ehlert, Ulrike; Eltbogen, Roger; Ging, Ankica; Streuli, Isabelle; von Wolff, Michael

2017-05-01

Premenstrual disorders (PMD) can affect women throughout their entire reproductive years. In 2016, an interdisciplinary expert meeting of general gynecologists, gynecological endocrinologists, psychiatrists and psychologists from Switzerland was held to provide an interdisciplinary algorithm on PMD management taking reproductive stages into account. The Swiss PMD algorithm differentiates between primary and secondary PMD care providers incorporating different levels of diagnostic and treatment. Treatment options include cognitive behavioral therapy, alternative therapy, antidepressants, ovulation suppression and diuretics. Treatment choice depends on prevalent PMD symptoms, (reproductive) age, family planning, cardiovascular risk factors, comorbidities, comedication and the woman's preference. Regular follow-ups are mandatory.

Research Diagnostic Criteria for Temporomandibular Disorders: Validity of Axis I Diagnoses

PubMed Central

Truelove, Edmond; Pan, Wei; Look, John O.; Mancl, Lloyd A.; Ohrbach, Richard K.; Velly, Ana; Huggins, Kimberly; Lenton, Patricia; Schiffman, Eric L.

2011-01-01

AIMS To estimate the criterion validity of the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) Axis I TMD diagnoses. METHODS A combined total of 614 TMD community and clinic cases and 91 controls were examined at 3 study sites. RDC/TMD Axis I diagnoses were algorithmically derived from an examination performed by calibrated dental hygienists. Reference standards (Gold Standards) were established by means of consensus diagnoses rendered by 2 TMD experts using all available clinical data, including imaging studies. Validity of the RDC/TMD Axis I TMD diagnoses was estimated relative to reference-standard diagnoses (gold standard diagnoses). Target sensitivity and specificity were set a priori at ≥ 0.70 and ≥ 0.95, respectively. RESULTS Target sensitivity and specificity were not observed for any of the 8 RDC/TMD diagnoses. The highest validity was achieved for Group Ia myofascial pain (sensitivity 0.65, specificity 0.92) and Group Ib myofascial pain with limited opening (sensitivity 0.79, specificity 0.92). Target sensitivity and specificity were observed only when both Group I diagnoses were combined (0.87 and 0.98, respectively). For Group II (disc displacements) and Group III (arthralgia, arthritis, arthrosis) diagnoses, all estimates for sensitivity were below target (0.03 to 0.53), and specificity ranged from below to on target (0.86 to 0.99). CONCLUSION The RDC/TMD Axis I TMD diagnoses did not reach the targets set at sensitivity of ≥ 0.70 and specificity of ≥ 0.95. Target validity was obtained only for myofascial pain without differentiation between normal and limited opening. Revision of the current Axis I TMD diagnostic algorithms is warranted to improve their validity. PMID:20213030

Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

NASA Astrophysics Data System (ADS)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.

SeaWiFS Technical Report Series. Volume 42; Satellite Primary Productivity Data and Algorithm Development: A Science Plan for Mission to Planet Earth

NASA Technical Reports Server (NTRS)

Falkowski, Paul G.; Behrenfeld, Michael J.; Esaias, Wayne E.; Balch, William; Campbell, Janet W.; Iverson, Richard L.; Kiefer, Dale A.; Morel, Andre; Yoder, James A.; Hooker, Stanford B. (Editor);

Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neurobehavioral assessment.

PubMed

Schnakers, Caroline; Vanhaudenhuyse, Audrey; Giacino, Joseph; Ventura, Manfredi; Boly, Melanie; Majerus, Steve; Moonen, Gustave; Laureys, Steven

2009-07-21

Previously published studies have reported that up to 43% of patients with disorders of consciousness are erroneously assigned a diagnosis of vegetative state (VS). However, no recent studies have investigated the accuracy of this grave clinical diagnosis. In this study, we compared consensus-based diagnoses of VS and MCS to those based on a well-established standardized neurobehavioral rating scale, the JFK Coma Recovery Scale-Revised (CRS-R). We prospectively followed 103 patients (55 +/- 19 years) with mixed etiologies and compared the clinical consensus diagnosis provided by the physician on the basis of the medical staff's daily observations to diagnoses derived from CRS-R assessments performed by research staff. All patients were assigned a diagnosis of 'VS', 'MCS' or 'uncertain diagnosis.' Of the 44 patients diagnosed with VS based on the clinical consensus of the medical team, 18 (41%) were found to be in MCS following standardized assessment with the CRS-R. In the 41 patients with a consensus diagnosis of MCS, 4 (10%) had emerged from MCS, according to the CRS-R. We also found that the majority of patients assigned an uncertain diagnosis by clinical consensus (89%) were in MCS based on CRS-R findings. Despite the importance of diagnostic accuracy, the rate of misdiagnosis of VS has not substantially changed in the past 15 years. Standardized neurobehavioral assessment is a more sensitive means of establishing differential diagnosis in patients with disorders of consciousness when compared to diagnoses determined by clinical consensus.

Stability switches of arbitrary high-order consensus in multiagent networks with time delays.

PubMed

Yang, Bo

2013-01-01

High-order consensus seeking, in which individual high-order dynamic agents share a consistent view of the objectives and the world in a distributed manner, finds its potential broad applications in the field of cooperative control. This paper presents stability switches analysis of arbitrary high-order consensus in multiagent networks with time delays. By employing a frequency domain method, we explicitly derive analytical equations that clarify a rigorous connection between the stability of general high-order consensus and the system parameters such as the network topology, communication time-delays, and feedback gains. Particularly, our results provide a general and a fairly precise notion of how increasing communication time-delay causes the stability switches of consensus. Furthermore, under communication constraints, the stability and robustness problems of consensus algorithms up to third order are discussed in details to illustrate our central results. Numerical examples and simulation results for fourth-order consensus are provided to demonstrate the effectiveness of our theoretical results.

Development of an algorithm for the management of cervical lymphadenopathy in children: consensus of the Italian Society of Preventive and Social Pediatrics, jointly with the Italian Society of Pediatric Infectious Diseases and the Italian Society of Pediatric Otorhinolaryngology.

PubMed

Chiappini, Elena; Camaioni, Angelo; Benazzo, Marco; Biondi, Andrea; Bottero, Sergio; De Masi, Salvatore; Di Mauro, Giuseppe; Doria, Mattia; Esposito, Susanna; Felisati, Giovanni; Felisati, Dino; Festini, Filippo; Gaini, Renato Maria; Galli, Luisa; Gambini, Claudio; Gianelli, Umberto; Landi, Massimo; Lucioni, Marco; Mansi, Nicola; Mazzantini, Rachele; Marchisio, Paola; Marseglia, Gian Luigi; Miniello, Vito Leonardo; Nicola, Marta; Novelli, Andrea; Paulli, Marco; Picca, Marina; Pillon, Marta; Pisani, Paolo; Pipolo, Carlotta; Principi, Nicola; Sardi, Iacopo; Succo, Giovanni; Tomà, Paolo; Tortoli, Enrico; Tucci, Filippo; Varricchio, Attilio; de Martino, Maurizio; Italian Guideline Panel For Management Of Cervical Lymphadenopathy In Children

2015-01-01

Cervical lymphadenopathy is a common disorder in children due to a wide spectrum of disorders. On the basis of a complete history and physical examination, paediatricians have to select, among the vast majority of children with a benign self-limiting condition, those at risk for other, more complex, diseases requiring laboratory tests, imaging and, finally, tissue sampling. At the same time, they should avoid expensive and invasive examinations when unnecessary. The Italian Society of Preventive and Social Pediatrics, jointly with the Italian Society of Pediatric Infectious Diseases, the Italian Society of Pediatric Otorhinolaryngology, and other Scientific Societies, issued a National Consensus document, based on the most recent literature findings, including an algorithm for the management of cervical lymphadenopathy in children. The Consensus Conference method was used, following the Italian National Plan Guidelines. Relevant publications in English were identified through a systematic review of MEDLINE and the Cochrane Database of Systematic Reviews from their inception through March 21, 2014. Basing on literature results, an algorithm was developed, including several possible clinical scenarios. Situations requiring a watchful waiting strategy, those requiring an empiric antibiotic therapy, and those necessitating a prompt diagnostic workup, considering the risk for a severe underling disease, have been identified. The present algorithm is a practice tool for the management of pediatric cervical lymphadenopathy in the hospital and the ambulatory settings. A multidisciplinary approach is paramount. Further studies are required for its validation in the clinical field.

Distributed Position-Based Consensus of Second-Order Multiagent Systems With Continuous/Intermittent Communication.

PubMed

Song, Qiang; Liu, Fang; Wen, Guanghui; Cao, Jinde; Yang, Xinsong

2017-04-24

This paper considers the position-based consensus in a network of agents with double-integrator dynamics and directed topology. Two types of distributed observer algorithms are proposed to solve the consensus problem by utilizing continuous and intermittent position measurements, respectively, where each observer does not interact with any other observers. For the case of continuous communication between network agents, some convergence conditions are derived for reaching consensus in the network with a single constant delay or multiple time-varying delays on the basis of the eigenvalue analysis and the descriptor method. When the network agents can only obtain intermittent position data from local neighbors at discrete time instants, the consensus in the network without time delay or with nonuniform delays is investigated by using the Wirtinger's inequality and the delayed-input approach. Numerical examples are given to illustrate the theoretical analysis.

EAACI position paper on occupational rhinitis

PubMed Central

Moscato, Gianna; Vandenplas, Olivier; Van Wijk, Roy Gerth; Malo, Jean-Luc; Perfetti, Luca; Quirce, Santiago; Walusiak, Jolanta; Castano, Roberto; Pala, Gianni; Gautrin, Denyse; De Groot, Hans; Folletti, Ilenia; Yacoub, Mona Rita; Siracusa, Andrea

2009-01-01

The present document is the result of a consensus reached by a panel of experts from European and non-European countries on Occupational Rhinitis (OR), a disease of emerging relevance which has received little attention in comparison to occupational asthma. The document covers the main items of OR including epidemiology, diagnosis, management, socio-economic impact, preventive strategies and medicolegal issues. An operational definition and classification of OR tailored on that of occupational asthma, as well as a diagnostic algorithm based on steps allowing for different levels of diagnostic evidence are proposed. The needs for future research are pointed out. Key messages are issued for each item. PMID:19257881

Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence

PubMed Central

Gimeno-Blanes, Francisco J.; Blanco-Velasco, Manuel; Barquero-Pérez, Óscar; García-Alberola, Arcadi; Rojo-Álvarez, José L.

2016-01-01

Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indices, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indices in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indices which are tackled from the aforementioned viewpoints, namely, heart rate turbulence (HRT), heart rate variability (HRV), and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future. PMID:27014083

Understanding diagnostic variability in breast pathology: lessons learned from an expert consensus review panel

PubMed Central

Allison, Kimberly H; Reisch, Lisa M; Carney, Patricia A; Weaver, Donald L; Schnitt, Stuart J; O’Malley, Frances P; Geller, Berta M; Elmore, Joann G

2015-01-01

Aims To gain a better understanding of the reasons for diagnostic variability, with the aim of reducing the phenomenon. Methods and results In preparation for a study on the interpretation of breast specimens (B-PATH), a panel of three experienced breast pathologists reviewed 336 cases to develop consensus reference diagnoses. After independent assessment, cases coded as diagnostically discordant were discussed at consensus meetings. By the use of qualitative data analysis techniques, transcripts of 16 h of consensus meetings for a subset of 201 cases were analysed. Diagnostic variability could be attributed to three overall root causes: (i) pathologist-related; (ii) diagnostic coding/study methodology-related; and (iii) specimen-related. Most pathologist-related root causes were attributable to professional differences in pathologists’ opinions about whether the diagnostic criteria for a specific diagnosis were met, most frequently in cases of atypia. Diagnostic coding/study methodology-related root causes were primarily miscategorizations of descriptive text diagnoses, which led to the development of a standardized electronic diagnostic form (BPATH-Dx). Specimen-related root causes included artefacts, limited diagnostic material, and poor slide quality. After re-review and discussion, a consensus diagnosis could be assigned in all cases. Conclusions Diagnostic variability is related to multiple factors, but consensus conferences, standardized electronic reporting formats and comments on suboptimal specimen quality can be used to reduce diagnostic variability. PMID:24511905

Comparison of four morphometric definitions and a semiquantitative consensus reading for assessing prevalent vertebral fractures.

PubMed

Grados, F; Roux, C; de Vernejoul, M C; Utard, G; Sebert, J L; Fardellone, P

2001-01-01

The assessment of vertebral fracture in patients with osteoporosis by conventional radiography has been improved over the past 10 years using either the semiquantitative (SQ) method devised by Genant et al. or quantitative morphometry. However, there is still no internationally agreed definition for vertebral fracture and there have been few comparative studies between these different approaches. Our study assessed the reproducibility of the SQ method and of four commonly used morphometric algorithms (Melton's, Eastell's, Minne's and McCloskey's methods) for assessing prevalent vertebral fractures, and examined the agreement of each morphometric algorithm with a SQ consensus reading performed by three experts. With this consensus reading in place of a gold standard, we determined relative measures of sensitivity, specificity and optimal cutoff threshold for each morphometric algorithm. The study was conducted in 39 postmenopausal women who had at least one osteoporotic vertebral fracture. Normal values were derived from 84 healthy postmenopausal women with apparently normal vertebral bodies. Our results indicate that the concordance of SQ method was excellent (intraobserver agreement on serial radiographs = 96.4%, kappa = 0.91; agreement between individual readings and the consensus reading = 98%, kappa = 0.95). Three morphometric approaches demonstrated good intra- and interobserver concordance (Melton: intraobserver agreement on serial radiographs = 92.7%, kappa = 0.82, interobserver agreement = 91.1%, kappa = 0.79; Eastell: intraobserver agreement on serial radiographs = 87.6%, kappa = 0.66, interobserver agreement = 88.6%, kappa = 0.68; McCloskey: intraobserver agreement on serial radiographs = 91.5%, kappa = 0.72, interobserver agreement = 93.9%, kappa = 0.78). Except for McCloskey's method, the optimal cutoff thresholds defined in our study by highest kappa score or Youden index in comparison with the SQ consensus reading were near the cutoff thresholds that were arbitrarily fixed. The four morphometric algorithms provided a good agreement with the results of the SQ consensus reading, but the more complex algorithm did not provide better results and even if we adjusted the cutoff threshold, no morphometric algorithm agreed perfectly with the SQ consensus reading. We conclude that morphometric approaches currently used should not be employed alone to detect prevalent vertebral fractures in studies on osteoporosis, but should rather be used in combination with a visual assessment. The SQ approach that allows differential diagnosis of vertebral deformities and has demonstrated a better reproducibility can be employed alone when it is performed by experienced and well-trained readers.

Chiropractic Integrated Care Pathway for Low Back Pain in Veterans: Results of a Delphi Consensus Process.

PubMed

Lisi, Anthony J; Salsbury, Stacie A; Hawk, Cheryl; Vining, Robert D; Wallace, Robert B; Branson, Richard; Long, Cynthia R; Burgo-Black, A Lucille; Goertz, Christine M

2018-02-01

The purpose of this study was to develop an integrated care pathway for doctors of chiropractic, primary care providers, and mental health professionals who manage veterans with low back pain, with or without mental health comorbidity, within Department of Veterans Affairs health care facilities. The research method used was a consensus process. A multidisciplinary investigative team reviewed clinical guidelines and Veterans Affairs pain and mental health initiatives to develop seed statements and care algorithms to guide chiropractic management and collaborative care of veterans with low back pain. A 5-member advisory committee approved initial recommendations. Veterans Affairs-based panelists (n = 58) evaluated the pathway via e-mail using a modified RAND/UCLA methodology. Consensus was defined as agreement by 80% of panelists. The modified Delphi process was conducted in July to December 2016. Most (93%) seed statements achieved consensus during the first round, with all statements reaching consensus after 2 rounds. The final care pathway addressed the topics of informed consent, clinical evaluation including history and examination, screening for red flags, documentation, diagnostic imaging, patient-reported outcomes, adverse event reporting, chiropractic treatment frequency and duration standards, tailored approaches to chiropractic care in veteran populations, and clinical presentation of common mental health conditions. Care algorithms outlined chiropractic case management and interprofessional collaboration and referrals between doctors of chiropractic and primary care and mental health providers. This study offers an integrative care pathway that includes chiropractic care for veterans with low back pain. Copyright © 2018. Published by Elsevier Inc.

Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: Recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group†

PubMed Central

Schiffman, Eric; Ohrbach, Richard; Truelove, Edmond; Look, John; Anderson, Gary; Goulet, Jean-Paul; List, Thomas; Svensson, Peter; Gonzalez, Yoly; Lobbezoo, Frank; Michelotti, Ambra; Brooks, Sharon L.; Ceusters, Werner; Drangsholt, Mark; Ettlin, Dominik; Gaul, Charly; Goldberg, Louis J.; Haythornthwaite, Jennifer A.; Hollender, Lars; Jensen, Rigmor; John, Mike T.; De Laat, Antoon; de Leeuw, Reny; Maixner, William; van der Meulen, Marylee; Murray, Greg M.; Nixdorf, Donald R.; Palla, Sandro; Petersson, Arne; Pionchon, Paul; Smith, Barry; Visscher, Corine M.; Zakrzewska, Joanna; Dworkin, Samuel F.

2015-01-01

Aims The original Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) Axis I diagnostic algorithms have been demonstrated to be reliable. However, the Validation Project determined that the RDC/TMD Axis I validity was below the target sensitivity of ≥ 0.70 and specificity of ≥ 0.95. Consequently, these empirical results supported the development of revised RDC/TMD Axis I diagnostic algorithms that were subsequently demonstrated to be valid for the most common pain-related TMD and for one temporomandibular joint (TMJ) intra-articular disorder. The original RDC/TMD Axis II instruments were shown to be both reliable and valid. Working from these findings and revisions, two international consensus workshops were convened, from which recommendations were obtained for the finalization of new Axis I diagnostic algorithms and new Axis II instruments. Methods Through a series of workshops and symposia, a panel of clinical and basic science pain experts modified the revised RDC/TMD Axis I algorithms by using comprehensive searches of published TMD diagnostic literature followed by review and consensus via a formal structured process. The panel's recommendations for further revision of the Axis I diagnostic algorithms were assessed for validity by using the Validation Project's data set, and for reliability by using newly collected data from the ongoing TMJ Impact Project—the follow-up study to the Validation Project. New Axis II instruments were identified through a comprehensive search of the literature providing valid instruments that, relative to the RDC/TMD, are shorter in length, are available in the public domain, and currently are being used in medical settings. Results The newly recommended Diagnostic Criteria for TMD (DC/TMD) Axis I protocol includes both a valid screener for detecting any pain-related TMD as well as valid diagnostic criteria for differentiating the most common pain-related TMD (sensitivity ≥ 0.86, specificity ≥ 0.98) and for one intra-articular disorder (sensitivity of 0.80 and specificity of 0.97). Diagnostic criteria for other common intra-articular disorders lack adequate validity for clinical diagnoses but can be used for screening purposes. Inter-examiner reliability for the clinical assessment associated with the validated DC/TMD criteria for pain-related TMD is excellent (kappa ≥ 0.85). Finally, a comprehensive classification system that includes both the common and less common TMD is also presented. The Axis II protocol retains selected original RDC/TMD screening instruments augmented with new instruments to assess jaw function as well as behavioral and additional psychosocial factors. The Axis II protocol is divided into screening and comprehensive self-report instrument sets. The screening instruments’ 41 questions assess pain intensity, pain-related disability, psychological distress, jaw functional limitations, and parafunctional behaviors, and a pain drawing is used to assess locations of pain. The comprehensive instruments, composed of 81 questions, assess in further detail jaw functional limitations and psychological distress as well as additional constructs of anxiety and presence of comorbid pain conditions. Conclusion The recommended evidence-based new DC/TMD protocol is appropriate for use in both clinical and research settings. More comprehensive instruments augment short and simple screening instruments for Axis I and Axis II. These validated instruments allow for identification of patients with a range of simple to complex TMD presentations. PMID:24482784

Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment

PubMed Central

Schnakers, Caroline; Vanhaudenhuyse, Audrey; Giacino, Joseph; Ventura, Manfredi; Boly, Melanie; Majerus, Steve; Moonen, Gustave; Laureys, Steven

2009-01-01

Background Previously published studies have reported that up to 43% of patients with disorders of consciousness are erroneously assigned a diagnosis of vegetative state (VS). However, no recent studies have investigated the accuracy of this grave clinical diagnosis. In this study, we compared consensus-based diagnoses of VS and MCS to those based on a well-established standardized neurobehavioral rating scale, the JFK Coma Recovery Scale-Revised (CRS-R). Methods We prospectively followed 103 patients (55 ± 19 years) with mixed etiologies and compared the clinical consensus diagnosis provided by the physician on the basis of the medical staff's daily observations to diagnoses derived from CRS-R assessments performed by research staff. All patients were assigned a diagnosis of 'VS', 'MCS' or 'uncertain diagnosis.' Results Of the 44 patients diagnosed with VS based on the clinical consensus of the medical team, 18 (41%) were found to be in MCS following standardized assessment with the CRS-R. In the 41 patients with a consensus diagnosis of MCS, 4 (10%) had emerged from MCS, according to the CRS-R. We also found that the majority of patients assigned an uncertain diagnosis by clinical consensus (89%) were in MCS based on CRS-R findings. Conclusion Despite the importance of diagnostic accuracy, the rate of misdiagnosis of VS has not substantially changed in the past 15 years. Standardized neurobehavioral assessment is a more sensitive means of establishing differential diagnosis in patients with disorders of consciousness when compared to diagnoses determined by clinical consensus. PMID:19622138

A Family of Algorithms for Computing Consensus about Node State from Network Data

PubMed Central

Brush, Eleanor R.; Krakauer, David C.; Flack, Jessica C.

2013-01-01

Biological and social networks are composed of heterogeneous nodes that contribute differentially to network structure and function. A number of algorithms have been developed to measure this variation. These algorithms have proven useful for applications that require assigning scores to individual nodes–from ranking websites to determining critical species in ecosystems–yet the mechanistic basis for why they produce good rankings remains poorly understood. We show that a unifying property of these algorithms is that they quantify consensus in the network about a node's state or capacity to perform a function. The algorithms capture consensus by either taking into account the number of a target node's direct connections, and, when the edges are weighted, the uniformity of its weighted in-degree distribution (breadth), or by measuring net flow into a target node (depth). Using data from communication, social, and biological networks we find that that how an algorithm measures consensus–through breadth or depth– impacts its ability to correctly score nodes. We also observe variation in sensitivity to source biases in interaction/adjacency matrices: errors arising from systematic error at the node level or direct manipulation of network connectivity by nodes. Our results indicate that the breadth algorithms, which are derived from information theory, correctly score nodes (assessed using independent data) and are robust to errors. However, in cases where nodes “form opinions” about other nodes using indirect information, like reputation, depth algorithms, like Eigenvector Centrality, are required. One caveat is that Eigenvector Centrality is not robust to error unless the network is transitive or assortative. In these cases the network structure allows the depth algorithms to effectively capture breadth as well as depth. Finally, we discuss the algorithms' cognitive and computational demands. This is an important consideration in systems in which individuals use the collective opinions of others to make decisions. PMID:23874167

Epidemic failure detection and consensus for extreme parallelism

DOE PAGES

Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas; ...

2017-02-01

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less

Robust consensus algorithm for multi-agent systems with exogenous disturbances under convergence conditions

NASA Astrophysics Data System (ADS)

Jiang, Yulian; Liu, Jianchang; Tan, Shubin; Ming, Pingsong

2014-09-01

In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katti, Amogh; Di Fatta, Giuseppe; Naughton, Thomas

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that inmore » all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.« less

Development and clinical validation of a novel photography-based skin erythema evaluation system: a comparison with the calculated consensus of dermatologists.

PubMed

Cho, M; Lee, D-H; Doh, E J; Kim, Y; Chung, J H; Kim, H C; Kim, S

2017-08-01

Erythema is the most common presenting sign in patients with skin diseases, and various methods to treat erythema symptoms have become common. To evaluate changes in erythema, a reliable device that can support objective diagnosis is required. We developed a novel photography-based system for erythema diagnosis that provides a high-resolution three-view photograph taken in a consistent photography environment with a curved surface light source and can be integrated with optimized image processing algorithms. A new diagnostic algorithm was applied to photographs from 32 patients to determine areas of erythema automatically. To assess the performance in comparison to dermatologists' evaluations, five dermatologists independently evaluate the areas of erythema, and we defined an area called the clinical consensus area of erythema (CCAE), which is based on the majority opinion of dermatologists during evaluation. The CCAE values obtained were compared with the erythema areas determined by the system's diagnostic algorithm. Forty-one photographs with areas of erythema were evaluated by the proposed system and by dermatologists. The results obtained with the proposed system had a mean accuracy of 93.18% with a standard deviation of 3.52% when compared with the CCAE results. The results also showed that the proposed system could detect erythema areas without any pigmentation. In contrast to assessments by individual dermatologists, use of the CCAE reduced the amount of error that occurred owing to bias or subjectivity. A new erythema evaluation system was developed and validated through CCAE, suggesting that the system can support dermatologists' objective diagnoses of erythema. © 2017 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Kyoto global consensus report on Helicobacter pylori gastritis and its impact on Chinese clinical practice.

PubMed

Chen, Qi; Lu, Hong

2016-06-01

The Kyoto global consensus report on Helicobacter pylori (H. pylori) gastritis has had a great effect on the field of H. pylori studies worldwide. For the first time H. pylori gastritis was defined entirely as an infectious disease and H. pylori-associated dyspepsia as a new category of organic dyspepsia apart from functional dyspepsia, together with a proposed diagnostic algorithm. Accordingly, the report states that the eradication of H. pylori should be regarded as the first-line treatment for dyspepsia. Moreover, H. pylori eradication before the development of pre-neoplastic changes is recommended to reduce the risk of more serious complications of H. pylori gastritis. Despite the recommendations of this new global consensus, the task of transforming them into feasible and practical recommendations for individual countries will require them to become region-specific, which requires further discussion. © 2016 Chinese Medical Association Shanghai Branch, Chinese Society of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

Non-fragile consensus algorithms for a network of diffusion PDEs with boundary local interaction

NASA Astrophysics Data System (ADS)

Xiong, Jun; Li, Junmin

2017-07-01

In this study, non-fragile consensus algorithm is proposed to solve the average consensus problem of a network of diffusion PDEs, modelled by boundary controlled heat equations. The problem deals with the case where the Neumann-type boundary controllers are corrupted by additive persistent disturbances. To achieve consensus between agents, a linear local interaction rule addressing this requirement is given. The proposed local interaction rules are analysed by applying a Lyapunov-based approach. The multiplicative and additive non-fragile feedback control algorithms are designed and sufficient conditions for the consensus of the multi-agent systems are presented in terms of linear matrix inequalities, respectively. Simulation results are presented to support the effectiveness of the proposed algorithms.

A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.

PubMed

Baltzer, Pascal A T; Dietzel, Matthias; Kaiser, Werner A

2013-08-01

In the face of multiple available diagnostic criteria in MR-mammography (MRM), a practical algorithm for lesion classification is needed. Such an algorithm should be as simple as possible and include only important independent lesion features to differentiate benign from malignant lesions. This investigation aimed to develop a simple classification tree for differential diagnosis in MRM. A total of 1,084 lesions in standardised MRM with subsequent histological verification (648 malignant, 436 benign) were investigated. Seventeen lesion criteria were assessed by 2 readers in consensus. Classification analysis was performed using the chi-squared automatic interaction detection (CHAID) method. Results include the probability for malignancy for every descriptor combination in the classification tree. A classification tree incorporating 5 lesion descriptors with a depth of 3 ramifications (1, root sign; 2, delayed enhancement pattern; 3, border, internal enhancement and oedema) was calculated. Of all 1,084 lesions, 262 (40.4 %) and 106 (24.3 %) could be classified as malignant and benign with an accuracy above 95 %, respectively. Overall diagnostic accuracy was 88.4 %. The classification algorithm reduced the number of categorical descriptors from 17 to 5 (29.4 %), resulting in a high classification accuracy. More than one third of all lesions could be classified with accuracy above 95 %. • A practical algorithm has been developed to classify lesions found in MR-mammography. • A simple decision tree consisting of five criteria reaches high accuracy of 88.4 %. • Unique to this approach, each classification is associated with a diagnostic certainty. • Diagnostic certainty of greater than 95 % is achieved in 34 % of all cases.

Distributed Data-aggregation Consensus for Sensor Networks: Relaxation of Consensus Concept and Convergence Property

DTIC Science & Technology

2014-08-01

consensus algorithm called randomized gossip is more suitable [7, 8]. In asynchronous randomized gossip algorithms, pairs of neighboring nodes exchange...messages and perform updates in an asynchronous and unattended manner, and they also 1 The class of broadcast gossip algorithms [9, 10, 11, 12] are...dynamics [2] and asynchronous pairwise randomized gossip [7, 8], broadcast gossip algorithms do not require that nodes know the identities of their

Reporting standards for studies of diagnostic test accuracy in dementia

PubMed Central

Noel-Storr, Anna H.; McCleery, Jenny M.; Richard, Edo; Ritchie, Craig W.; Flicker, Leon; Cullum, Sarah J.; Davis, Daniel; Quinn, Terence J.; Hyde, Chris; Rutjes, Anne W.S.; Smailagic, Nadja; Marcus, Sue; Black, Sandra; Blennow, Kaj; Brayne, Carol; Fiorivanti, Mario; Johnson, Julene K.; Köpke, Sascha; Schneider, Lon S.; Simmons, Andrew; Mattsson, Niklas; Zetterberg, Henrik; Bossuyt, Patrick M.M.; Wilcock, Gordon

2014-01-01

Objective: To provide guidance on standards for reporting studies of diagnostic test accuracy for dementia disorders. Methods: An international consensus process on reporting standards in dementia and cognitive impairment (STARDdem) was established, focusing on studies presenting data from which sensitivity and specificity were reported or could be derived. A working group led the initiative through 4 rounds of consensus work, using a modified Delphi process and culminating in a face-to-face consensus meeting in October 2012. The aim of this process was to agree on how best to supplement the generic standards of the STARD statement to enhance their utility and encourage their use in dementia research. Results: More than 200 comments were received during the wider consultation rounds. The areas at most risk of inadequate reporting were identified and a set of dementia-specific recommendations to supplement the STARD guidance were developed, including better reporting of patient selection, the reference standard used, avoidance of circularity, and reporting of test-retest reliability. Conclusion: STARDdem is an implementation of the STARD statement in which the original checklist is elaborated and supplemented with guidance pertinent to studies of cognitive disorders. Its adoption is expected to increase transparency, enable more effective evaluation of diagnostic tests in Alzheimer disease and dementia, contribute to greater adherence to methodologic standards, and advance the development of Alzheimer biomarkers. PMID:24944261

Embedding strategies for effective use of information from multiple sequence alignments.

PubMed Central

Henikoff, S.; Henikoff, J. G.

1997-01-01

We describe a new strategy for utilizing multiple sequence alignment information to detect distant relationships in searches of sequence databases. A single sequence representing a protein family is enriched by replacing conserved regions with position-specific scoring matrices (PSSMs) or consensus residues derived from multiple alignments of family members. In comprehensive tests of these and other family representations, PSSM-embedded queries produced the best results overall when used with a special version of the Smith-Waterman searching algorithm. Moreover, embedding consensus residues instead of PSSMs improved performance with readily available single sequence query searching programs, such as BLAST and FASTA. Embedding PSSMs or consensus residues into a representative sequence improves searching performance by extracting multiple alignment information from motif regions while retaining single sequence information where alignment is uncertain. PMID:9070452

Validation of administrative data used for the diagnosis of upper gastrointestinal events following nonsteroidal anti-inflammatory drug prescription.

PubMed

Abraham, N S; Cohen, D C; Rivers, B; Richardson, P

2006-07-15

To validate veterans affairs (VA) administrative data for the diagnosis of nonsteroidal anti-inflammatory drug (NSAID)-related upper gastrointestinal events (UGIE) and to develop a diagnostic algorithm. A retrospective study of veterans prescribed an NSAID as identified from the national pharmacy database merged with in-patient and out-patient data, followed by primary chart abstraction. Contingency tables were constructed to allow comparison with a random sample of patients prescribed an NSAID, but without UGIE. Multivariable logistic regression analysis was used to derive a predictive algorithm. Once derived, the algorithm was validated in a separate cohort of veterans. Of 906 patients, 606 had a diagnostic code for UGIE; 300 were a random subsample of 11 744 patients (control). Only 161 had a confirmed UGIE. The positive predictive value (PPV) of diagnostic codes was poor, but improved from 27% to 51% with the addition of endoscopic procedural codes. The strongest predictors of UGIE were an in-patient ICD-9 code for gastric ulcer, duodenal ulcer and haemorrhage combined with upper endoscopy. This algorithm had a PPV of 73% when limited to patients >or=65 years (c-statistic 0.79). Validation of the algorithm revealed a PPV of 80% among patients with an overlapping NSAID prescription. NSAID-related UGIE can be assessed using VA administrative data. The optimal algorithm includes an in-patient ICD-9 code for gastric or duodenal ulcer and gastrointestinal bleeding combined with a procedural code for upper endoscopy.

RANdom SAmple Consensus (RANSAC) algorithm for material-informatics: application to photovoltaic solar cells.

PubMed

Kaspi, Omer; Yosipof, Abraham; Senderowitz, Hanoch

2017-06-06

An important aspect of chemoinformatics and material-informatics is the usage of machine learning algorithms to build Quantitative Structure Activity Relationship (QSAR) models. The RANdom SAmple Consensus (RANSAC) algorithm is a predictive modeling tool widely used in the image processing field for cleaning datasets from noise. RANSAC could be used as a "one stop shop" algorithm for developing and validating QSAR models, performing outlier removal, descriptors selection, model development and predictions for test set samples using applicability domain. For "future" predictions (i.e., for samples not included in the original test set) RANSAC provides a statistical estimate for the probability of obtaining reliable predictions, i.e., predictions within a pre-defined number of standard deviations from the true values. In this work we describe the first application of RNASAC in material informatics, focusing on the analysis of solar cells. We demonstrate that for three datasets representing different metal oxide (MO) based solar cell libraries RANSAC-derived models select descriptors previously shown to correlate with key photovoltaic properties and lead to good predictive statistics for these properties. These models were subsequently used to predict the properties of virtual solar cells libraries highlighting interesting dependencies of PV properties on MO compositions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katti, Amogh; Di Fatta, Giuseppe; Naughton III, Thomas J

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implementedmore » and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.« less

Imaging Algorithms for Evaluating Suspected Rotator Cuff Disease: Society of Radiologists in Ultrasound Consensus Conference Statement

PubMed Central

Jacobson, Jon A.; Benson, Carol B.; Bancroft, Laura W.; Bedi, Asheesh; McShane, John M.; Miller, Theodore T.; Parker, Laurence; Smith, Jay; Steinbach, Lynne S.; Teefey, Sharlene A.; Thiele, Ralf G.; Tuite, Michael J.; Wise, James N.; Yamaguchi, Ken

2013-01-01

The Society of Radiologists in Ultrasound convened a panel of specialists from a variety of medical disciplines to reach a consensus about the recommended imaging evaluation of painful shoulders with clinically suspected rotator cuff disease. The panel met in Chicago, Ill, on October 18 and 19, 2011, and created this consensus statement regarding the roles of radiography, ultrasonography (US), computed tomography (CT), CT arthrography, magnetic resonance (MR) imaging, and MR arthrography. The consensus panel consisted of two co-moderators, a facilitator, a statistician and health care economist, and 10 physicians who have specialty expertise in shoulder pain evaluation and/or treatment. Of the 13 physicians on the panel, nine were radiologists who were chosen to represent a broad range of skill sets in diagnostic imaging, different practice types (private and academic), and different geographical regions of the United States. Five of the radiologists routinely performed musculoskeletal US as part of their practice and four did not. There was also one representative from each of the following clinical specialties: rheumatology, physical medicine and rehabilitation, orthopedic surgery, and nonoperative sports medicine. The goal of this conference was to construct several algorithms with which to guide the imaging evaluation of suspected rotator cuff disease in patients with a native rotator cuff, patients with a repaired rotator cuff, and patients who have undergone shoulder replacement. The panel hopes that these recommendations will lead to greater uniformity in rotator cuff imaging and more cost-effective care for patients suspected of having rotator cuff abnormality. © RSNA, 2013 PMID:23401583

Texas Children's Medication Algorithm Project: Update from Texas Consensus Conference Panel on Medication Treatment of Childhood Major Depressive Disorder

ERIC Educational Resources Information Center

Hughes, Carroll W.; Emslie, Graham J.; Crismon, M. Lynn; Posner, Kelly; Birmaher, Boris; Ryan, Neal; Jensen, Peter; Curry, John; Vitiello, Benedetto; Lopez, Molly; Shon, Steve P.; Pliszka, Steven R.; Trivedi, Madhukar H.

2007-01-01

Objective: To revise and update consensus guidelines for medication treatment algorithms for childhood major depressive disorder based on new scientific evidence and expert clinical consensus when evidence is lacking. Method: A consensus conference was held January 13-14, 2005, that included academic clinicians and researchers, practicing…

Challenges in Diagnosing Narcolepsy without Cataplexy: A Consensus Statement

PubMed Central

Baumann, Christian R.; Mignot, Emmanuel; Lammers, Gert Jan; Overeem, Sebastiaan; Arnulf, Isabelle; Rye, David; Dauvilliers, Yves; Honda, Makoto; Owens, Judith A.; Plazzi, Giuseppe; Scammell, Thomas E.

2014-01-01

Background: Diagnosing narcolepsy without cataplexy is often a challenge as the symptoms are nonspecific, current diagnostic tests are limited, and there are no useful biomarkers. In this report, we review the clinical and physiological aspects of narcolepsy without cataplexy, the limitations of available diagnostic procedures, and the differential diagnoses, and we propose an approach for more accurate diagnosis of narcolepsy without cataplexy. Methods: A group of clinician-scientists experienced in narcolepsy reviewed the literature and convened to discuss current diagnostic tools, and to map out directions for research that should lead to a better understanding and more accurate diagnosis of narcolepsy without cataplexy. Recommendations: To aid in the identification of narcolepsy without cataplexy, we review key indicators of narcolepsy and present a diagnostic algorithm. A detailed clinical history is mainly helpful to rule out other possible causes of chronic sleepiness. The multiple sleep latency test remains the most important measure, and prior sleep deprivation, shift work, or circadian disorders should be excluded by actigraphy or sleep logs. A short REM sleep latency (≤ 15 minutes) on polysomnography can aid in the diagnosis of narcolepsy without cataplexy, although sensitivity is low. Finally, measurement of hypocretin levels can helpful, as levels are low to intermediate in 10% to 30% of narcolepsy without cataplexy patients. Citation: Baumann CR, Mignot E, Lammers GJ, Overeem S, Arnulf I, Rye D, Dauvilliers Y, Honda M, Owens JA, Plazzi G, Scammell TE. Challenges in diagnosing narcolepsy without cataplexy: a consensus statement. SLEEP 2014;37(6):1035-1042. PMID:24882898

Polynomial-Time Algorithms for Building a Consensus MUL-Tree

PubMed Central

Cui, Yun; Jansson, Jesper

2012-01-01

Abstract A multi-labeled phylogenetic tree, or MUL-tree, is a generalization of a phylogenetic tree that allows each leaf label to be used many times. MUL-trees have applications in biogeography, the study of host–parasite cospeciation, gene evolution studies, and computer science. Here, we consider the problem of inferring a consensus MUL-tree that summarizes a given set of conflicting MUL-trees, and present the first polynomial-time algorithms for solving it. In particular, we give a straightforward, fast algorithm for building a strict consensus MUL-tree for any input set of MUL-trees with identical leaf label multisets, as well as a polynomial-time algorithm for building a majority rule consensus MUL-tree for the special case where every leaf label occurs at most twice. We also show that, although it is NP-hard to find a majority rule consensus MUL-tree in general, the variant that we call the singular majority rule consensus MUL-tree can be constructed efficiently whenever it exists. PMID:22963134

Polynomial-time algorithms for building a consensus MUL-tree.

PubMed

Cui, Yun; Jansson, Jesper; Sung, Wing-Kin

2012-09-01

A multi-labeled phylogenetic tree, or MUL-tree, is a generalization of a phylogenetic tree that allows each leaf label to be used many times. MUL-trees have applications in biogeography, the study of host-parasite cospeciation, gene evolution studies, and computer science. Here, we consider the problem of inferring a consensus MUL-tree that summarizes a given set of conflicting MUL-trees, and present the first polynomial-time algorithms for solving it. In particular, we give a straightforward, fast algorithm for building a strict consensus MUL-tree for any input set of MUL-trees with identical leaf label multisets, as well as a polynomial-time algorithm for building a majority rule consensus MUL-tree for the special case where every leaf label occurs at most twice. We also show that, although it is NP-hard to find a majority rule consensus MUL-tree in general, the variant that we call the singular majority rule consensus MUL-tree can be constructed efficiently whenever it exists.

Validation of consensus panel diagnosis in dementia.

PubMed

Gabel, Matthew J; Foster, Norman L; Heidebrink, Judith L; Higdon, Roger; Aizenstein, Howard J; Arnold, Steven E; Barbas, Nancy R; Boeve, Bradley F; Burke, James R; Clark, Christopher M; Dekosky, Steven T; Farlow, Martin R; Jagust, William J; Kawas, Claudia H; Koeppe, Robert A; Leverenz, James B; Lipton, Anne M; Peskind, Elaine R; Turner, R Scott; Womack, Kyle B; Zamrini, Edward Y

2010-12-01

The clinical diagnosis of dementing diseases largely depends on the subjective interpretation of patient symptoms. Consensus panels are frequently used in research to determine diagnoses when definitive pathologic findings are unavailable. Nevertheless, research on group decision making indicates that many factors can adversely affect panel performance. To determine conditions that improve consensus panel diagnosis. Comparison of neuropathologic diagnoses with individual and consensus panel diagnoses based on clinical scenarios only, fludeoxyglucose F 18 positron emission tomography images only, and scenarios plus images. Expert and trainee individual and consensus panel deliberations using a modified Delphi method in a pilot research study of the diagnostic utility of fludeoxyglucose F 18 positron emission tomography. Forty-five patients with pathologically confirmed Alzheimer disease or frontotemporal dementia. Statistical measures of diagnostic accuracy, agreement, and confidence for individual raters and panelists before and after consensus deliberations. The consensus protocol using trainees and experts surpassed the accuracy of individual expert diagnoses when clinical information elicited diverse judgments. In these situations, consensus was 3.5 times more likely to produce positive rather than negative changes in the accuracy and diagnostic certainty of individual panelists. A rule that forced group consensus was at least as accurate as majority and unanimity rules. Using a modified Delphi protocol to arrive at a consensus diagnosis is a reasonable substitute for pathologic information. This protocol improves diagnostic accuracy and certainty when panelist judgments differ and is easily adapted to other research and clinical settings while avoiding the potential pitfalls of group decision making.

On the Control of Consensus Networks: Theory and Applications

NASA Astrophysics Data System (ADS)

Hudoba de Badyn, Mathias

Signed networks allow the study of positive and negative interactions between agents. In this thesis, three papers are presented that address controllability of networked dynamics. First, controllability of signed consensus networks is approached from a symmetry perspective, for both linear and nonlinear consensus protocols. It is shown that the graph-theoretic property of signed networks known as structural balance renders the consensus protocol uncontrollable when coupled with a certain type of symmetry. Stabilizability and output controllability of signed linear consensus is also examined, as well as a data-driven approach to finding bipartite consensus stemming from structural balance for signed nonlinear consensus. Second, an algorithm is constructed that allows one to grow a network while preserving controllability, and some generalizations of this algorithm are presented. Submodular optimization is used to analyze a second algorithm that adds nodes to a network to maximize the network connectivity.

Medical management of hyperglycaemia in type 2 diabetes mellitus: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement from the American Diabetes Association and the European Association for the Study of Diabetes.

PubMed

Nathan, D M; Buse, J B; Davidson, M B; Ferrannini, E; Holman, R R; Sherwin, R; Zinman, B

2009-01-01

The consensus algorithm for the medical management of type 2 diabetes was published in August 2006 with the expectation that it would be updated, based on the availability of new interventions and new evidence to establish their clinical role. The authors continue to endorse the principles used to develop the algorithm and its major features. We are sensitive to the risks of changing the algorithm cavalierly or too frequently, without compelling new information. An update to the consensus algorithm published in January 2008 specifically addressed safety issues surrounding the thiazolidinediones. In this revision, we focus on the new classes of medications that now have more clinical data and experience.

Evidence-based development of a diagnosis-dependent therapy planning system and its implementation in modern diagnostic software.

PubMed

Ahlers, M O; Jakstat, H A

2005-07-01

The prerequisite for structured individual therapy of craniomandibular dysfunctions is differential diagnostics. Suggestions for the structured recording of findings and their structured evaluation beyond the global diagnosis of "craniomandibular disorders" have been published. Only this structured approach enables computerization of the diagnostic process. The respective software is available for use in practice (CMDcheck for CMD screening, CMDfact for the differential diagnostics). Based on this structured diagnostics, knowledge-based therapy planning is also conceivable. The prerequisite for this would be a model of achieving consensus on the indicated forms of therapy related to the diagnosis. Therefore, a procedure for evidence-based achievement of consensus on suitable forms of therapy in CMD was developed first in multicentric cooperation, and then implemented in corresponding software. The clinical knowledge of experienced specialists was included consciously for the consensus achievement process. At the same time, anonymized mathematical statistical evaluations were used for control and objectification. Different examiners form different departments of several universities working independently of one another assigned the theoretically conceiveable therapeutic alternatives to the already published diagnostic scheme. After anonymization, the correlation of these assignments was then calculated mathematically. For achieving consensus in those cases for which no agreement initally existed, agreement was subsequently arrived at in the course of a consensus conference on the basis of literature evaluations and the discussion of clinical case examples. This consensus in turn finally served as the basis of a therapy planner implemented in the above-mentioned diagnostic software CMDfact. Contributing to quality assurance, the principles of programming this assistant as well as the interface for linking into the diagnostic software are documented and also published here.

[Spanish consensus on infantile haemangioma].

PubMed

Baselga Torres, Eulalia; Bernabéu Wittel, José; van Esso Arbolave, Diego L; Febrer Bosch, María Isabel; Carrasco Sanz, Ángel; de Lucas Laguna, Raúl; Del Pozo Losada, Jesús; Hernández Martín, Ángela; Jiménez Montañés, Lorenzo; López Gutiérrez, Juan Carlos; Martín-Santiago, Ana; Redondo Bellón, Pedro; Ruíz-Canela Cáceres, Juan; Torrelo Fernández, Antonio; Vera Casaño, Ángel; Vicente Villa, María Asunción

2016-11-01

Infantile haemangiomas are benign tumours produced by the proliferation of endothelial cells of blood vessels, with a high incidence in children under the age of one year (4-10%). It is estimated that 12% of them require treatment. This treatment must be administered according to clinical practice guidelines, expert experience, patient characteristics and parent preferences. The consensus process was performed by using scientific evidence on the diagnosis and treatment of infantile haemangiomas, culled from a systematic review of the literature, together with specialist expert opinions. The recommendations issued were validated by the specialists, who also provided their level of agreement. This document contains recommendations on the classification, associations, complications, diagnosis, treatment, and follow-up of patients with infantile haemangioma. It also includes action algorithms, and addresses multidisciplinary management and referral criteria between the different specialities involved in the clinical management of this type of patient. The recommendations and the diagnostic and therapeutic algorithms of infantile haemangiomas contained in this document are a useful tool for the proper management of these patients. Copyright © 2015 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

IAC Standardized Reporting of Breast Fine-Needle Aspiration Biopsy Cytology.

PubMed

Field, Andrew S; Schmitt, Fernando; Vielh, Philippe

2017-01-01

There have been many changes in the roles of fine-needle aspiration biopsy (FNAB) and core needle biopsy (CNB) in the diagnostic workup of breast lesions in routine breast clinics and in mammographic breast screening programs, as well as changes in the management algorithms utilized and the treatments available, since the NCI consensus on breast FNAB cytology in 1996. A standardized approach will improve training and performance of FNAB and smear-making techniques, and structured reporting will improve the quality and reproducibility of reports across departments, cities and countries providing a basis for quality assurance measures and improving patient care and facilitating research. Linking cytology reports to management algorithms will increase the clinicians' use of FNAB cytology and where appropriate CNB, and enhance the use of ancillary tests for prognostic testing. The IAC recognizes that the local medical infrastructure and resources for breast imaging, biopsy and treatment will influence the diagnostic workup and management of breast disease, but best practice guidelines should be established and modified as required. © 2016 S. Karger AG, Basel.

Current Approaches and Clinician Attitudes to the Use of Cerebrospinal Fluid Biomarkers in Diagnostic Evaluation of Dementia in Europe.

PubMed

Miller, Anne-Marie; Balasa, Mircea; Blennow, Kaj; Gardiner, Mary; Rutkowska, Aleksandra; Scheltens, Philip; Teunissen, Charlotte E; Visser, Pieter Jelle; Winblad, Bengt; Waldemar, Gunhild; Lawlor, Brian

2017-01-01

BIOMARKAPD seeks to diminish the barriers associated with the clinical use of cerebrospinal fluid (CSF) biomarker analysis by reducing variation in CSF laboratory methodologies and generating consensus recommendations on their clinical interpretation and application for dementia diagnosis. To examine the disparity in practitioner attitudes and clinical practice relating to the use of CSF biomarkers for dementia diagnosis across Europe. Clinical dementia experts were surveyed on the prevalence of national consensus guidelines and analytical reimbursement across Europe, their biomarker platform preferences, lumbar puncture methodologies and application of reference values and cut-offs for CSF analysis. 74% of respondents (total n = 51) use CSF biomarkers in clinical practice and 69% perform lumbar punctures on an outpatient basis. Most use CSF biomarkers to diagnose atypical (84%) and early-onset cases of cognitive impairment (71%) and for the differential diagnosis of other dementias (69%). 82% state they are sufficiently informed about CSF biomarkers yet 61% report a lack of national consensus guidelines on their use for dementia diagnosis. 48% of countries represented do not reimburse clinical CSF analysis costs. 43% report using normal reference ranges derived from publications. Variations in attitude and practice relating to CSF biomarkers, widely recognised as barriers to their clinical acceptance, remain evident within and between countries across Europe, even in expert centres. These shortcomings must be addressed by developing consensus guidelines on CSF-related methodologies and their clinical application, to further their use for the diagnostic evaluation of dementia.

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Model of Decision Making through Consensus in Ranking Case

NASA Astrophysics Data System (ADS)

Tarigan, Gim; Darnius, Open

2018-01-01

The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

Document-Level Classification of CT Pulmonary Angiography Reports based on an Extension of the ConText Algorithm

PubMed Central

Chapman, Brian E.; Lee, Sean; Kang, Hyunseok Peter; Chapman, Wendy W.

2011-01-01

In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes’ classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes’ classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes’ classifier using bigrams. PMID:21459155

An expert panel-based study on recognition of gastro-esophageal reflux in difficult esophageal pH-impedance tracings.

PubMed

Smits, M J; Loots, C M; van Wijk, M P; Bredenoord, A J; Benninga, M A; Smout, A J P M

2015-05-01

Despite existing criteria for scoring gastro-esophageal reflux (GER) in esophageal multichannel pH-impedance measurement (pH-I) tracings, inter- and intra-rater variability is large and agreement with automated analysis is poor. To identify parameters of difficult to analyze pH-I patterns and combine these into a statistical model that can identify GER episodes with an international consensus as gold standard. Twenty-one experts from 10 countries were asked to mark GER presence for adult and pediatric pH-I patterns in an online pre-assessment. During a consensus meeting, experts voted on patterns not reaching majority consensus (>70% agreement). Agreement was calculated between raters, between consensus and individual raters, and between consensus and software generated automated analysis. With eight selected parameters, multiple logistic regression analysis was performed to describe an algorithm sensitive and specific for detection of GER. Majority consensus was reached for 35/79 episodes in the online pre-assessment (interrater κ = 0.332). Mean agreement between pre-assessment scores and final consensus was moderate (κ = 0.466). Combining eight pH-I parameters did not result in a statistically significant model able to identify presence of GER. Recognizing a pattern as retrograde is the best indicator of GER, with 100% sensitivity and 81% specificity with expert consensus as gold standard. Agreement between experts scoring difficult impedance patterns for presence or absence of GER is poor. Combining several characteristics into a statistical model did not improve diagnostic accuracy. Only the parameter 'retrograde propagation pattern' is an indicator of GER in difficult pH-I patterns. © 2015 John Wiley & Sons Ltd.

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine (AEM) consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization," was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to: 1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; 2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and 3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified prior to the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were 164 individuals involved in the conference spanning various specialties, including emergency medicine (EM), radiology, surgery, medical physics, and the decision sciences. This issue of AEM is dedicated to the proceedings of the 16th annual AEM consensus conference as well as original research related to emergency diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Consensus generation and variant detection by Celera Assembler.

PubMed

Denisov, Gennady; Walenz, Brian; Halpern, Aaron L; Miller, Jason; Axelrod, Nelson; Levy, Samuel; Sutton, Granger

2008-04-15

We present an algorithm to identify allelic variation given a Whole Genome Shotgun (WGS) assembly of haploid sequences, and to produce a set of haploid consensus sequences rather than a single consensus sequence. Existing WGS assemblers take a column-by-column approach to consensus generation, and produce a single consensus sequence which can be inconsistent with the underlying haploid alleles, and inconsistent with any of the aligned sequence reads. Our new algorithm uses a dynamic windowing approach. It detects alleles by simultaneously processing the portions of aligned reads spanning a region of sequence variation, assigns reads to their respective alleles, phases adjacent variant alleles and generates a consensus sequence corresponding to each confirmed allele. This algorithm was used to produce the first diploid genome sequence of an individual human. It can also be applied to assemblies of multiple diploid individuals and hybrid assemblies of multiple haploid organisms. Being applied to the individual human genome assembly, the new algorithm detects exactly two confirmed alleles and reports two consensus sequences in 98.98% of the total number 2,033311 detected regions of sequence variation. In 33,269 out of 460,373 detected regions of size >1 bp, it fixes the constructed errors of a mosaic haploid representation of a diploid locus as produced by the original Celera Assembler consensus algorithm. Using an optimized procedure calibrated against 1 506 344 known SNPs, it detects 438 814 new heterozygous SNPs with false positive rate 12%. The open source code is available at: http://wgs-assembler.cvs.sourceforge.net/wgs-assembler/

Algorithms used in the Airborne Lidar Processing System (ALPS)

USGS Publications Warehouse

Nagle, David B.; Wright, C. Wayne

2016-05-23

The Airborne Lidar Processing System (ALPS) analyzes Experimental Advanced Airborne Research Lidar (EAARL) data—digitized laser-return waveforms, position, and attitude data—to derive point clouds of target surfaces. A full-waveform airborne lidar system, the EAARL seamlessly and simultaneously collects mixed environment data, including submerged, sub-aerial bare earth, and vegetation-covered topographies.ALPS uses three waveform target-detection algorithms to determine target positions within a given waveform: centroid analysis, leading edge detection, and bottom detection using water-column backscatter modeling. The centroid analysis algorithm detects opaque hard surfaces. The leading edge algorithm detects topography beneath vegetation and shallow, submerged topography. The bottom detection algorithm uses water-column backscatter modeling for deeper submerged topography in turbid water.The report describes slant range calculations and explains how ALPS uses laser range and orientation measurements to project measurement points into the Universal Transverse Mercator coordinate system. Parameters used for coordinate transformations in ALPS are described, as are Interactive Data Language-based methods for gridding EAARL point cloud data to derive digital elevation models. Noise reduction in point clouds through use of a random consensus filter is explained, and detailed pseudocode, mathematical equations, and Yorick source code accompany the report.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology

PubMed Central

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y.-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-01-01

Abstract Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy. PMID:29850871

Fast and Accurate Construction of Ultra-Dense Consensus Genetic Maps Using Evolution Strategy Optimization

PubMed Central

Mester, David; Ronin, Yefim; Schnable, Patrick; Aluru, Srinivas; Korol, Abraham

2015-01-01

Our aim was to develop a fast and accurate algorithm for constructing consensus genetic maps for chip-based SNP genotyping data with a high proportion of shared markers between mapping populations. Chip-based genotyping of SNP markers allows producing high-density genetic maps with a relatively standardized set of marker loci for different mapping populations. The availability of a standard high-throughput mapping platform simplifies consensus analysis by ignoring unique markers at the stage of consensus mapping thereby reducing mathematical complicity of the problem and in turn analyzing bigger size mapping data using global optimization criteria instead of local ones. Our three-phase analytical scheme includes automatic selection of ~100-300 of the most informative (resolvable by recombination) markers per linkage group, building a stable skeletal marker order for each data set and its verification using jackknife re-sampling, and consensus mapping analysis based on global optimization criterion. A novel Evolution Strategy optimization algorithm with a global optimization criterion presented in this paper is able to generate high quality, ultra-dense consensus maps, with many thousands of markers per genome. This algorithm utilizes "potentially good orders" in the initial solution and in the new mutation procedures that generate trial solutions, enabling to obtain a consensus order in reasonable time. The developed algorithm, tested on a wide range of simulated data and real world data (Arabidopsis), outperformed two tested state-of-the-art algorithms by mapping accuracy and computation time. PMID:25867943

Minimum-Time Consensus-Based Approach for Power System Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Tao; Wu, Di; Sun, Yannan

2016-02-01

This paper presents minimum-time consensus based distributed algorithms for power system applications, such as load shedding and economic dispatch. The proposed algorithms are capable of solving these problems in a minimum number of time steps instead of asymptotically as in most of existing studies. Moreover, these algorithms are applicable to both undirected and directed communication networks. Simulation results are used to validate the proposed algorithms.

Validated methods for identifying tuberculosis patients in health administrative databases: systematic review.

PubMed

Ronald, L A; Ling, D I; FitzGerald, J M; Schwartzman, K; Bartlett-Esquilant, G; Boivin, J-F; Benedetti, A; Menzies, D

2017-05-01

An increasing number of studies are using health administrative databases for tuberculosis (TB) research. However, there are limitations to using such databases for identifying patients with TB. To summarise validated methods for identifying TB in health administrative databases. We conducted a systematic literature search in two databases (Ovid Medline and Embase, January 1980-January 2016). We limited the search to diagnostic accuracy studies assessing algorithms derived from drug prescription, International Classification of Diseases (ICD) diagnostic code and/or laboratory data for identifying patients with TB in health administrative databases. The search identified 2413 unique citations. Of the 40 full-text articles reviewed, we included 14 in our review. Algorithms and diagnostic accuracy outcomes to identify TB varied widely across studies, with positive predictive value ranging from 1.3% to 100% and sensitivity ranging from 20% to 100%. Diagnostic accuracy measures of algorithms using out-patient, in-patient and/or laboratory data to identify patients with TB in health administrative databases vary widely across studies. Use solely of ICD diagnostic codes to identify TB, particularly when using out-patient records, is likely to lead to incorrect estimates of case numbers, given the current limitations of ICD systems in coding TB.

A report on the Academic Emergency Medicine 2015 consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization".

PubMed

Gunn, Martin L; Marin, Jennifer R; Mills, Angela M; Chong, Suzanne T; Froemming, Adam T; Johnson, Jamlik O; Kumaravel, Manickam; Sodickson, Aaron D

2016-08-01

In May 2015, the Academic Emergency Medicine consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization" was held. The goal of the conference was to develop a high-priority research agenda regarding emergency diagnostic imaging on which to base future research. In addition to representatives from the Society of Academic Emergency Medicine, the multidisciplinary conference included members of several radiology organizations: American Society for Emergency Radiology, Radiological Society of North America, the American College of Radiology, and the American Association of Physicists in Medicine. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Through a multistep consensus process, participants developed targeted research questions for future research in six content areas within emergency diagnostic imaging: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use.

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2006 update.

PubMed

Moore, Troy A; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Robinson, Delbert G; Schooler, Nina R; Shon, Steven P; Stroup, T Scott; Miller, Alexander L

2007-11-01

A panel of academic psychiatrists and pharmacists, clinicians from the Texas public mental health system, advocates, and consumers met in June 2006 in Dallas, Tex., to review recent evidence in the pharmacologic treatment of schizophrenia. The goal of the consensus conference was to update and revise the Texas Medication Algorithm Project (TMAP) algorithm for schizophrenia used in the Texas Implementation of Medication Algorithms, a statewide quality assurance program for treatment of major psychiatric illness. Four questions were identified via premeeting teleconferences. (1) Should antipsychotic treatment of first-episode schizophrenia be different from that of multiepisode schizophrenia? (2) In which algorithm stages should first-generation antipsychotics (FGAs) be an option? (3) How many antipsychotic trials should precede a clozapine trial? (4) What is the status of augmentation strategies for clozapine? Subgroups reviewed the evidence in each area and presented their findings at the conference. The algorithm was updated to incorporate the following recommendations. (1) Persons with first-episode schizophrenia typically require lower antipsychotic doses and are more sensitive to side effects such as weight gain and extrapyramidal symptoms (group consensus). Second-generation antipsychotics (SGAs) are preferred for treatment of first-episode schizophrenia (majority opinion). (2) FGAs should be included in algorithm stages after first episode that include SGAs other than clozapine as options (group consensus). (3) The recommended number of trials of other antipsychotics that should precede a clozapine trial is 2, but earlier use of clozapine should be considered in the presence of persistent problems such as suicidality, comorbid violence, and substance abuse (group consensus). (4) Augmentation is reasonable for persons with inadequate response to clozapine, but published results on augmenting agents have not identified replicable positive results (group consensus). These recommendations are meant to provide a framework for clinical decision making, not to replace clinical judgment. As with any algorithm, treatment practices will evolve beyond the recommendations of this consensus conference as new evidence and additional medications become available.

Defining the Needs for Next Generation Assays for Tuberculosis

PubMed Central

Denkinger, Claudia M.; Kik, Sandra V.; Cirillo, Daniela Maria; Casenghi, Martina; Shinnick, Thomas; Weyer, Karin; Gilpin, Chris; Boehme, Catharina C.; Schito, Marco; Kimerling, Michael; Pai, Madhukar

2015-01-01

To accelerate the fight against tuberculosis, major diagnostic challenges need to be addressed urgently. Post-2015 targets are unlikely to be met without the use of novel diagnostics that are more accurate and can be used closer to where patients first seek care in affordable diagnostic algorithms. This article describes the efforts by the stakeholder community that led to the identification of the high-priority diagnostic needs in tuberculosis. Subsequently target product profiles for the high-priority diagnostic needs were developed and reviewed in a World Health Organization (WHO)-led consensus meeting. The high-priority diagnostic needs included (1) a sputum-based replacement test for smear-microscopy; (2) a non-sputum-based biomarker test for all forms of tuberculosis, ideally suitable for use at levels below microscopy centers; (3) a simple, low cost triage test for use by first-contact care providers as a rule-out test, ideally suitable for use by community health workers; and (4) a rapid drug susceptibility test for use at the microscopy center level. The developed target product profiles, along with complimentary work presented in this supplement, will help to facilitate the interaction between the tuberculosis community and the diagnostics industry with the goal to lead the way toward the post-2015 global tuberculosis targets. PMID:25765104

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion

PubMed Central

Bone, Daniel; Bishop, Somer; Black, Matthew P.; Goodwin, Matthew S.; Lord, Catherine; Narayanan, Shrikanth S.

2016-01-01

Background Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely-used ASD screening and diagnostic tools. Methods The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders (DD), split at age 10. Algorithms were created via a robust ML classifier, support vector machine (SVM), while targeting best-estimate clinical diagnosis of ASD vs. non-ASD. Parameter settings were tuned in multiple levels of cross-validation. Results The created algorithms were more effective (higher performing) than current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. Conclusions ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. PMID:27090613

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

PubMed

Bone, Daniel; Bishop, Somer L; Black, Matthew P; Goodwin, Matthew S; Lord, Catherine; Narayanan, Shrikanth S

2016-08-01

Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely used ASD screening and diagnostic tools. The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders, split at age 10. Algorithms were created via a robust ML classifier, support vector machine, while targeting best-estimate clinical diagnosis of ASD versus non-ASD. Parameter settings were tuned in multiple levels of cross-validation. The created algorithms were more effective (higher performing) than the current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight the limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. © 2016 Association for Child and Adolescent Mental Health.

Accurate derivation of heart rate variability signal for detection of sleep disordered breathing in children.

PubMed

Chatlapalli, S; Nazeran, H; Melarkod, V; Krishnam, R; Estrada, E; Pamula, Y; Cabrera, S

2004-01-01

The electrocardiogram (ECG) signal is used extensively as a low cost diagnostic tool to provide information concerning the heart's state of health. Accurate determination of the QRS complex, in particular, reliable detection of the R wave peak, is essential in computer based ECG analysis. ECG data from Physionet's Sleep-Apnea database were used to develop, test, and validate a robust heart rate variability (HRV) signal derivation algorithm. The HRV signal was derived from pre-processed ECG signals by developing an enhanced Hilbert transform (EHT) algorithm with built-in missing beat detection capability for reliable QRS detection. The performance of the EHT algorithm was then compared against that of a popular Hilbert transform-based (HT) QRS detection algorithm. Autoregressive (AR) modeling of the HRV power spectrum for both EHT- and HT-derived HRV signals was achieved and different parameters from their power spectra as well as approximate entropy were derived for comparison. Poincare plots were then used as a visualization tool to highlight the detection of the missing beats in the EHT method After validation of the EHT algorithm on ECG data from the Physionet, the algorithm was further tested and validated on a dataset obtained from children undergoing polysomnography for detection of sleep disordered breathing (SDB). Sensitive measures of accurate HRV signals were then derived to be used in detecting and diagnosing sleep disordered breathing in children. All signal processing algorithms were implemented in MATLAB. We present a description of the EHT algorithm and analyze pilot data for eight children undergoing nocturnal polysomnography. The pilot data demonstrated that the EHT method provides an accurate way of deriving the HRV signal and plays an important role in extraction of reliable measures to distinguish between periods of normal and sleep disordered breathing (SDB) in children.

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization" was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging use and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified before the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with the planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were a total of 164 individuals involved in the conference and spanned various specialties, including general emergency medicine, pediatric emergency medicine, radiology, surgery, medical physics, and the decision sciences.

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

PubMed Central

Ambros, P F; Ambros, I M; Brodeur, G M; Haber, M; Khan, J; Nakagawara, A; Schleiermacher, G; Speleman, F; Spitz, R; London, W B; Cohn, S L; Pearson, A D J; Maris, J M

2009-01-01

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies. PMID:19401703

[Consensus statement on the clinical management of human immunodeficiency virus-associated neurocognitive disorders].

PubMed

Podzamczer Palter, Daniel; Muñoz-Moreno, José A; Alcolea Rodríguez, Daniel; Alonso Villaverde, Carlos; Antela López, Antonio; Blanch Andreu, Jordi; Casado Osorio, José Luis; Galindo Puerto, M José; Garolera i Freixa, Maite; Locutura Rupérez, Jaime; Lleó Bisa, Albert; Prats París, Anna; Pérez-Valero, Ignacio; Portilla Sogorb, Joaquín; Rovira Cañellas, Alex; Téllez Molina, M Jesús; Tiraboschi, Juan Manuel; Vergara Moragues, Esperanza; Arribas López, José Ramón; Goenaga Sánchez, Miguel Ángel; de León-Naranjo, Fernando Lozano; Martínez Chamorro, Esteban; Polo Rodríguez, Rosa; Muñoz-Moreno, José A; Podzamczer, Daniel

2014-01-01

To develop a consensus document containing clinical recommendations for the management of human immunodeficiency virus (HIV)-associated neurocognitive disorder (HAND). We assembled a panel of experts appointed by GeSIDA and the Secretariat of the National AIDS Plan (PNS), including internal medicine physicians with expertise in the field of HIV, neuropsychologists, neurologists and neuroradiologists. Scientific information was reviewed to October 2012 in publications and conference papers. In support of the recommendations using two levels of evidence: the strength of the recommendation in the opinion of the experts (A, B, C) and the level of empirical evidence (I, II, III), two levels based on the criteria of the Infectious Disease Society of America, already used in previous documents GeSIDA/SPNS. Multiple recommendations for the clinical management of these disorders are provided, including two graphics algorithms, considering both the diagnostic and possible therapeutic strategies. Neurocognitive disorders associated with HIV infection is currently highly prevalent, are associated with a decreased quality of life and daily activities, and given the possibility of occurrence of an increase in the coming years, there is a need to adequately manage these disorders, from a diagnostic as well as therapeutic point of view, and always from a multidisciplinary perspective. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Consensus Algorithms for Networks of Systems with Second- and Higher-Order Dynamics

NASA Astrophysics Data System (ADS)

Fruhnert, Michael

This thesis considers homogeneous networks of linear systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilizable. We show that, in continuous-time, consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. For networks of continuous-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback. For networks of discrete-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Schur. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. We show that consensus can always be achieved for marginally stable systems and discretized systems. Simple conditions for consensus achieving controllers are obtained when the Laplacian eigenvalues are all real. For networks of continuous-time time-variant higher-order systems, we show that uniform consensus can always be achieved if systems are quadratically stabilizable. In this case, we provide a simple condition to obtain a linear feedback control. For networks of discrete-time higher-order systems, we show that constant gains can be chosen such that consensus is achieved for a variety of network topologies. First, we develop simple results for networks of time-invariant systems and networks of time-variant systems that are given in controllable canonical form. Second, we formulate the problem in terms of Linear Matrix Inequalities (LMIs). The condition found simplifies the design process and avoids the parallel solution of multiple LMIs. The result yields a modified Algebraic Riccati Equation (ARE) for which we present an equivalent LMI condition.

Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

PubMed

Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

2016-03-03

This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

From autoantibody research to standardized diagnostic assays in the management of human diseases - report of the 12th Dresden Symposium on Autoantibodies.

PubMed

Conrad, K; Andrade, L E C; Chan, E K L; Mahler, M; Meroni, P L; Pruijn, G J M; Steiner, G; Shoenfeld, Y

2016-07-01

Testing for autoantibodies (AABs) is becoming more and more relevant, not only for diagnosing autoimmune diseases (AIDs) but also for the differentiation of defined AID subtypes with different clinical manifestations, course and prognosis as well as the very early diagnosis for adequate management in the context of personalized medicine. A major challenge to improve diagnostic accuracy is to harmonize or even standardize AAB analyses. This review presents the results of the 12th Dresden Symposium on Autoantibodies that focused on several aspects of improving autoimmune diagnostics. Topics that are addressed include the International Consensus on ANA Patterns (ICAP) and the International Autoantibody Standardization (IAS) initiatives, the optimization of diagnostic algorithms, the description and evaluation of novel disease-specific AABs as well as the development and introduction of novel assays into routine diagnostics. This review also highlights important developments of recent years, most notably the improvement in diagnosing and predicting the course of rheumatoid arthritis, systemic sclerosis, idiopathic inflammatory myopathies, and of autoimmune neurological, gastrointestinal and liver diseases; the potential diagnostic role of anti-DFS70 antibodies and tumor-associated AABs. Furthermore, some hot topics in autoimmunity regarding disease pathogenesis and management are described. © The Author(s) 2016.

Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.

PubMed

Chapman, Brian E; Lee, Sean; Kang, Hyunseok Peter; Chapman, Wendy W

2011-10-01

In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes' classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes' classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes' classifier using bigrams. Copyright © 2011 Elsevier Inc. All rights reserved.

Digestive disease management in Japan: a report on the 6th diagnostic pathology summer fest in 2012.

PubMed

Ichikawa, Kazuhito; Fujimori, Takahiro; Moriya, Takuya; Ochiai, Atsushi; Yoshinaga, Shigetaka; Kushima, Ryouji; Nagahama, Ryuji; Ohkura, Yasuo; Tanaka, Shinji; Ajioka, Yoichi; Hirata, Ichiro; Tanaka, Masanori; Hoshihara, Yoshio; Kinoshita, Yoshikazu; Sasano, Hironobu; Iwashita, Akinori; Tomita, Shigeki; Hirota, Seiichi; Yao, Takashi; Fujii, Shigehiko; Matsuda, Takahisa; Ueno, Hideki; Ishikawa, Yuichi; Takubo, Kaiyo; Fukushima, Noriyoshi; Sugai, Tamotsu; Iwafuchi, Mitsuya; Imura, Jhoji; Manabe, Toshiaki; Fukayama, Masahisa

2013-01-01

The 6th Diagnostic Pathology Summer Fest, held in Tokyo on August 25-26, 2012, opened its gates for everyone in the medical profession. Basic pathology training can contribute to the improvement of algorithms for diagnosis and treatment. The 6th Summer Fest with the theme 'Pathology and Clinical Treatment of Gastrointestinal Diseases' was held at the Ito International Research Center, The University of Tokyo. On August 25, 'Treatment of Early Gastrointestinal Cancer and New Guidelines' was discussed in the first session, followed by 'Biopsy Diagnosis of Digestive Tract: Key Points of Pathological Diagnosis for Inflammation and Their Clinical Significance' in the second session. On August 26, cases were discussed in the third session, and issues on pathological diagnosis and classification of neuroendorcrine tumor in the fourth session. The summaries of speeches and discussions are introduced along with the statements of each speaker. This meeting was not a formal evidence-based consensus conference, and 20 experts gave talks on their areas of specialty. Discussion was focused on how the management strategy should be standardized on the algorithm of patient care. © 2013 S. Karger AG, Basel.

Improvement of diagnostic agreement among pathologists in resolving an "atypical glands suspicious for cancer" diagnosis in prostate biopsies using a novel "Disease-Focused Diagnostic Review" quality improvement process.

PubMed

Shah, Rajal B; Leandro, Gioacchino; Romerocaces, Gloria; Bentley, James; Yoon, Jiyoon; Mendrinos, Savvas; Tadros, Yousef; Tian, Wei; Lash, Richard

2016-10-01

One of the major goals of an anatomic pathology laboratory quality program is to minimize unwarranted diagnostic variability and equivocal reporting. This study evaluated the utility of Miraca Life Sciences' "Disease-Focused Diagnostic Review" (DFDR) quality program in improving interobserver diagnostic reproducibility associated with classification of "atypical glands suspicious for adenocarcinoma" (ATYP) in prostate biopsies. Seventy-one selected prostate biopsies with a focus of ATYP were reviewed by 8 pathologists. Participants were blinded to the original diagnosis and were first asked to classify the ATYP as benign, atypical, or limited adenocarcinoma. DFDR comprised a "theoretical consensus" (in which pathologists first reached consensus on the morphological features they considered relevant for the diagnosis of limited prostatic adenocarcinoma), a didactic review including relevant literature, and "practical consensus" (pathologists performed joint microscopic sessions, reconciling each other's observations and positions evaluating a separate unique slide set). Participants were finally asked to reclassify the original 71 ATYP cases based on knowledge gleaned from DFDR. Pre- and post-DFDR interobserver reproducibility of overall diagnostic agreement was assessed. Interobserver reproducibility measured by Fleiss κ values of pre- and post-DFDR was 0.36 and 0.59, respectively (P=.006). Post-DFDR, there were significant improvement for "100% concordance" (P=.011) and reduction for "no consensus" (P=.0004) categories. Despite a lower pre-DFDR reproducibility for non-uropathology fellowship-trained (n=3, κ=0.38) versus uropathology fellowship-trained (n=5, κ=0.43) pathologists, both groups achieved similarly high post-DFDR κ levels (κ=0.58 and 0.56, respectively). DFDR represents an effective tool to formally achieve diagnostic consensus and reduce variability associated with critical diagnoses in an anatomic pathology practice. Copyright © 2016 Elsevier Inc. All rights reserved.

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

Consensus-based distributed estimation in multi-agent systems with time delay

NASA Astrophysics Data System (ADS)

Abdelmawgoud, Ahmed

During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

Management and prevention of refeeding syndrome in medical inpatients: An evidence-based and consensus-supported algorithm.

PubMed

Friedli, Natalie; Stanga, Zeno; Culkin, Alison; Crook, Martin; Laviano, Alessandro; Sobotka, Lubos; Kressig, Reto W; Kondrup, Jens; Mueller, Beat; Schuetz, Philipp

2018-03-01

Refeeding syndrome (RFS) can be a life-threatening metabolic condition after nutritional replenishment if not recognized early and treated adequately. There is a lack of evidence-based treatment and monitoring algorithm for daily clinical practice. The aim of the study was to propose an expert consensus guideline for RFS for the medical inpatient (not including anorexic patients) regarding risk factors, diagnostic criteria, and preventive and therapeutic measures based on a previous systematic literature search. Based on a recent qualitative systematic review on the topic, we developed clinically relevant recommendations as well as a treatment and monitoring algorithm for the clinical management of inpatients regarding RFS. With international experts, these recommendations were discussed and agreement with the recommendation was rated. Upon hospital admission, we recommend the use of specific screening criteria (i.e., low body mass index, large unintentional weight loss, little or no nutritional intake, history of alcohol or drug abuse) for risk assessment regarding the occurrence of RFS. According to the patient's individual risk for RFS, a careful start of nutritional therapy with a stepwise increase in energy and fluids goals and supplementation of electrolyte and vitamins, as well as close clinical monitoring, is recommended. We also propose criteria for the diagnosis of imminent and manifest RFS with practical treatment recommendations with adoption of the nutritional therapy. Based on the available evidence, we developed a practical algorithm for risk assessment, treatment, and monitoring of RFS in medical inpatients. In daily routine clinical care, this may help to optimize and standardize the management of this vulnerable patient population. We encourage future quality studies to further refine these recommendations. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential diagnosis of suspected multiple sclerosis: a consensus approach

PubMed Central

Miller, DH; Weinshenker, BG; Filippi, M; Banwell, BL; Cohen, JA; Freedman, MS; Galetta, SL; Hutchinson, M; Johnson, RT; Kappos, L; Kira, J; Lublin, FD; McFarland, HF; Montalban, X; Panitch, H; Richert, JR; Reingold, SC; Polman, CH

2008-01-01

Background and objectives Diagnosis of multiple sclerosis (MS) requires exclusion of diseases that could better explain the clinical and paraclinical findings. A systematic process for exclusion of alternative diagnoses has not been defined. An International Panel of MS experts developed consensus perspectives on MS differential diagnosis. Methods Using available literature and consensus, we developed guidelines for MS differential diagnosis, focusing on exclusion of potential MS mimics, diagnosis of common initial isolated clinical syndromes, and differentiating between MS and non-MS idiopathic inflammatory demyelinating diseases. Results We present recommendations for 1) clinical and paraclinical red flags suggesting alternative diagnoses to MS; 2) more precise definition of “clinically isolated syndromes” (CIS), often the first presentations of MS or its alternatives; 3) algorithms for diagnosis of three common CISs related to MS in the optic nerves, brainstem, and spinal cord; and 4) a classification scheme and diagnosis criteria for idiopathic inflammatory demyelinating disorders of the central nervous system. Conclusions Differential diagnosis leading to MS or alternatives is complex and a strong evidence base is lacking. Consensus-determined guidelines provide a practical path for diagnosis and will be useful for the non-MS specialist neurologist. Recommendations are made for future research to validate and support these guidelines. Guidance on the differential diagnosis process when MS is under consideration will enhance diagnostic accuracy and precision. PMID:18805839

Operator Objective Function Guidance for a Real-Time Unmanned Vehicle Scheduling Algorithm

DTIC Science & Technology

2012-12-01

Consensus - Based Decentralized Auctions for Robust Task Allocation ,” IEEE Transactions on Robotics and Automation, Vol. 25, No. 4, No. 4, 2009, pp. 912...planning for the fleet. The decentralized task planner used in OPS-USERS is the consensus - based bundle algorithm (CBBA), a decentralized , polynomial...and surveillance (OPS-USERS), which leverages decentralized algorithms for vehicle routing and task allocation . This

Transitional lumbosacral vertebrae and low back pain: diagnostic pitfalls and management of Bertolotti's syndrome.

PubMed

Almeida, Daniel Benzecry de; Mattei, Tobias Alécio; Sória, Marília Grando; Prandini, Mirto Nelso; Leal, André Giacomelli; Milano, Jerônimo Buzzeti; Ramina, Ricardo

2009-06-01

Bertolotti's syndrome is a spine disorder characterized by the occurrence of a congenital lumbar transverse mega-apophysis in a transitional vertebral body that usually articulates with the sacrum or the iliac bone. It has been considered a possible cause of low back pain. We analyzed the cases of Bertolotti's syndrome that failed clinical treatment and reviewed the literature concerning this subject. Five patients in our series had severe low back pain due to the neo-articulation and two of them were successfully submitted to surgical resection of the transverse mega-apophysis. Taking into account the clinical and surgical experience acquired with these cases, we propose a diagnostic-therapeutic algorithm. There is still no consensus about the most appropriate therapy for Bertolotti's syndrome. In patients in whom the mega-apophysis itself may be the source of back pain, surgical resection may be a safe and effective procedure.

Distributed consensus for metamorphic systems using a gossip algorithm for CAT(0) metric spaces

NASA Astrophysics Data System (ADS)

Bellachehab, Anass; Jakubowicz, Jérémie

2015-01-01

We present an application of distributed consensus algorithms to metamorphic systems. A metamorphic system is a set of identical units that can self-assemble to form a rigid structure. For instance, one can think of a robotic arm composed of multiple links connected by joints. The system can change its shape in order to adapt to different environments via reconfiguration of its constituting units. We assume in this work that several metamorphic systems form a network: two systems are connected whenever they are able to communicate with each other. The aim of this paper is to propose a distributed algorithm that synchronizes all the systems in the network. Synchronizing means that all the systems should end up having the same configuration. This aim is achieved in two steps: (i) we cast the problem as a consensus problem on a metric space and (ii) we use a recent distributed consensus algorithm that only make use of metrical notions.

Accurate ECG diagnosis of atrial tachyarrhythmias using quantitative analysis: a prospective diagnostic and cost-effectiveness study.

PubMed

Krummen, David E; Patel, Mitul; Nguyen, Hong; Ho, Gordon; Kazi, Dhruv S; Clopton, Paul; Holland, Marian C; Greenberg, Scott L; Feld, Gregory K; Faddis, Mitchell N; Narayan, Sanjiv M

2010-11-01

Quantitative ECG Analysis. Optimal atrial tachyarrhythmia management is facilitated by accurate electrocardiogram interpretation, yet typical atrial flutter (AFl) may present without sawtooth F-waves or RR regularity, and atrial fibrillation (AF) may be difficult to separate from atypical AFl or rapid focal atrial tachycardia (AT). We analyzed whether improved diagnostic accuracy using a validated analysis tool significantly impacts costs and patient care. We performed a prospective, blinded, multicenter study using a novel quantitative computerized algorithm to identify atrial tachyarrhythmia mechanism from the surface ECG in patients referred for electrophysiology study (EPS). In 122 consecutive patients (age 60 ± 12 years) referred for EPS, 91 sustained atrial tachyarrhythmias were studied. ECGs were also interpreted by 9 physicians from 3 specialties for comparison and to allow healthcare system modeling. Diagnostic accuracy was compared to the diagnosis at EPS. A Markov model was used to estimate the impact of improved arrhythmia diagnosis. We found 13% of typical AFl ECGs had neither sawtooth flutter waves nor RR regularity, and were misdiagnosed by the majority of clinicians (0/6 correctly diagnosed by consensus visual interpretation) but correctly by quantitative analysis in 83% (5/6, P = 0.03). AF diagnosis was also improved through use of the algorithm (92%) versus visual interpretation (primary care: 76%, P < 0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost-savings of $1,303 and 0.007 quality-adjusted-life-years per patient. Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes. © 2010 Wiley Periodicals, Inc.

Harnessing Diversity towards the Reconstructing of Large Scale Gene Regulatory Networks

PubMed Central

Yamanaka, Ryota; Kitano, Hiroaki

2013-01-01

Elucidating gene regulatory network (GRN) from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i) a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii) TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks. PMID:24278007

Cystic Fibrosis Diagnostic Challenges over 4 Decades: Historical Perspectives and Lessons Learned.

PubMed

Farrell, Philip M; White, Terry B; Derichs, Nico; Castellani, Carlo; Rosenstein, Beryl J

2017-02-01

Because cystic fibrosis (CF) can be difficult to diagnose, and because information about the genetic complexities and pathologic basis of the disease has grown so rapidly over the decades, several consensus conferences have been held by the US CF Foundation, and a variety of other efforts to improve diagnostic practices have been organized by the European CF Society. Despite these efforts, the application of diagnostic criteria has been variable and caused confusion. To improve diagnosis and achieve standardization in terms and definitions worldwide, the CF Foundation in 2015 convened a committee of 32 experts in the diagnosis of CF from 9 countries. As part of the process, all previous consensus-seeking exercises sponsored by the CF Foundation, along with the important efforts of the European CF Society, were comprehensively and critically reviewed. The goal was to better understand why consensus conferences and their publications have not led to the desired results. Lessons learned from previous diagnosis consensus processes and products were identified. It was decided that participation in developing a consensus was generally not inclusive enough for global impact. It was also found that many efforts to address sweat test issues were valuable but did not always improve clinical practices as CF diagnostic testing evolved. It also became clear from this review that premature applications of potential diagnostic tests such as nasal potential difference and intestinal current measurement should be avoided until validation and standardization occur. Finally, we have learned that due to the significant and growing number of cases that are challenging to diagnose, an associated continuing medical education program is both desirable and necessary. It is necessary but not sufficient to organize and publish CF diagnosis consensus processes. Follow-up implementation efforts and monitoring practices seem essential. Copyright © 2016. Published by Elsevier Inc.

Assessment of Homology Templates and an Anesthetic Binding Site within the γ-Aminobutyric Acid Receptor

PubMed Central

Bertaccini, Edward J.; Yoluk, Ozge; Lindahl, Erik R.; Trudell, James R.

2013-01-01

Background Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). While its molecular structure remains unknown, significant progress has been made towards understanding its interactions with anesthetics via molecular modeling. Methods The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50’s. Results Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between alpha and beta subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Conclusion Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed correlation of ligand docking scores with experimentally measured GABAaR potentiation. PMID:23770602

Assessment of homology templates and an anesthetic binding site within the γ-aminobutyric acid receptor.

PubMed

Bertaccini, Edward J; Yoluk, Ozge; Lindahl, Erik R; Trudell, James R

2013-11-01

Anesthetics mediate portions of their activity via modulation of the γ-aminobutyric acid receptor (GABAaR). Although its molecular structure remains unknown, significant progress has been made toward understanding its interactions with anesthetics via molecular modeling. The structure of the torpedo acetylcholine receptor (nAChRα), the structures of the α4 and β2 subunits of the human nAChR, the structures of the eukaryotic glutamate-gated chloride channel (GluCl), and the prokaryotic pH-sensing channels, from Gloeobacter violaceus and Erwinia chrysanthemi, were aligned with the SAlign and 3DMA algorithms. A multiple sequence alignment from these structures and those of the GABAaR was performed with ClustalW. The Modeler and Rosetta algorithms independently created three-dimensional constructs of the GABAaR from the GluCl template. The CDocker algorithm docked a congeneric series of propofol derivatives into the binding pocket and scored calculated binding affinities for correlation with known GABAaR potentiation EC50s. Multiple structure alignments of templates revealed a clear consensus of residue locations relevant to anesthetic effects except for torpedo nAChR. Within the GABAaR models generated from GluCl, the residues notable for modulating anesthetic action within transmembrane segments 1, 2, and 3 converged on the intersubunit interface between α and β subunits. Docking scores of a propofol derivative series into this binding site showed strong linear correlation with GABAaR potentiation EC50. Consensus structural alignment based on homologous templates revealed an intersubunit anesthetic binding cavity within the transmembrane domain of the GABAaR, which showed a correlation of ligand docking scores with experimentally measured GABAaR potentiation.

Reaching consensus on the physiotherapeutic management of patients following upper abdominal surgery: a pragmatic approach to interpret equivocal evidence.

PubMed

Hanekom, Susan D; Brooks, Dina; Denehy, Linda; Fagevik-Olsén, Monika; Hardcastle, Timothy C; Manie, Shamila; Louw, Quinette

2012-02-06

Postoperative pulmonary complications remain the most significant cause of morbidity following open upper abdominal surgery despite advances in perioperative care. However, due to the poor quality primary research uncertainty surrounding the value of prophylactic physiotherapy intervention in the management of patients following abdominal surgery persists. The Delphi process has been proposed as a pragmatic methodology to guide clinical practice when evidence is equivocal. The objective was to develop a clinical management algorithm for the post operative management of abdominal surgery patients. Eleven draft algorithm statements extracted from the extant literature by the primary research team were verified and rated by scientist clinicians (n=5) in an electronic three round Delphi process. Algorithm statements which reached a priori defined consensus-semi-interquartile range (SIQR)<0.5-were collated into the algorithm. The five panelists allocated to the abdominal surgery Delphi panel were from Australia, Canada, Sweden, and South Africa. The 11 draft algorithm statements were edited and 5 additional statements were formulated. The panel reached consensus on the rating of all statements. Four statements were rated essential. An expert Delphi panel interpreted the equivocal evidence for the physiotherapeutic management of patients following upper abdominal surgery. Through a process of consensus a clinical management algorithm was formulated. This algorithm can now be used by clinicians to guide clinical practice in this population.

Optimal consensus algorithm integrated with obstacle avoidance

NASA Astrophysics Data System (ADS)

Wang, Jianan; Xin, Ming

2013-01-01

This article proposes a new consensus algorithm for the networked single-integrator systems in an obstacle-laden environment. A novel optimal control approach is utilised to achieve not only multi-agent consensus but also obstacle avoidance capability with minimised control efforts. Three cost functional components are defined to fulfil the respective tasks. In particular, an innovative nonquadratic obstacle avoidance cost function is constructed from an inverse optimal control perspective. The other two components are designed to ensure consensus and constrain the control effort. The asymptotic stability and optimality are proven. In addition, the distributed and analytical optimal control law only requires local information based on the communication topology to guarantee the proposed behaviours, rather than all agents' information. The consensus and obstacle avoidance are validated through simulations.

Automated consensus contour building for prostate MRI.

PubMed

Khalvati, Farzad

2014-01-01

Inter-observer variability is the lack of agreement among clinicians in contouring a given organ or tumour in a medical image. The variability in medical image contouring is a source of uncertainty in radiation treatment planning. Consensus contour of a given case, which was proposed to reduce the variability, is generated by combining the manually generated contours of several clinicians. However, having access to several clinicians (e.g., radiation oncologists) to generate a consensus contour for one patient is costly. This paper presents an algorithm that automatically generates a consensus contour for a given case using the atlases of different clinicians. The algorithm was applied to prostate MR images of 15 patients manually contoured by 5 clinicians. The automatic consensus contours were compared to manual consensus contours where a median Dice similarity coefficient (DSC) of 88% was achieved.

Possible world based consistency learning model for clustering and classifying uncertain data.

PubMed

Liu, Han; Zhang, Xianchao; Zhang, Xiaotong

2018-06-01

Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.

GREIT: a unified approach to 2D linear EIT reconstruction of lung images.

PubMed

Adler, Andy; Arnold, John H; Bayford, Richard; Borsic, Andrea; Brown, Brian; Dixon, Paul; Faes, Theo J C; Frerichs, Inéz; Gagnon, Hervé; Gärber, Yvo; Grychtol, Bartłomiej; Hahn, Günter; Lionheart, William R B; Malik, Anjum; Patterson, Robert P; Stocks, Janet; Tizzard, Andrew; Weiler, Norbert; Wolf, Gerhard K

2009-06-01

Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.

Iron deficiency anemia: diagnosis and management.

PubMed

Clark, Susan F

2009-03-01

Iron deficiency anemia (IDA) still remains universally problematic worldwide. The primary focus of this review is to critique articles published over the past 18 months that describe strategies for the diagnosis and management of this prevalent condition. The medical community continues to lack consensus when identifying the optimal approach for the diagnosis and management of IDA. Current diagnostic recommendations revolve around the validity and practicality of current biomarkers such as soluble transferrin-receptor concentrations and others, and cause-based diagnostics that potentially include endoscopy. Management of IDA is based on supplementation combined with effective etiological treatment. Advances in oral and parenteral low-molecular-weight iron preparations has expanded and improved treatment modalities for IDA. Since the introduction of low versus high-molecular-weight intravenous iron administration, there have been fewer serious adverse events associated with parenteral iron preparations. Best practice guidelines for diagnosing and managing IDA should include the design of an algorithm that is inclusive of multiple biomarkers and cause-based diagnostics, which will provide direction in managing IDA, and distinguish between IDA from the anemia of chronic disease.

[Diagnostic work-up of pulmonary nodules : Management of pulmonary nodules detected with low‑dose CT screening].

PubMed

Wormanns, D

2016-09-01

Pulmonary nodules are the most frequent pathological finding in low-dose computed tomography (CT) scanning for early detection of lung cancer. Early stages of lung cancer are often manifested as pulmonary nodules; however, the very commonly occurring small nodules are predominantly benign. These benign nodules are responsible for the high percentage of false positive test results in screening studies. Appropriate diagnostic algorithms are necessary to reduce false positive screening results and to improve the specificity of lung cancer screening. Such algorithms are based on some of the basic principles comprehensively described in this article. Firstly, the diameter of nodules allows a differentiation between large (>8 mm) probably malignant and small (<8 mm) probably benign nodules. Secondly, some morphological features of pulmonary nodules in CT can prove their benign nature. Thirdly, growth of small nodules is the best non-invasive predictor of malignancy and is utilized as a trigger for further diagnostic work-up. Non-invasive testing using positron emission tomography (PET) and contrast enhancement as well as invasive diagnostic tests (e.g. various procedures for cytological and histological diagnostics) are briefly described in this article. Different nodule morphology using CT (e.g. solid and semisolid nodules) is associated with different biological behavior and different algorithms for follow-up are required. Currently, no obligatory algorithm is available in German-speaking countries for the management of pulmonary nodules, which reflects the current state of knowledge. The main features of some international and American recommendations are briefly presented in this article from which conclusions for the daily clinical use are derived.

Optically-derived estimates of phytoplankton size class and taxonomic group biomass in the Eastern Subarctic Pacific Ocean

NASA Astrophysics Data System (ADS)

Zeng, Chen; Rosengard, Sarah Z.; Burt, William; Peña, M. Angelica; Nemcek, Nina; Zeng, Tao; Arrigo, Kevin R.; Tortell, Philippe D.

2018-06-01

We evaluate several algorithms for the estimation of phytoplankton size class (PSC) and functional type (PFT) biomass from ship-based optical measurements in the Subarctic Northeast Pacific Ocean. Using underway measurements of particulate absorption and backscatter in surface waters, we derived estimates of PSC/PFT based on chlorophyll-a concentrations (Chl-a), particulate absorption spectra and the wavelength dependence of particulate backscatter. Optically-derived [Chl-a] and phytoplankton absorption measurements were validated against discrete calibration samples, while the derived PSC/PFT estimates were validated using size-fractionated Chl-a measurements and HPLC analysis of diagnostic photosynthetic pigments (DPA). Our results showflo that PSC/PFT algorithms based on [Chl-a] and particulate absorption spectra performed significantly better than the backscatter slope approach. These two more successful algorithms yielded estimates of phytoplankton size classes that agreed well with HPLC-derived DPA estimates (RMSE = 12.9%, and 16.6%, respectively) across a range of hydrographic and productivity regimes. Moreover, the [Chl-a] algorithm produced PSC estimates that agreed well with size-fractionated [Chl-a] measurements, and estimates of the biomass of specific phytoplankton groups that were consistent with values derived from HPLC. Based on these results, we suggest that simple [Chl-a] measurements should be more fully exploited to improve the classification of phytoplankton assemblages in the Northeast Pacific Ocean.

Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment

NASA Astrophysics Data System (ADS)

Barnawi, Waleed T.

Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned vehicle. Civil applications that involve missions where human observability would be limited could benefit from the independent UAV task assignment, such as exploration and fire surveillance are also notable uses for this approach.

The diagnosis of urinary tract infections in young children (DUTY): protocol for a diagnostic and prospective observational study to derive and validate a clinical algorithm for the diagnosis of UTI in children presenting to primary care with an acute illness.

PubMed

Downing, Harriet; Thomas-Jones, Emma; Gal, Micaela; Waldron, Cherry-Ann; Sterne, Jonathan; Hollingworth, William; Hood, Kerenza; Delaney, Brendan; Little, Paul; Howe, Robin; Wootton, Mandy; Macgowan, Alastair; Butler, Christopher C; Hay, Alastair D

2012-07-19

Urinary tract infection (UTI) is common in children, and may cause serious illness and recurrent symptoms. However, obtaining a urine sample from young children in primary care is challenging and not feasible for large numbers. Evidence regarding the predictive value of symptoms, signs and urinalysis for UTI in young children is urgently needed to help primary care clinicians better identify children who should be investigated for UTI. This paper describes the protocol for the Diagnosis of Urinary Tract infection in Young children (DUTY) study. The overall study aim is to derive and validate a cost-effective clinical algorithm for the diagnosis of UTI in children presenting to primary care acutely unwell. DUTY is a multicentre, diagnostic and prospective observational study aiming to recruit at least 7,000 children aged before their fifth birthday, being assessed in primary care for any acute, non-traumatic, illness of ≤ 28 days duration. Urine samples will be obtained from eligible consented children, and data collected on medical history and presenting symptoms and signs. Urine samples will be dipstick tested in general practice and sent for microbiological analysis. All children with culture positive urines and a random sample of children with urine culture results in other, non-positive categories will be followed up to record symptom duration and healthcare resource use. A diagnostic algorithm will be constructed and validated and an economic evaluation conducted.The primary outcome will be a validated diagnostic algorithm using a reference standard of a pure/predominant growth of at least >103, but usually >105 CFU/mL of one, but no more than two uropathogens.We will use logistic regression to identify the clinical predictors (i.e. demographic, medical history, presenting signs and symptoms and urine dipstick analysis results) most strongly associated with a positive urine culture result. We will then use economic evaluation to compare the cost effectiveness of the candidate prediction rules. This study will provide novel, clinically important information on the diagnostic features of childhood UTI and the cost effectiveness of a validated prediction rule, to help primary care clinicians improve the efficiency of their diagnostic strategy for UTI in young children.

The diagnosis of urinary tract infections in young children (DUTY): protocol for a diagnostic and prospective observational study to derive and validate a clinical algorithm for the diagnosis of UTI in children presenting to primary care with an acute illness

PubMed Central

2012-01-01

Background Urinary tract infection (UTI) is common in children, and may cause serious illness and recurrent symptoms. However, obtaining a urine sample from young children in primary care is challenging and not feasible for large numbers. Evidence regarding the predictive value of symptoms, signs and urinalysis for UTI in young children is urgently needed to help primary care clinicians better identify children who should be investigated for UTI. This paper describes the protocol for the Diagnosis of Urinary Tract infection in Young children (DUTY) study. The overall study aim is to derive and validate a cost-effective clinical algorithm for the diagnosis of UTI in children presenting to primary care acutely unwell. Methods/design DUTY is a multicentre, diagnostic and prospective observational study aiming to recruit at least 7,000 children aged before their fifth birthday, being assessed in primary care for any acute, non-traumatic, illness of ≤ 28 days duration. Urine samples will be obtained from eligible consented children, and data collected on medical history and presenting symptoms and signs. Urine samples will be dipstick tested in general practice and sent for microbiological analysis. All children with culture positive urines and a random sample of children with urine culture results in other, non-positive categories will be followed up to record symptom duration and healthcare resource use. A diagnostic algorithm will be constructed and validated and an economic evaluation conducted. The primary outcome will be a validated diagnostic algorithm using a reference standard of a pure/predominant growth of at least >103, but usually >105 CFU/mL of one, but no more than two uropathogens. We will use logistic regression to identify the clinical predictors (i.e. demographic, medical history, presenting signs and symptoms and urine dipstick analysis results) most strongly associated with a positive urine culture result. We will then use economic evaluation to compare the cost effectiveness of the candidate prediction rules. Discussion This study will provide novel, clinically important information on the diagnostic features of childhood UTI and the cost effectiveness of a validated prediction rule, to help primary care clinicians improve the efficiency of their diagnostic strategy for UTI in young children. PMID:22812651

Analyzing the BBOB results by means of benchmarking concepts.

PubMed

Mersmann, O; Preuss, M; Trautmann, H; Bischl, B; Weihs, C

2015-01-01

We present methods to answer two basic questions that arise when benchmarking optimization algorithms. The first one is: which algorithm is the "best" one? and the second one is: which algorithm should I use for my real-world problem? Both are connected and neither is easy to answer. We present a theoretical framework for designing and analyzing the raw data of such benchmark experiments. This represents a first step in answering the aforementioned questions. The 2009 and 2010 BBOB benchmark results are analyzed by means of this framework and we derive insight regarding the answers to the two questions. Furthermore, we discuss how to properly aggregate rankings from algorithm evaluations on individual problems into a consensus, its theoretical background and which common pitfalls should be avoided. Finally, we address the grouping of test problems into sets with similar optimizer rankings and investigate whether these are reflected by already proposed test problem characteristics, finding that this is not always the case.

Can human experts predict solubility better than computers?

PubMed

Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

2017-12-13

In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stassi, D.; Ma, H.; Schmidt, T. G., E-mail: taly.gilat-schmidt@marquette.edu

Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, makingmore » it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. Results: There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. Conclusions: The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.« less

The 2016 Academic Emergency Medicine Consensus Conference, "Shared Decision Making in the Emergency Department: Development of a Policy-relevant Patient-centered Research Agenda" Diagnostic Testing Breakout Session Report.

PubMed

Barrett, Tyler W; Rising, Kristin L; Bellolio, M Fernanda; Hall, M Kennedy; Brody, Aaron; Dodd, Kenneth W; Grieser, Mira; Levy, Phillip D; Raja, Ali S; Self, Wesley H; Weingarten, Gail; Hess, Erik P; Hollander, Judd E

2016-12-01

Diagnostic testing is an integral component of patient evaluation in the emergency department (ED). Emergency clinicians frequently use diagnostic testing to more confidently exclude "worst-case" diagnoses rather than to determine the most likely etiology for a presenting complaint. Increased utilization of diagnostic testing has not been associated with reductions in disease-related mortality but has led to increased overall healthcare costs and other unintended consequences (e.g., incidental findings requiring further workup, unnecessary exposure to ionizing radiation or potentially nephrotoxic contrast). Shared decision making (SDM) presents an opportunity for clinicians to discuss the benefits and harms associated with diagnostic testing with patients to more closely tailor testing to patient risk. This article introduces the challenges and opportunities associated with incorporating SDM into emergency care by summarizing the conclusions of the diagnostic testing group at the 2016 Academic Emergency Medicine Consensus Conference on SDM. Three primary domains emerged: 1) characteristics of a condition or test appropriate for SDM, 2) critical elements of and potential barriers to SDM discussions on diagnostic testing, and 3) financial aspects of SDM applied to diagnostic testing. The most critical research questions to improve engagement of patients in their acute care diagnostic decisions were determined by consensus. © 2016 by the Society for Academic Emergency Medicine.

Operational modelling: the mechanisms influencing TB diagnostic yield in an Xpert® MTB/RIF-based algorithm.

PubMed

Dunbar, R; Naidoo, P; Beyers, N; Langley, I

2017-04-01

Cape Town, South Africa. To compare the diagnostic yield for smear/culture and Xpert® MTB/RIF algorithms and to investigate the mechanisms influencing tuberculosis (TB) yield. We developed and validated an operational model of the TB diagnostic process, first with the smear/culture algorithm and then with the Xpert algorithm. We modelled scenarios by varying TB prevalence, adherence to diagnostic algorithms and human immunodeficiency virus (HIV) status. This enabled direct comparisons of diagnostic yield in the two algorithms to be made. Routine data showed that diagnostic yield had decreased over the period of the Xpert algorithm roll-out compared to the yield when the smear/culture algorithm was in place. However, modelling yield under identical conditions indicated a 13.3% increase in diagnostic yield from the Xpert algorithm compared to smear/culture. The model demonstrated that the extensive use of culture in the smear/culture algorithm and the decline in TB prevalence are the main factors contributing to not finding an increase in diagnostic yield in the routine data. We demonstrate the benefits of an operational model to determine the effect of scale-up of a new diagnostic algorithm, and recommend that policy makers use operational modelling to make appropriate decisions before new diagnostic algorithms are scaled up.

Evaluation of tuberculosis diagnostics in children: 1. Proposed clinical case definitions for classification of intrathoracic tuberculosis disease. Consensus from an expert panel.

PubMed

Graham, Stephen M; Ahmed, Tahmeed; Amanullah, Farhana; Browning, Renee; Cardenas, Vicky; Casenghi, Martina; Cuevas, Luis E; Gale, Marianne; Gie, Robert P; Grzemska, Malgosia; Handelsman, Ed; Hatherill, Mark; Hesseling, Anneke C; Jean-Philippe, Patrick; Kampmann, Beate; Kabra, Sushil Kumar; Lienhardt, Christian; Lighter-Fisher, Jennifer; Madhi, Shabir; Makhene, Mamodikoe; Marais, Ben J; McNeeley, David F; Menzies, Heather; Mitchell, Charles; Modi, Surbhi; Mofenson, Lynne; Musoke, Philippa; Nachman, Sharon; Powell, Clydette; Rigaud, Mona; Rouzier, Vanessa; Starke, Jeffrey R; Swaminathan, Soumya; Wingfield, Claire

2012-05-15

There is a critical need for improved diagnosis of tuberculosis in children, particularly in young children with intrathoracic disease as this represents the most common type of tuberculosis in children and the greatest diagnostic challenge. There is also a need for standardized clinical case definitions for the evaluation of diagnostics in prospective clinical research studies that include children in whom tuberculosis is suspected but not confirmed by culture of Mycobacterium tuberculosis. A panel representing a wide range of expertise and child tuberculosis research experience aimed to develop standardized clinical research case definitions for intrathoracic tuberculosis in children to enable harmonized evaluation of new tuberculosis diagnostic technologies in pediatric populations. Draft definitions and statements were proposed and circulated widely for feedback. An expert panel then considered each of the proposed definitions and statements relating to clinical definitions. Formal group consensus rules were established and consensus was reached for each statement. The definitions presented in this article are intended for use in clinical research to evaluate diagnostic assays and not for individual patient diagnosis or treatment decisions. A complementary article addresses methodological issues to consider for research of diagnostics in children with suspected tuberculosis.

Defining the needs for next generation assays for tuberculosis.

PubMed

Denkinger, Claudia M; Kik, Sandra V; Cirillo, Daniela Maria; Casenghi, Martina; Shinnick, Thomas; Weyer, Karin; Gilpin, Chris; Boehme, Catharina C; Schito, Marco; Kimerling, Michael; Pai, Madhukar

2015-04-01

To accelerate the fight against tuberculosis, major diagnostic challenges need to be addressed urgently. Post-2015 targets are unlikely to be met without the use of novel diagnostics that are more accurate and can be used closer to where patients first seek care in affordable diagnostic algorithms. This article describes the efforts by the stakeholder community that led to the identification of the high-priority diagnostic needs in tuberculosis. Subsequently target product profiles for the high-priority diagnostic needs were developed and reviewed in a World Health Organization (WHO)-led consensus meeting. The high-priority diagnostic needs included (1) a sputum-based replacement test for smear-microscopy; (2) a non-sputum-based biomarker test for all forms of tuberculosis, ideally suitable for use at levels below microscopy centers; (3) a simple, low cost triage test for use by first-contact care providers as a rule-out test, ideally suitable for use by community health workers; and (4) a rapid drug susceptibility test for use at the microscopy center level. The developed target product profiles, along with complimentary work presented in this supplement, will help to facilitate the interaction between the tuberculosis community and the diagnostics industry with the goal to lead the way toward the post-2015 global tuberculosis targets. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

International Expert Consensus Document on Takotsubo Syndrome (Part II): Diagnostic Workup, Outcome, and Management.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

The clinical expert consensus statement on takotsubo syndrome (TTS) part II focuses on the diagnostic workup, outcome, and management. The recommendations are based on interpretation of the limited clinical trial data currently available and experience of international TTS experts. It summarizes the diagnostic approach, which may facilitate correct and timely diagnosis. Furthermore, the document covers areas where controversies still exist in risk stratification and management of TTS. Based on available data the document provides recommendations on optimal care of such patients for practising physicians.

International Expert Consensus Document on Takotsubo Syndrome (Part II): Diagnostic Workup, Outcome, and Management

PubMed Central

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y.-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-01-01

Abstract The clinical expert consensus statement on takotsubo syndrome (TTS) part II focuses on the diagnostic workup, outcome, and management. The recommendations are based on interpretation of the limited clinical trial data currently available and experience of international TTS experts. It summarizes the diagnostic approach, which may facilitate correct and timely diagnosis. Furthermore, the document covers areas where controversies still exist in risk stratification and management of TTS. Based on available data the document provides recommendations on optimal care of such patients for practising physicians. PMID:29850820

The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

PubMed

Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

2014-06-01

Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

Autoimmune Retinopathy: Current Concepts and Practices (An American Ophthalmological Society Thesis).

PubMed

Sen, H Nida; Grange, Landon; Akanda, Marib; Fox, Austin

2017-08-01

To elicit and evaluate opinions in the diagnosis and management of nonparaneoplastic autoimmune retinopathy (npAIR) among members of the American Uveitis Society (AUS) and to further the development of consensus and criteria in the diagnosis and management of npAIR. We hypothesize that despite lack of any clear guidelines, a general consensus in the clinical diagnosis and treatment of npAIR exists among uveitis experts. A literature review was performed and a panel of uveitis experts was consulted to formulate a survey regarding the diagnosis and management of npAIR. An online survey of 10 questions was developed, and a link was distributed through the AUS membership discussion list. We defined "general consensus" as meaning that a majority (>50%) of the respondents provided the same answer to a question. Fifty-four members of the AUS responded to the survey. Thirty-eight members (70.4%) see one to three AIR patients per year. Greater than 50% consensus was reached on most items, particularly items relating to diagnostic features and tests (up to 96% consensus). The diagnosis and management of npAIR is challenging, as standardized clinical and laboratory diagnostic criteria have yet to be established. The results of this study support the presence of consensus regarding certain aspects of npAIR, but also indicate the need for developing clear clinical diagnostic criteria and treatment guidelines.

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

Adolescence transitional care in neurogenic detrusor overactivity and the use of OnabotulinumtoxinA: A clinical algorithm from an Italian consensus statement.

PubMed

Palleschi, Giovanni; Mosiello, Giovanni; Iacovelli, Valerio; Musco, Stefania; Del Popolo, Giulio; Giannantoni, Antonella; Carbone, Antonio; Carone, Roberto; Tubaro, Andrea; De Gennaro, Mario; Marte, Antonio; Finazzi Agrò, Enrico

2018-03-01

OnabotulinumtoxinA (onaBNTa) for treating neurogenic detrusor overactivity (NDO) is widely used after its regulatory approval in adults. Although the administration of onaBNTa is still considered off-label in children, data have already been reported on its efficacy and safety. Nowadays, there is a lack of standardized protocols for treatment of NDO with onaBNTa in adolescent patients in their transition from the childhood to the adult age. With the aim to address this issue a consensus panel was obtained. A panel of leading urologists and urogynaecologists skilled in functional urology, neuro-urology, urogynaecology, and pediatric urology participated in a consensus-forming project using a Delphi method to reach national consensus on NDO-onaBNTa treatment in adolescence transitional care. In total, 11 experts participated. All panelists participated in the four phases of the consensus process. Consensus was reached if ≥70% of the experts agreed on recommendations. To facilitate a common understanding among all experts, a face-to-face consensus meeting was held in Rome in march 2015 and then with a follow-up teleconference in march 2017. By the end of the Delphi process, formal consensus was achieved for 100% of the items and an algorithm was then developed. This manuscript represents the first report on the onaBNTa in adolescents. Young adults should be treated as a distinct sub-population in policy, planning, programming, and research, as strongly sustained by national public health care. This consensus and the algorithm could support multidisciplinary communication, reduce the extent of variations in clinical practice and optimize clinical decision making. © 2017 Wiley Periodicals, Inc.

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction.

PubMed

Stassi, D; Dutta, S; Ma, H; Soderman, A; Pazzani, D; Gros, E; Okerlund, D; Schmidt, T G

2016-01-01

Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

Treatment of Seborrhoeic Dermatitis in Asia: A Consensus Guide

PubMed Central

Cheong, Wai Kwong; Yeung, Chi Keung; Torsekar, Raghunandan Govind; Suh, Dae Hun; Ungpakorn, Rataporn; Widaty, Sandra; Azizan, Noor Zalmy; Gabriel, Maria Teresita; Tran, Hau Khang; Chong, Wei Sheng; Shih, I-Hsin; Dall'Oglio, Federica; Micali, Giuseppe

2016-01-01

Seborrhoeic dermatitis (SD) is common in Asia. Its prevalence is estimated to be 1-5% in adults. However, larger population-based studies into the epidemiology of SD in Asia are lacking, and the aetiology of SD may differ widely from Western countries and in different parts of Asia. In addition, clinically significant differences between Asian and Caucasian skin have been reported. There is a need to define standardized clinical diagnostic criteria and/or a grading system to help determine appropriate treatments for SD within Asia. With this in mind, experts from India, South Korea, Taiwan, Malaysia, Vietnam, Singapore, Thailand, the Philippines, Indonesia, and Italy convened to define the landscape of SD in Asia at a meeting held in Singapore. The consensus group developed a comprehensive algorithm to aid clinicians to recommend appropriate treatment of SD in both adults and children. In most cases, satisfactory therapeutic results can be accomplished with topical antifungal agents or topical corticosteroids. Non-steroidal anti-inflammatory agents with antifungal properties have been shown to be a viable option for both acute and maintenance therapy. PMID:27386464

Recurrent Acute Pancreatitis: International State-of-the-Science Conference With Recommendations.

PubMed

Guda, Nalini M; Muddana, Venkata; Whitcomb, David C; Levy, Philippe; Garg, Pramod; Cote, Gregory; Uc, Aliye; Varadarajulu, Shyam; Vege, Santhi S; Chari, Suresh T; Forsmark, Chris E; Yadav, Dhiraj; Reddy, D Nageshwar; Tenner, Scott; Johnson, Colin D; Akisik, Fatih; Saluja, Ashok K; Lerch, Markus M; Mallery, J Shawn; Freeman, Martin L

2018-07-01

Recurrent acute pancreatitis (RAP) is a clinically significant problem globally. The etiology remains unclear in approximately 10% to 15% of patients despite a thorough workup. Data on natural history and efficacy of treatments are limited. We aimed to establish criteria for diagnosis, evaluate the causative factors, and arrive at a consensus on the appropriate workup and management of patients with RAP. The organizing committee was formed, and a set of questions was developed based on the current evidence, controversies, and topics that needed further research. After a vetting process, these topics were assigned to a group of experts from around the world with special interest in RAP. Data were presented as part of a workshop on RAP organized as a part of the annual meeting of the America Pancreatic Association. Pretest and Posttest questions were administered, and the responses were tabulated by the current Grades of Recommendation Assessment, Development and Evaluation system. The consensus guidelines were established in the format of a diagnostic algorithm. Several deficiencies were identified with respect to data on etiology, treatment efficacies, and areas that need immediate research.

Asia-Pacific consensus statement on the optimal use of high-sensitivity troponin assays in acute coronary syndromes diagnosis: focus on hs-TnI

PubMed Central

Tan, Jack Wei Chieh; Lam, Carolyn S P; Kasim, Sazzli Shahlan; Aw, Tar Choon; Abanilla, Joel M; Chang, Wei-Ting; Dang, Van Phuoc; Iboleon-Dy, Maria; Mumpuni, Sari Sri; Phommintikul, Arintaya; Ta, Manh Cuong; Topipat, Punkiat; Yiu, Kai Hang; Cullen, Louise

2017-01-01

Objective High-sensitivity troponin (hs-Tn) assays need to be applied appropriately to improve diagnosis and patient outcomes in acute coronary syndromes (ACS). Methods Experts from Asia Pacific convened in 2015 to provide data-driven consensus-based, region-specific recommendations and develop an algorithm for the appropriate incorporation of this assay into the ACS assessment and treatment pathway. Results Nine recommendations were developed by the expert panel: (1) troponin is the preferred cardiac biomarker for diagnostic assessment of ACS and is indicated for patients with symptoms of possible ACS; (2) hs-Tn assays are recommended; (3) serial testing is required for all patients; (4) testing should be performed at presentation and 3 hours later; (5) gender-specific cut-off values should be used for hs-Tn I assays; (6) hs-Tn I level >10 times the upper limit of normal should be considered to ‘rule in’ a diagnosis of ACS; (7) dynamic change >50% in hs-Tn I level from presentation to 3-hour retest identifies patients at high risk for ACS; (8) where only point-of-care testing is available, patients with elevated readings should be considered at high risk, while patients with low/undetectable readings should be retested after 6 hours or sent for laboratory testing and (9) regular education on the appropriate use of troponin tests is essential. Conclusions We propose an algorithm that will potentially reduce delays in discharge by the accurate ‘rule out’ of non-ACS patients within 3 hours. Appropriate research should be undertaken to ensure the efficacy and safety of the algorithm in clinical practice, with the long-term goal of improvement of care of patients with ACS in Asia Pacific. PMID:28466882

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

[Etiology and diagnostic methods in vocal cord paralysis].

PubMed

Jørgensen, Gita; Clausen, Eva Wiinstedt; Mantoni, Margit Y; Misciattelli, Lorenzo; Balle, Viggo

2003-02-10

The etiology of vocal cord paralysis (VCP) is varied. There is lack of consensus regarding the choice of investigations to be used in the evaluation of VCP. The aim of this study was to establish the etiology, assess the diagnostic methods used in the evaluation, and outline an algorithm for future evaluation of unilateral vocal cord paralysis (UVCP). Charts of all patients (n = 94) with the diagnostic code of VCP were reviewed, and reexaminations were performed of patients in whom no etiology was found after the initial symptoms. The etiology of UVCP was neoplasm in 34%, surgical trauma in 12%, and miscellaneous causes in 54%. The etiology of bilateral vocal cord paralysis (BVCP) was neoplasm in 24%, surgical trauma in 24%, and miscellaneous causes in 52%. The reexaminations did not reveal any cancer diseases in the patients concerned. The most effective diagnostic method was CT-scanning while the least effective was thyroid scanning. Because cancer is a common cause of VCP a thorough evaluation is necessary. For UVCP we recommend history and physical examination, X-ray of the chest, ultrasonography of the neck, and CT-scanning of the superior mediastinum. If these prove negative, panendoscopy should be performed. Workup of patients with idiopathic VCP should include examination, X-ray of the chest at 6-month intervals, and annual CT-scanning for two years.

Challenges in diagnosing narcolepsy without cataplexy: a consensus statement.

PubMed

Baumann, Christian R; Mignot, Emmanuel; Lammers, Gert Jan; Overeem, Sebastiaan; Arnulf, Isabelle; Rye, David; Dauvilliers, Yves; Honda, Makoto; Owens, Judith A; Plazzi, Giuseppe; Scammell, Thomas E

2014-06-01

Diagnosing narcolepsy without cataplexy is often a challenge as the symptoms are nonspecific, current diagnostic tests are limited, and there are no useful biomarkers. In this report, we review the clinical and physiological aspects of narcolepsy without cataplexy, the limitations of available diagnostic procedures, and the differential diagnoses, and we propose an approach for more accurate diagnosis of narcolepsy without cataplexy. A group of clinician-scientists experienced in narcolepsy reviewed the literature and convened to discuss current diagnostic tools, and to map out directions for research that should lead to a better understanding and more accurate diagnosis of narcolepsy without cataplexy. To aid in the identification of narcolepsy without cataplexy, we review key indicators of narcolepsy and present a diagnostic algorithm. A detailed clinical history is mainly helpful to rule out other possible causes of chronic sleepiness. The multiple sleep latency test remains the most important measure, and prior sleep deprivation, shift work, or circadian disorders should be excluded by actigraphy or sleep logs. A short REM sleep latency (≤ 15 minutes) on polysomnography can aid in the diagnosis of narcolepsy without cataplexy, although sensitivity is low. Finally, measurement of hypocretin levels can helpful, as levels are low to intermediate in 10% to 30% of narcolepsy without cataplexy patients.

[The guideline for the treatment of mood disorders in USA and Japan].

PubMed

Higuchi, T

2001-08-01

Recently, the number of available antidepressants has increased dramatically and psychopharmacological treatment is becoming complex. It is important to present some guideline for supporting clinical decision making. Three different kinds of guideline for the treatment of mood disorders, that is, the APA style guideline, the algorithm and the consensus guideline, have been developed in our country. The APA style guideline and the algorithm are basically evidence based and the consensus guideline is developed through the consensus panel format. These guidelines should be used as 'a starting point' for specifying decisions that will be modified occasionally.

Identification of Genetic Loci Underlying the Phenotypic Constructs of Autism Spectrum Disorders

ERIC Educational Resources Information Center

Liu, Xiao-Qing; Georgiades, Stelios; Duku, Eric; Thompson, Ann; Devlin, Bernie; Cook, Edwin H.; Wijsman, Ellen M.; Paterson, Andrew D.; Szatmari, Peter

2011-01-01

Objective: To investigate the underlying phenotypic constructs in autism spectrum disorders (ASD) and to identify genetic loci that are linked to these empirically derived factors. Method: Exploratory factor analysis was applied to two datasets with 28 selected Autism Diagnostic Interview-Revised (ADI-R) algorithm items. The first dataset was from…

Application of majority voting and consensus voting algorithms in N-version software

NASA Astrophysics Data System (ADS)

Tsarev, R. Yu; Durmuş, M. S.; Üstoglu, I.; Morozov, V. A.

2018-05-01

N-version programming is one of the most common techniques which is used to improve the reliability of software by building in fault tolerance, redundancy and decreasing common cause failures. N different equivalent software versions are developed by N different and isolated workgroups by considering the same software specifications. The versions solve the same task and return results that have to be compared to determine the correct result. Decisions of N different versions are evaluated by a voting algorithm or the so-called voter. In this paper, two of the most commonly used software voting algorithms such as the majority voting algorithm and the consensus voting algorithm are studied. The distinctive features of Nversion programming with majority voting and N-version programming with consensus voting are described. These two algorithms make a decision about the correct result on the base of the agreement matrix. However, if the equivalence relation on the agreement matrix is not satisfied it is impossible to make a decision. It is shown that the agreement matrix can be transformed into an appropriate form by using the Boolean compositions when the equivalence relation is satisfied.

Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: indicators recommended for the identification and documentation of pediatric malnutrition (undernutrition).

PubMed

Becker, Patricia; Carney, Liesje Nieman; Corkins, Mark R; Monczka, Jessica; Smith, Elizabeth; Smith, Susan E; Spear, Bonnie A; White, Jane V

2015-02-01

The Academy of Nutrition and Dietetics (the Academy) and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.), utilizing an evidence-informed, consensus-derived process, recommend that a standardized set of diagnostic indicators be used to identify and document pediatric malnutrition (undernutrition) in routine clinical practice. The recommended indicators include z scores for weight-for-height/length, body mass index-for-age, or length/height-for-age or mid-upper arm circumference when a single data point is available. When 2 or more data points are available, indicators may also include weight gain velocity (<2 years of age), weight loss (2-20 years of age), deceleration in weight for length/height z score, and inadequate nutrient intake. The purpose of this consensus statement is to identify a basic set of indicators that can be used to diagnose and document undernutrition in the pediatric population ages 1 month to 18 years. The indicators are intended for use in multiple settings (eg, acute, ambulatory care/outpatient, residential care). Several screening tools have been developed for use in hospitalized children. However, identifying criteria for use in screening for nutritional risk is not the purpose of this paper. Clinicians should use as many data points as available to identify and document the presence of malnutrition. The universal use of a single set of diagnostic parameters will expedite the recognition of pediatric undernutrition, lead to the development of more accurate estimates of its prevalence and incidence, direct interventions, and promote improved outcomes. A standardized diagnostic approach will also inform the prediction of the human and financial responsibilities and costs associated with the prevention and treatment of undernutrition in this vulnerable population and help to further ensure the provision of high-quality, cost-effective nutritional care. © 2014 American Society for Parenteral and Enteral Nutrition and Academy of Nutrition and Dietetics.

Diagnosis and Management of Patients with Paroxysmal Sympathetic Hyperactivity following Acute Brain Injuries Using a Consensus-Based Diagnostic Tool: A Single Institutional Case Series.

PubMed

Godo, Shigeo; Irino, Shigemi; Nakagawa, Atsuhiro; Kawazoe, Yu; Fujita, Motoo; Kudo, Daisuke; Nomura, Ryosuke; Shimokawa, Hiroaki; Kushimoto, Shigeki

2017-09-01

Paroxysmal sympathetic hyperactivity (PSH) is a distinct syndrome of episodic sympathetic hyperactivities following severe acquired brain injury, characterized by paroxysmal transient fever, tachycardia, hypertension, tachypnea, excessive diaphoresis and specific posturing. PSH remains to be an under-recognized condition with a diagnostic pitfall especially in the intensive care unit (ICU) settings due to the high prevalence of concomitant diseases that mimic PSH. A consensus set of diagnostic criteria named PSH-Assessment Measure (PSH-AM) has been developed recently, which is consisted of two components: a diagnosis likelihood tool derived from clinical characteristics of PSH, and a clinical feature scale assigned to the severity of each sympathetic hyperactivity. We herein present a case series of patients with PSH who were diagnosed and followed by using PSH-AM in our tertiary institutional medical and surgical ICU between April 2015 and March 2017 in order to evaluate the clinical efficacy of PSH-AM. Among 394 survivors of 521 patients admitted with acquired brain injury defined as acute brain injury at all levels of severity regardless of the presence of altered consciousness, including traumatic brain injury, stroke, infectious disease, and encephalopathy, 6 patients (1.5%) were diagnosed as PSH by using PSH-AM. PSH-AM served as a useful scoring system for early objective diagnosis, assessment of severity, and serial evaluation of treatment efficacy in the management of PSH in the ICU settings. In conclusion, critical care clinicians should consider the possibility of PSH and can use PSH-AM as a useful diagnostic and guiding tool in the management of PSH.

Evaluation of Tuberculosis Diagnostics in Children: 1. Proposed Clinical Case Definitions for Classification of Intrathoracic Tuberculosis Disease. Consensus From an Expert Panel

PubMed Central

Graham, Stephen M.; Ahmed, Tahmeed; Amanullah, Farhana; Browning, Renee; Cardenas, Vicky; Casenghi, Martina; Cuevas, Luis E.; Gale, Marianne; Gie, Robert P.; Grzemska, Malgosia; Handelsman, Ed; Hatherill, Mark; Hesseling, Anneke C.; Jean-Philippe, Patrick; Kampmann, Beate; Kabra, Sushil Kumar; Lienhardt, Christian; Lighter-Fisher, Jennifer; Madhi, Shabir; Makhene, Mamodikoe; Marais, Ben J.; McNeeley, David F.; Menzies, Heather; Mitchell, Charles; Modi, Surbhi; Mofenson, Lynne; Musoke, Philippa; Nachman, Sharon; Powell, Clydette; Rigaud, Mona; Rouzier, Vanessa; Starke, Jeffrey R.; Swaminathan, Soumya; Wingfield, Claire

2012-01-01

There is a critical need for improved diagnosis of tuberculosis in children, particularly in young children with intrathoracic disease as this represents the most common type of tuberculosis in children and the greatest diagnostic challenge. There is also a need for standardized clinical case definitions for the evaluation of diagnostics in prospective clinical research studies that include children in whom tuberculosis is suspected but not confirmed by culture of Mycobacterium tuberculosis. A panel representing a wide range of expertise and child tuberculosis research experience aimed to develop standardized clinical research case definitions for intrathoracic tuberculosis in children to enable harmonized evaluation of new tuberculosis diagnostic technologies in pediatric populations. Draft definitions and statements were proposed and circulated widely for feedback. An expert panel then considered each of the proposed definitions and statements relating to clinical definitions. Formal group consensus rules were established and consensus was reached for each statement. The definitions presented in this article are intended for use in clinical research to evaluate diagnostic assays and not for individual patient diagnosis or treatment decisions. A complementary article addresses methodological issues to consider for research of diagnostics in children with suspected tuberculosis. PMID:22448023

Consensus Guidelines on Evaluation and Management of the Febrile Child Presenting to the Emergency Department in India.

PubMed

Mahajan, Prashant; Batra, Prerna; Thakur, Neha; Patel, Reena; Rai, Narendra; Trivedi, Nitin; Fassl, Bernhard; Shah, Binita; Lozon, Marie; Oteng, Rockerfeller A; Saha, Abhijeet; Shah, Dheeraj; Galwankar, Sagar

2017-08-15

India, home to almost 1.5 billion people, is in need of a country-specific, evidence-based, consensus approach for the emergency department (ED) evaluation and management of the febrile child. We held two consensus meetings, performed an exhaustive literature review, and held ongoing web-based discussions to arrive at a formal consensus on the proposed evaluation and management algorithm. The first meeting was held in Delhi in October 2015, under the auspices of Pediatric Emergency Medicine (PEM) Section of Academic College of Emergency Experts in India (ACEE-INDIA); and the second meeting was conducted at Pune during Emergency Medical Pediatrics and Recent Trends (EMPART 2016) in March 2016. The second meeting was followed with futher e-mail-based discussions to arrive at a formal consensus on the proposed algorithm. To develop an algorithmic approach for the evaluation and management of the febrile child that can be easily applied in the context of emergency care and modified based on local epidemiology and practice standards. We created an algorithm that can assist the clinician in the evaluation and management of the febrile child presenting to the ED, contextualized to health care in India. This guideline includes the following key components: triage and the timely assessment; evaluation; and patient disposition from the ED. We urge the development and creation of a robust data repository of minimal standard data elements. This would provide a systematic measurement of the care processes and patient outcomes, and a better understanding of various etiologies of febrile illnesses in India; both of which can be used to further modify the proposed approach and algorithm.

Best practices recommendations in the application of immunohistochemistry in urologic pathology: report from the International Society of Urological Pathology consensus conference.

PubMed

Amin, Mahul B; Epstein, Jonathan I; Ulbright, Thomas M; Humphrey, Peter A; Egevad, Lars; Montironi, Rodolfo; Grignon, David; Trpkov, Kiril; Lopez-Beltran, Antonio; Zhou, Ming; Argani, Pedram; Delahunt, Brett; Berney, Daniel M; Srigley, John R; Tickoo, Satish K; Reuter, Victor E

2014-08-01

Members of the International Society of Urological Pathology (ISUP) participated in a half-day consensus conference to discuss guidelines and recommendations regarding best practice approaches to use of immunohistochemistry (IHC) in differential diagnostic situations in urologic pathology, including bladder, prostate, testis and, kidney lesions. Four working groups, selected by the ISUP leadership, identified several high-interest topics based on common or relevant challenging diagnostic situations and proposed best practice recommendations, which were discussed by the membership. The overall summary of the discussions and the consensus opinion forms the basis of a series of articles, one for each organ site. This Special Article summarizes the overall recommendations made by the four working groups. It is anticipated that this ISUP effort will be valuable to the entire practicing community in the appropriate use of IHC in diagnostic urologic pathology.

Optimal dynamic control of resources in a distributed system

NASA Technical Reports Server (NTRS)

Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang

1989-01-01

The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.

Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data.

PubMed

Horwitz, Leora I; Grady, Jacqueline N; Cohen, Dorothy B; Lin, Zhenqiu; Volpe, Mark; Ngo, Chi K; Masica, Andrew L; Long, Theodore; Wang, Jessica; Keenan, Megan; Montague, Julia; Suter, Lisa G; Ross, Joseph S; Drye, Elizabeth E; Krumholz, Harlan M; Bernheim, Susannah M

2015-10-01

It is desirable not to include planned readmissions in readmission measures because they represent deliberate, scheduled care. To develop an algorithm to identify planned readmissions, describe its performance characteristics, and identify improvements. Consensus-driven algorithm development and chart review validation study at 7 acute-care hospitals in 2 health systems. For development, all discharges qualifying for the publicly reported hospital-wide readmission measure. For validation, all qualifying same-hospital readmissions that were characterized by the algorithm as planned, and a random sampling of same-hospital readmissions that were characterized as unplanned. We calculated weighted sensitivity and specificity, and positive and negative predictive values of the algorithm (version 2.1), compared to gold standard chart review. In consultation with 27 experts, we developed an algorithm that characterizes 7.8% of readmissions as planned. For validation we reviewed 634 readmissions. The weighted sensitivity of the algorithm was 45.1% overall, 50.9% in large teaching centers and 40.2% in smaller community hospitals. The weighted specificity was 95.9%, positive predictive value was 51.6%, and negative predictive value was 94.7%. We identified 4 minor changes to improve algorithm performance. The revised algorithm had a weighted sensitivity 49.8% (57.1% at large hospitals), weighted specificity 96.5%, positive predictive value 58.7%, and negative predictive value 94.5%. Positive predictive value was poor for the 2 most common potentially planned procedures: diagnostic cardiac catheterization (25%) and procedures involving cardiac devices (33%). An administrative claims-based algorithm to identify planned readmissions is feasible and can facilitate public reporting of primarily unplanned readmissions. © 2015 Society of Hospital Medicine.

Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

PubMed Central

Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

2014-01-01

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website. PMID:24778629

Creation of a diagnostic wait times measurement framework based on evidence and consensus.

PubMed

Gilbert, Julie E; Dobrow, Mark J; Kaan, Melissa; Dobranowski, Julian; Srigley, John R; Jusko Friedman, Audrey; Irish, Jonathan C

2014-09-01

Public reporting of wait times worldwide has to date focused largely on treatment wait times and is limited in its ability to capture earlier parts of the patient journey. The interval between suspicion and diagnosis or ruling out of cancer is a complex phase of the cancer journey. Diagnostic delays and inefficient use of diagnostic imaging procedures can result in poor patient outcomes, both physical and psychosocial. This study was designed to develop a framework that could be adopted for multiple disease sites across different jurisdictions to enable the measurement of diagnostic wait times and diagnostic delay. Diagnostic benchmarks and targets in cancer systems were explored through a targeted literature review and jurisdictional scan. Cancer system leaders and clinicians were interviewed to validate the information found in the jurisdictional scan. An expert panel was assembled to review and, through a modified Delphi consensus process, provide feedback on a diagnostic wait times framework. The consensus process resulted in agreement on a measurement framework that identified suspicion, referral, diagnosis, and treatment as the main time points for measuring this critical phase of the patient journey. This work will help guide initiatives designed to improve patient access to health services by developing an evidence-based approach to standardization of the various waypoints during the diagnostic pathway. The diagnostic wait times measurement framework provides a yardstick to measure the performance of programs that are designed to manage and expedite care processes between referral and diagnosis or ruling out of cancer. Copyright © 2014 by American Society of Clinical Oncology.

The Texas Children's Medication Algorithm Project: Report of the Texas Consensus Conference Panel on Medication Treatment of Childhood Attention-Deficit/Hyperactivity Disorder. Part II: Tactics. Attention-Deficit/Hyperactivity Disorder.

PubMed

Pliszka, S R; Greenhill, L L; Crismon, M L; Sedillo, A; Carlson, C; Conners, C K; McCracken, J T; Swanson, J M; Hughes, C W; Llana, M E; Lopez, M; Toprac, M G

2000-07-01

Expert consensus methodology was used to develop a medication treatment algorithm for attention-deficit/hyperactivity disorder (ADHD). The algorithm broadly outlined the choice of medication for ADHD and some of its most common comorbid conditions. Specific tactical recommendations were developed with regard to medication dosage, assessment of drug response, management of side effects, and long-term medication management. The consensus conference of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families developed evidence-based tactics for the pharmacotherapy of childhood ADHD and its common comorbid disorders. The panel discussed specifics of treatment of ADHD and its comorbid conditions with stimulants, antidepressants, mood stabilizers, alpha-agonists, and (when appropriate) antipsychotics. Specific tactics for the use of each of the above agents are outlined. The tactics are designed to be practical for implementation in the public mental health sector, but they may have utility in many practice settings, including the private practice environment. Tactics for psychopharmacological management of ADHD can be developed with consensus.

Survivable algorithms and redundancy management in NASA's distributed computing systems

NASA Technical Reports Server (NTRS)

Malek, Miroslaw

1992-01-01

The design of survivable algorithms requires a solid foundation for executing them. While hardware techniques for fault-tolerant computing are relatively well understood, fault-tolerant operating systems, as well as fault-tolerant applications (survivable algorithms), are, by contrast, little understood, and much more work in this field is required. We outline some of our work that contributes to the foundation of ultrareliable operating systems and fault-tolerant algorithm design. We introduce our consensus-based framework for fault-tolerant system design. This is followed by a description of a hierarchical partitioning method for efficient consensus. A scheduler for redundancy management is introduced, and application-specific fault tolerance is described. We give an overview of our hybrid algorithm technique, which is an alternative to the formal approach given.

The use of ovarian reserve markers in IVF clinical practice: a national consensus.

PubMed

La Marca, Antonio; Ferraretti, Anna Pia; Palermo, Roberto; Ubaldi, Filippo M

2016-01-01

Ovarian reserve markers have been documented to perform very well in the clinical practice. While this is widely recognized, still now there is no consensus on how to use new biomarkers in the clinical practice. This study was conducted among Italian IVF centres using the Delphi technique, a validated consensus-building process. Briefly three consecutive questionnaires were developed for clinicians in charge of IVF centres. In the first rounds, participants were asked to rate the importance of a list of statements regarding the categorization of ovarian response and the diagnostic role of biomarkers. In round 3, participants were asked to rate their agreement and consensus on the list of statements derived from the first two rounds. There were 120 respondents. Consensus was achieved for many points: (a) poor ovarian response is predicted on the basis of the following: AMH < 1 ng/ml or AFC < 7, FSH ≥ 10 IU/l, age ≥ 40 yrs; (b) hyper-response is predicted on the basis of the following: AMH > 3 ng/ml or AFC > 14; (c) day 3 FSH measurement should always be associated to estradiol; (d) AMH can be measured on a random basis; (e) the measurement of the AFC with the 2D technology may be considered adequate and (f) the AFC should be measured in the early follicular phase and consists in the total number of 2-9 mm follicles in both the ovaries. The present study suggests that extensive consensus on the importance and use of new ovarian reserve markers to improve IVF safety and performance is already present among clinicians.

Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

PubMed Central

Aberer, Andre J.; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

Abstract The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees. PMID:22962004

Pruning rogue taxa improves phylogenetic accuracy: an efficient algorithm and webservice.

PubMed

Aberer, Andre J; Krompass, Denis; Stamatakis, Alexandros

2013-01-01

The presence of rogue taxa (rogues) in a set of trees can frequently have a negative impact on the results of a bootstrap analysis (e.g., the overall support in consensus trees). We introduce an efficient graph-based algorithm for rogue taxon identification as well as an interactive webservice implementing this algorithm. Compared with our previous method, the new algorithm is up to 4 orders of magnitude faster, while returning qualitatively identical results. Because of this significant improvement in scalability, the new algorithm can now identify substantially more complex and compute-intensive rogue taxon constellations. On a large and diverse collection of real-world data sets, we show that our method yields better supported reduced/pruned consensus trees than any competing rogue taxon identification method. Using the parallel version of our open-source code, we successfully identified rogue taxa in a set of 100 trees with 116 334 taxa each. For simulated data sets, we show that when removing/pruning rogue taxa with our method from a tree set, we consistently obtain bootstrap consensus trees as well as maximum-likelihood trees that are topologically closer to the respective true trees.

Resilient distributed control in the presence of misbehaving agents in networked control systems.

PubMed

Zeng, Wente; Chow, Mo-Yuen

2014-11-01

In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

Diagnosis of pulmonary hypertension from magnetic resonance imaging-based computational models and decision tree analysis.

PubMed

Lungu, Angela; Swift, Andrew J; Capener, David; Kiely, David; Hose, Rod; Wild, Jim M

2016-06-01

Accurately identifying patients with pulmonary hypertension (PH) using noninvasive methods is challenging, and right heart catheterization (RHC) is the gold standard. Magnetic resonance imaging (MRI) has been proposed as an alternative to echocardiography and RHC in the assessment of cardiac function and pulmonary hemodynamics in patients with suspected PH. The aim of this study was to assess whether machine learning using computational modeling techniques and image-based metrics of PH can improve the diagnostic accuracy of MRI in PH. Seventy-two patients with suspected PH attending a referral center underwent RHC and MRI within 48 hours. Fifty-seven patients were diagnosed with PH, and 15 had no PH. A number of functional and structural cardiac and cardiovascular markers derived from 2 mathematical models and also solely from MRI of the main pulmonary artery and heart were integrated into a classification algorithm to investigate the diagnostic utility of the combination of the individual markers. A physiological marker based on the quantification of wave reflection in the pulmonary artery was shown to perform best individually, but optimal diagnostic performance was found by the combination of several image-based markers. Classifier results, validated using leave-one-out cross validation, demonstrated that combining computation-derived metrics reflecting hemodynamic changes in the pulmonary vasculature with measurement of right ventricular morphology and function, in a decision support algorithm, provides a method to noninvasively diagnose PH with high accuracy (92%). The high diagnostic accuracy of these MRI-based model parameters may reduce the need for RHC in patients with suspected PH.

Carotid Consensus Panel duplex criteria can replace modified University of Washington criteria without affecting accuracy.

PubMed

Kim, Ann H; Augustin, Gener; Shevitz, Andrew; Kim, Hannah; Trivonovich, Michael R; Powell, Alexis R; Kumins, Norman; Tarr, Robert; Kashyap, Vikram S

2018-04-01

The decision to intervene for internal carotid stenosis often depends on the degree of stenosis seen on duplex ultrasound (US). The aim of this study is to compare the diagnostic accuracy of two criteria: modified University of Washington (UW) and 2003 Carotid Consensus Panel (CCP). All patients undergoing US in an accredited (IAC) vascular laboratory from January 2010 to June 2015 were reviewed ( n=18,772 US exams). Patients receiving a neck computed tomography angiography (CTA) within 6 months of the US were included in the study ( n=254). The degree of stenosis was determined by UW/CCP criteria and confirmed on CTA images using North American Symptomatic Carotid Endarterectomy Trial (NASCET)/European Carotid Surgery Trial (ECST) schema. Kappa analysis with 95% confidence intervals (CIs) were utilized to determine duplex-CTA agreement. A total of 417 carotid arteries from 221 patients were assessed in this study. The modified UW criteria accurately classified 266 (63.9%, kappa = 0.321, 95% CI 0.255 to 0.386) cases according to NASCET-derived measurements. The sensitivity, specificity, and accuracy at ≥ 60% stenosis were 65.7%, 81.3%, and 81.9%. The CCP criteria resulted in 296 (70.9%) accurate diagnoses (kappa = 0.359, 95% CI 0.280 to 0.437). At ≥ 70% stenosis, the sensitivity, specificity and accuracy were 38.8%, 91.6%, and 87.1% for NASCET. Comparison of the duplex results to ECST-derived CTA measurements revealed a similar trend (UW 53.1%, κ = 0.301 vs CCP 62.1%, κ = 0.315). The CCP criteria demonstrate a higher concordance rate with measurements taken from CTAs. The CCP criteria may be more sensitive in classifying clinically significant degrees of stenosis without a loss in diagnostic accuracy.

Code-based Diagnostic Algorithms for Idiopathic Pulmonary Fibrosis. Case Validation and Improvement.

PubMed

Ley, Brett; Urbania, Thomas; Husson, Gail; Vittinghoff, Eric; Brush, David R; Eisner, Mark D; Iribarren, Carlos; Collard, Harold R

2017-06-01

Population-based studies of idiopathic pulmonary fibrosis (IPF) in the United States have been limited by reliance on diagnostic code-based algorithms that lack clinical validation. To validate a well-accepted International Classification of Diseases, Ninth Revision, code-based algorithm for IPF using patient-level information and to develop a modified algorithm for IPF with enhanced predictive value. The traditional IPF algorithm was used to identify potential cases of IPF in the Kaiser Permanente Northern California adult population from 2000 to 2014. Incidence and prevalence were determined overall and by age, sex, and race/ethnicity. A validation subset of cases (n = 150) underwent expert medical record and chest computed tomography review. A modified IPF algorithm was then derived and validated to optimize positive predictive value. From 2000 to 2014, the traditional IPF algorithm identified 2,608 cases among 5,389,627 at-risk adults in the Kaiser Permanente Northern California population. Annual incidence was 6.8/100,000 person-years (95% confidence interval [CI], 6.1-7.7) and was higher in patients with older age, male sex, and white race. The positive predictive value of the IPF algorithm was only 42.2% (95% CI, 30.6 to 54.6%); sensitivity was 55.6% (95% CI, 21.2 to 86.3%). The corrected incidence was estimated at 5.6/100,000 person-years (95% CI, 2.6-10.3). A modified IPF algorithm had improved positive predictive value but reduced sensitivity compared with the traditional algorithm. A well-accepted International Classification of Diseases, Ninth Revision, code-based IPF algorithm performs poorly, falsely classifying many non-IPF cases as IPF and missing a substantial proportion of IPF cases. A modification of the IPF algorithm may be useful for future population-based studies of IPF.

Gossip-based solutions for discrete rendezvous in populations of communicating agents.

PubMed

Hollander, Christopher D; Wu, Annie S

2014-01-01

The objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location. We introduce the buffered gossip algorithm as a general solution to the rendezvous problem in a discrete domain with direct communication between decentralized agents. We compare the performance of the buffered gossip algorithm against the well known uniform gossip algorithm. We believe that a buffered solution is preferable to an unbuffered solution, such as the uniform gossip algorithm, because the use of a buffer allows an agent to use multiple information sources when determining its desired rendezvous point, and that access to multiple information sources may improve agent decision making by reinforcing or contradicting an initial choice. To show that the buffered gossip algorithm is an actual solution for the rendezvous problem, we construct a theoretical proof of convergence and derive the conditions under which the buffered gossip algorithm is guaranteed to produce a consensus on rendezvous location. We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem. We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms. Our results suggest that the buffered gossip algorithm can solve the rendezvous problem faster than the uniform gossip algorithm; however, the relative performance between these two solutions depends on the specific constraints of the problem and the parameters of the buffered gossip algorithm.

Gossip-Based Solutions for Discrete Rendezvous in Populations of Communicating Agents

PubMed Central

Hollander, Christopher D.; Wu, Annie S.

2014-01-01

The objective of the rendezvous problem is to construct a method that enables a population of agents to agree on a spatial (and possibly temporal) meeting location. We introduce the buffered gossip algorithm as a general solution to the rendezvous problem in a discrete domain with direct communication between decentralized agents. We compare the performance of the buffered gossip algorithm against the well known uniform gossip algorithm. We believe that a buffered solution is preferable to an unbuffered solution, such as the uniform gossip algorithm, because the use of a buffer allows an agent to use multiple information sources when determining its desired rendezvous point, and that access to multiple information sources may improve agent decision making by reinforcing or contradicting an initial choice. To show that the buffered gossip algorithm is an actual solution for the rendezvous problem, we construct a theoretical proof of convergence and derive the conditions under which the buffered gossip algorithm is guaranteed to produce a consensus on rendezvous location. We use these results to verify that the uniform gossip algorithm also solves the rendezvous problem. We then use a multi-agent simulation to conduct a series of simulation experiments to compare the performance between the buffered and uniform gossip algorithms. Our results suggest that the buffered gossip algorithm can solve the rendezvous problem faster than the uniform gossip algorithm; however, the relative performance between these two solutions depends on the specific constraints of the problem and the parameters of the buffered gossip algorithm. PMID:25397882

Diagnostic standards for dopaminergic augmentation of restless legs syndrome: report from a World Association of Sleep Medicine-International Restless Legs Syndrome Study Group consensus conference at the Max Planck Institute.

PubMed

García-Borreguero, Diego; Allen, Richard P; Kohnen, Ralf; Högl, Birgit; Trenkwalder, Claudia; Oertel, Wolfgang; Hening, Wayne A; Paulus, Walter; Rye, David; Walters, Arthur; Winkelmann, Juliane; Earley, Christopher J

2007-08-01

Augmentation of symptom severity is the main complication of dopaminergic treatment of restless legs syndrome (RLS). The current article reports on the considerations of augmentation that were made during a European Restless Legs Syndrome Study Group (EURLSSG)-sponsored Consensus Conference in April 2006 at the Max Planck Institute (MPI) in Munich, Germany, the conclusions of which were endorsed by the International RLS Study Group (IRLSSG) and the World Association of Sleep Medicine (WASM). The Consensus Conference sought to develop a better understanding of augmentation and generate a better operational definition for its clinical identification. Current concepts of the pathophysiology, clinical features, and therapy of RLS augmentation were evaluated by subgroups who presented a summary of their findings for general consideration and discussion. Recent data indicating sensitivity and specificity of augmentation features for identification of augmentation were also evaluated. The diagnostic criteria of augmentation developed at the National Institutes of Health (NIH) conference in 2002 were reviewed in light of current data and theoretical understanding of augmentation. The diagnostic value and criteria for each of the accepted features of augmentation were considered by the group. A consensus was then developed for a revised statement of the diagnostic criteria for augmentation. Five major diagnostic features of augmentation were identified: usual time of RLS symptom onset each day, number of body parts with RLS symptoms, latency to symptoms at rest, severity of the symptoms when they occur, and effects of dopaminergic medication on symptoms. The quantitative data available relating the time of RLS onset and the presence of other features indicated optimal augmentation criteria of either a 4-h advance in usual starting time for RLS symptoms or a combination of the occurrence of other features. A paradoxical response to changes in medication dose also indicates augmentation. Clinical significance of augmentation is defined. The Consensus Conference agreed upon new operational criteria for the clinical diagnosis of RLS augmentation: the MPI diagnostic criteria for augmentation. Areas needing further consideration for validating these criteria and for understanding the underlying biology of RLS augmentation are indicated.

Causal Evaluation of Acute Recurrent and Chronic Pancreatitis in Children: Consensus From the INSPPIRE Group.

PubMed

Gariepy, Cheryl E; Heyman, Melvin B; Lowe, Mark E; Pohl, John F; Werlin, Steven L; Wilschanski, Michael; Barth, Bradley; Fishman, Douglas S; Freedman, Steven D; Giefer, Matthew J; Gonska, Tanja; Himes, Ryan; Husain, Sohail Z; Morinville, Veronique D; Ooi, Chee Y; Schwarzenberg, Sarah J; Troendle, David M; Yen, Elizabeth; Uc, Aliye

2017-01-01

Acute recurrent pancreatitis (ARP) and chronic pancreatitis (CP) have been diagnosed in children at increasing rates during the past decade. As pediatric ARP and CP are still relatively rare conditions, little quality evidence is available on which to base the diagnosis and determination of etiology. The aim of the study was to review the current state of the literature regarding the etiology of these disorders and to developed a consensus among a panel of clinically active specialists caring for children with these disorders to help guide the diagnostic evaluation and identify areas most in need of future research. A systematic review of the literature was performed and scored for quality, followed by consensus statements developed and scored by each individual in the group for level of agreement and strength of the supporting data using a modified Delphi method. Scores were analyzed for the level of consensus achieved by the group. The panel reached consensus on 27 statements covering the definitions of pediatric ARP and CP, evaluation for potential etiologies of these disorders, and long-term monitoring. Statements for which the group reached consensus to make no recommendation or could not reach consensus are discussed. This consensus helps define the minimal diagnostic evaluation and monitoring of children with ARP and CP. Even in areas in which we reached consensus, the quality of the evidence is weak, highlighting the need for further research. Improved understanding of the underlying cause will facilitate treatment development and targeting.

The Causal Evaluation of Acute Recurrent and Chronic Pancreatitis in Children: Consensus From the INSPPIRE Group

PubMed Central

Gariepy, Cheryl E.; Heyman, Melvin B.; Lowe, Mark E.; Pohl, John F.; Werlin, Steven L.; Wilschanski, Michael; Barth, Bradley; Fishman, Douglas S.; Freedman, Steven D.; Giefer, Matthew J.; Gonska, Tanja; Himes, Ryan; Husain, Sohail Z.; Morinville, Veronique D.; Ooi, Chee Y.; Schwarzenberg, Sarah Jane; Troendle, David M.; Yen, Elizabeth; Uc, Aliye

2016-01-01

Acute recurrent pancreatitis (ARP) and chronic pancreatitis (CP) have been diagnosed in children at increasing rates over the past decade. However, as pediatric ARP and CP are still relatively rare conditions, little quality evidence is available on which to base the diagnosis and determination of etiology. Objectives: To review the current state of the literature regarding the etiology of these disorders and to developed a consensus among a panel of clinically active specialists caring for children with these disorders to help guide the diagnostic evaluation and identify areas most in need of future research. Methods: A systematic review of the literature was performed and scored for quality, then consensus statements developed and scored by each individual in the group for level of agreement and strength of the supporting data using a modified Delphi method. Scores were analyzed for the level of consensus achieved by the group. Results: The panel reached consensus on 27 statements covering the definitions of pediatric ARP and CP, evaluation for potential etiologies of these disorders, and long-term monitoring. Statements for which the group reached consensus to make no recommendation or could not reach consensus are discussed. Conclusion: This consensus helps define the minimal diagnostic evaluation and monitoring of children with ARP and CP. Even in areas in which we reached consensus, the quality of the evidence is weak, highlighting the need for further research. Improved understanding of the underlying cause will facilitate treatment development and targeting. PMID:27782962

Diagnostic tools in Rhinology EAACI position paper

PubMed Central

2011-01-01

This EAACI Task Force document aims at providing the readers with a comprehensive and complete overview of the currently available tools for diagnosis of nasal and sino-nasal disease. We have tried to logically order the different important issues related to history taking, clinical examination and additional investigative tools for evaluation of the severity of sinonasal disease into a consensus document. A panel of European experts in the field of Rhinology has contributed to this consensus document on Diagnostic Tools in Rhinology. PMID:22410181

International survey among orthopaedic trauma surgeons: Lack of a definition of fracture-related infection.

PubMed

Morgenstern, M; Moriarty, T F; Kuehl, R; Richards, R G; McNally, M A; Verhofstad, M H J; Borens, O; Zalavras, C; Raschke, M; Kates, S L; Metsemakers, W J

2018-03-01

Fracture-related infection (FRI) is one of the most challenging musculoskeletal complications in orthopaedic-trauma surgery. Although the orthopaedic community has developed and adopted a consensus definition of prosthetic joint infections (PJI), it still remains unclear how the trauma surgery community defines FRI in daily clinical practice or in performing clinical research studies. The central aim of this study was to survey the opinions of a global network of trauma surgeons on the definitions and criteria they routinely use, and their opinion on the need for a unified definition of FRI. The secondary aims were to survey their opinion on the utility of currently used definitions that may be at least partially applicable for FRI, and finally their opinion on the important clinical parameters that should be considered as diagnostic criteria for FRI. An 11-item questionnaire was developed to cover the above-mentioned aims. The questionnaire was administered by SurveyMonkey and was sent via blast email to all registered users of AO Trauma (Davos, Switzerland). Out of the 26'563 recipients who opened the email, 2'327 (8.8%) completed the questionnaire. Nearly 90% of respondents agreed that a consensus-derived definition for FRI is required and 66% of the surgeons also agreed that PJI and FRI are not equal with respect to diagnosis, treatment and outcome. Furthermore, "positive cultures from microbiology testing", "elevation of CRP", "purulent drainage" and "local clinical signs of infection" were voted the most important diagnostic parameters for FRI. This international survey infers the need for a consensus definition of FRI and provides insight into the clinical parameters seen by an international community of trauma surgeons as being critical for defining FRI. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fourier analysis algorithm for the posterior corneal keratometric data: clinical usefulness in keratoconus.

PubMed

Sideroudi, Haris; Labiris, Georgios; Georgantzoglou, Kimon; Ntonti, Panagiota; Siganos, Charalambos; Kozobolis, Vassilios

2017-07-01

To develop an algorithm for the Fourier analysis of posterior corneal videokeratographic data and to evaluate the derived parameters in the diagnosis of Subclinical Keratoconus (SKC) and Keratoconus (KC). This was a cross-sectional, observational study that took place in the Eye Institute of Thrace, Democritus University, Greece. Eighty eyes formed the KC group, 55 eyes formed the SKC group while 50 normal eyes populated the control group. A self-developed algorithm in visual basic for Microsoft Excel performed a Fourier series harmonic analysis for the posterior corneal sagittal curvature data. The algorithm decomposed the obtained curvatures into a spherical component, regular astigmatism, asymmetry and higher order irregularities for averaged central 4 mm and for each individual ring separately (1, 2, 3 and 4 mm). The obtained values were evaluated for their diagnostic capacity using receiver operating curves (ROC). Logistic regression was attempted for the identification of a combined diagnostic model. Significant differences were detected in regular astigmatism, asymmetry and higher order irregularities among groups. For the SKC group, the parameters with high diagnostic ability (AUC > 90%) were the higher order irregularities, the asymmetry and the regular astigmatism, mainly in the corneal periphery. Higher predictive accuracy was identified using diagnostic models that combined the asymmetry, regular astigmatism and higher order irregularities in averaged 3and 4 mm area (AUC: 98.4%, Sensitivity: 91.7% and Specificity:100%). Fourier decomposition of posterior Keratometric data provides parameters with high accuracy in differentiating SKC from normal corneas and should be included in the prompt diagnosis of KC. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

Using the modified Delphi method to establish clinical consensus for the diagnosis and treatment of patients with rotator cuff pathology.

PubMed

Eubank, Breda H; Mohtadi, Nicholas G; Lafave, Mark R; Wiley, J Preston; Bois, Aaron J; Boorman, Richard S; Sheps, David M

2016-05-20

Patients presenting to the healthcare system with rotator cuff pathology do not always receive high quality care. High quality care occurs when a patient receives care that is accessible, appropriate, acceptable, effective, efficient, and safe. The aim of this study was twofold: 1) to develop a clinical pathway algorithm that sets forth a stepwise process for making decisions about the diagnosis and treatment of rotator cuff pathology presenting to primary, secondary, and tertiary healthcare settings; and 2) to establish clinical practice guidelines for the diagnosis and treatment of rotator cuff pathology to inform decision-making processes within the algorithm. A three-step modified Delphi method was used to establish consensus. Fourteen experts representing athletic therapy, physiotherapy, sport medicine, and orthopaedic surgery were invited to participate as the expert panel. In round 1, 123 best practice statements were distributed to the panel. Panel members were asked to mark "agree" or "disagree" beside each statement, and provide comments. The same voting method was again used for round 2. Round 3 consisted of a final face-to-face meeting. In round 1, statements were grouped and reduced to 44 statements that met consensus. In round 2, five statements reached consensus. In round 3, ten statements reached consensus. Consensus was reached for 59 statements representing five domains: screening, diagnosis, physical examination, investigations, and treatment. The final face-to-face meeting was also used to develop clinical pathway algorithms (i.e., clinical care pathways) for three types of rotator cuff pathology: acute, chronic, and acute-on-chronic. This consensus guideline will help to standardize care, provide guidance on the diagnosis and treatment of rotator cuff pathology, and assist in clinical decision-making for all healthcare professionals.

A consensus algorithm for approximate string matching and its application to QRS complex detection

NASA Astrophysics Data System (ADS)

Alba, Alfonso; Mendez, Martin O.; Rubio-Rincon, Miguel E.; Arce-Santana, Edgar R.

2016-08-01

In this paper, a novel algorithm for approximate string matching (ASM) is proposed. The novelty resides in the fact that, unlike most other methods, the proposed algorithm is not based on the Hamming or Levenshtein distances, but instead computes a score for each symbol in the search text based on a consensus measure. Those symbols with sufficiently high scores will likely correspond to approximate instances of the pattern string. To demonstrate the usefulness of the proposed method, it has been applied to the detection of QRS complexes in electrocardiographic signals with competitive results when compared against the classic Pan-Tompkins (PT) algorithm. The proposed method outperformed PT in 72% of the test cases, with no extra computational cost.

Distributed consensus for discrete-time heterogeneous multi-agent systems

NASA Astrophysics Data System (ADS)

Zhao, Huanyu; Fei, Shumin

2018-06-01

This paper studies the consensus problem for a class of discrete-time heterogeneous multi-agent systems. Two kinds of consensus algorithms will be considered. The heterogeneous multi-agent systems considered are converted into equivalent error systems by a model transformation. Then we analyse the consensus problem of the original systems by analysing the stability problem of the error systems. Some sufficient conditions for consensus of heterogeneous multi-agent systems are obtained by applying algebraic graph theory and matrix theory. Simulation examples are presented to show the usefulness of the results.

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods

PubMed Central

Hancock, Matthew C.; Magnan, Jerry F.

2016-01-01

Abstract. In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists’ annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (±1.14)%, which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (±0.012), which increases to 0.949 (±0.007) when diameter and volume features are included and has an accuracy of 88.08 (±1.11)%. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification. PMID:27990453

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods.

PubMed

Hancock, Matthew C; Magnan, Jerry F

2016-10-01

In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 [Formula: see text], which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 ([Formula: see text]), which increases to 0.949 ([Formula: see text]) when diameter and volume features are included and has an accuracy of 88.08 [Formula: see text]. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.

Time-Resolved C-Arm Computed Tomographic Angiography Derived From Computed Tomographic Perfusion Acquisition: New Capability for One-Stop-Shop Acute Ischemic Stroke Treatment in the Angiosuite.

PubMed

Yang, Pengfei; Niu, Kai; Wu, Yijing; Struffert, Tobias; Dorfler, Arnd; Schafer, Sebastian; Royalty, Kevin; Strother, Charles; Chen, Guang-Hong

2015-12-01

Multimodal imaging using cone beam C-arm computed tomography (CT) may shorten the delay from ictus to revascularization for acute ischemic stroke patients with a large vessel occlusion. Largely because of limited temporal resolution, reconstruction of time-resolved CT angiography (CTA) from these systems has not yielded satisfactory results. We evaluated the image quality and diagnostic value of time-resolved C-arm CTA reconstructed using novel image processing algorithms. Studies were done under an Institutional Review Board approved protocol. Postprocessing of data from 21 C-arm CT dynamic perfusion acquisitions from 17 patients with acute ischemic stroke were done to derive time-resolved C-arm CTA images. Two observers independently evaluated image quality and diagnostic content for each case. ICC and receiver-operating characteristic analysis were performed to evaluate interobserver agreement and diagnostic value of this novel imaging modality. Time-resolved C-arm CTA images were successfully generated from 20 data sets (95.2%, 20/21). Two observers agreed well that the image quality for large cerebral arteries was good but was more limited for small cerebral arteries (distal to M1, A1, and P1). receiver-operating characteristic curves demonstrated excellent diagnostic value for detecting large vessel occlusions (area under the curve=0.987-1). Time-resolved CTAs derived from C-arm CT perfusion acquisitions provide high quality images that allowed accurate diagnosis of large vessel occlusions. Although image quality of smaller arteries in this study was not optimal ongoing modifications of the postprocessing algorithm will likely remove this limitation. Adding time-resolved C-arm CTAs to the capabilities of the angiography suite further enhances its suitability as a one-stop shop for care for patients with acute ischemic stroke. © 2015 American Heart Association, Inc.

Antibody-mediated rejection of the lung: A consensus report of the International Society for Heart and Lung Transplantation.

PubMed

Levine, Deborah J; Glanville, Allan R; Aboyoun, Christina; Belperio, John; Benden, Christian; Berry, Gerald J; Hachem, Ramsey; Hayes, Don; Neil, Desley; Reinsmoen, Nancy L; Snyder, Laurie D; Sweet, Stuart; Tyan, Dolly; Verleden, Geert; Westall, Glen; Yusen, Roger D; Zamora, Martin; Zeevi, Adriana

2016-04-01

Antibody-mediated rejection (AMR) is a recognized cause of allograft dysfunction in lung transplant recipients. Unlike AMR in other solid-organ transplant recipients, there are no standardized diagnostic criteria or an agreed-upon definition. Hence, a working group was created by the International Society for Heart and Lung Transplantation with the aim of determining criteria for pulmonary AMR and establishing a definition. Diagnostic criteria and a working consensus definition were established. Key diagnostic criteria include the presence of antibodies directed toward donor human leukocyte antigens and characteristic lung histology with or without evidence of complement 4d within the graft. Exclusion of other causes of allograft dysfunction increases confidence in the diagnosis but is not essential. Pulmonary AMR may be clinical (allograft dysfunction which can be asymptomatic) or sub-clinical (normal allograft function). This consensus definition will have clinical, therapeutic and research implications. Copyright © 2016 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Deep-learning derived features for lung nodule classification with limited datasets

NASA Astrophysics Data System (ADS)

Thammasorn, P.; Wu, W.; Pierce, L. A.; Pipavath, S. N.; Lampe, P. D.; Houghton, A. M.; Haynor, D. R.; Chaovalitwongse, W. A.; Kinahan, P. E.

2018-02-01

Only a few percent of indeterminate nodules found in lung CT images are cancer. However, enabling earlier diagnosis is important to avoid invasive procedures or long-time surveillance to those benign nodules. We are evaluating a classification framework using radiomics features derived with a machine learning approach from a small data set of indeterminate CT lung nodule images. We used a retrospective analysis of 194 cases with pulmonary nodules in the CT images with or without contrast enhancement from lung cancer screening clinics. The nodules were contoured by a radiologist and texture features of the lesion were calculated. In addition, sematic features describing shape were categorized. We also explored a Multiband network, a feature derivation path that uses a modified convolutional neural network (CNN) with a Triplet Network. This was trained to create discriminative feature representations useful for variable-sized nodule classification. The diagnostic accuracy was evaluated for multiple machine learning algorithms using texture, shape, and CNN features. In the CT contrast-enhanced group, the texture or semantic shape features yielded an overall diagnostic accuracy of 80%. Use of a standard deep learning network in the framework for feature derivation yielded features that substantially underperformed compared to texture and/or semantic features. However, the proposed Multiband approach of feature derivation produced results similar in diagnostic accuracy to the texture and semantic features. While the Multiband feature derivation approach did not outperform the texture and/or semantic features, its equivalent performance indicates promise for future improvements to increase diagnostic accuracy. Importantly, the Multiband approach adapts readily to different size lesions without interpolation, and performed well with relatively small amount of training data.

Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

PubMed

Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin

2017-08-16

The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

NASA Technical Reports Server (NTRS)

Hunter, H. E.

1972-01-01

The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

Simultaneous Sensor and Process Fault Diagnostics for Propellant Feed System

NASA Technical Reports Server (NTRS)

Cao, J.; Kwan, C.; Figueroa, F.; Xu, R.

2006-01-01

The main objective of this research is to extract fault features from sensor faults and process faults by using advanced fault detection and isolation (FDI) algorithms. A tank system that has some common characteristics to a NASA testbed at Stennis Space Center was used to verify our proposed algorithms. First, a generic tank system was modeled. Second, a mathematical model suitable for FDI has been derived for the tank system. Third, a new and general FDI procedure has been designed to distinguish process faults and sensor faults. Extensive simulations clearly demonstrated the advantages of the new design.

The computation of Laplacian smoothing splines with examples

NASA Technical Reports Server (NTRS)

Wendelberger, J. G.

1982-01-01

Laplacian smoothing splines (LSS) are presented as generalizations of graduation, cubic and thin plate splines. The method of generalized cross validation (GCV) to choose the smoothing parameter is described. The GCV is used in the algorithm for the computation of LSS's. An outline of a computer program which implements this algorithm is presented along with a description of the use of the program. Examples in one, two and three dimensions demonstrate how to obtain estimates of function values with confidence intervals and estimates of first and second derivatives. Probability plots are used as a diagnostic tool to check for model inadequacy.

Assessing operating characteristics of CAD algorithms in the absence of a gold standard

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy Choudhury, Kingshuk; Paik, David S.; Yi, Chin A.

2010-04-15

Purpose: The authors examine potential bias when using a reference reader panel as ''gold standard'' for estimating operating characteristics of CAD algorithms for detecting lesions. As an alternative, the authors propose latent class analysis (LCA), which does not require an external gold standard to evaluate diagnostic accuracy. Methods: A binomial model for multiple reader detections using different diagnostic protocols was constructed, assuming conditional independence of readings given true lesion status. Operating characteristics of all protocols were estimated by maximum likelihood LCA. Reader panel and LCA based estimates were compared using data simulated from the binomial model for a range ofmore » operating characteristics. LCA was applied to 36 thin section thoracic computed tomography data sets from the Lung Image Database Consortium (LIDC): Free search markings of four radiologists were compared to markings from four different CAD assisted radiologists. For real data, bootstrap-based resampling methods, which accommodate dependence in reader detections, are proposed to test of hypotheses of differences between detection protocols. Results: In simulation studies, reader panel based sensitivity estimates had an average relative bias (ARB) of -23% to -27%, significantly higher (p-value <0.0001) than LCA (ARB -2% to -6%). Specificity was well estimated by both reader panel (ARB -0.6% to -0.5%) and LCA (ARB 1.4%-0.5%). Among 1145 lesion candidates LIDC considered, LCA estimated sensitivity of reference readers (55%) was significantly lower (p-value 0.006) than CAD assisted readers' (68%). Average false positives per patient for reference readers (0.95) was not significantly lower (p-value 0.28) than CAD assisted readers' (1.27). Conclusions: Whereas a gold standard based on a consensus of readers may substantially bias sensitivity estimates, LCA may be a significantly more accurate and consistent means for evaluating diagnostic accuracy.« less

Computation of the target state and feedback controls for time optimal consensus in multi-agent systems

NASA Astrophysics Data System (ADS)

Mulla, Ameer K.; Patil, Deepak U.; Chakraborty, Debraj

2018-02-01

N identical agents with bounded inputs aim to reach a common target state (consensus) in the minimum possible time. Algorithms for computing this time-optimal consensus point, the control law to be used by each agent and the time taken for the consensus to occur, are proposed. Two types of multi-agent systems are considered, namely (1) coupled single-integrator agents on a plane and, (2) double-integrator agents on a line. At the initial time instant, each agent is assumed to have access to the state information of all the other agents. An algorithm, using convexity of attainable sets and Helly's theorem, is proposed, to compute the final consensus target state and the minimum time to achieve this consensus. Further, parts of the computation are parallelised amongst the agents such that each agent has to perform computations of O(N2) run time complexity. Finally, local feedback time-optimal control laws are synthesised to drive each agent to the target point in minimum time. During this part of the operation, the controller for each agent uses measurements of only its own states and does not need to communicate with any neighbouring agents.

New bone post-processing tools in forensic imaging: a multi-reader feasibility study to evaluate detection time and diagnostic accuracy in rib fracture assessment.

PubMed

Glemser, Philip A; Pfleiderer, Michael; Heger, Anna; Tremper, Jan; Krauskopf, Astrid; Schlemmer, Heinz-Peter; Yen, Kathrin; Simons, David

2017-03-01

The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.

Recommendations for the use of molecular diagnostics in the diagnosis of allergic dis-eases.

PubMed

Villalta, D; Tonutti, E; Bizzaro, N; Brusca, I; Sargentini, V; Asero, R; Bilo, M B; Manzotti, G; Murzilli, F; Cecchi, L; Musarra, A

2018-03-01

The Study Group on Allergology of the Italian Society of Clinical Pathology and Laboratory Medicine (SIPMeL) and the Associazione Italiana degli Allergologi e Immunologi Territoriali e Ospedalieri (AAIITO) developed the present recommendations on the diagnosis of allergic diseases based on the use of molecular allergenic components, whose purpose is to provide the pathologists and the clinicians with information and algorithms enabling a proper use of this second-level diagnostics. Molecular diagnostics allows definition of the exact sensitization profile of the allergic patient. The methodology followed to develop these recommendations included an initial phase of discussion between all the components to integrate the knowledge derived from scientific evidence, a revision of the recommendations made by Italian and foreign experts, and the subsequent production of this document to be disseminated to all those who deal with allergy diagnostics.

Is bruxism a disorder or a behaviour? Rethinking the international consensus on defining and grading of bruxism.

PubMed

Raphael, K G; Santiago, V; Lobbezoo, F

2016-10-01

Inspired by the international consensus on defining and grading of bruxism (Lobbezoo F, Ahlberg J, Glaros AG, Kato T, Koyano K, Lavigne GJ et al. J Oral Rehabil. 2013;40:2), this commentary examines its contribution and underlying assumptions for defining sleep bruxism (SB). The consensus' parsimonious redefinition of bruxism as a behaviour is an advance, but we explore an implied question: might SB be more than behaviour? Behaviours do not inherently require clinical treatment, making the consensus-proposed 'diagnostic grading system' inappropriate. However, diagnostic grading might be useful, if SB were considered a disorder. Therefore, to fully appreciate the contribution of the consensus statement, we first consider standards and evidence for determining whether SB is a disorder characterised by harmful dysfunction or a risk factor increasing probability of a disorder. Second, the strengths and weaknesses of the consensus statement's proposed 'diagnostic grading system' are examined. The strongest evidence-to-date does not support SB as disorder as implied by 'diagnosis'. Behaviour alone is not diagnosed; disorders are. Considered even as a grading system of behaviour, the proposed system is weakened by poor sensitivity of self-report for direct polysomnographic (PSG)-classified SB and poor associations between clinical judgments of SB and portable PSG; reliance on dichotomised reports; and failure to consider SB behaviour on a continuum, measurable and definable through valid behavioural observation. To date, evidence for validity of self-report or clinician report in placing SB behaviour on a continuum is lacking, raising concerns about their potential utility in any bruxism behavioural grading system, and handicapping future study of whether SB may be a useful risk factor for, or itself a disorder requiring treatment. © 2016 John Wiley & Sons Ltd.

Restarting and recentering genetic algorithm variations for DNA fragment assembly: The necessity of a multi-strategy approach.

PubMed

Hughes, James Alexander; Houghten, Sheridan; Ashlock, Daniel

2016-12-01

DNA Fragment assembly - an NP-Hard problem - is one of the major steps in of DNA sequencing. Multiple strategies have been used for this problem, including greedy graph-based algorithms, deBruijn graphs, and the overlap-layout-consensus approach. This study focuses on the overlap-layout-consensus approach. Heuristics and computational intelligence methods are combined to exploit their respective benefits. These algorithm combinations were able to produce high quality results surpassing the best results obtained by a number of competitive algorithms specially designed and tuned for this problem on thirteen of sixteen popular benchmarks. This work also reinforces the necessity of using multiple search strategies as it is clearly observed that algorithm performance is dependent on problem instance; without a deeper look into many searches, top solutions could be missed entirely. Copyright © 2016. Published by Elsevier Ireland Ltd.

Consensus-based recommendations for the management of juvenile dermatomyositis

PubMed Central

Enders, Felicitas Bellutti; Bader-Meunier, Brigitte; Baildam, Eileen; Constantin, Tamas; Dolezalova, Pavla; Feldman, Brian M; Lahdenne, Pekka; Magnusson, Bo; Nistala, Kiran; Ozen, Seza; Pilkington, Clarissa; Ravelli, Angelo; Russo, Ricardo; Uziel, Yosef; van Brussel, Marco; van der Net, Janjaap; Vastert, Sebastiaan; Wedderburn, Lucy R; Wulffraat, Nicolaas; McCann, Liza J; van Royen-Kerkhof, Annet

2017-01-01

Background In 2012, a European initiative called Single Hub and Access point for pediatric Rheumatology in Europe (SHARE) was launched to optimise and disseminate diagnostic and management regimens in Europe for children and young adults with rheumatic diseases. Juvenile dermatomyositis (JDM) is a rare disease within the group of paediatric rheumatic diseases (PRDs) and can lead to significant morbidity. Evidence-based guidelines are sparse and management is mostly based on physicians' experience. Consequently, treatment regimens differ throughout Europe. Objectives To provide recommendations for diagnosis and treatment of JDM. Methods Recommendations were developed by an evidence-informed consensus process using the European League Against Rheumatism standard operating procedures. A committee was constituted, consisting of 19 experienced paediatric rheumatologists and 2 experts in paediatric exercise physiology and physical therapy, mainly from Europe. Recommendations derived from a validated systematic literature review were evaluated by an online survey and subsequently discussed at two consensus meetings using nominal group technique. Recommendations were accepted if >80% agreement was reached. Results In total, 7 overarching principles, 33 recommendations on diagnosis and 19 recommendations on therapy were accepted with >80% agreement among experts. Topics covered include assessment of skin, muscle and major organ involvement and suggested treatment pathways. Conclusions The SHARE initiative aims to identify best practices for treatment of patients suffering from PRD. Within this remit, recommendations for the diagnosis and treatment of JDM have been formulated by an evidence-informed consensus process to produce a standard of care for patients with JDM throughout Europe. PMID:27515057

Retention or deletion of personality disorder diagnoses for DSM-5: an expert consensus approach.

PubMed

Mullins-Sweatt, Stephanie N; Bernstein, David P; Widiger, Thomas A

2012-10-01

One of the official proposals for the fifth edition of the American Psychiatric Association's (APA) diagnostic manual (DSM-5) is to delete half of the existing personality disorders (i.e., dependent, histrionic, narcissistic, paranoid, and schizoid). Within the APA guidelines for DSM-5 decisions, it is stated that there should be expert consensus agreement for the deletion of a diagnostic category. Additionally, categories to be deleted should have low clinical utility and/or minimal evidence for validity. The current study surveyed members of two personality disorder associations (n = 146) with respect to the utility, validity, and status of each DSM-IV-TR personality disorder diagnosis. Findings indicated that the proposal to delete five of the personality disorders lacks consensus support within the personality disorder community.

Clinical Evaluation of Youth with Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): Recommendations from the 2013 PANS Consensus Conference

PubMed Central

Frankovich, Jennifer; Cooperstock, Michael; Cunningham, Madeleine W.; Latimer, M. Elizabeth; Murphy, Tanya K.; Pasternack, Mark; Thienemann, Margo; Williams, Kyle; Walter, Jolan; Swedo, Susan E.

2015-01-01

Abstract On May 23 and 24, 2013, the First PANS Consensus Conference was convened at Stanford University, calling together a geographically diverse group of clinicians and researchers from complementary fields of pediatrics: General and developmental pediatrics, infectious diseases, immunology, rheumatology, neurology, and child psychiatry. Participants were academicians with clinical and research interests in pediatric autoimmune neuropsychiatric disorder associated with streptococcus (PANDAS) in youth, and the larger category of pediatric acute-onset neuropsychiatric syndrome (PANS). The goals were to clarify the diagnostic boundaries of PANS, to develop systematic strategies for evaluation of suspected PANS cases, and to set forth the most urgently needed studies in this field. Presented here is a consensus statement proposing recommendations for the diagnostic evaluation of youth presenting with PANS. PMID:25325534

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Derivation and validation of a two-biomarker panel for diagnosis of ARDS in patients with severe traumatic injuries

PubMed Central

Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S

2017-01-01

Background Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Methods Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Results Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). Discussion A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Level of evidence Diagnostic study, level II. PMID:29766112

Derivation and validation of a two-biomarker panel for diagnosis of ARDS in patients with severe traumatic injuries.

PubMed

Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S

2017-01-01

Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Diagnostic study, level II.

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

PubMed

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Stability of formation control using a consensus protocol under directed communications with two time delays and delay scheduling

NASA Astrophysics Data System (ADS)

Cepeda-Gomez, Rudy; Olgac, Nejat

2016-01-01

We consider a linear algorithm to achieve formation control in a group of agents which are driven by second-order dynamics and affected by two rationally independent delays. One of the delays is in the position and the other in the velocity information channels. These delays are taken as constant and uniform throughout the system. The communication topology is assumed to be directed and fixed. The formation is attained by adding a supplementary control term to the stabilising consensus protocol. In preparation for the formation control logic, we first study the stability of the consensus, using the recent cluster treatment of characteristic roots (CTCR) paradigm. This effort results in a unique depiction of the non-conservative stability boundaries in the domain of the delays. However, CTCR requires the knowledge of the potential stability switching loci exhaustively within this domain. The creation of these loci is done in a new surrogate coordinate system, called the 'spectral delay space (SDS)'. The relative stability is also investigated, which has to do with the speed of reaching consensus. This step leads to a paradoxical control design concept, called the 'delay scheduling', which highlights the fact that the group behaviour may be enhanced by increasing the delays. These steps lead to a control strategy to establish a desired group formation that guarantees spacing among the agents. Example case studies are presented to validate the underlying analytical derivations.

Adaptation of a cubic smoothing spline algortihm for multi-channel data stitching at the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, C; Adcock, A; Azevedo, S

2010-12-28

Some diagnostics at the National Ignition Facility (NIF), including the Gamma Reaction History (GRH) diagnostic, require multiple channels of data to achieve the required dynamic range. These channels need to be stitched together into a single time series, and they may have non-uniform and redundant time samples. We chose to apply the popular cubic smoothing spline technique to our stitching problem because we needed a general non-parametric method. We adapted one of the algorithms in the literature, by Hutchinson and deHoog, to our needs. The modified algorithm and the resulting code perform a cubic smoothing spline fit to multiple datamore » channels with redundant time samples and missing data points. The data channels can have different, time-varying, zero-mean white noise characteristics. The method we employ automatically determines an optimal smoothing level by minimizing the Generalized Cross Validation (GCV) score. In order to automatically validate the smoothing level selection, the Weighted Sum-Squared Residual (WSSR) and zero-mean tests are performed on the residuals. Further, confidence intervals, both analytical and Monte Carlo, are also calculated. In this paper, we describe the derivation of our cubic smoothing spline algorithm. We outline the algorithm and test it with simulated and experimental data.« less

3D-CAM: Derivation and Validation of a 3-Minute Diagnostic Interview for CAM-defined Delirium

PubMed Central

Marcantonio, Edward R.; Ngo, Long H.; O’Connor, Margaret; Jones, Richard N.; Crane, Paul K.; Metzger, Eran D.; Inouye, Sharon K.

2015-01-01

Background Delirium is common, morbid, and costly, yet remains often unrecognized in most clinical settings. The Confusion Assessment Method (CAM) is the most widely used diagnostic algorithm, and operationalizing its features would represent a substantial advance for clinical care. Objective To derive the 3D-CAM, a new 3-minute diagnostic assessment for CAM-defined delirium, and to validate it against a clinical reference standard. Design Diagnostic test study Setting 4 general medicine units in an academic medical center Participants 201 inpatients aged ≥ 75 years old Measurements We identified 20 items that best operationalized the 4 CAM diagnostic features to create the 3D-CAM. For prospective validation, 3D-CAM assessments were administered by trained research assistants. Independently, clinicians performed an extensive assessment that included patient interviews, family interviews, and review of the medical record. These data were considered by an expert panel to determine the presence or absence of delirium and dementia (reference standard). We compared the 3D-CAM delirium determination to the reference standard in all patients and in subgroups with and without dementia. Results The 201 participants in the prospective validation study had mean age (SD) of 84 (5.5) years, and 27% had dementia. The expert panel identified delirium in 21%. Median administration time for 3D-CAM was 3 minutes (inter-quartile range: 2–5 minutes). The sensitivity [95% CI] of 3D-CAM was 95% [84%, 99%] and the specificity was 94% [90%, 97%]. The 3D-CAM performed well in patients both with dementia (sensitivity=96% [82%, 100%], specificity=86% [67%, 96%]) and without dementia (sensitivity=93% [66%, 100%], specificity=96% [91%,99%]). Limitations Limited to single center, cross-sectional, and medicine patients only Conclusion The 3D-CAM operationalizes the CAM algorithm using a 3-minute structured assessment with high sensitivity and specificity relative to a reference standard and could be an important tool for improving recognition of delirium. PMID:25329203

Can we create a valid treatment algorithm for patients with drug resistant overactive bladder (OAB) syndrome or detrusor overactivity (DO)? Results from a think tank (ICI-RS 2015).

PubMed

Apostolidis, Apostolos; Averbeck, Marcio Augusto; Sahai, Arun; Rahnama'i, Mohhamad Sajjad; Anding, Ralf; Robinson, Dudley; Gravas, Stavros; Dmochowski, Roger

2017-04-01

To review and assess the definitions of drug resistance and the evidence supporting treatment for drug resistant overactive bladder/detrusor overactivity (OAB/DO). Evidence review of the extant literature and consensus of opinion was used to derive the summary recommendations. Drug resistance or drug refractory status has been inconsistently defined and reported in current evident sources. Recent publications use some correlation of lack of efficacy and or experienced side effects to define drug resistance. Algorithms based upon these definitions largely relate to the appropriate use of neuromodulation or botulinum neurotoxin, based upon patient selection and patient choice. Current treatment pathways are hampered by inability to consistently profile patients to optimize management, particularly after failure of initial pragmatic treatment. Further research is recommended to better identify patient phenotype for purposes of directing optimized therapy for OAB/DO. Current treatment algorithms are influenced by extensive data generated from recent neuromodulation and botulinum neurotoxin trials. © 2017 Wiley Periodicals, Inc.

Approximately adaptive neural cooperative control for nonlinear multiagent systems with performance guarantee

NASA Astrophysics Data System (ADS)

Wang, Jing; Yang, Tianyu; Staskevich, Gennady; Abbe, Brian

2017-04-01

This paper studies the cooperative control problem for a class of multiagent dynamical systems with partially unknown nonlinear system dynamics. In particular, the control objective is to solve the state consensus problem for multiagent systems based on the minimisation of certain cost functions for individual agents. Under the assumption that there exist admissible cooperative controls for such class of multiagent systems, the formulated problem is solved through finding the optimal cooperative control using the approximate dynamic programming and reinforcement learning approach. With the aid of neural network parameterisation and online adaptive learning, our method renders a practically implementable approximately adaptive neural cooperative control for multiagent systems. Specifically, based on the Bellman's principle of optimality, the Hamilton-Jacobi-Bellman (HJB) equation for multiagent systems is first derived. We then propose an approximately adaptive policy iteration algorithm for multiagent cooperative control based on neural network approximation of the value functions. The convergence of the proposed algorithm is rigorously proved using the contraction mapping method. The simulation results are included to validate the effectiveness of the proposed algorithm.

Optimizing Diagnostic Imaging in the Emergency Department

PubMed Central

Mills, Angela M.; Raja, Ali S.; Marin, Jennifer R.

2015-01-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging in order to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, “Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization.” The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. PMID:25731864

Optimizing diagnostic imaging in the emergency department.

PubMed

Mills, Angela M; Raja, Ali S; Marin, Jennifer R

2015-05-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. © 2015 by the Society for Academic Emergency Medicine.

Consensus recommendations for the postmortem diagnosis of Alzheimer's disease. The National Institute on Aging, and Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer's Disease.

PubMed

1997-01-01

This report summarizes the consensus recommendations of a panel of neuropathologists from the United States and Europe to improve the postmortem diagnostic criteria for Alzheimer's disease. The recommendations followed from a two-day workshop sponsored by the National Institute on Aging (NIA) and the Ronald and Nancy Reagan Institute of the Alzheimer's Association to reassess the original NIA criteria for the postmortem diagnosis of Alzheimer's disease published in 1985. The consensus recommendations for improving the neuropathological criteria for the postmortem diagnosis of Alzheimer's disease are reported here, and the "position papers" by members of the Working Group that accompany this report elaborate on the research findings and concepts upon which these recommendations were based. Further, commentaries by other experts in the field also are included here to provide additional perspectives on these recommendations. Finally, it is anticipated that future meetings of the Working Group will reassess these recommendations and the implementation of postmortem diagnostic criteria for Alzheimer's disease.

cWINNOWER algorithm for finding fuzzy dna motifs

NASA Technical Reports Server (NTRS)

Liang, S.; Samanta, M. P.; Biegel, B. A.

2004-01-01

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if a clique consisting of a sufficiently large number of mutated copies of the motif (i.e., the signals) is present in the DNA sequence. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum detectable clique size qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12,000 for (l, d) = (15, 4). Copyright Imperial College Press.

cWINNOWER Algorithm for Finding Fuzzy DNA Motifs

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2003-01-01

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if multiple mutated copies of the motif (i.e., the signals) are present in the DNA sequence in sufficient abundance. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum number of detectable motifs qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc, by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12000 for (l,d) = (15,4).

Research priorities for the influence of gender on diagnostic imaging choices in the emergency department setting.

PubMed

Ashurst, John V; Cherney, Alan R; Evans, Elizabeth M; Kennedy Hall, Michael; Hess, Erik P; Kline, Jeffrey A; Mitchell, Alice M; Mills, Angela M; Weigner, Michael B; Moore, Christopher L

2014-12-01

Diagnostic imaging is a cornerstone of patient evaluation in the acute care setting, but little effort has been devoted to understanding the appropriate influence of sex and gender on imaging choices. This article provides background on this issue and a description of the working group and consensus findings reached during the diagnostic imaging breakout session at the 2014 Academic Emergency Medicine consensus conference "Gender-specific Research in Emergency Care: Investigate, Understand, and Translate How Gender Affects Patient Outcomes." Our goal was to determine research priorities for how sex and gender may (or should) affect imaging choices in the acute care setting. Prior to the conference, the working group identified five areas for discussion regarding the research agenda in sex- and gender-based imaging using literature review and expert consensus. The nominal group technique was used to identify areas for discussion for common presenting complaints to the emergency department where ionizing radiation is often used for diagnosis: suspected pulmonary embolism, suspected kidney stone, lower abdominal pain with a concern for appendicitis, and chest pain concerning for coronary artery disease. The role of sex- and gender-based shared decision-making in diagnostic imaging decisions is also raised. © 2014 by the Society for Academic Emergency Medicine.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer.

PubMed

Wu, Abraham J; Bosch, Walter R; Chang, Daniel T; Hong, Theodore S; Jabbour, Salma K; Kleinberg, Lawrence R; Mamon, Harvey J; Thomas, Charles R; Goodman, Karyn A

2015-07-15

Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future. Copyright © 2015 Elsevier Inc. All rights reserved.

Expert consensus contouring guidelines for IMRT in esophageal and gastroesophageal junction cancer

PubMed Central

Wu, Abraham J.; Bosch, Walter R.; Chang, Daniel T.; Hong, Theodore S.; Jabbour, Salma K.; Kleinberg, Lawrence R.; Mamon, Harvey J.; Thomas, Charles R.; Goodman, Karyn A.

2015-01-01

Purpose/Objective(s) Current guidelines for esophageal cancer contouring are derived from traditional two-dimensional fields based on bony landmarks, and do not provide sufficient anatomical detail to ensure consistent contouring for more conformal radiotherapy techniques such as intensity-modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials Eight expert academically-based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform CT simulation datasets and an accompanying diagnostic PET-CT were distributed to each expert, and he/she was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results Kappa statistics indicated substantial agreement between panelists for each of the three test cases. A consensus CTV atlas was generated for the three test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets utilizing these guidelines may require modification in the future. PMID:26104943

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Abraham J., E-mail: wua@mskcc.org; Bosch, Walter R.; Chang, Daniel T.

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophagealmore » cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future.« less

An evidential reasoning extension to quantitative model-based failure diagnosis

NASA Technical Reports Server (NTRS)

Gertler, Janos J.; Anderson, Kenneth C.

1992-01-01

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster's rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith.

Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults.

PubMed

Eramudugolla, Ranmalee; Mortby, Moyra E; Sachdev, Perminder; Meslin, Chantal; Kumar, Rajeev; Anstey, Kaarin J

2017-03-04

There is little information on the application and impact of revised criteria for diagnosing dementia and mild cognitive impairment (MCI), now termed major and mild neurocognitive disorders (NCDs) in the DSM-5. We evaluate a psychometric algorithm for diagnosing DSM-5 NCDs in a community-dwelling sample, and characterize the neuropsychological and functional profile of expert-diagnosed DSM-5 NCDs relative to DSM-IV dementia and International Working Group criteria for MCI. A population-based sample of 1644 adults aged 72-78 years was assessed. Algorithmic diagnostic criteria used detailed neuropsychological data, medical history, longitudinal cognitive performance, and informant interview. Those meeting all criteria for at least one diagnosis had data reviewed by a neurologist (expert diagnosis) who achieved consensus with a psychiatrist for complex cases. The algorithm accurately classified DSM-5 major NCD (area under the curve (AUC) = 0.95, 95% confidence interval (CI) 0.92-0.97), DSM-IV dementia (AUC = 0.91, 95% CI 0.85-0.97), DSM-5 mild NCD (AUC = 0.75, 95% CI 0.70-0.80), and MCI (AUC = 0.76, 95% CI 0.72-0.81) when compared to expert diagnosis. Expert diagnosis of dementia using DSM-5 criteria overlapped with 90% of DSM-IV dementia cases, but resulted in a 127% increase in diagnosis relative to DSM-IV. Additional cases had less severe memory, language impairment, and instrumental activities of daily living (IADL) impairments compared to cases meeting DSM-IV criteria for dementia. DSM-5 mild NCD overlapped with 83% of MCI cases and resulted in a 19% increase in diagnosis. These additional cases had a subtly different neurocognitive profile to MCI cases, including poorer social cognition. DSM-5 NCD criteria can be operationalized in a psychometric algorithm in a population setting. Expert diagnosis using DSM-5 NCD criteria captured most cases with DSM-IV dementia and MCI in our sample, but included many additional cases suggesting that DSM-5 criteria are broader in their categorization.

Consensus guidelines for the use of empiric and diagnostic-driven antifungal treatment strategies in haematological malignancy, 2014.

PubMed

Morrissey, C O; Gilroy, N M; Macesic, N; Walker, P; Ananda-Rajah, M; May, M; Heath, C H; Grigg, A; Bardy, P G; Kwan, J; Kirsa, S W; Slavin, M; Gottlieb, T; Chen, S

2014-12-01

Invasive fungal disease (IFD) causes significant morbidity and mortality in patients undergoing allogeneic haemopoietic stem cell transplantation or chemotherapy for haematological malignancy. Much of these adverse outcomes are due to the limited ability of traditional diagnostic tests (i.e. culture and histology) to make an early and accurate diagnosis. As persistent or recurrent fevers of unknown origin (PFUO) in neutropenic patients despite broad-spectrum antibiotics have been associated with the development of IFD, most centres have traditionally administered empiric antifungal therapy (EAFT) to patients with PFUO. However, use of an EAFT strategy has not been shown to have an overall survival benefit and is associated with excessive antifungal therapy use. As a result, the focus has shifted to developing more sensitive and specific diagnostic tests for early and more targeted antifungal treatment. These tests, including the galactomannan enzyme-linked immunosorbent assay and Aspergillus polymerase chain reaction (PCR), have enabled the development of diagnostic-driven antifungal treatment (DDAT) strategies, which have been shown to be safe and feasible, reducing antifungal usage. In addition, the development of effective antifungal prophylactic strategies has changed the landscape in terms of the incidence and types of IFD that clinicians have encountered. In this review, we examine the current role of EAFT and provide up-to-date data on the newer diagnostic tests and algorithms available for use in EAFT and DDAT strategies, within the context of patient risk and type of antifungal prophylaxis used. © 2014 The Authors; Internal Medicine Journal © 2014 Royal Australasian College of Physicians.

Reproducible diagnosis of chronic lymphocytic leukemia by flow cytometry: An European Research Initiative on CLL (ERIC) & European Society for Clinical Cell Analysis (ESCCA) Harmonisation project

PubMed Central

Kreuzer, Karl‐Anton; Soosapilla, Asha; Spacek, Martin; Stehlikova, Olga; Gambell, Peter; McIver‐Brown, Neil; Villamor, Neus; Psarra, Katherina; Arroz, Maria; Milani, Raffaella; de la Serna, Javier; Cedena, M. Teresa; Jaksic, Ozren; Nomdedeu, Josep; Moreno, Carol; Rigolin, Gian Matteo; Cuneo, Antonio; Johansen, Preben; Johnsen, Hans E.; Rosenquist, Richard; Niemann, Carsten Utoft; Kern, Wolfgang; Westerman, David; Trneny, Marek; Mulligan, Stephen; Doubek, Michael; Pospisilova, Sarka; Hillmen, Peter; Oscier, David; Hallek, Michael; Ghia, Paolo; Montserrat, Emili

2018-01-01

The diagnostic criteria for CLL rely on morphology and immunophenotype. Current approaches have limitations affecting reproducibility and there is no consensus on the role of new markers. The aim of this project was to identify reproducible criteria and consensus on markers recommended for the diagnosis of CLL. ERIC/ESCCA members classified 14 of 35 potential markers as “required” or “recommended” for CLL diagnosis, consensus being defined as >75% and >50% agreement, respectively. An approach to validate “required” markers using normal peripheral blood was developed. Responses were received from 150 participants with a diagnostic workload >20 CLL cases per week in 23/150 (15%), 5–20 in 82/150 (55%), and <5 cases per week in 45/150 (30%). The consensus for “required” diagnostic markers included: CD19, CD5, CD20, CD23, Kappa, and Lambda. “Recommended” markers potentially useful for differential diagnosis were: CD43, CD79b, CD81, CD200, CD10, and ROR1. Reproducible criteria for component reagents were assessed retrospectively in 14,643 cases from 13 different centers and showed >97% concordance with current approaches. A pilot study to validate staining quality was completed in 11 centers. Markers considered as “required” for the diagnosis of CLL by the participants in this study (CD19, CD5, CD20, CD23, Kappa, and Lambda) are consistent with current diagnostic criteria and practice. Importantly, a reproducible approach to validate and apply these markers in individual laboratories has been identified. Finally, a consensus “recommended” panel of markers to refine diagnosis in borderline cases (CD43, CD79b, CD81, CD200, CD10, and ROR1) has been defined and will be prospectively evaluated. © 2017 International Clinical Cytometry Society PMID:29024461

Reproducible diagnosis of chronic lymphocytic leukemia by flow cytometry: An European Research Initiative on CLL (ERIC) & European Society for Clinical Cell Analysis (ESCCA) Harmonisation project.

PubMed

Rawstron, Andy C; Kreuzer, Karl-Anton; Soosapilla, Asha; Spacek, Martin; Stehlikova, Olga; Gambell, Peter; McIver-Brown, Neil; Villamor, Neus; Psarra, Katherina; Arroz, Maria; Milani, Raffaella; de la Serna, Javier; Cedena, M Teresa; Jaksic, Ozren; Nomdedeu, Josep; Moreno, Carol; Rigolin, Gian Matteo; Cuneo, Antonio; Johansen, Preben; Johnsen, Hans E; Rosenquist, Richard; Niemann, Carsten Utoft; Kern, Wolfgang; Westerman, David; Trneny, Marek; Mulligan, Stephen; Doubek, Michael; Pospisilova, Sarka; Hillmen, Peter; Oscier, David; Hallek, Michael; Ghia, Paolo; Montserrat, Emili

2018-01-01

The diagnostic criteria for CLL rely on morphology and immunophenotype. Current approaches have limitations affecting reproducibility and there is no consensus on the role of new markers. The aim of this project was to identify reproducible criteria and consensus on markers recommended for the diagnosis of CLL. ERIC/ESCCA members classified 14 of 35 potential markers as "required" or "recommended" for CLL diagnosis, consensus being defined as >75% and >50% agreement, respectively. An approach to validate "required" markers using normal peripheral blood was developed. Responses were received from 150 participants with a diagnostic workload >20 CLL cases per week in 23/150 (15%), 5-20 in 82/150 (55%), and <5 cases per week in 45/150 (30%). The consensus for "required" diagnostic markers included: CD19, CD5, CD20, CD23, Kappa, and Lambda. "Recommended" markers potentially useful for differential diagnosis were: CD43, CD79b, CD81, CD200, CD10, and ROR1. Reproducible criteria for component reagents were assessed retrospectively in 14,643 cases from 13 different centers and showed >97% concordance with current approaches. A pilot study to validate staining quality was completed in 11 centers. Markers considered as "required" for the diagnosis of CLL by the participants in this study (CD19, CD5, CD20, CD23, Kappa, and Lambda) are consistent with current diagnostic criteria and practice. Importantly, a reproducible approach to validate and apply these markers in individual laboratories has been identified. Finally, a consensus "recommended" panel of markers to refine diagnosis in borderline cases (CD43, CD79b, CD81, CD200, CD10, and ROR1) has been defined and will be prospectively evaluated. © 2017 International Clinical Cytometry Society. © 2017 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals, Inc. on behalf of International Clinical Cytometry Society.

Relevance of Web Documents:Ghosts Consensus Method.

ERIC Educational Resources Information Center

Gorbunov, Andrey L.

2002-01-01

Discusses how to improve the quality of Internet search systems and introduces the Ghosts Consensus Method which is free from the drawbacks of digital democracy algorithms and is based on linear programming tasks. Highlights include vector space models; determining relevant documents; and enriching query terms. (LRW)

On Federated and Proof Of Validation Based Consensus Algorithms In Blockchain

NASA Astrophysics Data System (ADS)

Ambili, K. N.; Sindhu, M.; Sethumadhavan, M.

2017-08-01

Almost all real world activities have been digitized and there are various client server architecture based systems in place to handle them. These are all based on trust on third parties. There is an active attempt to successfully implement blockchain based systems which ensures that the IT systems are immutable, double spending is avoided and cryptographic strength is provided to them. A successful implementation of blockchain as backbone of existing information technology systems is bound to eliminate various types of fraud and ensure quicker delivery of the item on trade. To adapt IT systems to blockchain architecture, an efficient consensus algorithm need to be designed. Blockchain based on proof of work first came up as the backbone of cryptocurrency. After this, several other methods with variety of interesting features have come up. In this paper, we conduct a survey on existing attempts to achieve consensus in block chain. A federated consensus method and a proof of validation method are being compared.

Histological features associated with diagnostic agreement in atypical ductal hyperplasia of the breast: illustrative cases from the B-Path study.

PubMed

Allison, Kimberly H; Rendi, Mara H; Peacock, Sue; Morgan, Tom; Elmore, Joann G; Weaver, Donald L

2016-12-01

This study examined the case-specific characteristics associated with interobserver diagnostic agreement in atypical ductal hyperplasia (ADH) of the breast. Seventy-two test set cases with a consensus diagnosis of ADH from the B-Path study were evaluated. Cases were scored for 17 histological features, which were then correlated with the participant agreement with the consensus ADH diagnosis. Participating pathologists' perceptions of case difficulty, borderline features or whether they would obtain a second opinion were also examined for associations with agreement. Of the 2070 participant interpretations of the 72 consensus ADH cases, 48% were scored by participants as difficult and 45% as borderline between two diagnoses; the presence of both of these features was significantly associated with increased agreement (P < 0.001). A second opinion would have been obtained in 80% of interpretations, and this was associated with increased agreement (P < 0.001). Diagnostic agreement ranged from 10% to 89% on a case-by-case basis. Cases with papillary lesions, cribriform architecture and obvious cytological monotony were associated with higher agreement. Lower agreement rates were associated with solid or micropapillary architecture, borderline cytological monotony, or cases without a diagnostic area that was obvious on low power. The results of this study suggest that pathologists frequently recognize the challenge of ADH cases, with some cases being more prone to diagnostic variability. In addition, there are specific histological features associated with diagnostic agreement on ADH cases. Multiple example images from cases in this test set are provided to serve as educational illustrations of these challenges. © 2016 John Wiley & Sons Ltd.

Histologic Features associated with Diagnostic Agreement in Atypical Ductal Hyperplasia of the Breast: Illustrative Cases from the B-Path Study

PubMed Central

Allison, Kimberly H.; Rendi, Mara H.; Peacock, Sue; Morgan, Tom; Elmore, Joann G.; Weaver, Donald L.

2016-01-01

Background Case specific characteristics associated with interobserver diagnostic agreement in atypical ductal hyperplasia (ADH) of the breast are poorly understood. Methods Seventy-two test set cases with a consensus diagnosis of ADH from the B-Path study were evaluated. Cases were scored for 17 histologic features which were then correlated with the participant agreement with the consensus ADH diagnosis. Participating pathologists’ perceptions of case difficulty, borderline features, or if they would obtain a second opinion were also examined for associations with agreement. Results Of the 2,070 participant interpretations on the 72 consensus ADH cases, 48% were scored by participants as difficult and 45% as borderline between two diagnoses; the presence of both of these features was significantly associated with increased agreement (p < 0.001). A second opinion would have been obtained in 80% of interpretations, and this was associated with increased agreement (p < 0.001). Diagnostic agreement ranged from 10–89% on a case-by-case basis. Cases with papillary lesions, cribriform architecture and obvious cytologic monotony were associated with higher agreement. Lower agreement rates were associated with solid or micro-papillary architecture, borderline cytologic monotony or cases without a diagnostic area that was obvious on low power. Conclusions The results of this study suggest that pathologists frequently recognize the challenge of ADH cases with some cases more prone to diagnostic variability. In addition, there are specific histologic features associated with diagnostic agreement on ADH cases. Multiple example images from cases in this test set are provided to serve as educational illustrations of these challenges. PMID:27398812

A consensus definition and core competencies for being an advocate for pharmacy.

PubMed

Bzowyckyj, Andrew S; Janke, Kristin K

2013-03-12

To develop a consensus definition for "advocacy for the profession of pharmacy" and core competencies for doctor of pharmacy (PharmD) graduates to be effective advocates for the profession. A 3-round modified Delphi process was conducted using a panel of 9 experts. Participants revised a definition for "advocacy for the profession" and ultimately rated their agreement using a 5-point Likert scale. Competency statements were developed and subsequently rated for importance for being an advocate and importance to address in PharmD curricula. A consensus-derived definition was developed. Two competency statements achieved consensus for both measures of importance. Four competency statements achieved consensus for only 1 measure and another 4 did not reach consensus for either measure. A consensus-derived definition was developed describing advocacy for the profession of pharmacy and began laying the groundwork for the knowledge and skills necessary to be an effective advocate for the profession of pharmacy.

Bruxism defined and graded: an international consensus.

PubMed

Lobbezoo, F; Ahlberg, J; Glaros, A G; Kato, T; Koyano, K; Lavigne, G J; de Leeuw, R; Manfredini, D; Svensson, P; Winocur, E

2013-01-01

To date, there is no consensus about the definition and diagnostic grading of bruxism. A written consensus discussion was held among an international group of bruxism experts as to formulate a definition of bruxism and to suggest a grading system for its operationalisation. The expert group defined bruxism as a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth and/or by bracing or thrusting of the mandible. Bruxism has two distinct circadian manifestations: it can occur during sleep (indicated as sleep bruxism) or during wakefulness (indicated as awake bruxism). For the operationalisation of this definition, the expert group proposes a diagnostic grading system of 'possible', 'probable' and 'definite' sleep or awake bruxism. The proposed definition and grading system are suggested for clinical and research purposes in all relevant dental and medical domains. © 2012 Blackwell Publishing Ltd.

Qualifying and quantifying minimal hepatic encephalopathy.

PubMed

Morgan, Marsha Y; Amodio, Piero; Cook, Nicola A; Jackson, Clive D; Kircheis, Gerald; Lauridsen, Mette M; Montagnese, Sara; Schiff, Sami; Weissenborn, Karin

2016-12-01

Minimal hepatic encephalopathy is the term applied to the neuropsychiatric status of patients with cirrhosis who are unimpaired on clinical examination but show alterations in neuropsychological tests exploring psychomotor speed/executive function and/or in neurophysiological variables. There is no gold standard for the diagnosis of this syndrome. As these patients have, by definition, no recognizable clinical features of brain dysfunction, the primary prerequisite for the diagnosis is careful exclusion of clinical symptoms and signs. A large number of psychometric tests/test systems have been evaluated in this patient group. Of these the best known and validated is the Portal Systemic Hepatic Encephalopathy Score (PHES) derived from a test battery of five paper and pencil tests; normative reference data are available in several countries. The electroencephalogram (EEG) has been used to diagnose hepatic encephalopathy since the 1950s but, once popular, the technology is not as accessible now as it once was. The performance characteristics of the EEG are critically dependent on the type of analysis undertaken; spectral analysis has better performance characteristics than visual analysis; evolving analytical techniques may provide better diagnostic information while the advent of portable wireless headsets may facilitate more widespread use. A large number of other diagnostic tools have been validated for the diagnosis of minimal hepatic encephalopathy including Critical Flicker Frequency, the Inhibitory Control Test, the Stroop test, the Scan package and the Continuous Reaction Time; each has its pros and cons; strengths and weaknesses; protagonists and detractors. Recent AASLD/EASL Practice Guidelines suggest that the diagnosis of minimal hepatic encephalopathy should be based on the PHES test together with one of the validated alternative techniques or the EEG. Minimal hepatic encephalopathy has a detrimental effect on the well-being of patients and their care-givers. It responds well to treatment with resolution of test abnormalities and the associated detrimental effects on quality of life, liver-related mortality and morbidity. Patients will only benefit in this way if they can be effectively diagnosed. Corporate efforts and consensus agreements are needed to develop effective diagnostic algorithms.

How I treat bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation.

PubMed

Williams, Kirsten M

2017-01-26

In past years, a diagnosis of bronchiolitis obliterans syndrome (BOS) after allogeneic hematopoietic cell transplant (HCT) conferred nearly universal mortality secondary to lack of consensus for diagnostic criteria, poorly understood disease pathogenesis, and very few studies of therapeutic or supportive care interventions. Recently, however, progress has been made in these areas: revised consensus diagnostic guidelines are now available, supportive care has improved, there is greater understanding of potential mechanisms of disease, and prospective trials are being conducted. This article describes these advances and provides suggestions to optimize therapy for patients with BOS after HCT.

The definition, diagnostic testing, and management of chronic inducible urticarias - The EAACI/GA(2) LEN/EDF/UNEV consensus recommendations 2016 update and revision.

PubMed

Magerl, M; Altrichter, S; Borzova, E; Giménez-Arnau, A; Grattan, C E H; Lawlor, F; Mathelier-Fusade, P; Meshkova, R Y; Zuberbier, T; Metz, M; Maurer, M

2016-06-01

These recommendations for the definition, diagnosis and management of chronic inducible urticaria (CIndU) extend, revise and update our previous consensus report on physical urticarias and cholinergic urticaria (Allergy, 2009). The aim of these recommendations is to improve the diagnosis and management of patients with CIndU. Our recommendations acknowledge the latest changes in our understanding of CIndU, and the available therapeutic options, as well as the development of novel diagnostic tools. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Integration of On-Line and Off-Line Diagnostic Algorithms for Aircraft Engine Health Management

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2007-01-01

This paper investigates the integration of on-line and off-line diagnostic algorithms for aircraft gas turbine engines. The on-line diagnostic algorithm is designed for in-flight fault detection. It continuously monitors engine outputs for anomalous signatures induced by faults. The off-line diagnostic algorithm is designed to track engine health degradation over the lifetime of an engine. It estimates engine health degradation periodically over the course of the engine s life. The estimate generated by the off-line algorithm is used to update the on-line algorithm. Through this integration, the on-line algorithm becomes aware of engine health degradation, and its effectiveness to detect faults can be maintained while the engine continues to degrade. The benefit of this integration is investigated in a simulation environment using a nonlinear engine model.

Perceptions of Emergency Medicine Residency and Hand Surgery Fellowship Program Directors in the Appropriate Disposition of Upper Extremity Emergencies.

PubMed

Drolet, Brian C; Lifchez, Scott D; Jacoby, Sidney M; Varone, Andrew; Regan, Linda A; Baren, Jill M; Akelman, Edward; Osterman, A Lee; Levin, L Scott

2015-12-01

To survey emergency medicine (EM) residency and hand surgery fellowship program directors (PDs) to identify consensus in their perceptions of appropriate emergency care of upper extremity emergencies. We created a framework to group common upper extremity emergency diagnoses and surveyed PDs to evaluate the training background--EM, general orthopedic or plastic surgery, or hand fellowship--most appropriate to provide acute, point-of-care management for each of these diagnostic groupings. Responses were pooled and consensus was established with greater than 75% agreement between groups. We received 79 responses from hand fellowship PDs (90% response rate) and 151 responses from EM PDs (49% response rate). We identified consensus for the training background that PDs in both specialties felt was appropriate to care for 17 of 21 diagnostic groupings in the framework. There was a high level of consensus between EM and hand surgery PDs regarding diagnoses that acutely require training in hand surgery versus those that can be managed by an EM physician. Our diagnostic framework may help reduce unnecessary hand surgery consultation and may help to identify patients who do not require more specialized acute care and thus decrease unnecessary transfers. Economic and Decision Analyses IV. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

Speeding up the Consensus Clustering methodology for microarray data analysis

PubMed Central

2011-01-01

Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, Consensus is a natural candidate for a speed-up. Results Since the time-precision performance of Consensus depends on two parameters, our first task is to show that a simple adjustment of the parameters is not enough to obtain a good precision-time trade-off. Our second task is to provide a fast approximation algorithm for Consensus. That is, the closely related algorithm FC (Fast Consensus) that would have the same precision as Consensus with a substantially better time performance. The performance of FC has been assessed via extensive experiments on twelve benchmark datasets that summarize key features of microarray applications, such as cancer studies, gene expression with up and down patterns, and a full spectrum of dimensionality up to over a thousand. Based on their outcome, compared with previous benchmarking results available in the literature, FC turns out to be among the fastest internal validation methods, while retaining the same outstanding precision of Consensus. Moreover, it also provides a consensus matrix that can be used as a dissimilarity matrix, guaranteeing the same performance as the corresponding matrix produced by Consensus. We have also experimented with the use of Consensus and FC in conjunction with NMF (Nonnegative Matrix Factorization), in order to identify the correct number of clusters in a dataset. Although NMF is an increasingly popular technique for biological data mining, our results are somewhat disappointing and complement quite well the state of the art about NMF, shedding further light on its merits and limitations. Conclusions In summary, FC with a parameter setting that makes it robust with respect to small and medium-sized datasets, i.e, number of items to cluster in the hundreds and number of conditions up to a thousand, seems to be the internal validation measure of choice. Moreover, the technique we have developed here can be used in other contexts, in particular for the speed-up of stability-based validation measures. PMID:21235792

Diagnostic Algorithm Benchmarking

NASA Technical Reports Server (NTRS)

Poll, Scott

2011-01-01

A poster for the NASA Aviation Safety Program Annual Technical Meeting. It describes empirical benchmarking on diagnostic algorithms using data from the ADAPT Electrical Power System testbed and a diagnostic software framework.

Impact of lossy compression on diagnostic accuracy of radiographs for periapical lesions

NASA Technical Reports Server (NTRS)

Eraso, Francisco E.; Analoui, Mostafa; Watson, Andrew B.; Rebeschini, Regina

2002-01-01

OBJECTIVES: The purpose of this study was to evaluate the lossy Joint Photographic Experts Group compression for endodontic pretreatment digital radiographs. STUDY DESIGN: Fifty clinical charge-coupled device-based, digital radiographs depicting periapical areas were selected. Each image was compressed at 2, 4, 8, 16, 32, 48, and 64 compression ratios. One root per image was marked for examination. Images were randomized and viewed by four clinical observers under standardized viewing conditions. Each observer read the image set three times, with at least two weeks between each reading. Three pre-selected sites per image (mesial, distal, apical) were scored on a five-scale score confidence scale. A panel of three examiners scored the uncompressed images, with a consensus score for each site. The consensus score was used as the baseline for assessing the impact of lossy compression on the diagnostic values of images. The mean absolute error between consensus and observer scores was computed for each observer, site, and reading session. RESULTS: Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05). After converting the five-scale score to two-level diagnostic values, the diagnostic accuracy was strongly correlated (R (2) = 0.91) with the compression ratio. CONCLUSION: The results of this study suggest that high compression ratios can have a severe impact on the diagnostic quality of the digital radiographs for detection of periapical lesions.

Diagnostic work-up and loss of tuberculosis suspects in Jogjakarta, Indonesia.

PubMed

Ahmad, Riris Andono; Matthys, Francine; Dwihardiani, Bintari; Rintiswati, Ning; de Vlas, Sake J; Mahendradhata, Yodi; van der Stuyft, Patrick

2012-02-15

Early and accurate diagnosis of pulmonary tuberculosis (TB) is critical for successful TB control. To assist in the diagnosis of smear-negative pulmonary TB, the World Health Organisation (WHO) recommends the use of a diagnostic algorithm. Our study evaluated the implementation of the national tuberculosis programme's diagnostic algorithm in routine health care settings in Jogjakarta, Indonesia. The diagnostic algorithm is based on the WHO TB diagnostic algorithm, which had already been implemented in the health facilities. We prospectively documented the diagnostic work-up of all new tuberculosis suspects until a diagnosis was reached. We used clinical audit forms to record each step chronologically. Data on the patient's gender, age, symptoms, examinations (types, dates, and results), and final diagnosis were collected. Information was recorded for 754 TB suspects; 43.5% of whom were lost during the diagnostic work-up in health centres, 0% in lung clinics. Among the TB suspects who completed diagnostic work-ups, 51.1% and 100.0% were diagnosed without following the national TB diagnostic algorithm in health centres and lung clinics, respectively. However, the work-up in the health centres and lung clinics generally conformed to international standards for tuberculosis care (ISTC). Diagnostic delays were significantly longer in health centres compared to lung clinics. The high rate of patients lost in health centres needs to be addressed through the implementation of TB suspect tracing and better programme supervision. The national TB algorithm needs to be revised and differentiated according to the level of care.

Benchmarking Diagnostic Algorithms on an Electrical Power System Testbed

NASA Technical Reports Server (NTRS)

Kurtoglu, Tolga; Narasimhan, Sriram; Poll, Scott; Garcia, David; Wright, Stephanie

2009-01-01

Diagnostic algorithms (DAs) are key to enabling automated health management. These algorithms are designed to detect and isolate anomalies of either a component or the whole system based on observations received from sensors. In recent years a wide range of algorithms, both model-based and data-driven, have been developed to increase autonomy and improve system reliability and affordability. However, the lack of support to perform systematic benchmarking of these algorithms continues to create barriers for effective development and deployment of diagnostic technologies. In this paper, we present our efforts to benchmark a set of DAs on a common platform using a framework that was developed to evaluate and compare various performance metrics for diagnostic technologies. The diagnosed system is an electrical power system, namely the Advanced Diagnostics and Prognostics Testbed (ADAPT) developed and located at the NASA Ames Research Center. The paper presents the fundamentals of the benchmarking framework, the ADAPT system, description of faults and data sets, the metrics used for evaluation, and an in-depth analysis of benchmarking results obtained from testing ten diagnostic algorithms on the ADAPT electrical power system testbed.

The Prevention and Management of Urinary Tract Infection among People with Spinal Cord Injuries.

ERIC Educational Resources Information Center

NIDRR Consensus Statement, 1992

1992-01-01

A 1992 Urinary Tract Infection Consensus Validation Conference brought together researchers, clinicians, and consumers to arrive at consensus on the best practices for preventing and treating urinary tract infections (UBI) in people with spinal cord injuries; the risk factors and diagnostic studies that should be done; indications for antibiotic…

A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus

NASA Astrophysics Data System (ADS)

Mohammadi, Jafar; Limmer, Steffen; Stańczak, Sławomir

2016-07-01

This paper considers eigenvalue estimation for the decentralized inference problem for spectrum sensing. We propose a decentralized eigenvalue computation algorithm based on the power method, which is referred to as generalized power method GPM; it is capable of estimating the eigenvalues of a given covariance matrix under certain conditions. Furthermore, we have developed a decentralized implementation of GPM by splitting the iterative operations into local and global computation tasks. The global tasks require data exchange to be performed among the nodes. For this task, we apply an average consensus algorithm to efficiently perform the global computations. As a special case, we consider a structured graph that is a tree with clusters of nodes at its leaves. For an accelerated distributed implementation, we propose to use computation over multiple access channel (CoMAC) as a building block of the algorithm. Numerical simulations are provided to illustrate the performance of the two algorithms.

[Consensus on clinical diagnosis, treatment and pedigree management of hereditary colorectal cancer in China].

PubMed

2018-01-23

Hereditary colorectal cancer can be divded into two categories based on the presence or absence of polyps. The first category is characterized by the development of polyposis, which includes familial adenomatous polyposis (FAP); The second category is nonpolyposis colorectal cancer, which is represented by Lynch syndrome. "Consensus on clinical diagnosis, treatment and pedigree management of hereditary colorectal cancer in China" developed by the Genetics Group of the Committee of Colorectal Cancer, Chinese Anti-cancer Association, is composed of three sections, including hereditary nonpolyposis syndrome, polyposis syndrome as well as genetic evaluation of hereditary colorectal cancer. The consensus aims to provide recommendations on management of the respective hereditary syndromes in terms of definition, clinical and pathological features, diagnostic standards, treatment, and follow-ups. In addition to describing diagnostic and treatment strategies, prophylactic treatment as well as genetic screening and pedigree monitoring is highly recommended. Through the establishment of this expert consensus, we hope to promote better understanding of hereditary colorectal cancer for clinicians and encourage standardized treatment through multidisciplinery approaches, eventually improving clinical treatment and pedigree management of hereditary colorectal cancer in China.

Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications

PubMed Central

Soares, Jaqueline S.; Barman, Ishan; Dingari, Narahara Chari; Volynskaya, Zoya; Liu, Wendy; Klein, Nina; Plecha, Donna; Dasari, Ramachandra R.; Fitzmaurice, Maryann

2013-01-01

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologic assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt. PMID:23267090

Observations on the Invalid Scoring Algorithm of "NASA" and Similar Consensus Tasks.

ERIC Educational Resources Information Center

Slevin, Dennis P.

1978-01-01

The NASA ranking task and similar ranking activities used to demonstrate the superiority of group thinking are examined. It is argued that the current scores cannot be used to prove the superiority of group-consensus decision making in either training or research settings. (Author)

A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins

PubMed Central

Tsolis, Antonios C.; Papandreou, Nikos C.; Iconomidou, Vassiliki A.; Hamodrakas, Stavros J.

2013-01-01

The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/‘aggregation-prone’ peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins). PMID:23326595

French national consensus clinical guidelines for the management of ulcerative colitis.

PubMed

Peyrin-Biroulet, Laurent; Bouhnik, Yoram; Roblin, Xavier; Bonnaud, Guillaume; Hagège, Hervé; Hébuterne, Xavier

2016-07-01

Ulcerative colitis (UC) is a chronic inflammatory bowel disease of multifactorial etiology that primarily affects the colonic mucosa. The disease progresses over time, and clinical management guidelines should reflect its dynamic nature. There is limited evidence supporting UC management in specific clinical situations, thus precluding an evidence-based approach. To use a formal consensus method - the nominal group technique (NGT) - to develop a clinical practice expert opinion to outline simple algorithms and practices, optimize UC management, and assist clinicians in making treatment decisions. The consensus was developed by an expert panel of 37 gastroenterologists from various professional organizations with experience in UC management using the qualitative and iterative NGT, incorporating deliberations based on the European Crohn's and Colitis Organisation recommendations, recent reviews of scientific literature, and pertinent discussion topics developed by a steering committee. Examples of clinical cases for which there are limited evidence-based data from clinical trials were used. Two working groups proposed and voted on treatment algorithms that were then discussed and voted for by the nominal group as a whole, in order to reach a consensus. A clinical practice guideline covering management of the following clinical situations was developed: (i) moderate and severe UC; (ii) acute severe UC; (iii) pouchitis; (iv) refractory proctitis, in the form of treatment algorithms. Given the limited available evidence-based data, a formal consensus methodology was used to develop simple treatment guidelines for UC management in different clinical situations that is now accessible via an online application. Copyright © 2016 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

The DSM-5: Hyperbole, Hope or Hypothesis?

PubMed

Berk, Michael

2013-05-14

The furore preceding the release of the new edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) is in contrast to the incremental changes to several diagnostic categories, which are derived from new research since its predecessor's birth in 1990. While many of these changes are indeed controversial, they do reflect the intrinsic ambiguity of the extant literature. Additionally, this may be a mirror of the frustration of the field's limited progress, especially given the false hopes at the dawn of the "decade of the brain". In the absence of a coherent pathophysiology, the DSM remains no more than a set of consensus based operationalized adjectives, albeit with some degree of reliability. It does not cleave nature at its joints, nor does it aim to, but neither does alternate systems. The largest problem with the DSM system is how it's used; sometimes too loosely by clinicians, and too rigidly by regulators, insurers, lawyers and at times researchers, who afford it reference and deference disproportionate to its overt acknowledged limitations.

The International Association for the Study of Lung Cancer Consensus Statement on Optimizing Management of EGFR Mutation-Positive Non-Small Cell Lung Cancer: Status in 2016.

PubMed

Tan, Daniel S W; Yom, Sue S; Tsao, Ming S; Pass, Harvey I; Kelly, Karen; Peled, Nir; Yung, Rex C; Wistuba, Ignacio I; Yatabe, Yasushi; Unger, Michael; Mack, Philip C; Wynes, Murry W; Mitsudomi, Tetsuya; Weder, Walter; Yankelevitz, David; Herbst, Roy S; Gandara, David R; Carbone, David P; Bunn, Paul A; Mok, Tony S K; Hirsch, Fred R

2016-07-01

Mutations in the epidermal growth factor receptor gene (EGFR) represent one of the most frequent "actionable" alterations in non-small cell lung cancer (NSCLC). Typified by high response rates to targeted therapies, EGFR tyrosine kinase inhibitors (TKIs) are now established first-line treatment options and have transformed the treatment paradigm for NSCLC. With the recent breakthrough designation and approval of the third-generation EGFR TKI osimertinib, available systemic and local treatment options have expanded, requiring new clinical algorithms that take into account individual patient molecular and clinical profiles. In this International Association for the Study of Lung Cancer commissioned consensus statement, key pathologic, diagnostic, and therapeutic considerations, such as optimal choice of EGFR TKI and management of brain metastasis, are discussed. In addition, recommendations are made for clinical guidelines and research priorities, such as the role of repeat biopsies and use of circulating free DNA for molecular studies. With the rapid pace of progress in treating EGFR-mutant NSCLC, this statement provides a state-of-the-art review of the contemporary issues in managing this unique subgroup of patients. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

European consensus on the concepts and measurement of the pathophysiological neuromuscular responses to passive muscle stretch.

PubMed

van den Noort, J C; Bar-On, L; Aertbeliën, E; Bonikowski, M; Braendvik, S M; Broström, E W; Buizer, A I; Burridge, J H; van Campenhout, A; Dan, B; Fleuren, J F; Grunt, S; Heinen, F; Horemans, H L; Jansen, C; Kranzl, A; Krautwurst, B K; van der Krogt, M; Lerma Lara, S; Lidbeck, C M; Lin, J-P; Martinez, I; Meskers, C; Metaxiotis, D; Molenaers, G; Patikas, D A; Rémy-Néris, O; Roeleveld, K; Shortland, A P; Sikkens, J; Sloot, L; Vermeulen, R J; Wimmer, C; Schröder, A S; Schless, S; Becher, J G; Desloovere, K; Harlaar, J

2017-07-01

To support clinical decision-making in central neurological disorders, a physical examination is used to assess responses to passive muscle stretch. However, what exactly is being assessed is expressed and interpreted in different ways. A clear diagnostic framework is lacking. Therefore, the aim was to arrive at unambiguous terminology about the concepts and measurement around pathophysiological neuromuscular response to passive muscle stretch. During two consensus meetings, 37 experts from 12 European countries filled online questionnaires based on a Delphi approach, followed by plenary discussion after rounds. Consensus was reached for agreement ≥75%. The term hyper-resistance should be used to describe the phenomenon of impaired neuromuscular response during passive stretch, instead of for example 'spasticity' or 'hypertonia'. From there, it is essential to distinguish non-neural (tissue-related) from neural (central nervous system related) contributions to hyper-resistance. Tissue contributions are elasticity, viscosity and muscle shortening. Neural contributions are velocity dependent stretch hyperreflexia and non-velocity dependent involuntary background activation. The term 'spasticity' should only be used next to stretch hyperreflexia, and 'stiffness' next to passive tissue contributions. When joint angle, moment and electromyography are recorded, components of hyper-resistance within the framework can be quantitatively assessed. A conceptual framework of pathophysiological responses to passive muscle stretch is defined. This framework can be used in clinical assessment of hyper-resistance and will improve communication between clinicians. Components within the framework are defined by objective parameters from instrumented assessment. These parameters need experimental validation in order to develop treatment algorithms based on the aetiology of the clinical phenomena. © 2017 EAN.

The Autism Diagnostic Observation Schedule, Module 4: Revised Algorithm and Standardized Severity Scores

ERIC Educational Resources Information Center

Hus, Vanessa; Lord, Catherine

2014-01-01

The recently published Autism Diagnostic Observation Schedule, 2nd edition (ADOS-2) includes revised diagnostic algorithms and standardized severity scores for modules used to assess younger children. A revised algorithm and severity scores are not yet available for Module 4, used with verbally fluent adults. The current study revises the Module 4…

Improved Diagnostic Validity of the ADOS Revised Algorithms: A Replication Study in an Independent Sample

ERIC Educational Resources Information Center

Oosterling, Iris; Roos, Sascha; de Bildt, Annelies; Rommelse, Nanda; de Jonge, Maretha; Visser, Janne; Lappenschaar, Martijn; Swinkels, Sophie; van der Gaag, Rutger Jan; Buitelaar, Jan

2010-01-01

Recently, Gotham et al. ("2007") proposed revised algorithms for the Autism Diagnostic Observation Schedule (ADOS) with improved diagnostic validity. The aim of the current study was to replicate predictive validity, factor structure, and correlations with age and verbal and nonverbal IQ of the ADOS revised algorithms for Modules 1 and 2…

National implementation of multi-parametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting.

PubMed

Brizmohun Appayya, Mrishta; Adshead, Jim; Ahmed, Hashim U; Allen, Clare; Bainbridge, Alan; Barrett, Tristan; Giganti, Francesco; Graham, John; Haslam, Phil; Johnston, Edward W; Kastner, Christof; Kirkham, Alexander P S; Lipton, Alexandra; McNeill, Alan; Moniz, Larissa; Moore, Caroline M; Nabi, Ghulam; Padhani, Anwar R; Parker, Chris; Patel, Amit; Pursey, Jacqueline; Richenberg, Jonathan; Staffurth, John; van der Meulen, Jan; Walls, Darren; Punwani, Shonit

2018-07-01

To identify areas of agreement and disagreement in the implementation of multi-parametric magnetic resonance imaging (mpMRI) of the prostate in the diagnostic pathway. Fifteen UK experts in prostate mpMRI and/or prostate cancer management across the UK (involving nine NHS centres to provide for geographical spread) participated in a consensus meeting following the Research and Development Corporation and University of California-Los Angeles (UCLA-RAND) Appropriateness Method, and were moderated by an independent chair. The experts considered 354 items pertaining to who can request an mpMRI, prostate mpMRI protocol, reporting guidelines, training, quality assurance (QA) and patient management based on mpMRI levels of suspicion for cancer. Each item was rated for agreement on a 9-point scale. A panel median score of ≥7 constituted 'agreement' for an item; for an item to reach 'consensus', a panel majority scoring was required. Consensus was reached on 59% of items (208/354); these were used to provide recommendations for the implementation of prostate mpMRI in the UK. Key findings include prostate mpMRI requests should be made in consultation with the urological team; mpMRI scanners should undergo QA checks to guarantee consistently high diagnostic quality scans; scans should only be reported by trained and experienced radiologists to ensure that men with unsuspicious prostate mpMRI might consider avoiding an immediate biopsy. Our consensus statements demonstrate a set of criteria that are required for the practical dissemination of consistently high-quality prostate mpMRI as a diagnostic test before biopsy in men at risk. © 2018 The Authors BJU International published by John Wiley & Sons Ltd on behalf of BJU International.

To create a consensus on malnutrition diagnostic criteria: A report from the Global Leadership Initiative on Malnutrition (GLIM) meeting at the ESPEN Congress 2016.

PubMed

Cederholm, Tommy; Jensen, Gordon L

2017-02-01

During the ESPEN Congress in Copenhagen, Denmark (September 2016) representatives of the 4 largest global PEN-societies from Europe (ESPEN), USA (ASPEN), Asia (PENSA) and Latin America (FELANPE), and from national PEN-societies around the world met to continue the conversation on how to diagnose malnutrition that started during the Clinical Nutrition Week, Austin, USA (February 2016). Current thinking on diagnostic approaches was shared; ESPEN suggested a grading approach that could encompass various types of signs, symptoms and etiologies to support diagnosis. ASPEN emphasized where the parties agree; i.e. that the three major published approaches (ESPEN, ASPEN/AND and Subjective Global Assessment (SGA)) all propose weight loss as a key indicator for malnutrition. FELANPE suggested that the anticipated consensus approach needs to prioritize a diagnostic methodology that is available for everybody since resources differ globally. PENSA highlighted that BMI varies by ethnicity/race, and that sarcopenia/muscle mass evaluation is important for the diagnosis of malnutrition. A Core Working Committee of the Global Leadership Initiative on Malnutrition (GLIM) has been established (comprised of two representatives each from the 4 largest PEN-societies) that will lead consensus development in collaboration with a larger Working Group with broad global representation, using e-mail, telephone conferences, and face-to-face meetings during the up-coming ASPEN and ESPEN Congresses. Transparency and external input will be sought. Objectives include: 1. Consensus development around evidence-based criteria for broad application. 2. Promotion of global dissemination of the consensus criteria. 3. Seeking adoption by the World Health Organization (WHO) and the International Classification of Diseases (ICD). Copyright © 2017 American Society for Parenteral and Enteral Nutrition, Elsevier Ltd, European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd.. All rights reserved.

Is bruxism a disorder or a behaviour? Rethinking the international consensus on defining and grading of bruxism

PubMed Central

RAPHAEL, K. G.; SANTIAGO, V.; LOBBEZOO, F.

2017-01-01

Summary Inspired by the international consensus on defining and grading of bruxism (Lobbezoo F, Ahlberg J, Glaros AG, Kato T, Koyano K, Lavigne GJ et al. J Oral Rehabil. 2013;40:2), this commentary examines its contribution and underlying assumptions for defining sleep bruxism (SB). The consensus’ parsimonious redefinition of bruxism as a behaviour is an advance, but we explore an implied question: might SB be more than behaviour? Behaviours do not inherently require clinical treatment, making the consensus-proposed ‘diagnostic grading system’ inappropriate. However, diagnostic grading might be useful, if SB were considered a disorder. Therefore, to fully appreciate the contribution of the consensus statement, we first consider standards and evidence for determining whether SB is a disorder characterised by harmful dysfunction or a risk factor increasing probability of a disorder. Second, the strengths and weaknesses of the consensus statement’s proposed ‘diagnostic grading system’ are examined. The strongest evidence-to-date does not support SB as disorder as implied by ‘diagnosis’. Behaviour alone is not diagnosed; disorders are. Considered even as a grading system of behaviour, the proposed system is weakened by poor sensitivity of self-report for direct polysomnographic (PSG)-classified SB and poor associations between clinical judgments of SB and portable PSG; reliance on dichotomised reports; and failure to consider SB behaviour on a continuum, measurable and definable through valid behavioural observation. To date, evidence for validity of self-report or clinician report in placing SB behaviour on a continuum is lacking, raising concerns about their potential utility in any bruxism behavioural grading system, and handicapping future study of whether SB may be a useful risk factor for, or itself a disorder requiring treatment. PMID:27283599

To Create a Consensus on Malnutrition Diagnostic Criteria.

PubMed

Cederholm, Tommy; Jensen, Gordon L

2017-03-01

During the European Society for Clinical Nutrition and Metabolism (ESPEN) Congress in Copenhagen, Denmark (September 2016), representatives of the 4 largest global parenteral and enteral nutrition (PEN) societies from Europe (ESPEN), the United States (American Society for Parenteral and Enteral Nutrition [ASPEN]), Asia (Parenteral and Enteral Nutrition Society of Asia [PENSA]), and Latin America (Latin American Federation of Parenteral and Enteral Nutrition [FELANPE]) and from national PEN societies around the world met to continue the conversation on how to diagnose malnutrition that started during the Clinical Nutrition Week, Austin, Texas (February 2016). Current thinking on diagnostic approaches was shared; ESPEN suggested a grading approach that could encompass various types of signs, symptoms, and etiologies to support diagnosis. ASPEN emphasized where the parties agree; that is, that the 3 major published approaches (ESPEN, ASPEN-Academy of Nutrition and Dietetics, and Subjective Global Assessment [SGA]) all propose weight loss as a key indicator for malnutrition. FELANPE suggested that the anticipated consensus approach needs to prioritize a diagnostic method that is available for everybody since resources differ globally. PENSA highlighted that body mass index varies by ethnicity/race and that sarcopenia/muscle mass evaluation is important for the diagnosis of malnutrition. A Core Working Committee of the Global Leadership Initiative on Malnutrition has been established (comprising 2 representatives each from the 4 largest PEN societies) that will lead consensus development in collaboration with a larger working group with broad global representation, using e-mail, telephone conferences, and face-to-face meetings during the upcoming ASPEN and ESPEN congresses. Transparency and external input will be sought. Objectives include (1) consensus development around evidence-based criteria for broad application, (2) promotion of global dissemination of the consensus criteria, and (3) seeking adoption by the World Health Organization and the International Classification of Diseases.

Thoracoabdominal Computed Tomography in Trauma Patients: A Cost-Consequences Analysis

PubMed Central

van Vugt, Raoul; Kool, Digna R.; Brink, Monique; Dekker, Helena M.; Deunk, Jaap; Edwards, Michael J.

2014-01-01

Background: CT is increasingly used during the initial evaluation of blunt trauma patients. In this era of increasing cost-awareness, the pros and cons of CT have to be assessed. Objectives: This study was performed to evaluate cost-consequences of different diagnostic algorithms that use thoracoabdominal CT in primary evaluation of adult patients with high-energy blunt trauma. Materials and Methods: We compared three different algorithms in which CT was applied as an immediate diagnostic tool (rush CT), a diagnostic tool after limited conventional work-up (routine CT), and a selective tool (selective CT). Probabilities of detecting and missing clinically relevant injuries were retrospectively derived. We collected data on radiation exposure and performed a micro-cost analysis on a reference case-based approach. Results: Both rush and routine CT detected all thoracoabdominal injuries in 99.1% of the patients during primary evaluation (n = 1040). Selective CT missed one or more diagnoses in 11% of the patients in which a change of treatment was necessary in 4.8%. Rush CT algorithm costed € 2676 (US$ 3660) per patient with a mean radiation dose of 26.40 mSv per patient. Routine CT costed € 2815 (US$ 3850) and resulted in the same radiation exposure. Selective CT resulted in less radiation dose (23.23 mSv) and costed € 2771 (US$ 3790). Conclusions: Rush CT seems to result in the least costs and is comparable in terms of radiation dose exposure and diagnostic certainty with routine CT after a limited conventional work-up. However, selective CT results in less radiation dose exposure but a slightly higher cost and less certainty. PMID:25337521

Diagnosis and management of acute appendicitis. EAES consensus development conference 2015.

PubMed

Gorter, Ramon R; Eker, Hasan H; Gorter-Stam, Marguerite A W; Abis, Gabor S A; Acharya, Amish; Ankersmit, Marjolein; Antoniou, Stavros A; Arolfo, Simone; Babic, Benjamin; Boni, Luigi; Bruntink, Marlieke; van Dam, Dieuwertje A; Defoort, Barbara; Deijen, Charlotte L; DeLacy, F Borja; Go, Peter Mnyh; Harmsen, Annelieke M K; van den Helder, Rick S; Iordache, Florin; Ket, Johannes C F; Muysoms, Filip E; Ozmen, M Mahir; Papoulas, Michail; Rhodes, Michael; Straatman, Jennifer; Tenhagen, Mark; Turrado, Victor; Vereczkei, Andras; Vilallonga, Ramon; Deelder, Jort D; Bonjer, Jaap

2016-11-01

Unequivocal international guidelines regarding the diagnosis and management of patients with acute appendicitis are lacking. The aim of the consensus meeting 2015 of the EAES was to generate a European guideline based on best available evidence and expert opinions of a panel of EAES members. After a systematic review of the literature by an international group of surgical research fellows, an expert panel with extensive clinical experience in the management of appendicitis discussed statements and recommendations. Statements and recommendations with more than 70 % agreement by the experts were selected for a web survey and the consensus meeting of the EAES in Bucharest in June 2015. EAES members and attendees at the EAES meeting in Bucharest could vote on these statements and recommendations. In the case of more than 70 % agreement, the statement or recommendation was defined as supported by the scientific community. Results from both the web survey and the consensus meeting in Bucharest are presented as percentages. In total, 46 statements and recommendations were selected for the web survey and consensus meeting. More than 232 members and attendees voted on them. In 41 of 46 statements and recommendations, more than 70 % agreement was reached. All 46 statements and recommendations are presented in this paper. They comprise topics regarding the diagnostic work-up, treatment indications, procedural aspects and post-operative care. The consensus meeting produced 46 statements and recommendations on the diagnostic work-up and management of appendicitis. The majority of the EAES members supported these statements. These consensus proceedings provide additional guidance to surgeons and surgical residents providing care to patients with appendicitis.

Global tracking of space debris via CPHD and consensus

NASA Astrophysics Data System (ADS)

Wei, Baishen; Nener, Brett; Liu, Weifeng; Ma, Liang

2017-05-01

Space debris tracking is of great importance for safe operation of spacecraft. This paper presents an algorithm that achieves global tracking of space debris with a multi-sensor network. The sensor network has unknown and possibly time-varying topology. A consensus algorithm is used to effectively counteract the effects of data incest. Gaussian Mixture-Cardinalized Probability Hypothesis Density (GM-CPHD) filtering is used to estimate the state of the space debris. As an example of the method, 45 clusters of sensors are used to achieve global tracking. The performance of the proposed approach is demonstrated by simulation experiments.

Diagnostic work-up and loss of tuberculosis suspects in Jogjakarta, Indonesia

PubMed Central

2012-01-01

Background Early and accurate diagnosis of pulmonary tuberculosis (TB) is critical for successful TB control. To assist in the diagnosis of smear-negative pulmonary TB, the World Health Organisation (WHO) recommends the use of a diagnostic algorithm. Our study evaluated the implementation of the national tuberculosis programme's diagnostic algorithm in routine health care settings in Jogjakarta, Indonesia. The diagnostic algorithm is based on the WHO TB diagnostic algorithm, which had already been implemented in the health facilities. Methods We prospectively documented the diagnostic work-up of all new tuberculosis suspects until a diagnosis was reached. We used clinical audit forms to record each step chronologically. Data on the patient's gender, age, symptoms, examinations (types, dates, and results), and final diagnosis were collected. Results Information was recorded for 754 TB suspects; 43.5% of whom were lost during the diagnostic work-up in health centres, 0% in lung clinics. Among the TB suspects who completed diagnostic work-ups, 51.1% and 100.0% were diagnosed without following the national TB diagnostic algorithm in health centres and lung clinics, respectively. However, the work-up in the health centres and lung clinics generally conformed to international standards for tuberculosis care (ISTC). Diagnostic delays were significantly longer in health centres compared to lung clinics. Conclusions The high rate of patients lost in health centres needs to be addressed through the implementation of TB suspect tracing and better programme supervision. The national TB algorithm needs to be revised and differentiated according to the level of care. PMID:22333111

PERMANENT GENETIC RESOURCES: Consensus primers of cyp73 genes discriminate willow species and hybrids (Salix, Salicaceae).

PubMed

Trung, Le Quang; VAN Puyvelde, Karolien; Triest, Ludwig

2008-03-01

Consensus primers, based on exon sequences of the cyp73 gene family coding for cinnamate 4-hydroxylase (C4H) of the lignin biosynthesis pathway, were designed for the tetraploid willow species Salix alba and Salix fragilis. Diagnostic alleles at species level were observed among introns of three cyp73 genes and allowed unambiguous detection of the first generation and introgressed hybrids in populations. Progeny analysis of a female S. alba with a male introgressed hybrid confirmed the codominant inheritance of each intron. Sequences of the diagnostic alleles of both species were similar to those found in the hybrids. © 2007 The Authors.

A Proposed Algorithm for Improved Recognition and Treatment of the Depression/Anxiety Spectrum in Primary Care.

PubMed

Ballenger, James C.; Davidson, Jonathan R. T.; Lecrubier, Yves; Nutt, David J.

2001-04-01

The International Consensus Group on Depression and Anxiety has held 7 meetings over the last 3 years that focused on depression and specific anxiety disorders. During the course of the meeting series, a number of common themes have developed. At the last meeting of the Consensus Group, we reviewed these areas of commonality across the spectrum of depression and anxiety disorders. With the aim of improving the recognition and management of depression and anxiety in the primary care setting, we developed an algorithm that is presented in this article. We attempted to balance currently available scientific knowledge about the treatment of these disorders and to reformat it to provide an acceptable algorithm that meets the practical aspects of recognizing and treating these disorders in primary care.

Guidelines for the diagnosis and treatment of idiopathic pulmonary fibrosis. Sociedad Española de Neumología y Cirugía Torácica (SEPAR) Research Group on Diffuse Pulmonary Diseases.

PubMed

Xaubet, Antoni; Ancochea, Julio; Bollo, Elena; Fernández-Fabrellas, Estrella; Franquet, Tomás; Molina-Molina, Maria; Montero, Maria Angeles; Serrano-Mollar, Anna

2013-08-01

Idiopathic pulmonary fibrosis is defined as a chronic fibrosing interstitial pneumonia limited to the lung, of unknown cause, with poor prognosis and few treatment options. In recent years there has been an increase in their prevalence, probably due to the optimization of diagnostic methods and increased life expectancy. The ATS/ERS Consensus (2000) established the diagnostic criteria and recommendations for the assessment of the disease course and treatment. Later studies have helped to redefine diagnostic criteria and treatment options. In 2011, an international consensus was published, establishing diagnostic criteria and new treatment strategies. These guidelines have been updated with the newest aspects of diagnosis and treatment of idiopathic pulmonary fibrosis. A level of evidence has been identified for the most relevant questions, particularly with regard to treatment options. Copyright © 2012 SEPAR. Published by Elsevier Espana. All rights reserved.

Evaluation of the International Consensus Guidelines for the Surgical Resection of Intraductal Papillary Mucinous Neoplasms.

PubMed

Tsukagoshi, Mariko; Araki, Kenichiro; Saito, Fumiyoshi; Kubo, Norio; Watanabe, Akira; Igarashi, Takamichi; Ishii, Norihiro; Yamanaka, Takahiro; Shirabe, Ken; Kuwano, Hiroyuki

2018-04-01

International consensus guidelines for intraductal papillary mucinous neoplasms (IPMNs) were revised in 2012. We aimed to evaluate the clinical utility of each predictor in the 2006 and 2012 guidelines and validate the diagnostic value and surgical indications. Forty-two patients with surgically resected IPMNs were included. Each predictor was applied to evaluate its diagnostic value. The 2012 guidelines had greater accuracy for invasive carcinoma than the 2006 guidelines (64.3 vs. 31.0%). Moreover, the accuracy for high-grade dysplasia was also increased (48.6 vs. 77.1%). When the main pancreatic duct (MPD) size ≥8 mm was substituted for MPD size ≥10 mm in the 2012 guidelines, the accuracy for high-grade dysplasia was 80.0%. The 2012 guidelines exhibited increased diagnostic accuracy for invasive IPMN. It is important to consider surgical resection prior to invasive carcinoma, and high-risk stigmata might be a useful diagnostic criterion. Furthermore, MPD size ≥8 mm may be predictive of high-grade dysplasia.

In-silico analysis of putative HCV epitopes against Pakistani human leukocyte antigen background: An approach towards development of future vaccines for Pakistani population.

PubMed

Ashraf, Naeem Mahmood; Bilal, Muhammad; Mahmood, Malik Siddique; Hussain, Aadil; Mehboob, Muhammad Zubair

2016-09-01

Mounting burden of HCV-infected individuals and soaring cost of treatment is a serious source of unease for developing countries. Numbers of various approaches have been anticipated to develop a vaccine against HCV but the majority of them proved ineffective. Development of vaccine by considering geographical distribution of HCV genotypes and host genetics shows potential. In this research article, we have tried to predict most putative HCV epitopes which are efficiently restricted by most common HLA alleles in Pakistani population through different computational algorithms. Thirteen selected, experimentally identified epitopes sequences were used to derived consensus sequences in all genotypes of HCV. Obtained consensus sequences were used to predict their binding affinities with most prevalent HLA alleles in Pakistani population. Two Class-I epitopes from NS4B region, one from Class-I epitope from NS5A and one Class-II epitope from NS3 region showed effective binding and proved to be highly putative to boost immune response. A cocktail of these four have been checked for population coverage and they gave 75.53% for Pakistani Asian and 70.77% for Pakistani Mixed populations with no allergenic response. Computational algorithms are robust way to shortlist potential candidate epitopes for vaccine development but further, in vivo and in-vitro studies are required to confirm their immunogenic properties. Copyright © 2016 Elsevier B.V. All rights reserved.

Insight in Frontotemporal Dementia: Conceptual Analysis and Empirical Evaluation of the Consensus Criterion ''Loss of Insight'' in Frontotemporal Dementia

ERIC Educational Resources Information Center

Evers, Kathinka; Kilander, Lena; Lindau, Maria

2007-01-01

The objective of this study was to suggest a new formulation of the core research diagnostic consensus criterion ''loss of insight'' in frontotemporal dementia (FTD). Eight patients with FTD (diagnoses made by interviews, medical and neuropsychological examination, CT scan, and regional cerebral glucose metabolism measured by positron emission…

Systematic Benchmarking of Diagnostic Technologies for an Electrical Power System

NASA Technical Reports Server (NTRS)

Kurtoglu, Tolga; Jensen, David; Poll, Scott

2009-01-01

Automated health management is a critical functionality for complex aerospace systems. A wide variety of diagnostic algorithms have been developed to address this technical challenge. Unfortunately, the lack of support to perform large-scale V&V (verification and validation) of diagnostic technologies continues to create barriers to effective development and deployment of such algorithms for aerospace vehicles. In this paper, we describe a formal framework developed for benchmarking of diagnostic technologies. The diagnosed system is the Advanced Diagnostics and Prognostics Testbed (ADAPT), a real-world electrical power system (EPS), developed and maintained at the NASA Ames Research Center. The benchmarking approach provides a systematic, empirical basis to the testing of diagnostic software and is used to provide performance assessment for different diagnostic algorithms.

Vagus Nerve Stimulation for Electrographic Status Epilepticus in Slow-Wave Sleep.

PubMed

Carosella, Christopher M; Greiner, Hansel M; Byars, Anna W; Arthur, Todd M; Leach, James L; Turner, Michele; Holland, Katherine D; Mangano, Francesco T; Arya, Ravindra

2016-07-01

Electrographic status epilepticus in slow sleep or continuous spike and waves during slow-wave sleep is an epileptic encephalopathy characterized by seizures, neurocognitive regression, and significant activation of epileptiform discharges during nonrapid eye movement sleep. There is no consensus on the diagnostic criteria and evidence-based optimal treatment algorithm for children with electrographic status epilepticus in slow sleep. We describe a 12-year-old girl with drug-resistant electrographic status epilepticus in slow wave sleep that was successfully treated with vagus nerve stimulation. Her clinical presentation, presurgical evaluation, decision-making, and course after vagus nerve stimulator implantation are described in detail. After vagus nerve stimulator implantation, the girl remained seizure free for more than a year, resolved the electrographic status epilepticus in slow sleep pattern on electroencephalography, and exhibited significant cognitive improvement. Vagus nerve stimulation may be considered for electrographic status epilepticus in slow sleep. Copyright © 2016 Elsevier Inc. All rights reserved.

Hydrocephalus and mucopolysaccharidoses: what do we know and what do we not know?

PubMed

Dalla Corte, Amauri; de Souza, Carolina F M; Anés, Maurício; Giugliani, Roberto

2017-07-01

The precise incidence of hydrocephalus in patients with mucopolysaccharidoses (MPS) is hard to determine, because the condition lacks a formal, consensus-based definition. The diagnosis of hydrocephalus depends on symptom profile, presence of neuroimaging features, and the outcome of diagnostic tests. Although numerous techniques are used to identify MPS patients who are most likely to have hydrocephalus and respond to treatment, no definitive method exists to prove diagnosis. The authors propose an algorithm to aid in the diagnosis and management of hydrocephalus in MPS patients. The theory of venous hypertension associated with the morphological changes in the skull base and craniocervical junction indicate the need for future neuroimaging studies including cerebrospinal fluid (CSF) and venous flow measurements to monitor hydrocephalus progression and select therapeutic interventions in MPS patients. Preoperative planning should also be based on the increased risk of intraoperative and postoperative hemorrhagic complications.

Image microarrays (IMA): Digital pathology's missing tool

PubMed Central

Hipp, Jason; Cheng, Jerome; Pantanowitz, Liron; Hewitt, Stephen; Yagi, Yukako; Monaco, James; Madabhushi, Anant; Rodriguez-canales, Jaime; Hanson, Jeffrey; Roy-Chowdhuri, Sinchita; Filie, Armando C.; Feldman, Michael D.; Tomaszewski, John E.; Shih, Natalie NC.; Brodsky, Victor; Giaccone, Giuseppe; Emmert-Buck, Michael R.; Balis, Ulysses J.

2011-01-01

Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. PMID:22200030

Distributed Matrix Completion: Applications to Cooperative Positioning in Noisy Environments

DTIC Science & Technology

2013-12-11

positioning, and a gossip version of low-rank approximation were developed. A convex relaxation for positioning in the presence of noise was shown...computing the leading eigenvectors of a large data matrix through gossip algorithms. A new algorithm is proposed that amounts to iteratively multiplying...generalization of gossip algorithms for consensus. The algorithms outperform state-of-the-art methods in a communication-limited scenario. Positioning via

Distributed attitude synchronization of formation flying via consensus-based virtual structure

NASA Astrophysics Data System (ADS)

Cong, Bing-Long; Liu, Xiang-Dong; Chen, Zhen

2011-06-01

This paper presents a general framework for synchronized multiple spacecraft rotations via consensus-based virtual structure. In this framework, attitude control systems for formation spacecrafts and virtual structure are designed separately. Both parametric uncertainty and external disturbance are taken into account. A time-varying sliding mode control (TVSMC) algorithm is designed to improve the robustness of the actual attitude control system. As for the virtual attitude control system, a behavioral consensus algorithm is presented to accomplish the attitude maneuver of the entire formation and guarantee a consistent attitude among the local virtual structure counterparts during the attitude maneuver. A multiple virtual sub-structures (MVSSs) system is introduced to enhance current virtual structure scheme when large amounts of spacecrafts are involved in the formation. The attitude of spacecraft is represented by modified Rodrigues parameter (MRP) for its non-redundancy. Finally, a numerical simulation with three synchronization situations is employed to illustrate the effectiveness of the proposed strategy.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular Pathology of Patient Tumors, Patient-Derived Xenografts, and Cancer Cell Lines.

PubMed

Guo, Sheng; Qian, Wubin; Cai, Jie; Zhang, Likun; Wery, Jean-Pierre; Li, Qi-Xiang

2016-08-15

The Cancer Genome Atlas (TCGA) project has generated abundant genomic data for human cancers of various histopathology types and enabled exploring cancer molecular pathology per big data approach. We developed a new algorithm based on most differentially expressed genes (DEG) per pairwise comparisons to calculate correlation coefficients to be used to quantify similarity within and between cancer types. We systematically compared TCGA cancers, demonstrating high correlation within types and low correlation between types, thus establishing molecular specificity of cancer types and an alternative diagnostic method largely equivalent to histopathology. Different coefficients for different cancers in study may reveal that the degree of the within-type homogeneity varies by cancer types. We also performed the same calculation using the TCGA-derived DEGs on patient-derived xenografts (PDX) of different histopathology types corresponding to the TCGA types, as well as on cancer cell lines. We, for the first time, demonstrated highly similar patterns for within- and between-type correlation between PDXs and patient samples in a systematic study, confirming the high relevance of PDXs as surrogate experimental models for human diseases. In contrast, cancer cell lines have drastically reduced expression similarity to both PDXs and patient samples. The studies also revealed high similarity between some types, for example, LUSC and HNSCC, but low similarity between certain subtypes, for example, LUAD and LUSC. Our newly developed algorithm seems to be a practical diagnostic method to classify and reclassify a disease, either human or xenograft, with better accuracy than traditional histopathology. Cancer Res; 76(16); 4619-26. ©2016 AACR. ©2016 American Association for Cancer Research.

The Added Value of the Combined Use of the Autism Diagnostic Interview-Revised and the Autism Diagnostic Observation Schedule: Diagnostic Validity in a Clinical Swedish Sample of Toddlers and Young Preschoolers

ERIC Educational Resources Information Center

Zander, Eric; Sturm, Harald; Bölte, Sven

2015-01-01

The diagnostic validity of the new research algorithms of the Autism Diagnostic Interview-Revised and the revised algorithms of the Autism Diagnostic Observation Schedule was examined in a clinical sample of children aged 18-47 months. Validity was determined for each instrument separately and their combination against a clinical consensus…

Performance of the 2015 International Task Force Consensus Statement Risk Stratification Algorithm for Implantable Cardioverter-Defibrillator Placement in Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy.

PubMed

Orgeron, Gabriela M; Te Riele, Anneline; Tichnell, Crystal; Wang, Weijia; Murray, Brittney; Bhonsale, Aditya; Judge, Daniel P; Kamel, Ihab R; Zimmerman, Stephan L; Tandri, Harikrishna; Calkins, Hugh; James, Cynthia A

2018-02-01

Ventricular arrhythmias are a feared complication of arrhythmogenic right ventricular dysplasia/cardiomyopathy. In 2015, an International Task Force Consensus Statement proposed a risk stratification algorithm for implantable cardioverter-defibrillator placement in arrhythmogenic right ventricular dysplasia/cardiomyopathy. To evaluate performance of the algorithm, 365 arrhythmogenic right ventricular dysplasia/cardiomyopathy patients were classified as having a Class I, IIa, IIb, or III indication per the algorithm at baseline. Survival free from sustained ventricular arrhythmia (VT/VF) in follow-up was the primary outcome. Incidence of ventricular fibrillation/flutter cycle length <240 ms was also assessed. Two hundred twenty-four (61%) patients had a Class I implantable cardioverter-defibrillator indication; 80 (22%), Class IIa; 54 (15%), Class IIb; and 7 (2%), Class III. During a median 4.2 (interquartile range, 1.7-8.4)-year follow-up, 190 (52%) patients had VT/VF and 60 (16%) had ventricular fibrillation/flutter. Although the algorithm appropriately differentiated risk of VT/VF, incidence of VT/VF was underestimated (observed versus expected: 29.6 [95% confidence interval, 25.2-34.0] versus >10%/year Class I; 15.5 [confidence interval 11.1-21.6] versus 1% to 10%/year Class IIa). In addition, the algorithm did not differentiate survival free from ventricular fibrillation/flutter between Class I and IIa patients ( P =0.97) or for VT/VF in Class I and IIa primary prevention patients ( P =0.22). Adding Holter results (<1000 premature ventricular contractions/24 hours) to International Task Force Consensus classification differentiated risks. While the algorithm differentiates arrhythmic risk well overall, it did not distinguish ventricular fibrillation/flutter risks of patients with Class I and IIa implantable cardioverter-defibrillator indications. Limited differentiation was seen for primary prevention cases. As these are vital uncertainties in clinical decision-making, refinements to the algorithm are suggested prior to implementation. © 2018 American Heart Association, Inc.

Refining the Global Spatial Limits of Dengue Virus Transmission by Evidence-Based Consensus

PubMed Central

Brady, Oliver J.; Gething, Peter W.; Bhatt, Samir; Messina, Jane P.; Brownstein, John S.; Hoen, Anne G.; Moyes, Catherine L.; Farlow, Andrew W.; Scott, Thomas W.; Hay, Simon I.

2012-01-01

Background Dengue is a growing problem both in its geographical spread and in its intensity, and yet current global distribution remains highly uncertain. Challenges in diagnosis and diagnostic methods as well as highly variable national health systems mean no single data source can reliably estimate the distribution of this disease. As such, there is a lack of agreement on national dengue status among international health organisations. Here we bring together all available information on dengue occurrence using a novel approach to produce an evidence consensus map of the disease range that highlights nations with an uncertain dengue status. Methods/Principal Findings A baseline methodology was used to assess a range of evidence for each country. In regions where dengue status was uncertain, additional evidence types were included to either clarify dengue status or confirm that it is unknown at this time. An algorithm was developed that assesses evidence quality and consistency, giving each country an evidence consensus score. Using this approach, we were able to generate a contemporary global map of national-level dengue status that assigns a relative measure of certainty and identifies gaps in the available evidence. Conclusion The map produced here provides a list of 128 countries for which there is good evidence of dengue occurrence, including 36 countries that have previously been classified as dengue-free by the World Health Organization and/or the US Centers for Disease Control. It also identifies disease surveillance needs, which we list in full. The disease extents and limits determined here using evidence consensus, marks the beginning of a five-year study to advance the mapping of dengue virus transmission and disease risk. Completion of this first step has allowed us to produce a preliminary estimate of population at risk with an upper bound of 3.97 billion people. This figure will be refined in future work. PMID:22880140

Refining the global spatial limits of dengue virus transmission by evidence-based consensus.

PubMed

Brady, Oliver J; Gething, Peter W; Bhatt, Samir; Messina, Jane P; Brownstein, John S; Hoen, Anne G; Moyes, Catherine L; Farlow, Andrew W; Scott, Thomas W; Hay, Simon I

2012-01-01

Dengue is a growing problem both in its geographical spread and in its intensity, and yet current global distribution remains highly uncertain. Challenges in diagnosis and diagnostic methods as well as highly variable national health systems mean no single data source can reliably estimate the distribution of this disease. As such, there is a lack of agreement on national dengue status among international health organisations. Here we bring together all available information on dengue occurrence using a novel approach to produce an evidence consensus map of the disease range that highlights nations with an uncertain dengue status. A baseline methodology was used to assess a range of evidence for each country. In regions where dengue status was uncertain, additional evidence types were included to either clarify dengue status or confirm that it is unknown at this time. An algorithm was developed that assesses evidence quality and consistency, giving each country an evidence consensus score. Using this approach, we were able to generate a contemporary global map of national-level dengue status that assigns a relative measure of certainty and identifies gaps in the available evidence. The map produced here provides a list of 128 countries for which there is good evidence of dengue occurrence, including 36 countries that have previously been classified as dengue-free by the World Health Organization and/or the US Centers for Disease Control. It also identifies disease surveillance needs, which we list in full. The disease extents and limits determined here using evidence consensus, marks the beginning of a five-year study to advance the mapping of dengue virus transmission and disease risk. Completion of this first step has allowed us to produce a preliminary estimate of population at risk with an upper bound of 3.97 billion people. This figure will be refined in future work.

Specific Pathogen Free Macaque Colonies: A Review of Principles and Recent Advances for Viral Testing and Colony Management

PubMed Central

Yee, JoAnn L.; Vandeford, Thomas H.; Didier, Elizabeth S.; Gray, Stanton; Lewis, Anne; Roberts, Jeffrey; Taylor, Kerry; Bohm, Rudolf P.

2016-01-01

Specific Pathogen Free (SPF) macaques provide valuable animal models for biomedical research. In 1989 the National Center for Research Resources (now Office of Research Infrastructure Programs ORIP) of the National Institutes of Health initiated experimental research contracts to establish and maintain SPF colonies. The derivation and maintenance of SPF macaque colonies is a complex undertaking requiring knowledge of the biology of the agents for exclusion and normal physiology and behavior of macaques, application of the latest diagnostic technology, facilities management, and animal husbandry. This review provides information on the biology of the four viral agents targeted for exclusion in ORIP SPF macaque colonies, describes current state-of-the-art viral diagnostic algorithms, presents data from proficiency testing of diagnostic assays between laboratories at institutions participating in the ORIP SPF program, and outlines management strategies for maintaining the integrity of SPF colonies using results of diagnostic testing as a guide to decision making. PMID:26932456

Mean square consensus of leader-following multi-agent systems with measurement noises and time delays.

PubMed

Ren, Hongwei; Deng, Feiqi

2017-11-01

This paper investigates the mean square consensus problem of dynamical networks of leader-following multi-agent systems with measurement noises and time-varying delays. We consider that the fixed undirected communication topologies are connected. A neighbor-based tracking algorithm together with distributed estimators are presented. Using tools of algebraic graph theory and the Gronwall-Bellman-Halanay type inequality, we establish sufficient conditions to reach consensus in mean square sense via the proposed consensus protocols. Finally, a numerical simulation is provided to demonstrate the effectiveness of the obtained theoretical result. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Poor concordance among nine immunohistochemistry classifiers of cell-of-origin for Diffuse Large B-cell Lymphoma: implications for therapeutic strategies

PubMed Central

Coutinho, Rita; Clear, Andrew James; Owen, Andrew; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Calaminici, Maria; Gribben, John G.

2014-01-01

Purpose The opportunity to improve therapeutic choices on the basis of molecular features of the tumour cells is on the horizon in Diffuse Large B-cell Lymphoma (DLBCL). Agents such as bortezomib exhibit selective activity against the poor outcome activated B-cell type DLBCL. In order for targeted therapies to succeed in this disease, robust strategies that segregate patients into molecular groups with high reliability are needed. While molecular studies are considered gold standard, several immunohistochemistry (IHC) algorithms have been published that claim to be able to stratify patients according to their cell-of-origin and to be relevant for patient outcome. However results are poorly reproducible by independent groups. Experimental design We investigated nine IHC algorithms for molecular classification in a dataset of DLBCL diagnostic biopsies, incorporating immunostaining for CD10, BCL6, BCL2, MUM1, FOXP1, GCET1 and LMO2. IHC profiles were assessed and agreed among three expert observers. A consensus matrix based on all scoring combinations and the number of subjects for each combination allowed to assess reliability. The survival impact of individual markers and classifiers was evaluated using Kaplan-Meier curves and the log-rank test. Results The concordance in patient’s classification across the different algorithms was low. Only 4% the tumors have been classified as GCB and 21% as ABC/non-GCB by all methods. None of the algorithms provided prognostic information in the R-CHOP treated cohort. Conclusion Further work is required to standardize IHC algorithms for DLBCL cell-of-origin classification for these to be considered reliable alternatives to molecular-based methods to be used for clinical decisions. PMID:24122791

Poor concordance among nine immunohistochemistry classifiers of cell-of-origin for diffuse large B-cell lymphoma: implications for therapeutic strategies.

PubMed

Coutinho, Rita; Clear, Andrew James; Owen, Andrew; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; Gomes da Silva, Maria; Cabeçadas, José; Calaminici, Maria; Gribben, John G

2013-12-15

The opportunity to improve therapeutic choices on the basis of molecular features of the tumor cells is on the horizon in diffuse large B-cell lymphoma (DLBCL). Agents such as bortezomib exhibit selective activity against the poor outcome activated B-cell type (ABC) DLBCL. In order for targeted therapies to succeed in this disease, robust strategies that segregate patients into molecular groups with high reliability are needed. Although molecular studies are considered gold standard, several immunohistochemistry (IHC) algorithms have been published that claim to be able to stratify patients according to their cell-of-origin and to be relevant for patient outcome. However, results are poorly reproducible by independent groups. We investigated nine IHC algorithms for molecular classification in a dataset of DLBCL diagnostic biopsies, incorporating immunostaining for CD10, BCL6, BCL2, MUM1, FOXP1, GCET1, and LMO2. IHC profiles were assessed and agreed among three expert observers. A consensus matrix based on all scoring combinations and the number of subjects for each combination allowed us to assess reliability. The survival impact of individual markers and classifiers was evaluated using Kaplan-Meier curves and the log-rank test. The concordance in patient's classification across the different algorithms was low. Only 4% of the tumors have been classified as germinal center B-cell type (GCB) and 21% as ABC/non-GCB by all methods. None of the algorithms provided prognostic information in the R-CHOP (rituximab plus cyclophosphamide-adriamycin-vincristine-prednisone)-treated cohort. Further work is required to standardize IHC algorithms for DLBCL cell-of-origin classification for these to be considered reliable alternatives to molecular-based methods to be used for clinical decisions. ©2013 AACR.

Evaluation of Bioinformatic Programmes for the Analysis of Variants within Splice Site Consensus Regions

PubMed Central

Tang, Rongying; Prosser, Debra O.; Love, Donald R.

2016-01-01

The increasing diagnostic use of gene sequencing has led to an expanding dataset of novel variants that lie within consensus splice junctions. The challenge for diagnostic laboratories is the evaluation of these variants in order to determine if they affect splicing or are merely benign. A common evaluation strategy is to use in silico analysis, and it is here that a number of programmes are available online; however, currently, there are no consensus guidelines on the selection of programmes or protocols to interpret the prediction results. Using a collection of 222 pathogenic mutations and 50 benign polymorphisms, we evaluated the sensitivity and specificity of four in silico programmes in predicting the effect of each variant on splicing. The programmes comprised Human Splice Finder (HSF), Max Entropy Scan (MES), NNSplice, and ASSP. The MES and ASSP programmes gave the highest performance based on Receiver Operator Curve analysis, with an optimal cut-off of score reduction of 10%. The study also showed that the sensitivity of prediction is affected by the level of conservation of individual positions, with in silico predictions for variants at positions −4 and +7 within consensus splice sites being largely uninformative. PMID:27313609

[Consensus document on spasticity in patients with multiple sclerosis. Grupo de Enfermedades Desmielinizantes de la Sociedad Española de Neurología].

PubMed

Oreja-Guevara, Celia; Montalban, Xavier; de Andrés, Clara; Casanova-Estruch, Bonaventura; Muñoz-García, Delicias; García, Inmaculada; Fernández, Óscar

2013-10-16

Multiple sclerosis is a chronic neurological inflammatory demyelinating disease. Specialists involved in the symptomatic treatment of this disease tend to apply heterogeneous diagnostic and treatment criteria. To establish homogeneous criteria for treating spasticity based on available scientific knowledge, facilitating decision-making in regular clinical practice. A group of multiple sclerosis specialists from the Spanish Neurological Society demyelinating diseases working group met to review aspects related to spasticity in this disease and draw up the consensus. After an exhaustive bibliographic search and following a metaplan technique, a number of preliminary recommendations were established to incorporate into the document. Finally, each argument was classified depending on the degree of recommendation according to the SIGN (Scottish Intercollegiate Guidelines Network) system. The resulting text was submitted for review by the demyelinating disease group. An experts' consensus was reached regarding spasticity triggering factors, related symptoms, diagnostic criteria, assessment methods, quality of life and therapeutic management (drug and non-drug) criteria. The recommendations included in this consensus can be a useful tool for improving the quality of life of multiple sclerosis patients, as they enable improved diagnosis and treatment of spasticity.

Survey of gene splicing algorithms based on reads.

PubMed

Si, Xiuhua; Wang, Qian; Zhang, Lei; Wu, Ruo; Ma, Jiquan

2017-11-02

Gene splicing is the process of assembling a large number of unordered short sequence fragments to the original genome sequence as accurately as possible. Several popular splicing algorithms based on reads are reviewed in this article, including reference genome algorithms and de novo splicing algorithms (Greedy-extension, Overlap-Layout-Consensus graph, De Bruijn graph). We also discuss a new splicing method based on the MapReduce strategy and Hadoop. By comparing these algorithms, some conclusions are drawn and some suggestions on gene splicing research are made.

Consensus properties and their large-scale applications for the gene duplication problem.

PubMed

Moon, Jucheol; Lin, Harris T; Eulenstein, Oliver

2016-06-01

Solving the gene duplication problem is a classical approach for species tree inference from gene trees that are confounded by gene duplications. This problem takes a collection of gene trees and seeks a species tree that implies the minimum number of gene duplications. Wilkinson et al. posed the conjecture that the gene duplication problem satisfies the desirable Pareto property for clusters. That is, for every instance of the problem, all clusters that are commonly present in the input gene trees of this instance, called strict consensus, will also be found in every solution to this instance. We prove that this conjecture does not generally hold. Despite this negative result we show that the gene duplication problem satisfies a weaker version of the Pareto property where the strict consensus is found in at least one solution (rather than all solutions). This weaker property contributes to our design of an efficient scalable algorithm for the gene duplication problem. We demonstrate the performance of our algorithm in analyzing large-scale empirical datasets. Finally, we utilize the algorithm to evaluate the accuracy of standard heuristics for the gene duplication problem using simulated datasets.

Algorithmic Approaches for Place Recognition in Featureless, Walled Environments

DTIC Science & Technology

2015-01-01

inertial measurement unit LIDAR light detection and ranging RANSAC random sample consensus SLAM simultaneous localization and mapping SUSAN smallest...algorithm 38 21 Typical input image for general junction based algorithm 39 22 Short exposure image of hallway junction taken by LIDAR 40 23...discipline of simultaneous localization and mapping ( SLAM ) has been studied intensively over the past several years. Many technical approaches

Reducing false-positive detections by combining two stage-1 computer-aided mass detection algorithms

NASA Astrophysics Data System (ADS)

Bedard, Noah D.; Sampat, Mehul P.; Stokes, Patrick A.; Markey, Mia K.

2006-03-01

In this paper we present a strategy for reducing the number of false-positives in computer-aided mass detection. Our approach is to only mark "consensus" detections from among the suspicious sites identified by different "stage-1" detection algorithms. By "stage-1" we mean that each of the Computer-aided Detection (CADe) algorithms is designed to operate with high sensitivity, allowing for a large number of false positives. In this study, two mass detection methods were used: (1) Heath and Bowyer's algorithm based on the average fraction under the minimum filter (AFUM) and (2) a low-threshold bi-lateral subtraction algorithm. The two methods were applied separately to a set of images from the Digital Database for Screening Mammography (DDSM) to obtain paired sets of mass candidates. The consensus mass candidates for each image were identified by a logical "and" operation of the two CADe algorithms so as to eliminate regions of suspicion that were not independently identified by both techniques. It was shown that by combining the evidence from the AFUM filter method with that obtained from bi-lateral subtraction, the same sensitivity could be reached with fewer false-positives per image relative to using the AFUM filter alone.

Integration of next-generation sequencing in clinical diagnostic molecular pathology laboratories for analysis of solid tumours; an expert opinion on behalf of IQN Path ASBL.

PubMed

Deans, Zandra C; Costa, Jose Luis; Cree, Ian; Dequeker, Els; Edsjö, Anders; Henderson, Shirley; Hummel, Michael; Ligtenberg, Marjolijn Jl; Loddo, Marco; Machado, Jose Carlos; Marchetti, Antonio; Marquis, Katherine; Mason, Joanne; Normanno, Nicola; Rouleau, Etienne; Schuuring, Ed; Snelson, Keeda-Marie; Thunnissen, Erik; Tops, Bastiaan; Williams, Gareth; van Krieken, Han; Hall, Jacqueline A

2017-01-01

The clinical demand for mutation detection within multiple genes from a single tumour sample requires molecular diagnostic laboratories to develop rapid, high-throughput, highly sensitive, accurate and parallel testing within tight budget constraints. To meet this demand, many laboratories employ next-generation sequencing (NGS) based on small amplicons. Building on existing publications and general guidance for the clinical use of NGS and learnings from germline testing, the following guidelines establish consensus standards for somatic diagnostic testing, specifically for identifying and reporting mutations in solid tumours. These guidelines cover the testing strategy, implementation of testing within clinical service, sample requirements, data analysis and reporting of results. In conjunction with appropriate staff training and international standards for laboratory testing, these consensus standards for the use of NGS in molecular pathology of solid tumours will assist laboratories in implementing NGS in clinical services.

New Autism Diagnostic Interview-Revised Algorithms for Toddlers and Young Preschoolers from 12 to 47 Months of Age

ERIC Educational Resources Information Center

Kim, So Hyun; Lord, Catherine

2012-01-01

Autism Diagnostic Interview-Revised (Rutter et al. in "Autism diagnostic interview-revised." Western Psychological Services, Los Angeles, 2003) diagnostic algorithms specific to toddlers and young preschoolers were created using 829 assessments of children aged from 12 to 47 months with ASD, nonspectrum disorders, and typical development. The…

Small renal mass biopsy--how, what and when: report from an international consensus panel.

PubMed

Tsivian, Matvey; Rampersaud, Edward N; del Pilar Laguna Pes, Maria; Joniau, Steven; Leveillee, Raymond J; Shingleton, William B; Aron, Monish; Kim, Charles Y; DeMarzo, Angelo M; Desai, Mihir M; Meler, James D; Donovan, James F; Klingler, Hans Christoph; Sopko, David R; Madden, John F; Marberger, Michael; Ferrandino, Michael N; Polascik, Thomas J

2014-06-01

To discuss the use of renal mass biopsy (RMB) for small renal masses (SRMs), formulate technical aspects, outline potential pitfalls and provide recommendations for the practicing clinician. The meeting was conducted as an informal consensus process and no scoring system was used to measure the levels of agreement on the different topics. A moderated general discussion was used as the basis for consensus and arising issues were resolved at this point. A consensus was established and lack of agreement to topics or specific items was noted at this point. Recommended biopsy technique: at least two cores, sampling different tumour regions with ultrasonography being the preferred method of image guidance. Pathological interpretation: 'non-diagnostic samples' should refer to insufficient material, inconclusive and normal renal parenchyma. For non-diagnostic samples, a repeat biopsy is recommended. Fine-needle aspiration may provide additional information but cannot substitute for core biopsy. Indications for RMB: biopsy is recommended in most cases except in patients with imaging or clinical characteristics indicative of pathology (syndromes, imaging characteristics) and cases whereby conservative management is not contemplated. RMB is recommended for active surveillance but not for watchful-waiting candidates. We report the results of an international consensus meeting on the use of RMB for SRMs, defining the technique, pathological interpretation and indications. © 2013 The Authors. BJU International © 2013 BJU International.

Research Priorities in the Utilization and Interpretation of Diagnostic Imaging: Education, Assessment, and Competency.

PubMed

Lewiss, Resa E; Chan, Wilma; Sheng, Alexander Y; Soto, Jorge; Castro, Alexandra; Meltzer, Andrew C; Cherney, Alan; Kumaravel, Manickam; Cody, Dianna; Chen, Esther H

2015-12-01

The appropriate selection and accurate interpretation of diagnostic imaging is a crucial skill for emergency practitioners. To date, the majority of the published literature and research on competency assessment comes from the subspecialty of point-of-care ultrasound. A group of radiologists, physicists, and emergency physicians convened at the 2015 Academic Emergency Medicine consensus conference to discuss and prioritize a research agenda related to education, assessment, and competency in ordering and interpreting diagnostic imaging. A set of questions for the continued development of an educational curriculum on diagnostic imaging for trainees and competency assessment using specific assessment methods based on current best practices was delineated. The research priorities were developed through an iterative consensus-driven process using a modified nominal group technique that culminated in an in-person breakout session. The four recommendations are: 1) develop a diagnostic imaging curriculum for emergency medicine (EM) residency training; 2) develop, study, and validate tools to assess competency in diagnostic imaging interpretation; 3) evaluate the role of simulation in education, assessment, and competency measures for diagnostic imaging; 4) study is needed regarding the American College of Radiology Appropriateness Criteria, an evidence-based peer-reviewed resource in determining the use of diagnostic imaging, to maximize its value in EM. In this article, the authors review the supporting reliability and validity evidence and make specific recommendations for future research on the education, competency, and assessment of learning diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Usefulness of magnifying endoscopy with narrow-band imaging for diagnosis of depressed gastric lesions

PubMed Central

SUMIE, HIROAKI; SUMIE, SHUJI; NAKAHARA, KEITA; WATANABE, YASUTOMO; MATSUO, KEN; MUKASA, MICHITA; SAKAI, TAKESHI; YOSHIDA, HIKARU; TSURUTA, OSAMU; SATA, MICHIO

2014-01-01

The usefulness of magnifying endoscopy with narrow-band imaging (ME-NBI) for the diagnosis of early gastric cancer is well known, however, there are no evaluation criteria. The aim of this study was to devise and evaluate a novel diagnostic algorithm for ME-NBI in depressed early gastric cancer. Between August, 2007 and May, 2011, 90 patients with a total of 110 depressed gastric lesions were enrolled in the study. A diagnostic algorithm was devised based on ME-NBI microvascular findings: microvascular irregularity and abnormal microvascular patterns (fine network, corkscrew and unclassified patterns). The diagnostic efficiency of the algorithm for gastric cancer and histological grade was assessed by measuring its mean sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Furthermore, inter- and intra-observer variation were measured. In the differential diagnosis of gastric cancer from non-cancerous lesions, the mean sensitivity, specificity, PPV, NPV, and accuracy of the diagnostic algorithm were 86.7, 48.0, 94.4, 26.7, and 83.2%, respectively. Furthermore, in the differential diagnosis of undifferentiated adenocarcinoma from differentiated adenocarcinoma, the mean sensitivity, specificity, PPV, NPV, and accuracy of the diagnostic algorithm were 61.6, 86.3, 69.0, 84.8, and 79.1%, respectively. For the ME-NBI final diagnosis using this algorithm, the mean κ values for inter- and intra-observer agreement were 0.50 and 0.77, respectively. In conclusion, the diagnostic algorithm based on ME-NBI microvascular findings was convenient and had high diagnostic accuracy, reliability and reproducibility in the differential diagnosis of depressed gastric lesions. PMID:24649321

Quantized Average Consensus on Gossip Digraphs with Reduced Computation

NASA Astrophysics Data System (ADS)

Cai, Kai; Ishii, Hideaki

The authors have recently proposed a class of randomized gossip algorithms which solve the distributed averaging problem on directed graphs, with the constraint that each node has an integer-valued state. The essence of this algorithm is to maintain local records, called “surplus”, of individual state updates, thereby achieving quantized average consensus even though the state sum of all nodes is not preserved. In this paper we study a modified version of this algorithm, whose feature is primarily in reducing both computation and communication effort. Concretely, each node needs to update fewer local variables, and can transmit surplus by requiring only one bit. Under this modified algorithm we prove that reaching the average is ensured for arbitrary strongly connected graphs. The condition of arbitrary strong connection is less restrictive than those known in the literature for either real-valued or quantized states; in particular, it does not require the special structure on the network called balanced. Finally, we provide numerical examples to illustrate the convergence result, with emphasis on convergence time analysis.

Consensus-based recommendations for the management of juvenile dermatomyositis.

PubMed

Enders, Felicitas Bellutti; Bader-Meunier, Brigitte; Baildam, Eileen; Constantin, Tamas; Dolezalova, Pavla; Feldman, Brian M; Lahdenne, Pekka; Magnusson, Bo; Nistala, Kiran; Ozen, Seza; Pilkington, Clarissa; Ravelli, Angelo; Russo, Ricardo; Uziel, Yosef; van Brussel, Marco; van der Net, Janjaap; Vastert, Sebastiaan; Wedderburn, Lucy R; Wulffraat, Nicolaas; McCann, Liza J; van Royen-Kerkhof, Annet

2017-02-01

In 2012, a European initiative called Single Hub and Access point for pediatric Rheumatology in Europe (SHARE) was launched to optimise and disseminate diagnostic and management regimens in Europe for children and young adults with rheumatic diseases. Juvenile dermatomyositis (JDM) is a rare disease within the group of paediatric rheumatic diseases (PRDs) and can lead to significant morbidity. Evidence-based guidelines are sparse and management is mostly based on physicians' experience. Consequently, treatment regimens differ throughout Europe. To provide recommendations for diagnosis and treatment of JDM. Recommendations were developed by an evidence-informed consensus process using the European League Against Rheumatism standard operating procedures. A committee was constituted, consisting of 19 experienced paediatric rheumatologists and 2 experts in paediatric exercise physiology and physical therapy, mainly from Europe. Recommendations derived from a validated systematic literature review were evaluated by an online survey and subsequently discussed at two consensus meetings using nominal group technique. Recommendations were accepted if >80% agreement was reached. In total, 7 overarching principles, 33 recommendations on diagnosis and 19 recommendations on therapy were accepted with >80% agreement among experts. Topics covered include assessment of skin, muscle and major organ involvement and suggested treatment pathways. The SHARE initiative aims to identify best practices for treatment of patients suffering from PRD. Within this remit, recommendations for the diagnosis and treatment of JDM have been formulated by an evidence-informed consensus process to produce a standard of care for patients with JDM throughout Europe. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Consensus-based recommendations for the management of uveitis associated with juvenile idiopathic arthritis: the SHARE initiative.

PubMed

Constantin, Tamas; Foeldvari, Ivan; Anton, Jordi; de Boer, Joke; Czitrom-Guillaume, Severine; Edelsten, Clive; Gepstein, Raz; Heiligenhaus, Arnd; Pilkington, Clarissa A; Simonini, Gabriele; Uziel, Yosef; Vastert, Sebastian J; Wulffraat, Nico M; Haasnoot, Anne-Mieke; Walscheid, Karoline; Pálinkás, Annamária; Pattani, Reshma; Györgyi, Zoltán; Kozma, Richárd; Boom, Victor; Ponyi, Andrea; Ravelli, Angelo; Ramanan, Athimalaipet V

2018-03-28

In 2012, a European initiative called S ingle Hub and Access point for pediatric Rheumatology in Europe (SHARE) was launched to optimise and disseminate diagnostic and management regimens in Europe for children and young adults with rheumatic diseases. Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children and uveitis is possibly its most devastating extra-articular manifestation. Evidence-based guidelines are sparse and management is mostly based on physicians' experience. Consequently, treatment practices differ widely, within and between nations. To provide recommendations for the diagnosis and treatment of JIA-associated uveitis. Recommendations were developed by an evidence-informed consensus process using the European League Against Rheumatism standard operating procedures. A committee was constituted, consisting of nine experienced paediatric rheumatologists and three experts in ophthalmology from Europe. Recommendations derived from a validated systematic literature review were evaluated by an Expert Committee and subsequently discussed at two consensus meetings using nominal group techniques. Recommendations were accepted if >80% agreement was reached (including all three ophthalmologists). In total, 22 recommendations were accepted (with >80% agreement among experts): 3 on diagnosis, 5 on disease activity measurements, 12 on treatment and 2 on future recommendations. The SHARE initiative aims to identify best practices for treatment of patients suffering from JIA-associated uveitis. Within this remit, recommendations for the diagnosis and treatment of JIA-associated uveitis have been formulated by an evidence-informed consensus process to suggest a standard of care for JIA-associated uveitis patients throughout Europe. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A smartphone-based pain management app for adolescents with cancer: establishing system requirements and a pain care algorithm based on literature review, interviews, and consensus.

PubMed

Jibb, Lindsay A; Stevens, Bonnie J; Nathan, Paul C; Seto, Emily; Cafazzo, Joseph A; Stinson, Jennifer N

2014-03-19

Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required. To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer. A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app. The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the functional requirements of the app. These results were used to build a detailed prototype algorithm capable of providing adolescents with pain management support based on their individual pain. Analysis of qualitative interviews with 9 multidisciplinary health care professionals and 10 adolescents resulted in 4 themes that helped to adapt the algorithm and requirements to the needs of adolescents. Specifically, themes were overall endorsement of the system, the need for a clinical expert, the need to individualize the system, and changes to the algorithm to improve potential clinical effectiveness. This study used a phased and user-centered approach to develop a pain management algorithm for adolescents with cancer and the system requirements of an associated app. The smartphone software is currently being created and subsequent work will focus on the usability, feasibility, and effectiveness testing of the app for adolescents with cancer pain.

A Smartphone-Based Pain Management App for Adolescents With Cancer: Establishing System Requirements and a Pain Care Algorithm Based on Literature Review, Interviews, and Consensus

PubMed Central

Stevens, Bonnie J; Nathan, Paul C; Seto, Emily; Cafazzo, Joseph A; Stinson, Jennifer N

2014-01-01

Background Pain that occurs both within and outside of the hospital setting is a common and distressing problem for adolescents with cancer. The use of smartphone technology may facilitate rapid, in-the-moment pain support for this population. To ensure the best possible pain management advice is given, evidence-based and expert-vetted care algorithms and system design features, which are designed using user-centered methods, are required. Objective To develop the decision algorithm and system requirements that will inform the pain management advice provided by a real-time smartphone-based pain management app for adolescents with cancer. Methods A systematic approach to algorithm development and system design was utilized. Initially, a comprehensive literature review was undertaken to understand the current body of knowledge pertaining to pediatric cancer pain management. A user-centered approach to development was used as the results of the review were disseminated to 15 international experts (clinicians, scientists, and a consumer) in pediatric pain, pediatric oncology and mHealth design, who participated in a 2-day consensus conference. This conference used nominal group technique to develop consensus on important pain inputs, pain management advice, and system design requirements. Using data generated at the conference, a prototype algorithm was developed. Iterative qualitative testing was conducted with adolescents with cancer, as well as pediatric oncology and pain health care providers to vet and refine the developed algorithm and system requirements for the real-time smartphone app. Results The systematic literature review established the current state of research related to nonpharmacological pediatric cancer pain management. The 2-day consensus conference established which clinically important pain inputs by adolescents would require action (pain management advice) from the app, the appropriate advice the app should provide to adolescents in pain, and the functional requirements of the app. These results were used to build a detailed prototype algorithm capable of providing adolescents with pain management support based on their individual pain. Analysis of qualitative interviews with 9 multidisciplinary health care professionals and 10 adolescents resulted in 4 themes that helped to adapt the algorithm and requirements to the needs of adolescents. Specifically, themes were overall endorsement of the system, the need for a clinical expert, the need to individualize the system, and changes to the algorithm to improve potential clinical effectiveness. Conclusions This study used a phased and user-centered approach to develop a pain management algorithm for adolescents with cancer and the system requirements of an associated app. The smartphone software is currently being created and subsequent work will focus on the usability, feasibility, and effectiveness testing of the app for adolescents with cancer pain. PMID:24646454

Breast cancer screening in the era of density notification legislation: summary of 2014 Massachusetts experience and suggestion of an evidence-based management algorithm by multi-disciplinary expert panel.

PubMed

Freer, Phoebe E; Slanetz, Priscilla J; Haas, Jennifer S; Tung, Nadine M; Hughes, Kevin S; Armstrong, Katrina; Semine, A Alan; Troyan, Susan L; Birdwell, Robyn L

2015-09-01

Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review, the Cochrane review, National Comprehensive Cancer Network guidelines, American Cancer Society recommendations, and American College of Radiology appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (<15% lifetime risk), do not routinely require supplemental screening per the expert consensus. Women of high risk (>20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman.

Computer-aided US diagnosis of breast lesions by using cell-based contour grouping.

PubMed

Cheng, Jie-Zhi; Chou, Yi-Hong; Huang, Chiun-Sheng; Chang, Yeun-Chung; Tiu, Chui-Mei; Chen, Kuei-Wu; Chen, Chung-Ming

2010-06-01

To develop a computer-aided diagnostic algorithm with automatic boundary delineation for differential diagnosis of benign and malignant breast lesions at ultrasonography (US) and investigate the effect of boundary quality on the performance of a computer-aided diagnostic algorithm. This was an institutional review board-approved retrospective study with waiver of informed consent. A cell-based contour grouping (CBCG) segmentation algorithm was used to delineate the lesion boundaries automatically. Seven morphologic features were extracted. The classifier was a logistic regression function. Five hundred twenty breast US scans were obtained from 520 subjects (age range, 15-89 years), including 275 benign (mean size, 15 mm; range, 5-35 mm) and 245 malignant (mean size, 18 mm; range, 8-29 mm) lesions. The newly developed computer-aided diagnostic algorithm was evaluated on the basis of boundary quality and differentiation performance. The segmentation algorithms and features in two conventional computer-aided diagnostic algorithms were used for comparative study. The CBCG-generated boundaries were shown to be comparable with the manually delineated boundaries. The area under the receiver operating characteristic curve (AUC) and differentiation accuracy were 0.968 +/- 0.010 and 93.1% +/- 0.7, respectively, for all 520 breast lesions. At the 5% significance level, the newly developed algorithm was shown to be superior to the use of the boundaries and features of the two conventional computer-aided diagnostic algorithms in terms of AUC (0.974 +/- 0.007 versus 0.890 +/- 0.008 and 0.788 +/- 0.024, respectively). The newly developed computer-aided diagnostic algorithm that used a CBCG segmentation method to measure boundaries achieved a high differentiation performance. Copyright RSNA, 2010

Diagnosis of Acute Cellular Rejection Using Probe-Based Confocal Laser Endomicroscopy in Lung Transplant Recipients: a Prospective, Multicenter Trial.

PubMed

Keller, Cesar A; Khoor, Andras; Arenberg, Douglas A; Smith, Michael A; Islam, Shaheen U

2018-05-29

Acute cellular rejection (ACR) in lung transplant recipients requires demonstration of perivascular lymphocytic infiltration in alveolar tissue samples from transbronchial biopsies (TBBs). Probe-based confocal laser endomicroscopy (pCLE) allows in vivo observation of alveolar, vascular, and cellular microstructures in the lung with potential to identify ACR. The objective of our prospective, blinded, multicenter observational study was to identify pCLE findings in patients with ACR diagnosed histopathologically by TBB. Lung transplant recipients undergoing diagnostic bronchoscopies within 1 year posttransplant for suspected ACR had pCLE video imaging obtained immediately prior to tissue sampling via TBB. Findings of 2 pCLE criteria, abundant alveolar cellularity and perivascular cellularity (PVC), were assessed by 4 investigators familiar with pCLE and compared to histopathologic criteria of ACR to derive sensitivity, specificity, area under the receiver operating characteristic curve, and accuracy. Interobserver agreement was assessed by calculating intraclass coefficient and Fleiss κ. Findings were analyzed before and after a consensus meeting of investigators on interpreting images. Thirty pCLE procedures were performed on 24 patients, 8 showing ACR in TBB. Diagnostic performance and interobserver agreement using pCLE to identify PVC were significantly higher than those of abundant alveolar cellularity (P<.01). The number of blood vessels identified with PVC on pCLE was significantly correlated with histopathologic activity grading of ACR (P<.01). PVC agreement among investigators significantly improved after consensus meeting (P<.01) CONCLUSIONS: When found on pCLE, PVC is a feasible and reproducible criterion for assessment of ACR in vivo, but there is a learning curve for image interpretation.

Diagnostic Performance of a Novel Coronary CT Angiography Algorithm: Prospective Multicenter Validation of an Intracycle CT Motion Correction Algorithm for Diagnostic Accuracy.

PubMed

Andreini, Daniele; Lin, Fay Y; Rizvi, Asim; Cho, Iksung; Heo, Ran; Pontone, Gianluca; Bartorelli, Antonio L; Mushtaq, Saima; Villines, Todd C; Carrascosa, Patricia; Choi, Byoung Wook; Bloom, Stephen; Wei, Han; Xing, Yan; Gebow, Dan; Gransar, Heidi; Chang, Hyuk-Jae; Leipsic, Jonathon; Min, James K

2018-06-01

Motion artifact can reduce the diagnostic accuracy of coronary CT angiography (CCTA) for coronary artery disease (CAD). The purpose of this study was to compare the diagnostic performance of an algorithm dedicated to correcting coronary motion artifact with the performance of standard reconstruction methods in a prospective international multicenter study. Patients referred for clinically indicated invasive coronary angiography (ICA) for suspected CAD prospectively underwent an investigational CCTA examination free from heart rate-lowering medications before they underwent ICA. Blinded core laboratory interpretations of motion-corrected and standard reconstructions for obstructive CAD (≥ 50% stenosis) were compared with ICA findings. Segments unevaluable owing to artifact were considered obstructive. The primary endpoint was per-subject diagnostic accuracy of the intracycle motion correction algorithm for obstructive CAD found at ICA. Among 230 patients who underwent CCTA with the motion correction algorithm and standard reconstruction, 92 (40.0%) had obstructive CAD on the basis of ICA findings. At a mean heart rate of 68.0 ± 11.7 beats/min, the motion correction algorithm reduced the number of nondiagnostic scans compared with standard reconstruction (20.4% vs 34.8%; p < 0.001). Diagnostic accuracy for obstructive CAD with the motion correction algorithm (62%; 95% CI, 56-68%) was not significantly different from that of standard reconstruction on a per-subject basis (59%; 95% CI, 53-66%; p = 0.28) but was superior on a per-vessel basis: 77% (95% CI, 74-80%) versus 72% (95% CI, 69-75%) (p = 0.02). The motion correction algorithm was superior in subgroups of patients with severely obstructive (≥ 70%) stenosis, heart rate ≥ 70 beats/min, and vessels in the atrioventricular groove. The motion correction algorithm studied reduces artifacts and improves diagnostic performance for obstructive CAD on a per-vessel basis and in selected subgroups on a per-subject basis.

Fitting-free algorithm for efficient quantification of collagen fiber alignment in SHG imaging applications.

PubMed

Hall, Gunnsteinn; Liang, Wenxuan; Li, Xingde

2017-10-01

Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.

An effective non-rigid registration approach for ultrasound image based on "demons" algorithm.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong; Tian, Jiawei

2013-06-01

Medical image registration is an important component of computer-aided diagnosis system in diagnostics, therapy planning, and guidance of surgery. Because of its low signal/noise ratio (SNR), ultrasound (US) image registration is a difficult task. In this paper, a fully automatic non-rigid image registration algorithm based on demons algorithm is proposed for registration of ultrasound images. In the proposed method, an "inertia force" derived from the local motion trend of pixels in a Moore neighborhood system is produced and integrated into optical flow equation to estimate the demons force, which is helpful to handle the speckle noise and preserve the geometric continuity of US images. In the experiment, a series of US images and several similarity measure metrics are utilized for evaluating the performance. The experimental results demonstrate that the proposed method can register ultrasound images efficiently, robust to noise, quickly and automatically.

Use of the National Institutes of Health Consensus Guidelines Improves the Diagnostic Sensitivity of Gastrointestinal Graft-Versus-Host Disease.

PubMed

Cardona, Diana M; Detweiler, Claire J; Shealy, Michael J; Sung, Anthony D; Wild, Daniel M; Poleski, Martin H; Balmadrid, Bryan L; Cirrincione, Constance T; Howell, David N; Sullivan, Keith M

2018-04-26

- Graft-versus-host disease of the gastrointestinal tract is a common complication of hematopoietic stem cell transplant associated with significant morbidity and mortality. Accurate diagnosis can be difficult and is a truly clinicopathologic endeavor. - To assess the diagnostic sensitivity of gastrointestinal graft-versus-host disease using the 2015 National Institutes of Health (NIH) histology consensus guidelines and to analyze histologic findings that support the guidelines. - Patients with allogeneic hematopoietic stem cell transplants were identified via a retrospective search of our electronic medical record from January 1, 2005, to January 1, 2011. Endoscopies with available histology were reviewed by 2 pathologists using the 2015 NIH guidelines. The clinical diagnosis was used as the gold standard. A nontransplant set of endoscopic biopsies was used as a control. - Of the 250 total endoscopies, 217 (87%) had a clinical diagnosis of gastrointestinal graft-versus-host disease. Use of the NIH consensus guidelines showed a sensitivity of 86% and a specificity of 65%. Thirty-seven of 58 (64%) cases with an initial false-negative histopathologic diagnosis were diagnosed as graft-versus-host disease on our review. - Use of the NIH histology consensus guidelines results in a high sensitivity and specificity, thereby decreasing false-negatives. Additionally, use of the NIH guidelines aids in creating uniformity and diagnostic clarity. Correlation with clinical and laboratory findings is critical in evaluating the differential diagnosis and to avoid false-positives. As expected, increased apoptosis with decreased inflammation was associated with a pathologic diagnosis of graft-versus-host disease and supports the NIH guidelines.

Using qualitative research to inform development of a diagnostic algorithm for UTI in children.

PubMed

de Salis, Isabel; Whiting, Penny; Sterne, Jonathan A C; Hay, Alastair D

2013-06-01

Diagnostic and prognostic algorithms can help reduce clinical uncertainty. The selection of candidate symptoms and signs to be measured in case report forms (CRFs) for potential inclusion in diagnostic algorithms needs to be comprehensive, clearly formulated and relevant for end users. To investigate whether qualitative methods could assist in designing CRFs in research developing diagnostic algorithms. Specifically, the study sought to establish whether qualitative methods could have assisted in designing the CRF for the Health Technology Association funded Diagnosis of Urinary Tract infection in Young children (DUTY) study, which will develop a diagnostic algorithm to improve recognition of urinary tract infection (UTI) in children aged <5 years presenting acutely unwell to primary care. Qualitative methods were applied using semi-structured interviews of 30 UK doctors and nurses working with young children in primary care and a Children's Emergency Department. We elicited features that clinicians believed useful in diagnosing UTI and compared these for presence or absence and terminology with the DUTY CRF. Despite much agreement between clinicians' accounts and the DUTY CRFs, we identified a small number of potentially important symptoms and signs not included in the CRF and some included items that could have been reworded to improve understanding and final data analysis. This study uniquely demonstrates the role of qualitative methods in the design and content of CRFs used for developing diagnostic (and prognostic) algorithms. Research groups developing such algorithms should consider using qualitative methods to inform the selection and wording of candidate symptoms and signs.

Development of an On-board Failure Diagnostics and Prognostics System for Solid Rocket Booster

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.; Osipov, Vyatcheslav V.; Timucin, Dogan A.; Uckun, Serdar

2009-01-01

We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.

Geriatric Assessment-Guided Care Processes for Older Adults: A Delphi Consensus of Geriatric Oncology Experts.

PubMed

Mohile, Supriya Gupta; Velarde, Carla; Hurria, Arti; Magnuson, Allison; Lowenstein, Lisa; Pandya, Chintan; O'Donovan, Anita; Gorawara-Bhat, Rita; Dale, William

2015-09-01

Structured care processes that provide a framework for how oncologists can incorporate geriatric assessment (GA) into clinical practice could improve outcomes for vulnerable older adults with cancer, a growing population at high risk of toxicity from cancer treatment. We sought to obtain consensus from an expert panel on the use of GA in clinical practice and to develop algorithms of GA-guided care processes. The Delphi technique, a well-recognized structured and reiterative process to reach consensus, was used. Participants were geriatric oncology experts who attended NIH-funded U13 or Cancer and Aging Research Group conferences. Consensus was defined as an interquartile range of 2 or more units, or 66.7% or greater, selecting a utility/helpfulness rating of 7 or greater on a 10-point Likert scale. For nominal data, consensus was defined as agreement among 66.7% or more of the group. From 33 invited, 30 participants completed all 3 rounds. Most experts (75%) used GA in clinical care, and the remainder were involved in geriatric oncology research. The panel met consensus that "all patients aged 75 years or older and those who are younger with age-related health concerns" should undergo GA and that all domains (function, physical performance, comorbidity/polypharmacy, cognition, nutrition, psychological status, and social support) should be included. Consensus was met for how GA could guide nononcologic interventions and cancer treatment decisions. Algorithms for GA-guided care processes were developed. This Delphi investigation of geriatric oncology experts demonstrated that GA should be performed for older patients with cancer to guide care processes. Copyright © 2015 by the National Comprehensive Cancer Network.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD without ID: A Multi-Site Study

ERIC Educational Resources Information Center

Pugliese, Cara E.; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L.; Yerys, Benjamin E.; Maddox, Brenna B.; White, Susan W.; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D.; Schultz, Robert T.; Martin, Alex; Anthony, Laura Gutermuth

2015-01-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised…

Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.

PubMed

Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia; Huaipin Zhang; Dong Yue; Wei Zhao; Songlin Hu; Chunxia Dou; Hu, Songlin; Zhang, Huaipin; Dou, Chunxia; Yue, Dong; Zhao, Wei

2018-06-01

This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

Consensus Report on Impulsive Aggression as a Symptom across Diagnostic Categories in Child Psychiatry: Implications for Medication Studies

ERIC Educational Resources Information Center

Jensen, Peter S.; Youngstrom, Eric A.; Steiner, Hans; Findling, Robert L.; Meyer, Roger E.; Malone, Richard P.; Carlson, Gabrielle A.; Coccaro, Emil F.; Aman, Michael G.; Blair, James; Dougherty, Donald; Ferris, Craig; Flynn, Laurie; Green, Evelyn; Hoagwood, Kimberly; Hutchinson, Janice; Laughren, Tom; Leve, Leslie D.; Novins, Douglas K.; Vitiello, Benedetto

2007-01-01

Objective: To determine whether impulsive aggression (IA) is a meaningful clinical construct and to ascertain whether it is sufficiently similar across diagnostic categories, such that parallel studies across disorders might constitute appropriate evidence for pursuing indications. If so, how should IA be assessed, pharmacological studies…

Assessment of a Revised Management Strategy for Patients With Intraductal Papillary Mucinous Neoplasms Involving the Main Pancreatic Duct.

PubMed

Sugimoto, Motokazu; Elliott, Irmina A; Nguyen, Andrew H; Kim, Stephen; Muthusamy, V Raman; Watson, Rabindra; Hines, O Joe; Dawson, David W; Reber, Howard A; Donahue, Timothy R

2017-01-18

According to the 2012 International Consensus Guidelines, the diagnostic criterion of intraductal papillary mucinous neoplasms (IPMNs) involving the main duct (MD IPMNs) or the main and branch ducts (mixed IPMNs) of the pancreatic system is a main pancreatic duct (MPD) diameter of 5.0 mm or greater on computed tomography (CT) or magnetic resonance imaging (MRI). However, surgical resection is recommended for patients with an MPD diameter of 10.0 mm or greater, which is characterized as a high-risk stigma. An MPD diameter of 5.0 to 9.0 mm is not an indication for immediate resection. To determine an appropriate cutoff (ie, one with high sensitivity and negative predictive value) of the MPD diameter on CT or MRI as a prognostic factor for malignant disease and to propose a new management algorithm for patients with MD or mixed IPMNs. This retrospective cohort study included 103 patients who underwent surgical resection for a preoperative diagnosis of MD or mixed IPMN and in whom IPMN was confirmed by surgical pathologic findings at a single institution from July 1, 1996, to December 31, 2015. Malignant disease was defined as high-grade dysplasia or invasive adenocarcinoma on results of surgical pathologic evaluation. An appropriate MPD diameter on preoperative CT or MRI to predict malignant disease was determined using a receiver operating characteristic curve analysis. The prognostic value of the new management algorithm that incorporated the new MPD diameter cutoff was evaluated. Among the 103 patients undergoing resection for an MD or mixed IPMN (59 men [57.3%]; 44 women [42.7%]; median [range] age, 71 [48-86] years), 64 (62.1%) had malignant disease. Diagnostic accuracy for malignant neoplasms was highest at an MPD diameter cutoff of 7.2 mm (area under the receiver operating characteristic curve, 0.70; 95% CI, 0.59-0.81). An MPD diameter of 7.2 mm or greater was also an independent prognostic factor for malignant neoplasms (odds ratio, 12.76; 95% CI, 2.43-66.88; P = .003) on logistic regression analysis after controlling for preoperative variables. The new management algorithm, which included an MPD diameter of 7.2 mm or greater as one of the high-risk stigmata, had a higher sensitivity (100%), negative predictive value (100%), and accuracy (66%) for malignant disease than the 2012 version of the International Consensus Guidelines (95%, 57%, and 63%, respectively). In this single-center, retrospective analysis, an MPD diameter of 7.2 mm was identified as an optimal cutoff for a prognostic factor for malignant disease in MD or mixed IPMN. These data support lowering the accepted criteria for MPD diameter when selecting patients for resection vs surveillance so as not to overlook cancer in IPMN.

Diagnostic reproducibility of hydatidiform moles: ancillary techniques (p57 immunohistochemistry and molecular genotyping) improve morphologic diagnosis.

PubMed

Vang, Russell; Gupta, Mamta; Wu, Lee-Shu-Fune; Yemelyanova, Anna V; Kurman, Robert J; Murphy, Kathleen M; Descipio, Cheryl; Ronnett, Brigitte M

2012-03-01

Distinction of hydatidiform moles (HMs) from nonmolar specimens (NMs) and subclassification of HMs as complete hydatidiform moles (CHMs) and partial hydatidiform moles (PHMs) are important for clinical practice and investigational studies; yet, diagnosis based solely on morphology is affected by interobserver variability. Molecular genotyping can distinguish these entities by discerning androgenetic diploidy, diandric triploidy, and biparental diploidy to diagnose CHMs, PHMs, and NMs, respectively. Eighty genotyped cases (27 CHMs, 27 PHMs, and 26 NMs) were selected from a series of 200 potentially molar specimens previously diagnosed using p57 immunostaining and genotyping. Cases were classified by 3 gynecologic pathologists on the basis of H&E slides (masked to p57 immunostaining and genotyping results) into 1 of 3 categories (CHM, PHM, or NM) during 2 diagnostic rounds; a third round incorporating p57 immunostaining results was also conducted. Consensus diagnoses (those rendered by 2 of 3 pathologists) were determined. Genotyping results were used as the gold standard for assessing diagnostic performance. Sensitivity of a diagnosis of CHM ranged from 59% to 100% for individual pathologists and from 70% to 81% by consensus; specificity ranged from 91% to 96% for individuals and from 94% to 98% by consensus. Sensitivity of a diagnosis of PHM ranged from 56% to 93% for individual pathologists and from 70% to 78% by consensus; specificity ranged from 58% to 92% for individuals and from 74% to 85% by consensus. The percentage of correct classification of all cases by morphology ranged from 55% to 75% for individual pathologists and from 70% to 75% by consensus. The κ values for interobserver agreement ranged from 0.59 to 0.73 (moderate to good) for a diagnosis of CHM, from 0.15 to 0.43 (poor to moderate) for PHM, and from 0.13 to 0.42 (poor to moderate) for NM. The κ values for intraobserver agreement ranged from 0.44 to 0.67 (moderate to good). Addition of the p57 immunostain improved sensitivity of a diagnosis of CHM to a range of 93% to 96% for individual pathologists and 96% by consensus; specificity was improved from a range of 96% to 98% for individual pathologists and 96% by consensus; there was no substantial impact on diagnosis of PHMs and NMs. Interobserver agreement for interpretation of the p57 immunostain was 0.96 (almost perfect). Even with morphologic assessment by gynecologic pathologists and p57 immunohistochemistry, 20% to 30% of cases will be misclassified, and, in particular, distinction of PHMs and NMs will remain problematic.

Constrained dynamics approach for motion synchronization and consensus

NASA Astrophysics Data System (ADS)

Bhatia, Divya

In this research we propose to develop constrained dynamical systems based stable attitude synchronization, consensus and tracking (SCT) control laws for the formation of rigid bodies. The generalized constrained dynamics Equations of Motion (EOM) are developed utilizing constraint potential energy functions that enforce communication constraints. Euler-Lagrange equations are employed to develop the non-linear constrained dynamics of multiple vehicle systems. The constraint potential energy is synthesized based on a graph theoretic formulation of the vehicle-vehicle communication. Constraint stabilization is achieved via Baumgarte's method. The performance of these constrained dynamics based formations is evaluated for bounded control authority. The above method has been applied to various cases and the results have been obtained using MATLAB simulations showing stability, synchronization, consensus and tracking of formations. The first case corresponds to an N-pendulum formation without external disturbances, in which the springs and the dampers connected between the pendulums act as the communication constraints. The damper helps in stabilizing the system by damping the motion whereas the spring acts as a communication link relaying relative position information between two connected pendulums. Lyapunov stabilization (energy based stabilization) technique is employed to depict the attitude stabilization and boundedness. Various scenarios involving different values of springs and dampers are simulated and studied. Motivated by the first case study, we study the formation of N 2-link robotic manipulators. The governing EOM for this system is derived using Euler-Lagrange equations. A generalized set of communication constraints are developed for this system using graph theory. The constraints are stabilized using Baumgarte's techniques. The attitude SCT is established for this system and the results are shown for the special case of three 2-link robotic manipulators. These methods are then applied to the formation of N-spacecraft. Modified Rodrigues Parameters (MRP) are used for attitude representation of the spacecraft because of their advantage of being a minimum parameter representation. Constrained non-linear equations of motion for this system are developed and stabilized using a Proportional-Derivative (PD) controller derived based on Baumgarte's method. A system of 3 spacecraft is simulated and the results for SCT are shown and analyzed. Another problem studied in this research is that of maintaining SCT under unknown external disturbances. We use an adaptive control algorithm to derive control laws for the actuator torques and develop an estimation law for the unknown disturbance parameters to achieve SCT. The estimate of the disturbance is added as a feed forward term in the actual control law to obtain the stabilization of a 3-spacecraft formation. The disturbance estimates are generated via a Lyapunov analysis of the closed loop system. In summary, the constrained dynamics method shows a lot of potential in formation control, achieving stabilization, synchronization, consensus and tracking of a set of dynamical systems.

Getting It Right the First Time: Defining Regionally Relevant Training Curricula and Provider Core Competencies for Point-of-Care Ultrasound Education on the African Continent.

PubMed

Salmon, Margaret; Landes, Megan; Hunchak, Cheryl; Paluku, Justin; Malemo Kalisya, Luc; Salmon, Christian; Muller, Mundenga Mutendi; Wachira, Benjamin; Mangan, James; Chhaganlal, Kajal; Kalanzi, Joseph; Azazh, Aklilu; Berman, Sara; Zied, El-Sayed; Lamprecht, Hein

2017-02-01

Significant evidence identifies point-of-care ultrasound (PoCUS) as an important diagnostic and therapeutic tool in resource-limited settings. Despite this evidence, local health care providers on the African continent continue to have limited access to and use of ultrasound, even in potentially high-impact fields such as obstetrics and trauma. Dedicated postgraduate emergency medicine residency training programs now exist in 8 countries, yet no current consensus exists in regard to core PoCUS competencies. The current practice of transferring resource-rich PoCUS curricula and delivery methods to resource-limited health systems fails to acknowledge the unique challenges, needs, and disease burdens of recipient systems. As emergency medicine leaders from 8 African countries, we introduce a practical algorithmic approach, based on the local epidemiology and resource constraints, to curriculum development and implementation. We describe an organizational structure composed of nexus learning centers for PoCUS learners and champions on the continent to keep credentialing rigorous and standardized. Finally, we put forth 5 key strategic considerations: to link training programs to hospital systems, to prioritize longitudinal learning models, to share resources to promote health equity, to maximize access, and to develop a regional consensus on training standards and credentialing. Copyright © 2016 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Unnecessary overuse. Study of "inadvisable practices" for patients with atrial fibrillation.

PubMed

Ortiz, M M; Llamas, P; Sanmartín, M; Egido, J A; Del Toro, J; Egocheaga, M I; Estévez, M S; Navarro, I M; Mira, J J

2017-05-01

To identify overuse (diagnostic, therapeutic and self-care practices that represent risks that outweigh the potential benefits) in patients with atrial fibrillation. The study was based on qualitative research techniques. Using the "Metaplan" technique, we identified and ordered potentially inappropriate, ineffective and inefficient practices. By means of a consensus conference, we then established a number of "inadvisable practice" measures (relatively common practices that should be eliminated based on the scientific evidence or clinical experience). Professionals from the specialties of cardiology, haematology, neurology, internal medicine, family medicine and nursing participated in the consensus. We developed a catalogue of 19 "inadvisable practices" related to the diagnosis, treatment and care of anticoagulated patients that were inappropriate, had questionable effectiveness or were ineffective, as well as 13 beliefs or behaviours for anticoagulated patients that could result in injury or were useless or inefficient. The "inadvisable practices" approach helps identify practices that represent greater risks than benefits for patients. It seems appropriate to include algorithms in the clinical decision-making support systems that consider this information for the diagnosis, treatment and for home care. For this last case, recommendations have also been prepared that define specific contents for the healthcare education of these patients. Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Treatment algorithm for anal fissure. Consensus document of the Spanish Association of Coloproctology and the Coloproctology Division of the Spanish Association of Surgeons.

PubMed

Arroyo, Antonio; Montes, Elisa; Calderón, Teresa; Blesa, Isabel; Elía, Manuela; Salgado, Gervasio; García-Armengol, Juan; de-la-Portilla, Fernando

2018-03-08

The Spanish Association of Coloproctology and the Coloproctology Division of the Spanish Association of Surgeons propose this consensus document with a treatment algorithm for anal fissure that could be used for decision making. Non-surgical therapy and surgical treatment of anal fissure are explained, and the recommended algorithm is provided. The methodology used was: creation of a group of experts; search in PubMed, MEDLINE and the Cochrane Library for publications from the last 10 years about anal fissure; presentation at the 21st National Meeting of the Spanish Association of Coloproctology Foundation 2017 with voting for/against each conclusion by the attendees and review by the scientific committee of the Spanish Association of Coloproctology. Copyright © 2018 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

Abdominal compartment syndrome--the prevention and treatment of possible lethal complications following hip arthroscopy: a case report.

PubMed

Ciemniewska-Gorzela, Kinga; Piontek, Tomasz; Szulc, Andrzej

2014-11-14

Intra-abdominal hypertension and abdominal compartment syndrome have been increasingly recognized as a hip arthroscopy complication over the past decade. In the absence of consensus definitions and treatment guidelines, the diagnosis and management of intra-abdominal hypertension and abdominal compartment syndrome remains variable from institution to institution. We report the occurrence of the extravasation of fluid into the abdomen during arthroscopic treatment of femoroacetabular impingement combined with resection of trochanteric bursa and our management of the condition in a 55-year old Caucasian woman. We present an algorithm of treatment of abdominal compartment syndrome, as a hip arthroscopy complication, according to the consensus definitions and recommendations of the World Society of the Abdominal Compartment Syndrome. In the algorithm options, we have included paracentesis and percutaneous catheter decompression as the main point of treatment. Our algorithm will have a broader clinical impact on orthopedic surgery, anesthesiology and emergency medicine.

Using MOEA with Redistribution and Consensus Branches to Infer Phylogenies.

PubMed

Min, Xiaoping; Zhang, Mouzhao; Yuan, Sisi; Ge, Shengxiang; Liu, Xiangrong; Zeng, Xiangxiang; Xia, Ningshao

2017-12-26

In recent years, to infer phylogenies, which are NP-hard problems, more and more research has focused on using metaheuristics. Maximum Parsimony and Maximum Likelihood are two effective ways to conduct inference. Based on these methods, which can also be considered as the optimal criteria for phylogenies, various kinds of multi-objective metaheuristics have been used to reconstruct phylogenies. However, combining these two time-consuming methods results in those multi-objective metaheuristics being slower than a single objective. Therefore, we propose a novel, multi-objective optimization algorithm, MOEA-RC, to accelerate the processes of rebuilding phylogenies using structural information of elites in current populations. We compare MOEA-RC with two representative multi-objective algorithms, MOEA/D and NAGA-II, and a non-consensus version of MOEA-RC on three real-world datasets. The result is, within a given number of iterations, MOEA-RC achieves better solutions than the other algorithms.

Best practices recommendations in the application of immunohistochemistry in testicular tumors: report from the International Society of Urological Pathology consensus conference.

PubMed

Ulbright, Thomas M; Tickoo, Satish K; Berney, Daniel M; Srigley, John R

2014-08-01

The judicious use of immunostains can be of significant diagnostic assistance in the interpretation of testicular neoplasms when the light microscopic features are ambiguous. A limited differential diagnosis by traditional morphology is required for the effective use of immunohistochemistry (IHC); otherwise, the inevitable occurrence of exceptions to anticipated patterns will lead to "immunoconfusion." The diagnosis of tumors in the germ cell lineage, the great majority of primary tumors of the testis, has been considerably facilitated over the past decade by IHC directed at developmentally important nuclear transcription factors, including OCT4, SALL4, SOX2, and SOX17, that are mostly restricted to certain tumor histotypes. In conjunction with other markers, a specific diagnosis can be achieved in most instances through a panel of 3 or 4 immunostains and often fewer. IHC among tumors in the sex cord-stromal group may produce a significant proportion of false-negative cases until more sensitive and equally specific markers are validated. The negativity of these tumors for the IHC stains used for germ cell tumors is key in the important distinction of neoplasms in these 2 general categories. In this review, the International Society of Urological Pathologists (ISUP) provides diagnostic guidelines in the form of algorithms to assist practicing pathologists confronting a differential diagnostic question concerning a testicular neoplasm. The goal of ISUP is to anticipate commonly encountered differential diagnoses and recommend an efficient and limited pattern of IHC stains to resolve the question.

Core Needle Biopsy of the Thyroid: 2016 Consensus Statement and Recommendations from Korean Society of Thyroid Radiology

PubMed Central

Na, Dong Gyu; Jung, So Lyung; Kim, Ji-hoon; Sung, Jin Yong; Kim, Kyu Sun; Lee, Jeong Hyun; Shin, Jung Hee; Choi, Yoon Jung; Ha, Eun Ju; Lim, Hyun Kyung; Kim, Soo Jin; Hahn, Soo Yeon; Lee, Kwang Hwi; Choi, Young Jun; Youn, Inyoung; Kim, Young Joong; Ahn, Hye Shin; Ryu, Ji Hwa; Baek, Seon Mi; Sim, Jung Suk; Jung, Chan Kwon; Lee, Joon Hyung

2017-01-01

Core needle biopsy (CNB) has been suggested as a complementary diagnostic method to fine-needle aspiration in patients with thyroid nodules. Many recent CNB studies have suggested a more advanced role for CNB, but there are still no guidelines on its use. Therefore, the Task Force Committee of the Korean Society of Thyroid Radiology has developed the present consensus statement and recommendations for the role of CNB in the diagnosis of thyroid nodules. These recommendations are based on evidence from the current literature and expert consensus. PMID:28096731

Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes.

PubMed

Lomsadze, Alexandre; Gemayel, Karl; Tang, Shiyuyun; Borodovsky, Mark

2018-05-17

In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts. © 2018 Lomsadze et al.; Published by Cold Spring Harbor Laboratory Press.

Diagnostic Utility of the ADI-R and DSM-5 in the Assessment of Latino Children and Adolescents.

PubMed

Magaña, Sandy; Vanegas, Sandra B

2017-05-01

Latino children in the US are systematically underdiagnosed with Autism Spectrum Disorder (ASD); therefore, it is important that recent changes to the diagnostic process do not exacerbate this pattern of under-identification. Previous research has found that the Autism Diagnostic Interview-Revised (ADI-R) algorithm, based on the Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition, Text Revision (DSM-IV-TR), has limitations with Latino children of Spanish speaking parents. We evaluated whether an ADI-R algorithm based on the new DSM-5 classification for ASD would be more sensitive in identifying Latino children of Spanish speaking parents who have a clinical diagnosis of ASD. Findings suggest that the DSM-5 algorithm shows better sensitivity than the DSM-IV-TR algorithm for Latino children.

[SECOT consensus on medial femorotibial osteoarthritis].

PubMed

Moreno, A; Silvestre, A; Carpintero, P

2013-01-01

A consensus, prepared by SECOT, is presented on the management of medial knee compartment osteoarthritis, in order to establish clinical criteria and recommendations directed at unifying the criteria in its management, dealing with the factors involved in the pathogenesis of medial femorotibial knee osteoarthritis, the usefulness of diagnostic imaging techniques, and the usefulness of arthroscopy. Conservative and surgical treatments are also analysed. The experts consulted showed a consensus (agreed or disagreed) in 65.8% of the items considered, leaving 14items where no consensus was found, which included the aetiopathogenesis of the osteoarthritis, the value of NMR in degenerative disease, the usefulness of COX-2 and the chondroprotective drugs, as well as on the ideal valgus tibial osteotomy technique. © 2013 SECOT. Published by Elsevier Espana. All rights reserved.

Development and evaluation of consensus-based sediment effect concentrations for polychlorinated biphenyls

USGS Publications Warehouse

MacDonald, Donald D.; Dipinto, Lisa M.; Field, Jay; Ingersoll, Christopher G.; Long, Edward R.; Swartz, Richard C.

2000-01-01

Sediment-quality guidelines (SQGs) have been published for polychlorinated biphenyls (PCBs) using both empirical and theoretical approaches. Empirically based guidelines have been developed using the screening-level concentration, effects range, effects level, and apparent effects threshold approaches. Theoretically based guidelines have been developed using the equilibrium-partitioning approach. Empirically-based guidelines were classified into three general categories, in accordance with their original narrative intents, and used to develop three consensus-based sediment effect concentrations (SECs) for total PCBs (tPCBs), including a threshold effect concentration, a midrange effect concentration, and an extreme effect concentration. Consensus-based SECs were derived because they estimate the central tendency of the published SQGs and, thus, reconcile the guidance values that have been derived using various approaches. Initially, consensus-based SECs for tPCBs were developed separately for freshwater sediments and for marine and estuarine sediments. Because the respective SECs were statistically similar, the underlying SQGs were subsequently merged and used to formulate more generally applicable SECs. The three consensus-based SECs were then evaluated for reliability using matching sediment chemistry and toxicity data from field studies, dose-response data from spiked-sediment toxicity tests, and SQGs derived from the equilibrium-partitioning approach. The results of this evaluation demonstrated that the consensus-based SECs can accurately predict both the presence and absence of toxicity in field-collected sediments. Importantly, the incidence of toxicity increases incrementally with increasing concentrations of tPCBs. Moreover, the consensus-based SECs are comparable to the chronic toxicity thresholds that have been estimated from dose-response data and equilibrium-partitioning models. Therefore, consensus-based SECs provide a unifying synthesis of existing SQGs, reflect causal rather than correlative effects, and accurately predict sediment toxicity in PCB-contaminated sediments.

The DSM-5: Hyperbole, Hope or Hypothesis?

PubMed Central

2013-01-01

The furore preceding the release of the new edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) is in contrast to the incremental changes to several diagnostic categories, which are derived from new research since its predecessor’s birth in 1990. While many of these changes are indeed controversial, they do reflect the intrinsic ambiguity of the extant literature. Additionally, this may be a mirror of the frustration of the field’s limited progress, especially given the false hopes at the dawn of the “decade of the brain”. In the absence of a coherent pathophysiology, the DSM remains no more than a set of consensus based operationalized adjectives, albeit with some degree of reliability. It does not cleave nature at its joints, nor does it aim to, but neither does alternate systems. The largest problem with the DSM system is how it’s used; sometimes too loosely by clinicians, and too rigidly by regulators, insurers, lawyers and at times researchers, who afford it reference and deference disproportionate to its overt acknowledged limitations. PMID:23672603

Comparison of dermatoscopic diagnostic algorithms based on calculation: The ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm in dermatoscopic evaluation of melanocytic lesions.

PubMed

Unlu, Ezgi; Akay, Bengu N; Erdem, Cengizhan

2014-07-01

Dermatoscopic analysis of melanocytic lesions using the CASH algorithm has rarely been described in the literature. The purpose of this study was to compare the sensitivity, specificity, and diagnostic accuracy rates of the ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist, and the CASH algorithm in the diagnosis and dermatoscopic evaluation of melanocytic lesions on the hairy skin. One hundred and fifteen melanocytic lesions of 115 patients were examined retrospectively using dermatoscopic images and compared with the histopathologic diagnosis. Four dermatoscopic algorithms were carried out for all lesions. The ABCD rule of dermatoscopy showed sensitivity of 91.6%, specificity of 60.4%, and diagnostic accuracy of 66.9%. The seven-point checklist showed sensitivity, specificity, and diagnostic accuracy of 87.5, 65.9, and 70.4%, respectively; the three-point checklist 79.1, 62.6, 66%; and the CASH algorithm 91.6, 64.8, and 70.4%, respectively. To our knowledge, this is the first study that compares the sensitivity, specificity and diagnostic accuracy of the ABCD rule of dermatoscopy, the three-point checklist, the seven-point checklist, and the CASH algorithm for the diagnosis of melanocytic lesions on the hairy skin. In our study, the ABCD rule of dermatoscopy and the CASH algorithm showed the highest sensitivity for the diagnosis of melanoma. © 2014 Japanese Dermatological Association.

Korean Medication Algorithm for Depressive Disorder: Comparisons with Other Treatment Guidelines

PubMed Central

Wang, Hee Ryung; Bahk, Won-Myong; Seo, Jeong Seok; Woo, Young Sup; Park, Young-Min; Jeong, Jong-Hyun; Kim, Won; Shim, Se-Hoon; Lee, Jung Goo; Jon, Duk-In; Min, Kyung Joon

2017-01-01

In this review, we compared recommendations from the Korean Medication Algorithm Project for Depressive Disorder 2017 (KMAP-DD 2017) to other global treatment guidelines for depression. Six global treatment guidelines were reviewed; among the six, 4 were evidence-based guidelines, 1 was an expert consensus-based guideline, and 1 was an amalgamation of both evidence and expert consensus-based recommendations. The recommendations in the KMAP-DD 2017 were generally similar to those in other global treatment guidelines, although there were some differences between the guidelines. The KMAP-DD 2017 appeared to reflect current changes in the psychopharmacology of depression quite well, like other recently published evidence-based guidelines. As an expert consensus-based guideline, the KMAP-DD 2017 had some limitations. However, considering there are situations in which clinical evidence cannot be drawn from planned clinical trials, the KMAP-DD 2017 may be helpful for Korean psychiatrists making decisions in the clinical settings by complementing previously published evidence-based guidelines. PMID:28783928

Different risk scores consider different types of risks: the deficiencies of the 2015 ESPEN consensus on diagnostic criteria for malnutrition.

PubMed

Xu, Jingyong; Jiang, Zhuming

2018-03-02

In 2015, an European Society for the Parenteral and Enteral Nutrition malnutrition diagnosis consensus was published to unify the definition and simplify the diagnostic procedure of malnutrition, in which 'nutritional risk', 'malnutrition risk' and 'at risk of malnutrition' were referred to several times, and 'at risk of malnutrition' was encouraged to be coded and reimbursed in the International Classification of Diseases and diagnosis-related group system systems. However, there may be some mistakes when using the concepts of different 'risk' mentioned above. In this study, we aimed to explain different 'risks' using the original concept by different screening tools to clarify the definition and provide a recommendation for nutritional screening.

Pediatric Baseline Patch Test Series: Initial Findings of the Pediatric Contact Dermatitis Workgroup.

PubMed

Yu, JiaDe; Atwater, Amber Reck; Brod, Bruce; Chen, Jennifer K; Chisolm, Sarah S; Cohen, David E; de la Feld, Salma; Gaspari, Anthony A; Martin, Kari Lyn; Montanez-Wiscovich, Marjorie; Sheehan, Michael; Silverberg, Nanette; Lugo-Somolinos, Aida; Thakur, Binod K; Watsky, Kalman; Jacob, Sharon E

2018-06-21

Allergic contact dermatitis is a challenging diagnostic problem in children. Although epicutaneous patch testing is the diagnostic standard for confirmation of contact sensitization, it is less used in children by dermatologists treating children, pediatric dermatologists, and pediatricians, when compared with adult practitioners. The aim of the study was to create and evaluate standardization of a pediatric patch test series for children older than 6 years. We surveyed dermatologists and allergists conducting epicutaneous patch testing in children attending the 2017 American Contact Dermatitis Society meeting held in Washington, DC. This was followed by discussion of collected data and consensus review by a pediatric contact dermatitis working group at the conference. A baseline pediatric patch test panel was established through working group consensus.

Self-Reported HIV-Positive Status But Subsequent HIV-Negative Test Result Using Rapid Diagnostic Testing Algorithms Among Seven Sub-Saharan African Military Populations

DTIC Science & Technology

2017-07-07

RESEARCH ARTICLE Self-reported HIV-positive status but subsequent HIV-negative test result using rapid diagnostic testing algorithms among seven sub...America * judith.harbertson.ctr@mail.mil Abstract HIV rapid diagnostic tests (RDTs) combined in an algorithm are the current standard for HIV diagnosis...in many sub-Saharan African countries, and extensive laboratory testing has con- firmed HIV RDTs have excellent sensitivity and specificity. However

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

PubMed

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.

MR and CT data with multiobserver delineations of organs in the pelvic area-Part of the Gold Atlas project.

PubMed

Nyholm, Tufve; Svensson, Stina; Andersson, Sebastian; Jonsson, Joakim; Sohlin, Maja; Gustafsson, Christian; Kjellén, Elisabeth; Söderström, Karin; Albertsson, Per; Blomqvist, Lennart; Zackrisson, Björn; Olsson, Lars E; Gunnlaugsson, Adalsteinn

2018-03-01

We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT). T1- and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset. The dataset has been made publically available to be used for academic purposes, and can be accessed from https://zenodo.org/record/583096. The dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm. © 2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

The Mexican consensus on chronic constipation.

PubMed

Remes-Troche, J M; Coss-Adame, E; Lopéz-Colombo, A; Amieva-Balmori, M; Carmona Sánchez, R; Charúa Guindic, L; Flores Rendón, R; Gómez Escudero, O; González Martínez, M; Icaza Chávez, M E; Morales Arámbula, M; Schmulson, M; Tamayo de la Cuesta, J L; Valdovinos, M Á; Vázquez Elizondo, G

Significant advances have been made in the knowledge and understanding of the epidemiology, pathophysiology, diagnosis, and treatment of chronic constipation, since the publication of the 2011 guidelines on chronic constipation diagnosis and treatment in Mexico from the Asociación Mexicana de Gastroenterología. To present a consensus review of the current state of knowledge about chronic constipation, providing updated information and integrating the new scientific evidence. Three general coordinators reviewed the literature published within the time frame of January 2011 and January 2017. From that information, 62 initial statements were formulated and then sent to 12 national experts for their revision. The statements were voted upon, using the Delphi system in 3 voting rounds (2 electronic and one face-to-face). The statements were classified through the GRADE system and those that reached agreement >75% were included in the consensus. The present consensus is made up of 42 final statements that provide updated knowledge, supplementing the information that had not been included in the previous guidelines. The strength of recommendation and quality (level) of evidence were established for each statement. The current definitions of chronic constipation, functional constipation, and opioid-induced constipation are given, and diagnostic strategies based on the available diagnostic methods are described. The consensus treatment recommendations were established from evidence on the roles of diet and exercise, fiber, laxatives, new drugs (such as prucalopride, lubiprostone, linaclotide, plecanatide), biofeedback therapy, and surgery. Copyright © 2018. Publicado por Masson Doyma México S.A.

[Guidelines for diagnosis and treatment of secondary iron overload in patients with congenital anemia].

PubMed

Cario, H; Grosse, R; Janssen, G; Jarisch, A; Meerpohl, J; Strauss, G

2010-11-01

In Germany and Central Europe, congenital disorders leading to secondary hemochromatosis are rare. The majority of these patients are treated in peripheral medical institutions. As a consequence, the experience of each institution in the treatment of secondary hemochromatosis in patients with congenital anemia is limited. Recent developments concerning new chelating agents, their combination for intensified chelation and new possibilities to diagnose and monitor iron overload have important consequences for the management of patients with secondary hemochromatosis and increase its complexity enormously. Therefore, the development of a guideline for rational and efficient diagnostics and treatment was necessary. The new guideline was developed within a formal consensus process and finally approved by a consensus conference with participants from both the pediatric and adult German hematology societies (GPOH and DGHO). Apart from general information and recommendations, the guideline contains 9 consensus statements on diagnostics (iron status, siderotic complications, chelator side-effects), the start of chelation, indications for intensified chelation, iron elimination in specific disorders, and iron elimination after stem cell transplantation. Here, these consensus statements are presented and discussed in detail. For the complete text of the guideline, please visit the AWMF homepage at http://www.leitlinien.net . © Georg Thieme Verlag KG Stuttgart · New York.

Breast Cancer Screening in the Era of Density Notification Legislation: Summary of 2014 Massachusetts Experience and Suggestion of An Evidence-Based Management Algorithm by Multi-disciplinary Expert Panel

PubMed Central

Freer, Phoebe E.; Slanetz, Priscilla J.; Haas, Jennifer S.; Tung, Nadine M.; Hughes, Kevin S.; Armstrong, Katrina; Semine, A. Alan; Troyan, Susan L.; Birdwell, Robyn L.

2015-01-01

Purpose Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. Methods We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review (ICER), the Cochrane review, National Comprehensive Cancer Network (NCCN) guidelines, American Cancer Society (ACS) recommendations, and American College of Radiology (ACR) appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. Results The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (<15% lifetime risk), do not routinely require supplemental screening per the expert consensus. Women of high risk (>20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. Conclusion We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman. PMID:26290416

The Impact of a Line Probe Assay Based Diagnostic Algorithm on Time to Treatment Initiation and Treatment Outcomes for Multidrug Resistant TB Patients in Arkhangelsk Region, Russia.

PubMed

Eliseev, Platon; Balantcev, Grigory; Nikishova, Elena; Gaida, Anastasia; Bogdanova, Elena; Enarson, Donald; Ornstein, Tara; Detjen, Anne; Dacombe, Russell; Gospodarevskaya, Elena; Phillips, Patrick P J; Mann, Gillian; Squire, Stephen Bertel; Mariandyshev, Andrei

2016-01-01

In the Arkhangelsk region of Northern Russia, multidrug-resistant (MDR) tuberculosis (TB) rates in new cases are amongst the highest in the world. In 2014, MDR-TB rates reached 31.7% among new cases and 56.9% among retreatment cases. The development of new diagnostic tools allows for faster detection of both TB and MDR-TB and should lead to reduced transmission by earlier initiation of anti-TB therapy. The PROVE-IT (Policy Relevant Outcomes from Validating Evidence on Impact) Russia study aimed to assess the impact of the implementation of line probe assay (LPA) as part of an LPA-based diagnostic algorithm for patients with presumptive MDR-TB focusing on time to treatment initiation with time from first-care seeking visit to the initiation of MDR-TB treatment rather than diagnostic accuracy as the primary outcome, and to assess treatment outcomes. We hypothesized that the implementation of LPA would result in faster time to treatment initiation and better treatment outcomes. A culture-based diagnostic algorithm used prior to LPA implementation was compared to an LPA-based algorithm that replaced BacTAlert and Löwenstein Jensen (LJ) for drug sensitivity testing. A total of 295 MDR-TB patients were included in the study, 163 diagnosed with the culture-based algorithm, 132 with the LPA-based algorithm. Among smear positive patients, the implementation of the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 50 and 66 days compared to the culture-based algorithm (BacTAlert and LJ respectively, p<0.001). In smear negative patients, the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, p<0.001). However, several weeks were still needed for treatment initiation in LPA-based algorithm, 24 days in smear positive, and 62 days in smear negative patients. Overall treatment outcomes were better in LPA-based algorithm compared to culture-based algorithm (p = 0.003). Treatment success rates at 20 months of treatment were higher in patients diagnosed with the LPA-based algorithm (65.2%) as compared to those diagnosed with the culture-based algorithm (44.8%). Mortality was also lower in the LPA-based algorithm group (7.6%) compared to the culture-based algorithm group (15.9%). There was no statistically significant difference in smear and culture conversion rates between the two algorithms. The results of the study suggest that the introduction of LPA leads to faster time to MDR diagnosis and earlier treatment initiation as well as better treatment outcomes for patients with MDR-TB. These findings also highlight the need for further improvements within the health system to reduce both patient and diagnostic delays to truly optimize the impact of new, rapid diagnostics.

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, S.; Simpson, J.; Olson, W. S.; Johnson, D.; Ferrier, B.; Kummerow, C.; Adler, R.

1999-01-01

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Clinical assessment of acute lateral ankle sprain injuries (ROAST): 2019 consensus statement and recommendations of the International Ankle Consortium.

PubMed

Delahunt, Eamonn; Bleakley, Chris M; Bossard, Daniela S; Caulfield, Brian M; Docherty, Carrie L; Doherty, Cailbhe; Fourchet, François; Fong, Daniel T; Hertel, Jay; Hiller, Claire E; Kaminski, Thomas W; McKeon, Patrick O; Refshauge, Kathryn M; Remus, Alexandria; Verhagen, Evert; Vicenzino, Bill T; Wikstrom, Erik A; Gribble, Phillip A

2018-06-09

Lateral ankle sprain injury is the most common musculoskeletal injury incurred by individuals who participate in sports and recreational physical activities. Following initial injury, a high proportion of individuals develop long-term injury-associated symptoms and chronic ankle instability. The development of chronic ankle instability is consequent on the interaction of mechanical and sensorimotor insufficiencies/impairments that manifest following acute lateral ankle sprain injury. To reduce the propensity for developing chronic ankle instability, clinical assessments should evaluate whether patients in the acute phase following lateral ankle sprain injury exhibit any mechanical and/or sensorimotor impairments. This modified Delphi study was undertaken under the auspices of the executive committee of the International Ankle Consortium. The primary aim was to develop recommendations, based on expert (n=14) consensus, for structured clinical assessment of acute lateral ankle sprain injuries. After two modified Delphi rounds, consensus was achieved on the clinical assessment of acute lateral ankle sprain injuries. Consensus was reached on a minimum standard clinical diagnostic assessment. Key components of this clinical diagnostic assessment include: establishing the mechanism of injury, as well as the assessment of ankle joint bones and ligaments. Through consensus, the expert panel also developed the International Ankle Consortium Rehabilitation-Oriented ASsessmenT (ROAST). The International Ankle Consortium ROAST will help clinicians identify mechanical and/or sensorimotor impairments that are associated with chronic ankle instability. This consensus statement from the International Ankle Consortium aims to be a key resource for clinicians who regularly assess individuals with acute lateral ankle sprain injuries. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Base-Calling Algorithm with Vocabulary (BCV) Method for Analyzing Population Sequencing Chromatograms

PubMed Central

Fantin, Yuri S.; Neverov, Alexey D.; Favorov, Alexander V.; Alvarez-Figueroa, Maria V.; Braslavskaya, Svetlana I.; Gordukova, Maria A.; Karandashova, Inga V.; Kuleshov, Konstantin V.; Myznikova, Anna I.; Polishchuk, Maya S.; Reshetov, Denis A.; Voiciehovskaya, Yana A.; Mironov, Andrei A.; Chulanov, Vladimir P.

2013-01-01

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3–14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing. PMID:23382983

Planetary Transmission Diagnostics

NASA Technical Reports Server (NTRS)

Lewicki, David G. (Technical Monitor); Samuel, Paul D.; Conroy, Joseph K.; Pines, Darryll J.

2004-01-01

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

The value of signs, symptoms and plasma heart-type fatty acid-binding protein (H-FABP) in evaluating patients presenting with symptoms possibly matching acute coronary syndrome: background and methods of a diagnostic study in primary care.

PubMed

Willemsen, Robert T A; Buntinx, Frank; Winkens, Bjorn; Glatz, Jan F; Dinant, Geert Jan

2014-12-12

Chest complaints presented to a general practitioner (GP) are frequently caused by diseases which have advantageous outcomes. However, in some cases, acute coronary syndrome (ACS) is present (1.5-22% of cases). The patient's signs, symptoms and electrocardiography results are insufficient diagnostic tools to distinguish mild disease from ACS. Therefore, most patients presenting chest complaints are referred to secondary care facilities where ACS is then ruled out in a majority of patients (78%). Recently, a point of care test for heart-type fatty acid-binding protein (H-FABP) using a low cut-off value between positive and negative of 4 ng/ml has become available. We aim to study the role of this point of care device in triage of patients presenting chest complaints possibly due to ACS, in primary care. Our research protocol is presented in this article. Results are expected in 2015. Participating GPs will register signs and symptoms in all patients presenting chest complaints possibly due to ACS. Point of care H-FABP testing will also be performed. Our study will be a derivation study to identify signs and symptoms that, combined with point of care H-FABP testing, can be part of an algorithm to either confirm or rule out ACS. The diagnostic value for ACS of this algorithm in general practice will be determined. A safe diagnostic elimination of ACS by application of the algorithm can be of significant clinical relevance. Improved triage and thus reduction of the number of patients with chest complaints without underlying ACS, that are referred to secondary care facilities, could lead to a substantial cost reduction. ClinicalTrials.gov, NCT01826994, accepted April 8th 2013.

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study.

PubMed

Sunwoo, Leonard; Kim, Young Jae; Choi, Seung Hong; Kim, Kwang-Gi; Kang, Ji Hee; Kang, Yeonah; Bae, Yun Jung; Yoo, Roh-Eul; Kim, Jihang; Lee, Kyong Joon; Lee, Seung Hyun; Choi, Byung Se; Jung, Cheolkyu; Sohn, Chul-Ho; Kim, Jae Hyoung

2017-01-01

To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard. The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy. The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time). CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers.

Expanding the Taxonomy of the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD)

PubMed Central

Peck, Christopher C.; Goulet, Jean-Paul; Lobbezoo, Frank; Schiffman, Eric L.; Alstergren, Per; Anderson, Gary C.; de Leeuw, Reny; Jensen, Rigmor; Michelotti, Ambra; Ohrbach, Richard; Petersson, Arne; List, Thomas

2014-01-01

Background There is a need to expand the current temporomandibular disorder (TMD) classification to include less common, but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing, and further criteria refinement. Methods A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria, and the ability to operationalize and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMD taxonomy was presented for feedback at international meetings. Results Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders, and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalized diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. Conclusions The expanded TMD taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalize and test the proposed taxonomy and diagnostic criteria. PMID:24443898

Expanding the taxonomy of the diagnostic criteria for temporomandibular disorders.

PubMed

Peck, C C; Goulet, J-P; Lobbezoo, F; Schiffman, E L; Alstergren, P; Anderson, G C; de Leeuw, R; Jensen, R; Michelotti, A; Ohrbach, R; Petersson, A; List, T

2014-01-01

There is a need to expand the current temporomandibular disorders' (TMDs) classification to include less common but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing and further criteria refinement. A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria and the ability to operationalise and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMDs taxonomy was presented for feedback at international meetings. Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalised diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. The expanded TMDs taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalise and test the proposed taxonomy and diagnostic criteria. © 2014 John Wiley & Sons Ltd.

Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix

NASA Astrophysics Data System (ADS)

Lange, Holger

2005-04-01

Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method used to detect cancer precursors and cancer of the uterine cervix, whereby a physician (colposcopist) visually inspects the metaplastic epithelium on the cervix for certain distinctly abnormal morphologic features. A contrast agent, a 3-5% acetic acid solution, is used, causing abnormal and metaplastic epithelia to turn white. The colposcopist considers diagnostic features such as the acetowhite, blood vessel structure, and lesion margin to derive a clinical diagnosis. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD, a complex image analysis system that at its core assesses the same visual features as used by colposcopists. The acetowhite feature has been identified as one of the most important individual predictors of lesion severity. Here, we present the details and preliminary results of a multi-level acetowhite region detection algorithm for RGB color images of the cervix, including the detection of the anatomic features: cervix, os and columnar region, which are used for the acetowhite region detection. The RGB images are assumed to be glare free, either obtained by cross-polarized image acquisition or glare removal pre-processing. The basic approach of the algorithm is to extract a feature image from the RGB image that provides a good acetowhite to cervix background ratio, to segment the feature image using novel pixel grouping and multi-stage region-growing algorithms that provide region segmentations with different levels of detail, to extract the acetowhite regions from the region segmentations using a novel region selection algorithm, and then finally to extract the multi-levels from the acetowhite regions using multiple thresholds. The performance of the algorithm is demonstrated using human subject data.

A distributed algorithm for machine learning

NASA Astrophysics Data System (ADS)

Chen, Shihong

2018-04-01

This paper considers a distributed learning problem in which a group of machines in a connected network, each learning its own local dataset, aim to reach a consensus at an optimal model, by exchanging information only with their neighbors but without transmitting data. A distributed algorithm is proposed to solve this problem under appropriate assumptions.

A collaborative platform for consensus sessions in pathology over Internet.

PubMed

Zapletal, Eric; Le Bozec, Christel; Degoulet, Patrice; Jaulent, Marie-Christine

2003-01-01

The design of valid databases in pathology faces the problem of diagnostic disagreement between pathologists. Organizing consensus sessions between experts to reduce the variability is a difficult task. The TRIDEM platform addresses the issue to organize consensus sessions in pathology over the Internet. In this paper, we present the basis to achieve such collaborative platform. On the one hand, the platform integrates the functionalities of the IDEM consensus module that alleviates the consensus task by presenting to pathologists preliminary computed consensus through ergonomic interfaces (automatic step). On the other hand, a set of lightweight interaction tools such as vocal annotations are implemented to ease the communication between experts as they discuss a case (interactive step). The architecture of the TRIDEM platform is based on a Java-Server-Page web server that communicate with the ObjectStore PSE/PRO database used for the object storage. The HTML pages generated by the web server run Java applets to perform the different steps (automatic and interactive) of the consensus. The current limitations of the platform is to only handle a synchronous process. Moreover, improvements like re-writing the consensus workflow with a protocol such as BPML are already forecast.

MRI CRITERIA FOR THE DIAGNOSIS OF MULTIPLE SCLEROSIS: MAGNIMS CONSENSUS GUIDELINES

PubMed Central

Filippi, M.; Rocca, M.A.; Ciccarelli, O.; De Stefano, N.; Evangelou, N.; Kappos, L.; Rovira, A.; Sastre-Garriga, J.; Tintorè, M.; Frederiksen, J.L.; Gasperini, C.; Palace, J.; Reich, D.S.; Banwell, B.; Montalban, X.; Barkhof, F.

2016-01-01

Summary In patients presenting with a clinically isolated syndrome (CIS), magnetic resonance imaging (MRI) can support and substitute clinical information for multiple sclerosis (MS) diagnosis demonstrating disease dissemination in space (DIS) and time (DIT) and helping to rule out other conditions that can mimic MS. From their inclusion in the diagnostic work-up for MS in 2001, several modifications of MRI diagnostic criteria have been proposed, in the attempt to simplify lesion-count models for demonstrating DIS, change the timing of MRI scanning for demonstrating DIT, and increase the value of spinal cord imaging. Since the last update of these criteria, new data regarding the application of MRI for demonstrating DIS and DIT have become available and improvement in MRI technology has occurred. State-of-the-art MRI findings in these patients were discussed in a MAGNIMS workshop, the goal of which was to provide an evidence-based and expert-opinion consensus on diagnostic MRI criteria modifications. PMID:26822746

Backstepping-based cooperative and adaptive tracking control design for a group of underactuated AUVs in horizontal plan

NASA Astrophysics Data System (ADS)

Ghommam, Jawhar; Saad, Maarouf

2014-05-01

In this paper, we investigate new implementable cooperative adaptive backstepping controllers for a group of underactuated autonomous vehicles that are communicating with their local neighbours to track a time-varying virtual leader of which the relative position may only be available to a portion of the team members. At the kinematic cooperative control level of the autonomous underwater vehicle, the virtual cooperative controller is basically designed on a proportional and derivative consensus algorithm presented in Ren (2010), which involves velocity information from local neighbours. In this paper, we propose a new design algorithm based on singular perturbation theory that precludes the use of the neighbours' velocity information in the cooperative design. At the dynamic cooperative control level, calculation of the partial derivatives of some stabilising functions which in turn will contain velocity information from the local neighbours is required. To facilitate the implementation of the cooperative controllers, we propose a command filter approach technique to avoid analytic differentiation of the virtual cooperative control laws. We show how Lyapunov-based techniques and graph theory can be combined together to yield a robust cooperative controller where the uncertain dynamics of the cooperating vehicles and the constraints on the communication topology which contains a directed spanning tree are explicitly taken into account. Simulation results with a dynamic model of underactuated autonomous underwater vehicles moving on the horizontal plane are presented and discussed.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD Without ID: A Multi-site Study.

PubMed

Pugliese, Cara E; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L; Yerys, Benjamin E; Maddox, Brenna B; White, Susan W; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D; Schultz, Robert T; Martin, Alex; Anthony, Laura Gutermuth

2015-12-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised algorithm demonstrated increased sensitivity, but lower specificity in the overall sample. Estimates were highest for females, individuals with a verbal IQ below 85 or above 115, and ages 16 and older. Best practice diagnostic procedures should include the Module 4 in conjunction with other assessment tools. Balancing needs for sensitivity and specificity depending on the purpose of assessment (e.g., clinical vs. research) and demographic characteristics mentioned above will enhance its utility.

The autism diagnostic observation schedule, module 4: revised algorithm and standardized severity scores.

PubMed

Hus, Vanessa; Lord, Catherine

2014-08-01

The recently published Autism Diagnostic Observation Schedule, 2nd edition (ADOS-2) includes revised diagnostic algorithms and standardized severity scores for modules used to assess younger children. A revised algorithm and severity scores are not yet available for Module 4, used with verbally fluent adults. The current study revises the Module 4 algorithm and calibrates raw overall and domain totals to provide metrics of autism spectrum disorder (ASD) symptom severity. Sensitivity and specificity of the revised Module 4 algorithm exceeded 80 % in the overall sample. Module 4 calibrated severity scores provide quantitative estimates of ASD symptom severity that are relatively independent of participant characteristics. These efforts increase comparability of ADOS scores across modules and should facilitate efforts to examine symptom trajectories from toddler to adulthood.

Implementation of an Algorithm for Prosthetic Joint Infection: Deviations and Problems.

PubMed

Mühlhofer, Heinrich M L; Kanz, Karl-Georg; Pohlig, Florian; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; von Eisenhart-Rothe, Ruediger; Schauwecker, Johannes

The outcome of revision surgery in arthroplasty is based on a precise diagnosis. In addition, the treatment varies based on whether the prosthetic failure is caused by aseptic or septic loosening. Algorithms can help to identify periprosthetic joint infections (PJI) and standardize diagnostic steps, however, algorithms tend to oversimplify the treatment of complex cases. We conducted a process analysis during the implementation of a PJI algorithm to determine problems and deviations associated with the implementation of this algorithm. Fifty patients who were treated after implementing a standardized algorithm were monitored retrospectively. Their treatment plans and diagnostic cascades were analyzed for deviations from the implemented algorithm. Each diagnostic procedure was recorded, compared with the algorithm, and evaluated statistically. We detected 52 deviations while treating 50 patients. In 25 cases, no discrepancy was observed. Synovial fluid aspiration was not performed in 31.8% of patients (95% confidence interval [CI], 18.1%-45.6%), while white blood cell counts (WBCs) and neutrophil differentiation were assessed in 54.5% of patients (95% CI, 39.8%-69.3%). We also observed that the prolonged incubation of cultures was not requested in 13.6% of patients (95% CI, 3.5%-23.8%). In seven of 13 cases (63.6%; 95% CI, 35.2%-92.1%), arthroscopic biopsy was performed; 6 arthroscopies were performed in discordance with the algorithm (12%; 95% CI, 3%-21%). Self-critical analysis of diagnostic processes and monitoring of deviations using algorithms are important and could increase the quality of treatment by revealing recurring faults.

International consensus statements on early chronic Pancreatitis. Recommendations from the working group for the international consensus guidelines for chronic pancreatitis in collaboration with The International Association of Pancreatology, American Pancreatic Association, Japan Pancreas Society, PancreasFest Working Group and European Pancreatic Club.

PubMed

Whitcomb, David C; Shimosegawa, Tooru; Chari, Suresh T; Forsmark, Christopher E; Frulloni, Luca; Garg, Pramod; Hegyi, Peter; Hirooka, Yoshiki; Irisawa, Atsushi; Ishikawa, Takuya; Isaji, Shuiji; Lerch, Markus M; Levy, Philippe; Masamune, Atsushi; Wilcox, Charles M; Windsor, John; Yadav, Dhiraj; Sheel, Andrea; Neoptolemos, John P

2018-05-21

Chronic pancreatitis (CP) is a progressive inflammatory disorder currently diagnosed by morphologic features. In contrast, an accurate diagnosis of Early CP is not possible using imaging criteria alone. If this were possible and early treatment instituted, the later, irreversible features and complications of CP could possibly be prevented. An international working group supported by four major pancreas societies (IAP, APA, JPS, and EPC) and a PancreasFest working group sought to develop a consensus definition and diagnostic criteria for Early CP. Ten statements (S1-10) concerning Early CP were used to gauge consensus on the Early CP concept using anonymous voting with a 9 point Likert scale. Consensus required an alpha ≥0.80. No consensus statement could be developed for a definition of Early-CP or diagnostic criteria. There was consensus on 5 statements: (S2) The word "Early" in early chronic pancreatitis is used to describe disease state, not disease duration. (S4) Early CP defines a stage of CP with preserved pancreatic function and potentially reversible features. (S8) Genetic variants are important risk factors for Early CP and can add specificity to the likely etiology, but they are neither necessary nor sufficient to make a diagnosis. (S9) Environmental risk factors can provide evidence to support the diagnosis of Early CP, but are neither necessary nor sufficient to make a diagnosis. (S10) The differential diagnosis for Early CP includes other disorders with morphological and functional features that overlap with CP. Morphology based diagnosis of Early CP is not possible without additional information. New approaches to the accurate diagnosis of Early CP will require a mechanistic definition that considers risk factors, biomarkers, clinical context and new models of disease. Such a definition will require prospective validation. Copyright © 2018. Published by Elsevier B.V.

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

PubMed

De Looze, Céline; Beausang, Alan; Cryan, Jane; Loftus, Teresa; Buckley, Patrick G; Farrell, Michael; Looby, Seamus; Reilly, Richard; Brett, Francesca; Kearney, Hugh

2018-05-16

Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a glioma. The aim of this study is to devise a machine learning algorithm that may be used by radiologists in routine practice to aid diagnosis of both: WHO grade and IDH mutation status in de novo gliomas. To evaluate the status quo, we interrogated the accuracy of neuroradiology reports in relation to WHO grade: grade II 96.49% (95% confidence intervals [CI] 0.88, 0.99); III 36.51% (95% CI 0.24, 0.50); IV 72.9% (95% CI 0.67, 0.78). We derived five MRI parameters from the same diagnostic brain scans, in under two minutes per case, and then supplied these data to a random forest algorithm. Machine learning resulted in a high level of accuracy in prediction of tumour grade: grade II/III; area under the receiver operating characteristic curve (AUC) = 98%, sensitivity = 0.82, specificity = 0.94; grade II/IV; AUC = 100%, sensitivity = 1.0, specificity = 1.0; grade III/IV; AUC = 97%, sensitivity = 0.83, specificity = 0.97. Furthermore, machine learning also facilitated the discrimination of IDH status: AUC of 88%, sensitivity = 0.81, specificity = 0.77. These data demonstrate the ability of machine learning to accurately classify diffuse gliomas by both WHO grade and IDH status from routine MRI alone-without significant image processing, which may facilitate usage as a diagnostic adjunct in clinical practice.

Overcoming barriers to population-based injury research: development and validation of an ICD-10–to–AIS algorithm

PubMed Central

Haas, Barbara; Xiong, Wei; Brennan-Barnes, Maureen; Gomez, David; Nathens, Avery B.

2012-01-01

Background Hospital administrative databases are a useful source of population-level data on injured patients; however, these databases use the International Classification of Diseases (ICD) system, which does not provide a direct means of estimating injury severity. We created and validated a crosswalk to derive Abbreviated Injury Scale (AIS) scores from injury-related diagnostic codes in the tenth revision of the ICD (ICD-10). Methods We assessed the validity of the crosswalk using data from the Ontario Trauma Registry Comprehensive Data Set (OTR-CDS). The AIS and Injury Severity Scores (ISS) derived using the algorithm were compared with those assigned by expert abstractors. We evaluated the ability of the algorithm to identify patients with AIS scores of 3 or greater. We used κ and intraclass correlation coefficients (ICC) as measures of concordance. Results In total, 10 431 patients were identified in the OTR-CDS. The algorithm accurately identified patients with at least 1 AIS score of 3 or greater (κ 0.65), as well as patients with a head AIS score of 3 or greater (κ 0.78). Mapped and abstracted ISS were similar; ICC across the entire cohort was 0.83 (95% confidence interval 0.81–0.84), indicating good agreement. When comparing mapped and abstracted ISS, the difference between scores was 10 or less in 87% of patients. Concordance between mapped and abstracted ISS was similar across strata of age, mechanism of injury and mortality. Conclusion Our ICD-10–to–AIS algorithm produces reliable estimates of injury severity from data available in administrative databases. This algorithm can facilitate the use of administrative data for population-based injury research in jurisdictions using ICD-10. PMID:22269308

Overcoming barriers to population-based injury research: development and validation of an ICD10-to-AIS algorithm.

PubMed

Haas, Barbara; Xiong, Wei; Brennan-Barnes, Maureen; Gomez, David; Nathens, Avery B

2012-02-01

Hospital administrative databases are a useful source of population-level data on injured patients; however, these databases use the International Classification of Diseases (ICD) system, which does not provide a direct means of estimating injury severity. We created and validated a crosswalk to derive Abbreviated Injury Scale (AIS) scores from injury-related diagnostic codes in the tenth revision of the ICD (ICD-10). We assessed the validity of the crosswalk using data from the Ontario Trauma Registry Comprehensive Data Set (OTRCDS). The AIS and Injury Severity Scores (ISS) derived using the algorithm were compared with those assigned by expert abstractors. We evaluated the ability of the algorithm to identify patients with AIS scores of 3 or greater. We used κ and intraclass correlation coefficients (ICC) as measures of concordance. In total, 10 431 patients were identified in the OTRCDS. The algorithm accurately identified patients with at least 1 AIS score of 3 or greater (κ 0.65), as well as patients with a head AIS score of 3 or greater (κ 0.78). Mapped and abstracted ISS were similar; ICC across the entire cohort was 0.83 (95% confidence interval 0.81-0.84), indicating good agreement. When comparing mapped and abstracted ISS, the difference between scores was 10 or less in 87% of patients. Concordance between mapped and abstracted ISS was similar across strata of age, mechanism of injury and mortality. Our ICD-10-to-AIS algorithm produces reliable estimates of injury severity from data available in administrative databases. This algorithm can facilitate the use of administrative data for population-based injury research in jurisdictions using ICD-10.

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

The Texas Medication Algorithm Project antipsychotic algorithm for schizophrenia: 2003 update.

PubMed

Miller, Alexander L; Hall, Catherine S; Buchanan, Robert W; Buckley, Peter F; Chiles, John A; Conley, Robert R; Crismon, M Lynn; Ereshefsky, Larry; Essock, Susan M; Finnerty, Molly; Marder, Stephen R; Miller, Del D; McEvoy, Joseph P; Rush, A John; Saeed, Sy A; Schooler, Nina R; Shon, Steven P; Stroup, Scott; Tarin-Godoy, Bernardo

2004-04-01

The Texas Medication Algorithm Project (TMAP) has been a public-academic collaboration in which guidelines for medication treatment of schizophrenia, bipolar disorder, and major depressive disorder were used in selected public outpatient clinics in Texas. Subsequently, these algorithms were implemented throughout Texas and are being used in other states. Guidelines require updating when significant new evidence emerges; the antipsychotic algorithm for schizophrenia was last updated in 1999. This article reports the recommendations developed in 2002 and 2003 by a group of experts, clinicians, and administrators. A conference in January 2002 began the update process. Before the conference, experts in the pharmacologic treatment of schizophrenia, clinicians, and administrators reviewed literature topics and prepared presentations. Topics included ziprasidone's inclusion in the algorithm, the number of antipsychotics tried before clozapine, and the role of first generation antipsychotics. Data were rated according to Agency for Healthcare Research and Quality criteria. After discussing the presentations, conference attendees arrived at consensus recommendations. Consideration of aripiprazole's inclusion was subsequently handled by electronic communications. The antipsychotic algorithm for schizophrenia was updated to include ziprasidone and aripiprazole among the first-line agents. Relative to the prior algorithm, the number of stages before clozapine was reduced. First generation antipsychotics were included but not as first-line choices. For patients refusing or not responding to clozapine and clozapine augmentation, preference was given to trying monotherapy with another antipsychotic before resorting to antipsychotic combinations. Consensus on algorithm revisions was achieved, but only further well-controlled research will answer many key questions about sequence and type of medication treatments of schizophrenia.

Predictive capabilities of statistical learning methods for lung nodule malignancy classification using diagnostic image features: an investigation using the Lung Image Database Consortium dataset

NASA Astrophysics Data System (ADS)

Hancock, Matthew C.; Magnan, Jerry F.

2017-03-01

To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capabilities of statistical learning methods for classifying nodule malignancy, utilizing the Lung Image Database Consortium (LIDC) dataset, and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists' annotations. We calculate theoretical upper bounds on the classification accuracy that is achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (+/-1.14)% which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (+/-0.012), which increases to 0.949 (+/-0.007) when diameter and volume features are included, along with the accuracy to 88.08 (+/-1.11)%. Our results are comparable to those in the literature that use algorithmically-derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features, and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.

Diagnostic rules and algorithms for the diagnosis of non-acute heart failure in patients 80 years of age and older: a diagnostic accuracy and validation study.

PubMed

Smeets, Miek; Degryse, Jan; Janssens, Stefan; Matheï, Catharina; Wallemacq, Pierre; Vanoverschelde, Jean-Louis; Aertgeerts, Bert; Vaes, Bert

2016-10-06

Different diagnostic algorithms for non-acute heart failure (HF) exist. Our aim was to compare the ability of these algorithms to identify HF in symptomatic patients aged 80 years and older and identify those patients at highest risk for mortality. Diagnostic accuracy and validation study. General practice, Belgium. 365 patients with HF symptoms aged 80 years and older (BELFRAIL cohort). Participants underwent a full clinical assessment, including a detailed echocardiographic examination at home. The diagnostic accuracy of 4 different algorithms was compared using an intention-to-diagnose analysis. The European Society of Cardiology (ESC) definition of HF was used as the reference standard for HF diagnosis. Kaplan-Meier curves for 5-year all-cause mortality were plotted and HRs and corresponding 95% CIs were calculated to compare the mortality risk predicting abilities of the different algorithms. Net reclassification improvement (NRI) was calculated. The prevalence of HF was 20% (n=74). The 2012 ESC algorithm yielded the highest sensitivity (92%, 95% CI 83% to 97%) as well as the highest referral rate (71%, n=259), whereas the Oudejans algorithm yielded the highest specificity (73%, 95% CI 68% to 78%) and the lowest referral rate (36%, n=133). These differences could be ascribed to differences in N-terminal probrain natriuretic peptide cut-off values (125 vs 400 pg/mL). The Kelder and Oudejans algorithms exhibited NRIs of 12% (95% CI 0.7% to 22%, p=0.04) and 22% (95% CI 9% to 32%, p<0.001), respectively, compared with the ESC algorithm. All algorithms detected patients at high risk for mortality (HR 1.9, 95% CI 1.4 to 2.5; Kelder) to 2.3 (95% CI 1.7 to 3.1; Oudejans). No significant differences were observed among the algorithms with respect to mortality risk predicting abilities. Choosing a diagnostic algorithm for non-acute HF in elderly patients represents a trade-off between sensitivity and specificity, mainly depending on differences between cut-off values for natriuretic peptides. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Cultural stereotypes of disabled and non-disabled men and women: consensus for global category representations and diagnostic domains.

PubMed

Nario-Redmond, Michelle R

2010-09-01

Despite the fact that disabled people comprise a heterogeneous social group, cross-impairment cultural stereotypes reflect a consistent set of beliefs used to characterize this population as dependent, incompetent, and asexual. Using a free-response methodology, stereotypical beliefs about disabled men (DM) and women (DW) were contrasted against the stereotypes of their non-disabled counterparts illustrating the dimensions considered most diagnostic of each group. Results revealed that both disabled and non-disabled participants expressed consensus about the contents of group stereotypes that exaggerate traditional gender role expectations of the non-disabled while minimizing perceived differences between DM and DW. Implications for the field of stereotyping and prejudice, and the individual and system justifying functions of cultural stereotypes are discussed.

A diagnostic algorithm for atypical spitzoid tumors: guidelines for immunohistochemical and molecular assessment.

PubMed

Cho-Vega, Jeong Hee

2016-07-01

Atypical spitzoid tumors are a morphologically diverse group of rare melanocytic lesions most frequently seen in children and young adults. As atypical spitzoid tumors bear striking resemblance to Spitz nevus and spitzoid melanomas clinically and histopathologically, it is crucial to determine its malignant potential and predict its clinical behavior. To date, many researchers have attempted to differentiate atypical spitzoid tumors from unequivocal melanomas based on morphological, immonohistochemical, and molecular diagnostic differences. A diagnostic algorithm is proposed here to assess the malignant potential of atypical spitzoid tumors by using a combination of immunohistochemical and cytogenetic/molecular tests. Together with classical morphological evaluation, this algorithm includes a set of immunohistochemistry assays (p16(Ink4a), a dual-color Ki67/MART-1, and HMB45), fluorescence in situ hybridization (FISH) with five probes (6p25, 8q24, 11q13, CEN9, and 9p21), and an array-based comparative genomic hybridization. This review discusses details of the algorithm, the rationale of each test used in the algorithm, and utility of this algorithm in routine dermatopathology practice. This algorithmic approach will provide a comprehensive diagnostic tool that complements conventional histological criteria and will significantly contribute to improve the diagnosis and prediction of the clinical behavior of atypical spitzoid tumors.

Portable Health Algorithms Test System

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Wong, Edmond; Fulton, Christopher E.; Sowers, Thomas S.; Maul, William A.

2010-01-01

A document discusses the Portable Health Algorithms Test (PHALT) System, which has been designed as a means for evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT system allows systems health management algorithms to be developed in a graphical programming environment, to be tested and refined using system simulation or test data playback, and to be evaluated in a real-time hardware-in-the-loop mode with a live test article. The integrated hardware and software development environment provides a seamless transition from algorithm development to real-time implementation. The portability of the hardware makes it quick and easy to transport between test facilities. This hard ware/software architecture is flexible enough to support a variety of diagnostic applications and test hardware, and the GUI-based rapid prototyping capability is sufficient to support development execution, and testing of custom diagnostic algorithms. The PHALT operating system supports execution of diagnostic algorithms under real-time constraints. PHALT can perform real-time capture and playback of test rig data with the ability to augment/ modify the data stream (e.g. inject simulated faults). It performs algorithm testing using a variety of data input sources, including real-time data acquisition, test data playback, and system simulations, and also provides system feedback to evaluate closed-loop diagnostic response and mitigation control.

Segmentation of large periapical lesions toward dental computer-aided diagnosis in cone-beam CT scans

NASA Astrophysics Data System (ADS)

Rysavy, Steven; Flores, Arturo; Enciso, Reyes; Okada, Kazunori

2008-03-01

This paper presents an experimental study for assessing the applicability of general-purpose 3D segmentation algorithms for analyzing dental periapical lesions in cone-beam computed tomography (CBCT) scans. In the field of Endodontics, clinical studies have been unable to determine if a periapical granuloma can heal with non-surgical methods. Addressing this issue, Simon et al. recently proposed a diagnostic technique which non-invasively classifies target lesions using CBCT. Manual segmentation exploited in their study, however, is too time consuming and unreliable for real world adoption. On the other hand, many technically advanced algorithms have been proposed to address segmentation problems in various biomedical and non-biomedical contexts, but they have not yet been applied to the field of dentistry. Presented in this paper is a novel application of such segmentation algorithms to the clinically-significant dental problem. This study evaluates three state-of-the-art graph-based algorithms: a normalized cut algorithm based on a generalized eigen-value problem, a graph cut algorithm implementing energy minimization techniques, and a random walks algorithm derived from discrete electrical potential theory. In this paper, we extend the original 2D formulation of the above algorithms to segment 3D images directly and apply the resulting algorithms to the dental CBCT images. We experimentally evaluate quality of the segmentation results for 3D CBCT images, as well as their 2D cross sections. The benefits and pitfalls of each algorithm are highlighted.

Consensus statement for standard of care in spinal muscular atrophy.

PubMed

Wang, Ching H; Finkel, Richard S; Bertini, Enrico S; Schroth, Mary; Simonds, Anita; Wong, Brenda; Aloysius, Annie; Morrison, Leslie; Main, Marion; Crawford, Thomas O; Trela, Anthony

2007-08-01

Spinal muscular atrophy is a neurodegenerative disease that requires multidisciplinary medical care. Recent progress in the understanding of molecular pathogenesis of spinal muscular atrophy and advances in medical technology have not been matched by similar developments in the care for spinal muscular atrophy patients. Variations in medical practice coupled with differences in family resources and values have resulted in variable clinical outcomes that are likely to compromise valid measure of treatment effects during clinical trials. The International Standard of Care Committee for Spinal Muscular Atrophy was formed in 2005, with a goal of establishing practice guidelines for clinical care of these patients. The 12 core committee members worked with more than 60 spinal muscular atrophy experts in the field through conference calls, e-mail communications, a Delphi survey, and 2 in-person meetings to achieve consensus on 5 care areas: diagnostic/new interventions, pulmonary, gastrointestinal/nutrition, orthopedics/rehabilitation, and palliative care. Consensus was achieved on several topics related to common medical problems in spinal muscular atrophy, diagnostic strategies, recommendations for assessment and monitoring, and therapeutic interventions in each care area. A consensus statement was drafted to address the 5 care areas according to 3 functional levels of the patients: nonsitter, sitter, and walker. The committee also identified several medical practices lacking consensus and warranting further investigation. It is the authors' intention that this document be used as a guideline, not as a practice standard for their care. A practice standard for spinal muscular atrophy is urgently needed to help with the multidisciplinary care of these patients.

Evaluation of Pulmonary Nodules: Clinical Practice Consensus Guidelines for Asia.

PubMed

Bai, Chunxue; Choi, Chang-Min; Chu, Chung Ming; Anantham, Devanand; Chung-Man Ho, James; Khan, Ali Zamir; Lee, Jang-Ming; Li, Shi Yue; Saenghirunvattana, Sawang; Yim, Anthony

2016-10-01

American College of Chest Physicians (CHEST) clinical practice guidelines on the evaluation of pulmonary nodules may have low adoption among clinicians in Asian countries. Unique patient characteristics of Asian patients affect the diagnostic evaluation of pulmonary nodules. The objective of these clinical practice guidelines was to adapt those of CHEST to provide consensus-based recommendations relevant to practitioners in Asia. A modified ADAPTE process was used by a multidisciplinary group of pulmonologists and thoracic surgeons in Asia. An initial panel meeting analyzed all CHEST recommendations to achieve consensus on recommendations and identify areas that required further investigation before consensus could be achieved. Revised recommendations were circulated to panel members for iterative review and redrafting to develop the final guidelines. Evaluation of pulmonary nodules in Asia broadly follows those of the CHEST guidelines with important caveats. Practitioners should be aware of the risk of lung cancer caused by high levels of indoor and outdoor air pollution, as well as the high incidence of adenocarcinoma in female nonsmokers. Furthermore, the high prevalence of granulomatous disease and other infectious causes of pulmonary nodules need to be considered. Therefore, diagnostic risk calculators developed in non-Asian patients may not be applicable. Overall, longer surveillance of nodules than those recommended by CHEST should be considered. TB in Asia favors lesser reliance on PET scanning and greater use of nonsurgical biopsy over surgical diagnosis or surveillance. Practitioners in Asia are encouraged to use these adapted consensus guidelines to facilitate consistent evaluation of pulmonary nodules. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Collective intelligence in medical diagnosis systems: A case study.

PubMed

Hernández-Chan, Gandhi S; Ceh-Varela, Edgar Eduardo; Sanchez-Cervantes, Jose L; Villanueva-Escalante, Marisol; Rodríguez-González, Alejandro; Pérez-Gallardo, Yuliana

2016-07-01

Diagnosing a patient's condition is one of the most important and challenging tasks in medicine. We present a study of the application of collective intelligence in medical diagnosis by applying consensus methods. We compared the accuracy obtained with this method against the diagnostics accuracy reached through the knowledge of a single expert. We used the ontological structures of ten diseases. Two knowledge bases were created by placing five diseases into each knowledge base. We conducted two experiments, one with an empty knowledge base and the other with a populated knowledge base. For both experiments, five experts added and/or eliminated signs/symptoms and diagnostic tests for each disease. After this process, the individual knowledge bases were built based on the output of the consensus methods. In order to perform the evaluation, we compared the number of items for each disease in the agreed knowledge bases against the number of items in the GS (Gold Standard). We identified that, while the number of items in each knowledge base is higher, the consensus level is lower. In all cases, the lowest level of agreement (20%) exceeded the number of signs that are in the GS. In addition, when all experts agreed, the number of items decreased. The use of collective intelligence can be used to increase the consensus of physicians. This is because, by using consensus, physicians can gather more information and knowledge than when obtaining information and knowledge from knowledge bases fed or populated from the knowledge found in the literature, and, at the same time, they can keep updated and collaborate dynamically. Copyright © 2016 Elsevier Ltd. All rights reserved.

Replication and Comparison of the Newly Proposed ADOS-2, Module 4 Algorithm in ASD without ID: A Multi-site Study

PubMed Central

Pugliese, Cara E.; Kenworthy, Lauren; Bal, Vanessa Hus; Wallace, Gregory L; Yerys, Benjamin E; Maddox, Brenna B.; White, Susan W.; Popal, Haroon; Armour, Anna Chelsea; Miller, Judith; Herrington, John D.; Schultz, Robert T.; Martin, Alex; Anthony, Laura Gutermuth

2015-01-01

Recent updates have been proposed to the Autism Diagnostic Observation Schedule-2 Module 4 diagnostic algorithm. This new algorithm, however, has not yet been validated in an independent sample without intellectual disability (ID). This multi-site study compared the original and revised algorithms in individuals with ASD without ID. The revised algorithm demonstrated increased sensitivity, but lower specificity in the overall sample. Estimates were highest for females, individuals with a verbal IQ below 85 or above 115, and ages 16 and older. Best practice diagnostic procedures should include the Module 4 in conjunction with other assessment tools. Balancing needs for sensitivity and specificity depending on the purpose of assessment (e.g., clinical vs. research) and demographic characteristics mentioned above will enhance its utility. PMID:26385796

Validation of an image-based technique to assess the perceptual quality of clinical chest radiographs with an observer study

NASA Astrophysics Data System (ADS)

Lin, Yuan; Choudhury, Kingshuk R.; McAdams, H. Page; Foos, David H.; Samei, Ehsan

2014-03-01

We previously proposed a novel image-based quality assessment technique1 to assess the perceptual quality of clinical chest radiographs. In this paper, an observer study was designed and conducted to systematically validate this technique. Ten metrics were involved in the observer study, i.e., lung grey level, lung detail, lung noise, riblung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. For each metric, three tasks were successively presented to the observers. In each task, six ROI images were randomly presented in a row and observers were asked to rank the images only based on a designated quality and disregard the other qualities. A range slider on the top of the images was used for observers to indicate the acceptable range based on the corresponding perceptual attribute. Five boardcertificated radiologists from Duke participated in this observer study on a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions. The observer data were analyzed in terms of the correlations between the observer ranking orders and the algorithmic ranking orders. Based on the collected acceptable ranges, quality consistency ranges were statistically derived. The observer study showed that, for each metric, the averaged ranking orders of the participated observers were strongly correlated with the algorithmic orders. For the lung grey level, the observer ranking orders completely accorded with the algorithmic ranking orders. The quality consistency ranges derived from this observer study were close to these derived from our previous study. The observer study indicates that the proposed image-based quality assessment technique provides a robust reflection of the perceptual image quality of the clinical chest radiographs. The derived quality consistency ranges can be used to automatically predict the acceptability of a clinical chest radiograph.

Mapping forested wetlands in the Great Zhan River Basin through integrating optical, radar, and topographical data classification techniques.

PubMed

Na, X D; Zang, S Y; Wu, C S; Li, W L

2015-11-01

Knowledge of the spatial extent of forested wetlands is essential to many studies including wetland functioning assessment, greenhouse gas flux estimation, and wildlife suitable habitat identification. For discriminating forested wetlands from their adjacent land cover types, researchers have resorted to image analysis techniques applied to numerous remotely sensed data. While with some success, there is still no consensus on the optimal approaches for mapping forested wetlands. To address this problem, we examined two machine learning approaches, random forest (RF) and K-nearest neighbor (KNN) algorithms, and applied these two approaches to the framework of pixel-based and object-based classifications. The RF and KNN algorithms were constructed using predictors derived from Landsat 8 imagery, Radarsat-2 advanced synthetic aperture radar (SAR), and topographical indices. The results show that the objected-based classifications performed better than per-pixel classifications using the same algorithm (RF) in terms of overall accuracy and the difference of their kappa coefficients are statistically significant (p<0.01). There were noticeably omissions for forested and herbaceous wetlands based on the per-pixel classifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (p<0.01) of Kappa coefficient between results performed based on RF and KNN algorithms. The object-based classification using RF provided a more visually adequate distribution of interested land cover types, while the object classifications based on the KNN algorithm showed noticeably commissions for forested wetlands and omissions for agriculture land. This research proves that the object-based classification with RF using optical, radar, and topographical data improved the mapping accuracy of land covers and provided a feasible approach to discriminate the forested wetlands from the other land cover types in forestry area.

Comparison of C-arm Computed Tomography and Digital Subtraction Angiography in Patients with Chronic Thromboembolic Pulmonary Hypertension

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hinrichs, Jan B., E-mail: hinrichs.jan@mh-hannover.de; Marquardt, Steffen, E-mail: marquardt.steffen@mh-hannover.de; Falck, Christian von, E-mail: falck.christian.von@mh-hannover.de

PurposeTo assess the feasibility and diagnostic performance of contrast-enhanced, C-arm computed tomography (CACT) of the pulmonary arteries compared to digital subtraction angiography (DSA) in patients suffering from chronic thromboembolic pulmonary hypertension (CTEPH).MaterialsFifty-two patients with CTEPH underwent ECG-gated DSA and contrast-enhanced CACT. Two readers (R1, R2) independently evaluated pulmonary artery segments and their sub-segmental branching using DSA and CACT for optimal image quality. Afterwards, the diagnostic findings, i.e., intraluminal filling defects, stenosis, and occlusion, were compared. Inter-modality and inter-observer agreement was calculated, and subsequently consensus reading was done and correlated to a reference standard representing the overall consensus of both modalities.more » Fisher’s exact test and Cohen’s Kappa were applied.ResultsA total of 1352 pulmonary segments were evaluated, of which 1255 (92.8 %) on DSA and 1256 (92.9 %) on CACT were rated to be fully diagnostic. The main causes of the non-diagnostic image quality were motion artifacts on CACT (R1:37, R2:78) and insufficient contrast enhancement on DSA (R1:59, R2:38). Inter-observer agreement was good for DSA (κ = 0.74) and CACT (κ = 0.75), while inter-modality agreement was moderate (R1: κ = 0.46, R2: κ = 0.47). Compared to the reference standard, the inter-modality agreement for CACT was excellent (κ = 0.96), whereas it was inferior for DSA (κ = 0.61) due to the higher number of abnormal consensus findings read as normal on DSA.ConclusionCACT of the pulmonary arteries is feasible and provides additional information to DSA. CACT has the potential to improve the diagnostic work-up of patients with CTEPH and may be particularly useful prior to surgical or interventional treatment.« less

Dermatologic and dental aspects of the 2012 International Tuberous Sclerosis Complex Consensus Statements.

PubMed

Teng, Joyce M C; Cowen, Edward W; Wataya-Kaneda, Mari; Gosnell, Elizabeth S; Witman, Patricia M; Hebert, Adelaide A; Mlynarczyk, Greg; Soltani, Keyoumars; Darling, Thomas N

2014-10-01

The 2012 International Tuberous Sclerosis Complex Clinical Consensus Conference was convened to update the last consensus statement in 1998. Skin and dental lesions are common in tuberous sclerosis complex (TSC) and are a frequent concern for patients. Recognition of these lesions is imperative for early diagnosis, given the treatment advances that may improve patient outcomes. To detail recommendations for the diagnosis, surveillance, and management of skin and dental lesions in TSC. The TSC Dermatology and Dentistry Subcommittee, 1 of 12 subcommittees, reviewed the relevant literature from 1997 to 2012. A consensus on skin and dental issues was achieved within the Dermatology and Dentistry Subcommittee before recommendations were presented, discussed, and agreed on in a group meeting of all subcommittees from June 14 to 15, 2012. Skin and dental findings comprise 4 of 11 major features and 3 of 6 minor features in the diagnostic criteria. A definite diagnosis of TSC is defined as the presence of at least 2 major features or 1 major and 2 or more minor features; in addition, a pathological mutation in TSC1 or TSC2 is diagnostic. Skin and oral examinations should be performed annually and every 3 to 6 months, respectively. Intervention may be indicated for TSC skin or oral lesions that are bleeding, symptomatic, disfiguring, or negatively affecting function. Options presented include surgical excision, laser(s), or use of a mammalian target of rapamycin inhibitor.

Clinical algorithms to aid osteoarthritis guideline dissemination.

PubMed

Meneses, S R F; Goode, A P; Nelson, A E; Lin, J; Jordan, J M; Allen, K D; Bennell, K L; Lohmander, L S; Fernandes, L; Hochberg, M C; Underwood, M; Conaghan, P G; Liu, S; McAlindon, T E; Golightly, Y M; Hunter, D J

2016-09-01

Numerous scientific organisations have developed evidence-based recommendations aiming to optimise the management of osteoarthritis (OA). Uptake, however, has been suboptimal. The purpose of this exercise was to harmonize the recent recommendations and develop a user-friendly treatment algorithm to facilitate translation of evidence into practice. We updated a previous systematic review on clinical practice guidelines (CPGs) for OA management. The guidelines were assessed using the Appraisal of Guidelines for Research and Evaluation for quality and the standards for developing trustworthy CPGs as established by the National Academy of Medicine (NAM). Four case scenarios and algorithms were developed by consensus of a multidisciplinary panel. Sixteen guidelines were included in the systematic review. Most recommendations were directed toward physicians and allied health professionals, and most had multi-disciplinary input. Analysis for trustworthiness suggests that many guidelines still present a lack of transparency. A treatment algorithm was developed for each case scenario advised by recommendations from guidelines and based on panel consensus. Strategies to facilitate the implementation of guidelines in clinical practice are necessary. The algorithms proposed are examples of how to apply recommendations in the clinical context, helping the clinician to visualise the patient flow and timing of different treatment modalities. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Image quality enhancement for skin cancer optical diagnostics

NASA Astrophysics Data System (ADS)

Bliznuks, Dmitrijs; Kuzmina, Ilona; Bolocko, Katrina; Lihachev, Alexey

2017-12-01

The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task - skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm - low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results' quality for images without illumination defects. Current filtering algorithm requires empirical tuning of filter parameters. Further work needed to test the algorithm in other biophotonic applications and propose automatic filter parameter selection.

The Autism Diagnostic Observation Schedule, Module 4: Revised Algorithm and Standardized Severity Scores

PubMed Central

Hus, Vanessa; Lord, Catherine

2014-01-01

The Autism Diagnostic Observation Schedule, 2nd Edition includes revised diagnostic algorithms and standardized severity scores for modules used to assess children and adolescents of varying language abilities. Comparable revisions have not yet been applied to the Module 4, used with verbally fluent adults. The current study revises the Module 4 algorithm and calibrates raw overall and domain totals to provide metrics of ASD symptom severity. Sensitivity and specificity of the revised Module 4 algorithm exceeded 80% in the overall sample. Module 4 calibrated severity scores provide quantitative estimates of ASD symptom severity that are relatively independent of participant characteristics. These efforts increase comparability of ADOS scores across modules and should facilitate efforts to increase understanding of adults with ASD. PMID:24590409

ANMCO/GICR-IACPR/SICI-GISE Consensus Document: the clinical management of chronic ischaemic cardiomyopathy

PubMed Central

Gulizia, Michele Massimo; Colivicchi, Furio; Di Lenarda, Andrea; Musumeci, Giuseppe; Faggiano, Pompilio Massimo; Abrignani, Maurizio Giuseppe; Rossini, Roberta; Fattirolli, Francesco; Valente, Serafina; Mureddu, Gian Francesco; Temporelli, Pier Luigi; Olivari, Zoran; Amico, Antonio Francesco; Casolo, Giancarlo; Fresco, Claudio; Menozzi, Alberto; Nardi, Federico

2017-01-01

Stable coronary artery disease (CAD) is a clinical entity of great epidemiological importance. It is becoming increasingly common due to the longer life expectancy, being strictly related to age and to advances in diagnostic techniques and pharmacological and non-pharmacological interventions. Stable CAD encompasses a variety of clinical and anatomic presentations, making the identification of its clinical and anatomical features challenging. Therapeutic interventions should be defined on an individual basis according to the patient’s risk profile. To this aim, management flow charts have been reviewed based on sustainability and appropriateness derived from recent evidence. Special emphasis has been placed on non-pharmacological interventions, stressing the importance of lifestyle changes, including smoking cessation, regular physical activity, and diet. Adherence to therapy as an emerging risk factor is also discussed. PMID:28533729

A Simple, Evidence-Based Approach to Help Guide Diagnosis of Heart Failure with Preserved Ejection Fraction.

PubMed

Reddy, Yogesh N V; Carter, Rickey E; Obokata, Masaru; Redfield, Margaret M; Borlaug, Barry A

2018-05-23

Background -Diagnosis of heart failure with preserved ejection fraction (HFpEF) is challenging in euvolemic patients with dyspnea, and no evidence-based criteria are available. We sought to develop and then validate non-invasive diagnostic criteria that could be used to estimate the likelihood that HFpEF is present among patients with unexplained dyspnea in order to guide further testing. Methods -Consecutive patients with unexplained dyspnea referred for invasive hemodynamic exercise testing were retrospectively evaluated. Diagnosis of HFpEF (case) or non-cardiac dyspnea (control) was ascertained by invasive hemodynamic exercise testing. Logistic regression was performed to evaluate the ability of clinical findings to discriminate cases from controls. A scoring system was developed and then validated in a separate test cohort. Results -The derivation cohort included 414 consecutive patients (267 HFpEF and 147 controls, HFpEF prevalence 64%). The test cohort included 100 consecutive patients (61 HFpEF, prevalence 61%). Obesity, atrial fibrillation, age>60 years, treatment with 2 or more antihypertensives, echocardiographic E/e' ratio>9 and echocardiographic pulmonary artery systolic pressure>35 mmHg were selected as the final set of predictive variables. A weighted score based on these six variables was used to create a composite score (H 2 FPEF score) ranging from 0-9. The odds of HFpEF doubled for each 1 unit score increase [OR 1.98 [1.74-2.30], p<0.0001], with an AUC of 0.841 (p<0.0001). The H 2 FPEF score was superior to a currently-used algorithm based upon expert consensus (increase in AUC of +0.169 [+0.120 to +0.217], p<0.0001). Performance in the independent test cohort was maintained [AUC 0.886, p<0.0001]. Conclusions -The H 2 FPEF score, which relies upon simple clinical characteristics and echocardiography, enables discrimination of HFpEF from non-cardiac causes of dyspnea, and can assist in determination of the need for further diagnostic testing in the evaluation of patients with unexplained exertional dyspnea.

Diagnostic Accuracy of a New Cardiac Electrical Biomarker for Detection of Electrocardiogram Changes Suggestive of Acute Myocardial Ischemic Injury

PubMed Central

Schreck, David M; Fishberg, Robert D

2014-01-01

Objective A new cardiac “electrical” biomarker (CEB) for detection of 12-lead electrocardiogram (ECG) changes indicative of acute myocardial ischemic injury has been identified. Objective was to test CEB diagnostic accuracy. Methods This is a blinded, observational retrospective case-control, noninferiority study. A total of 508 ECGs obtained from archived digital databases were interpreted by cardiologist and emergency physician (EP) blinded reference standards for presence of acute myocardial ischemic injury. CEB was constructed from three ECG cardiac monitoring leads using nonlinear modeling. Comparative active controls included ST voltage changes (J-point, ST area under curve) and a computerized ECG interpretive algorithm (ECGI). Training set of 141 ECGs identified CEB cutoffs by receiver-operating-characteristic (ROC) analysis. Test set of 367 ECGs was analyzed for validation. Poor-quality ECGs were excluded. Sensitivity, specificity, and negative and positive predictive values were calculated with 95% confidence intervals. Adjudication was performed by consensus. Results CEB demonstrated noninferiority to all active controls by hypothesis testing. CEB adjudication demonstrated 85.3–94.4% sensitivity, 92.5–93.0% specificity, 93.8–98.6% negative predictive value, and 74.6–83.5% positive predictive value. CEB was superior against all active controls in EP analysis, and against ST area under curve and ECGI by cardiologist. Conclusion CEB detects acute myocardial ischemic injury with high diagnostic accuracy. CEB is instantly constructed from three ECG leads on the cardiac monitor and displayed instantly allowing immediate cost-effective identification of patients with acute ischemic injury during cardiac rhythm monitoring. PMID:24118724

The Autism Diagnostic Observation Schedule, Module 4: Application of the Revised Algorithms in an Independent, Well-Defined, Dutch Sample (N = 93)

ERIC Educational Resources Information Center

de Bildt, Annelies; Sytema, Sjoerd; Meffert, Harma; Bastiaansen, Jojanneke A. C. J.

2016-01-01

This study examined the discriminative ability of the revised Autism Diagnostic Observation Schedule module 4 algorithm (Hus and Lord in "J Autism Dev Disord" 44(8):1996-2012, 2014) in 93 Dutch males with Autism Spectrum Disorder (ASD), schizophrenia, psychopathy or controls. Discriminative ability of the revised algorithm ASD cut-off…

Diagnostic value of a pancreatic mass on computed tomography in patients undergoing pancreatoduodenectomy for presumed pancreatic cancer.

PubMed

Gerritsen, Arja; Bollen, Thomas L; Nio, C Yung; Molenaar, I Quintus; Dijkgraaf, Marcel G W; van Santvoort, Hjalmar C; Offerhaus, G Johan; Brosens, Lodewijk A; Biermann, Katharina; Sieders, Egbert; de Jong, Koert P; van Dam, Ronald M; van der Harst, Erwin; van Goor, Harry; van Ramshorst, Bert; Bonsing, Bert A; de Hingh, Ignace H; Gerhards, Michael F; van Eijck, Casper H; Gouma, Dirk J; Borel Rinkes, Inne H M; Busch, Olivier R C; Besselink, Marc G H

2015-07-01

Previous studies have shown that 5-14% of patients undergoing pancreatoduodenectomy for suspected malignancy ultimately are diagnosed with benign disease. A "pancreatic mass" on computed tomography (CT) is considered to be the strongest predictor of malignancy, but studies describing its diagnostic value are lacking. The aim of this study was to determine the diagnostic value of a pancreatic mass on CT in patients with presumed pancreatic cancer, as well as the interobserver agreement among radiologists and the additional value of reassessment by expert-radiologists. Reassessment of preoperative CT scans was performed within a previously described multicenter retrospective cohort study in 344 patients undergoing pancreatoduodenectomy for suspected malignancy (2003-2010). Preoperative CT scans were reassessed by 2 experienced abdominal radiologists separately and subsequently in a consensus meeting, after defining a pancreatic mass as "a measurable space occupying soft tissue density, except for an enlarged papilla or focal steatosis". CT scans of 86 patients with benign and 258 patients with (pre)malignant disease were reassessed. In 66% of patients a pancreatic mass was reported in the original CT report, versus 48% and 50% on reassessment by the 2 expert radiologists separately and 44% in consensus (P < .001 vs original report). Interobserver agreement between the original CT report and expert consensus was fair (kappa = 0.32, 95% confidence interval 0.23-0.42). Among both expert-radiologists agreement was moderate (kappa = 0.47, 95% confidence interval 0.38-0.56), with disagreement on the presence of a pancreatic mass in 29% of cases. The specificity for malignancy of pancreatic masses identified in expert consensus was twice as high compared with the original CT report (87% vs 42%, respectively). Positive predictive value increased to 98% after expert consensus, but negative predictive value was low (12%). Clinicians need to be aware of potential considerable disagreement among radiologists about the presence of a pancreatic mass. The specificity for malignancy doubled by expert radiologist reassessment when a uniform definition of "pancreatic mass" was used. Copyright © 2015 Elsevier Inc. All rights reserved.

EMQN best practice guidelines for the molecular genetic diagnosis of hereditary hemochromatosis (HH).

PubMed

Porto, Graça; Brissot, Pierre; Swinkels, Dorine W; Zoller, Heinz; Kamarainen, Outi; Patton, Simon; Alonso, Isabel; Morris, Michael; Keeney, Steve

2016-04-01

Molecular genetic testing for hereditary hemochromatosis (HH) is recognized as a reference test to confirm the diagnosis of suspected HH or to predict its risk. The vast majority (typically >90%) of patients with clinically characterized HH are homozygous for the p.C282Y variant in the HFE gene, referred to as HFE-related HH. Since 1996, HFE genotyping was implemented in diagnostic algorithms for suspected HH, allowing its early diagnosis and prevention. However, the penetrance of disease in p.C282Y homozygotes is incomplete. Hence, homozygosity for p.C282Y is not sufficient to diagnose HH. Neither is p.C282Y homozygosity required for diagnosis as other rare forms of HH exist, generally referred to as non-HFE-related HH. These pose significant challenges when defining criteria for referral, testing protocols, interpretation of test results and reporting practices. We present best practice guidelines for the molecular genetic diagnosis of HH where recommendations are classified, as far as possible, according to the level and strength of evidence. For clarification, the guidelines' recommendations are preceded by a detailed description of the methodology and results obtained with a series of actions taken in order to achieve a wide expert consensus, namely: (i) a survey on the current practices followed by laboratories offering molecular diagnosis of HH; (ii) a systematic literature search focused on some identified controversial topics; (iii) an expert Best Practice Workshop convened to achieve consensus on the practical recommendations included in the guidelines.

EMQN best practice guidelines for the molecular genetic diagnosis of hereditary hemochromatosis (HH)

PubMed Central

Porto, Graça; Brissot, Pierre; Swinkels, Dorine W; Zoller, Heinz; Kamarainen, Outi; Patton, Simon; Alonso, Isabel; Morris, Michael; Keeney, Steve

2016-01-01

Molecular genetic testing for hereditary hemochromatosis (HH) is recognized as a reference test to confirm the diagnosis of suspected HH or to predict its risk. The vast majority (typically >90%) of patients with clinically characterized HH are homozygous for the p.C282Y variant in the HFE gene, referred to as HFE-related HH. Since 1996, HFE genotyping was implemented in diagnostic algorithms for suspected HH, allowing its early diagnosis and prevention. However, the penetrance of disease in p.C282Y homozygotes is incomplete. Hence, homozygosity for p.C282Y is not sufficient to diagnose HH. Neither is p.C282Y homozygosity required for diagnosis as other rare forms of HH exist, generally referred to as non-HFE-related HH. These pose significant challenges when defining criteria for referral, testing protocols, interpretation of test results and reporting practices. We present best practice guidelines for the molecular genetic diagnosis of HH where recommendations are classified, as far as possible, according to the level and strength of evidence. For clarification, the guidelines' recommendations are preceded by a detailed description of the methodology and results obtained with a series of actions taken in order to achieve a wide expert consensus, namely: (i) a survey on the current practices followed by laboratories offering molecular diagnosis of HH; (ii) a systematic literature search focused on some identified controversial topics; (iii) an expert Best Practice Workshop convened to achieve consensus on the practical recommendations included in the guidelines. PMID:26153218

Routine Use of Adjunctive p16 Immunohistochemistry Improves Diagnostic Agreement of Cervical Biopsy Interpretation: Results From the CERTAIN Study.

PubMed

Stoler, Mark H; Wright, Thomas C; Ferenczy, Alex; Ranger-Moore, James; Fang, Qijun; Kapadia, Monesh; Ridder, Ruediger

2018-04-24

The diagnosis of squamous intraepithelial lesions in cervical tissue specimens is subject to substantial variability. Adjunctive immunohistochemical (IHC) staining for p16 has been shown to add objective biomarker information to morphologic interpretation of hematoxylin and eosin (H&E)-stained tissues. In the CERvical Tissue AdjunctIve aNalysis (CERTAIN) study, we systematically analyzed the impact of adjunctive p16 IHC on the accuracy (agreement with reference pathology results) of diagnosing cervical intraepithelial neoplasia of grade 2 or worse (CIN2+) in the United States. Eleven hundred cervical biopsies were divided into 4 sets of 275 cases by stratified randomization. All H&E slides from each set were interpreted by 17 to 18 individual surgical pathologists, for a total of 19,250 reads by 70 surgical pathologists. After a wash-out period and blinding to original results, cases were re-read by the same pathologists using H&E+p16-stained slides. Using expert consensus diagnoses on H&E+p16 as reference, adjunctive p16 IHC use significantly improved diagnostic agreement of surgical pathologists by 4.7% (95% confidence interval [CI], 3.9, 5.4; P<0.0001). This improvement was driven by an increase of 11.5% (95% CI, 9.3, 13.5; P<0.0001) in sensitivity and an increase of 3.0% (95% CI, 2.2, 3.7; P<0.0001) in specificity. Diagnostic performance was significantly increased as well when expert consensus diagnoses established on H&E only was used as reference. Furthermore, interobserver reliability improved significantly from moderate (H&E: κ=0.58) to substantial (H&E+p16: κ=0.73; P<0.0001). Adjunctive use of p16 IHC provides more accurate and reproducible diagnostic results in the interpretation of cervical biopsies, ensuring that more patients are treated correctly without treating more patients.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

Diagnostic accuracy of combined FP-CIT, IBZM, and MIBG scintigraphy in the differential diagnosis of degenerative parkinsonism: a multidimensional statistical approach.

PubMed

Südmeyer, Martin; Antke, Christina; Zizek, Tanja; Beu, Markus; Nikolaus, Susanne; Wojtecki, Lars; Schnitzler, Alfons; Müller, Hans-Wilhelm

2011-05-01

In vivo molecular imaging of pre- and postsynaptic nigrostriatal neuronal degeneration and sympathetic cardiac innervation with SPECT is used to distinguish idiopathic Parkinson disease (PD) from atypical parkinsonian disorder (APD). However, the diagnostic accuracy of these imaging approaches as stand-alone procedures is often unsatisfying. The aim of this study was therefore to evaluate to which extent diagnostic accuracy can be increased by their combined use together with a multidimensional statistical algorithm. The SPECT radiotracers (123)I-(S)-2-hydroxy-3-iodo-6-methoxy-N-[1-ethyl-2-pyrrodinyl)-methyl]benzamide (IBZM), (123)I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropan (FP-CIT), and meta-(123)I-iodobenzylguanidine (MIBG) were used to assess striatal postsynaptic D(2) receptor binding, striatal presynaptic dopamine transporter binding, and myocardial adrenergic innervation, respectively. Thirty-one PD and 17 APD patients were prospectively investigated. PD and APD diagnoses were established using consensus criteria and reevaluated after 37.4 ± 12.4 and 26 ± 11.6 mo in PD and APD, respectively. Test accuracy (TA) for PD-APD differentiation was computed for all logical (Boolean) combinations of imaging modalities by receiver-operating-characteristic analysis--that is, after multidimensional optimization of cutoff values. Analysis showed moderate TA for PD-APD differentiation using each molecular approach alone (IBZM, 79%; MIBG, 73%; and FP-CIT, 73%). For combined use, the highest TA resulted under the assumption that at least 2 of the 3 biologic markers had to be positive for APD using the following cutoff values: 1.46 or less for IBZM, less than 2.10 for FP-CIT, and greater than 1.43 for MIBG. This algorithm distinguished APD from PD with a sensitivity of 94%, specificity of 94% (TA, 94%), positive predictive value of 89%, and negative predictive value of 97%. Results suggest that the multidimensional combination of FP-CIT, IBZM, and MIBG scintigraphy is likely to significantly increase TA in differentiating PD from APD. The differential diagnosis of degenerative parkinsonism may thus be facilitated.

3rd European Evidence-based Consensus on the Diagnosis and Management of Crohn's Disease 2016: Part 2: Surgical Management and Special Situations.

PubMed

Gionchetti, Paolo; Dignass, Axel; Danese, Silvio; Magro Dias, Fernando José; Rogler, Gerhard; Lakatos, Péter Laszlo; Adamina, Michel; Ardizzone, Sandro; Buskens, Christianne J; Sebastian, Shaji; Laureti, Silvio; Sampietro, Gianluca M; Vucelic, Boris; van der Woude, C Janneke; Barreiro-de Acosta, Manuel; Maaser, Christian; Portela, Francisco; Vavricka, Stephan R; Gomollón, Fernando

2017-02-01

This paper is the second in a series of two publications relating to the European Crohn's and Colitis Organisation [ECCO] evidence-based consensus on the diagnosis and management of Crohn's disease [CD] and concerns the surgical management of CD as well as special situations including management of perianal CD and extraintestinal manifestations. Diagnostic approaches and medical management of CD of this ECCO Consensus are covered in the first paper [Gomollon et al JCC 2016]. Copyright © 2016 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

[GEITDAH consensus on conduct disorders in children and adolescents].

PubMed

Sasot-Llevadot, Jordi; Ibáñez-Bordas, Rosa M; Soto-López, Antonio; Montañés-Rada, Francisco; Gastaminza-Pérez, Xavier; Alda-Díez, José A; Cantó-Díez, Tomás; Catalá, Miguel A; Ferrin-Erdozáin, Maite; García-Giral, Marta; Graell-Bernal, Montserrat; Granada-Jiménez, Olvido; Herreros-Rodríguez, Óscar; Mardomingo-Sanz, María J; Mojarro-Práxedes, Dolores; Morey-Canyelles, Jaume; Ortiz-Guerra, Juan; Pàmies-Massana, Montserrat; Rey-Sánchez, Francisco; Romera-Torrens, María; Rubio-Morell, Belén; Ruiz-Lázaro, Pedro M; Ruiz-Sanz, Francisco

2015-08-16

In this paper, the Special Interest Group on Attention Deficit Hyperactivity Disorder (GEITDAH, from its name in Spanish) presents a consensus reached by experts from all over Spain on conduct disorders in children and adolescents. Following the initial work by the team at the Pedopsychiatry Unit at the Quiron-Teknon Hospital in Barcelona, agreements have been reached on a number of basic aspects that could be the starting point for future consensuses. A top priority aim of the work was also to update the criteria in the Diagnostic and statistical manual of mental disorders, fifth edition, for conduct disorders in children and adolescents, together with their comorbidity with attention deficit hyperactivity disorder.

Major incident triage: A consensus based definition of the essential life-saving interventions during the definitive care phase of a major incident.

PubMed

Vassallo, James; Smith, Jason E; Bruijns, Stevan R; Wallis, Lee A

2016-09-01

Triage is a key principle in the effective management of major incidents. The process currently relies on algorithms assigning patients to specific triage categories; there is, however, little guidance as to what these categories represent. Previously, these algorithms were validated against injury severity scores, but it is accepted now that the need for life-saving intervention is a more important outcome. However, the definition of a life-saving intervention is unclear. The aim of this study was to define what constitutes a life-saving intervention, in order to facilitate the definition of an adult priority one patient during the definitive care phase of a major incident. We conducted a modified Delphi study, using a panel of subject matter experts drawn from the United Kingdom and Republic of South Africa with a background in Emergency Care or Major Incident Management. The study was conducted using an online survey tool, over three rounds between July and December 2013. A four point Likert scale was used to seek consensus for 50 possible interventions, with a consensus level set at 70%. 24 participants completed all three rounds of the Delphi, with 32 life-saving interventions reaching consensus. This study provides a consensus definition of what constitutes a life-saving intervention in the context of an adult, priority one patient during the definitive care phase of a major incident. The definition will contribute to further research into major incident triage, specifically in terms of validation of an adult major incident triage tool. Copyright © 2016 Elsevier Ltd. All rights reserved.

Challenges in Analyzing and Representing Cloud Microphysical Data Measured with Airborne Cloud Probes

NASA Astrophysics Data System (ADS)

Baumgardner, D.; Freer, M.; McFarquhar, G. M.; Heymsfield, A.; Cziczo, D. J.

2014-12-01

There are a variety of in-situ instruments that are deployed on aircraft for measuring cloud properties, some of which provide data which are used to produce number and mass concentrations of water droplets and ice crystals and their size and shape distributions. Each of these instruments has its strengths and limitations that must be recognized and taken into account during analysis of the data. Various processing techniques have been developed by different groups and techniques implemented to partially correct for the known uncertainties and limitations. The cloud measurement community has in general acknowledged the various issues associated with these instruments and numerous studies have published processing algorithms that seek to improve data quality; however, there has not been a forum in which these various algorithms and processing techniques have been discussed and consensus reached both on optimum analysis strategy and on quantification of uncertainties on the derived data products. Prior to the 2014 AMS Cloud Physics Conference, a study was conducted in which many data sets taken from various aircraft (NCAR-130, North Dakota Citation, Wyoming King Air and FAAM BAE-146) and many instruments (FSSP, CDP, SID, 2D-C/P, CIP/PIP, 2D-S, CPI, Nevzorov Probe and King Hot-wire LWC sensor) were processed by more than 20 individuals or groups to produce a large number of derived products (size distributions, ice fraction, number and mass concentrations, CCN/IN concentrations and median volume diameter). Each person or group that processed a selected data set used their own software and algorithm to produce a secondary data file with derived parameters whose name was encoded to conceal the source of the file so that this was a blind comparison. The workshop that was convened July 5 and 6, 2014, presented the results of the evaluation of the derived products with respect to individual instruments as well as the types of conditions under which the measurements were made. This comparison will ultimately allow quantifying the error bars of derived parameters as a function of the conditions in which the observations are made. The results of this evaluation and the recommendations that evolved from the workshop will be summarized in this presentation.

Achieving routine submillisievert CT scanning: report from the summit on management of radiation dose in CT.

PubMed

McCollough, Cynthia H; Chen, Guang Hong; Kalender, Willi; Leng, Shuai; Samei, Ehsan; Taguchi, Katsuyuki; Wang, Ge; Yu, Lifeng; Pettigrew, Roderic I

2012-08-01

This Special Report presents the consensus of the Summit on Management of Radiation Dose in Computed Tomography (CT) (held in February 2011), which brought together participants from academia, clinical practice, industry, and regulatory and funding agencies to identify the steps required to reduce the effective dose from routine CT examinations to less than 1 mSv. The most promising technologies and methods discussed at the summit include innovations and developments in x-ray sources; detectors; and image reconstruction, noise reduction, and postprocessing algorithms. Access to raw projection data and standard data sets for algorithm validation and optimization is a clear need, as is the need for new, clinically relevant metrics of image quality and diagnostic performance. Current commercially available techniques such as automatic exposure control, optimization of tube potential, beam-shaping filters, and dynamic z-axis collimators are important, and education to successfully implement these methods routinely is critically needed. Other methods that are just becoming widely available, such as iterative reconstruction, noise reduction, and postprocessing algorithms, will also have an important role. Together, these existing techniques can reduce dose by a factor of two to four. Technical advances that show considerable promise for additional dose reduction but are several years or more from commercial availability include compressed sensing, volume of interest and interior tomography techniques, and photon-counting detectors. This report offers a strategic roadmap for the CT user and research and manufacturer communities toward routinely achieving effective doses of less than 1 mSv, which is well below the average annual dose from naturally occurring sources of radiation.

Diagnosis, monitoring, and treatment of primary ciliary dyskinesia: PCD foundation consensus recommendations based on state of the art review.

PubMed

Shapiro, Adam J; Zariwala, Maimoona A; Ferkol, Thomas; Davis, Stephanie D; Sagel, Scott D; Dell, Sharon D; Rosenfeld, Margaret; Olivier, Kenneth N; Milla, Carlos; Daniel, Sam J; Kimple, Adam J; Manion, Michele; Knowles, Michael R; Leigh, Margaret W

2016-02-01

Primary ciliary dyskinesia (PCD) is a genetically heterogeneous, rare lung disease resulting in chronic oto-sino-pulmonary disease in both children and adults. Many physicians incorrectly diagnose PCD or eliminate PCD from their differential diagnosis due to inexperience with diagnostic testing methods. Thus far, all therapies used for PCD are unproven through large clinical trials. This review article outlines consensus recommendations from PCD physicians in North America who have been engaged in a PCD centered research consortium for the last 10 years. These recommendations have been adopted by the governing board of the PCD Foundation to provide guidance for PCD clinical centers for diagnostic testing, monitoring, and appropriate short and long-term therapeutics in PCD patients. © 2015 The Authors. Pediatric Pulmonology Published by Wiley Periodicals, Inc.

Neurophysiological localisation of ulnar neuropathy at the elbow: Validation of diagnostic criteria developed by a taskforce of the Danish Society of clinical neurophysiology.

PubMed

Pugdahl, K; Beniczky, S; Wanscher, B; Johnsen, B; Qerama, E; Ballegaard, M; Benedek, K; Juhl, A; Ööpik, M; Selmar, P; Sønderborg, J; Terney, D; Fuglsang-Frederiksen, A

2017-11-01

This study validates consensus criteria for localisation of ulnar neuropathy at elbow (UNE) developed by a taskforce of the Danish Society of Clinical Neurophysiology and compares them to the existing criteria from the American Association of Neuromuscular and Electrodiagnostic Medicine (AANEM). The Danish criteria are based on combinations of conduction slowing in the segments of the elbow and forearm expressed in Z-scores, and difference between the segments in m/s. Examining fibres to several muscles and sensory fibres can increase the certainty of the localisation. Diagnostic accuracy for UNE was evaluated on 181 neurophysiological studies of the ulnar nerve from 171 peer-reviewed patients from a mixed patient-group. The diagnostic reference standard was the consensus diagnosis based on all available clinical, laboratory, and electrodiagnostic information reached by a group of experienced Danish neurophysiologists. The Danish criteria had high specificity (98.4%) and positive predictive value (PPV) (95.2%) and fair sensitivity (76.9%). Compared to the AANEM criteria, the Danish criteria had higher specificity (p<0.001) and lower sensitivity (p=0.02). The Danish consensus criteria for UNE are very specific and have high PPV. The Danish criteria for UNE are reliable and well suited for use in different centres as they are based on Z-scores. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Saptarshi

Multi-agent systems are widely used for constructing a desired formation shape, exploring an area, surveillance, coverage, and other cooperative tasks. This dissertation introduces novel algorithms in the three main areas of shape formation, distributed estimation, and attitude control of large-scale multi-agent systems. In the first part of this dissertation, we address the problem of shape formation for thousands to millions of agents. Here, we present two novel algorithms for guiding a large-scale swarm of robotic systems into a desired formation shape in a distributed and scalable manner. These probabilistic swarm guidance algorithms adopt an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled using tunable Markov chains. In the first algorithm - Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) - each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain that is constructed in real-time using feedback from the current swarm distribution. This PSG-IMC algorithm minimizes the expected cost of the transitions required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes, and can also be adapted for area exploration applications. In the second algorithm - Probabilistic Swarm Guidance using Optimal Transport (PSG-OT) - each agent determines its bin transition probabilities by solving an optimal transport problem, which is recast as a linear program. In the presence of perfect feedback of the current swarm distribution, this algorithm minimizes the given cost function, guarantees faster convergence, reduces the number of transitions for achieving the desired formation, and is robust to disturbances or damages to the formation. We demonstrate the effectiveness of these two proposed swarm guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees global exponential convergence of tracking errors with finite-gain Lp stability in the presence of modeling uncertainties and disturbances, and reduces the resultant disturbance torque. Further, this control law permits the use of any attitude representation and its integral control formulation eliminates any constant disturbance. Under small uncertainties, the best strategy for stabilizing the combined system is to track a fuel-optimal reference trajectory using this nonlinear control law, because it consumes the least amount of fuel. In the presence of large uncertainties, the most effective strategy is to track the derivative plus proportional-derivative based reference trajectory, because it reduces the resultant disturbance torque. The effectiveness of the proposed attitude control law is demonstrated by using results of numerical simulation based on an Asteroid Redirect Mission concept. The new algorithms proposed in this dissertation will facilitate the development of versatile autonomous multi-agent systems that are capable of performing a variety of complex tasks in a robust and scalable manner.

Current trends in tendinopathy: consensus of the ESSKA basic science committee. Part I: biology, biomechanics, anatomy and an exercise-based approach.

PubMed

Abat, F; Alfredson, H; Cucchiarini, M; Madry, H; Marmotti, A; Mouton, C; Oliveira, J M; Pereira, H; Peretti, G M; Romero-Rodriguez, D; Spang, C; Stephen, J; van Bergen, C J A; de Girolamo, L

2017-12-01

Chronic tendinopathies represent a major problem in the clinical practice of sports orthopaedic surgeons, sports doctors and other health professionals involved in the treatment of athletes and patients that perform repetitive actions. The lack of consensus relative to the diagnostic tools and treatment modalities represents a management dilemma for these professionals. With this review, the purpose of the ESSKA Basic Science Committee is to establish guidelines for understanding, diagnosing and treating this complex pathology.

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Clinical study of quantitative diagnosis of early cervical cancer based on the classification of acetowhitening kinetics

NASA Astrophysics Data System (ADS)

Wu, Tao; Cheung, Tak-Hong; Yim, So-Fan; Qu, Jianan Y.

2010-03-01

A quantitative colposcopic imaging system for the diagnosis of early cervical cancer is evaluated in a clinical study. This imaging technology based on 3-D active stereo vision and motion tracking extracts diagnostic information from the kinetics of acetowhitening process measured from the cervix of human subjects in vivo. Acetowhitening kinetics measured from 137 cervical sites of 57 subjects are analyzed and classified using multivariate statistical algorithms. Cross-validation methods are used to evaluate the performance of the diagnostic algorithms. The results show that an algorithm for screening precancer produced 95% sensitivity (SE) and 96% specificity (SP) for discriminating normal and human papillomavirus (HPV)-infected tissues from cervical intraepithelial neoplasia (CIN) lesions. For a diagnostic algorithm, 91% SE and 90% SP are achieved for discriminating normal tissue, HPV infected tissue, and low-grade CIN lesions from high-grade CIN lesions. The results demonstrate that the quantitative colposcopic imaging system could provide objective screening and diagnostic information for early detection of cervical cancer.

Sampled-data-based consensus and containment control of multiple harmonic oscillators: A motion-planning approach

NASA Astrophysics Data System (ADS)

Liu, Yongfang; Zhao, Yu; Chen, Guanrong

2016-11-01

This paper studies the distributed consensus and containment problems for a group of harmonic oscillators with a directed communication topology. First, for consensus without a leader, a class of distributed consensus protocols is designed by using motion planning and Pontryagin's principle. The proposed protocol only requires relative information measurements at the sampling instants, without requiring information exchange over the sampled interval. By using stability theory and the properties of stochastic matrices, it is proved that the distributed consensus problem can be solved in the motion planning framework. Second, for the case with multiple leaders, a class of distributed containment protocols is developed for followers such that their positions and velocities can ultimately converge to the convex hull formed by those of the leaders. Compared with the existing consensus algorithms, a remarkable advantage of the proposed sampled-data-based protocols is that the sampling periods, communication topologies and control gains are all decoupled and can be separately designed, which relaxes many restrictions in controllers design. Finally, some numerical examples are given to illustrate the effectiveness of the analytical results.

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

FPGA based charge acquisition algorithm for soft x-ray diagnostics system

NASA Astrophysics Data System (ADS)

Wojenski, A.; Kasprowicz, G.; Pozniak, K. T.; Zabolotny, W.; Byszuk, A.; Juszczyk, B.; Kolasinski, P.; Krawczyk, R. D.; Zienkiewicz, P.; Chernyshova, M.; Czarski, T.

2015-09-01

Soft X-ray (SXR) measurement systems working in tokamaks or with laser generated plasma can expect high photon fluxes. Therefore it is necessary to focus on data processing algorithms to have the best possible efficiency in term of processed photon events per second. This paper refers to recently designed algorithm and data-flow for implementation of charge data acquisition in FPGA. The algorithms are currently on implementation stage for the soft X-ray diagnostics system. In this paper despite of the charge processing algorithm is also described general firmware overview, data storage methods and other key components of the measurement system. The simulation section presents algorithm performance and expected maximum photon rate.

Familial Hypercholesterolaemia in the Era of Genetic Testing.

PubMed

Hughes, D P; Viljoen, A; Wierzbicki, A S

2016-05-01

Familial hypercholesterolaemia (FH) is a relatively common autosomal dominant genetic condition leading to premature ischaemic vascular disease and mortality if left untreated. Currently, a universal consensus on the diagnostic criteria of FH does not exist but the diagnosis of FH largely relies on the evaluation of low density lipoprotein-cholesterol (LDL-C) levels, a careful documentation of family history, and the identification of clinical features. Diagnosis based purely on lipid levels remains common but there are several limitations to this method of diagnosis both practically and in the proportion of false-negatives and false-positives detected, resulting in substantial under-diagnosis of FH. In some countries, diagnostic algorithms are supplemented with genetic testing of the index case as well as genetic and lipid testing of relatives of the index case. Such "cascade" screening of families following identification of index cases appears to not only improve the rate of diagnosis but is also cost-effective. Currently, we observe a great variation in the excess mortality among patients with FH, which likely reflects a combination of additional genetic and environmental effects on risk overlaid on the risk associated with FH. Current accepted drug therapies for FH include statins and PSCK9 inhibitors. Further work is required to evaluate the cardiovascular disease risk in patients with genetically diagnosed FH and to determine whether a risk-based approach to the treatment of FH is appropriate.

EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes

PubMed Central

van Dongen, J J M; Lhermitte, L; Böttcher, S; Almeida, J; van der Velden, V H J; Flores-Montero, J; Rawstron, A; Asnafi, V; Lécrevisse, Q; Lucio, P; Mejstrikova, E; Szczepański, T; Kalina, T; de Tute, R; Brüggemann, M; Sedek, L; Cullen, M; Langerak, A W; Mendonça, A; Macintyre, E; Martin-Ayuso, M; Hrusak, O; Vidriales, M B; Orfao, A

2012-01-01

Most consensus leukemia & lymphoma antibody panels consist of lists of markers based on expert opinions, but they have not been validated. Here we present the validated EuroFlow 8-color antibody panels for immunophenotyping of hematological malignancies. The single-tube screening panels and multi-tube classification panels fit into the EuroFlow diagnostic algorithm with entries defined by clinical and laboratory parameters. The panels were constructed in 2–7 sequential design–evaluation–redesign rounds, using novel Infinicyt software tools for multivariate data analysis. Two groups of markers are combined in each 8-color tube: (i) backbone markers to identify distinct cell populations in a sample, and (ii) markers for characterization of specific cell populations. In multi-tube panels, the backbone markers were optimally placed at the same fluorochrome position in every tube, to provide identical multidimensional localization of the target cell population(s). The characterization markers were positioned according to the diagnostic utility of the combined markers. Each proposed antibody combination was tested against reference databases of normal and malignant cells from healthy subjects and WHO-based disease entities, respectively. The EuroFlow studies resulted in validated and flexible 8-color antibody panels for multidimensional identification and characterization of normal and aberrant cells, optimally suited for immunophenotypic screening and classification of hematological malignancies. PMID:22552007

Ultralow-dose computed tomography imaging for surgery of midfacial and orbital fractures using ASIR and MBIR.

PubMed

Widmann, G; Dalla Torre, D; Hoermann, R; Schullian, P; Gassner, E M; Bale, R; Puelacher, W

2015-04-01

The influence of dose reductions on diagnostic quality using a series of high-resolution ultralow-dose computed tomography (CT) scans for computer-assisted planning and surgery including the most recent iterative reconstruction algorithms was evaluated and compared with the fracture detectability of a standard cranial emergency protocol. A human cadaver head including the mandible was artificially prepared with midfacial and orbital fractures and scanned using a 64-multislice CT scanner. The CT dose index volume (CTDIvol) and effective doses were calculated using application software. Noise was evaluated as the standard deviation in Hounsfield units within an identical region of interest in the posterior fossa. Diagnostic quality was assessed by consensus reading of a craniomaxillofacial surgeon and radiologist. Compared with the emergency protocol at CTDIvol 35.3 mGy and effective dose 3.6 mSv, low-dose protocols down to CTDIvol 1.0 mGy and 0.1 mSv (97% dose reduction) may be sufficient for the diagnosis of dislocated craniofacial fractures. Non-dislocated fractures may be detected at CTDIvol 2.6 mGy and 0.3 mSv (93% dose reduction). Adaptive statistical iterative reconstruction (ASIR) 50 and 100 reduced average noise by 30% and 56%, and model-based iterative reconstruction (MBIR) by 93%. However, the detection rate of fractures could not be improved due to smoothing effects. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Observer-based output consensus of a class of heterogeneous multi-agent systems with unmatched disturbances

NASA Astrophysics Data System (ADS)

Zhang, Jiancheng; Zhu, Fanglai

2018-03-01

In this paper, the output consensus of a class of linear heterogeneous multi-agent systems with unmatched disturbances is considered. Firstly, based on the relative output information among neighboring agents, we propose an asymptotic sliding-mode based consensus control scheme, under which, the output consensus error can converge to zero by removing the disturbances from output channels. Secondly, in order to reach the consensus goal, we design a novel high-order unknown input observer for each agent. It can estimate not only each agent's states and disturbances, but also the disturbances' high-order derivatives, which are required in the control scheme aforementioned above. The observer-based consensus control laws and the convergence analysis of the consensus error dynamics are given. Finally, a simulation example is provided to verify the validity of our methods.

Renal Tumors

PubMed Central

Tan, Puay Hoon; Cheng, Liang; Rioux-Leclercq, Nathalie; Merino, Maria J.; Netto, George; Reuter, Victor E.; Shen, Steven S.; Grignon, David J.; Montironi, Rodolfo; Egevad, Lars; Srigley, John R.; Delahunt, Brett; Moch, Holger

2016-01-01

The International Society of Urological Pathology convened a consensus conference on renal cancer, preceded by an online survey, to address issues relating to the diagnosis and reporting of renal neoplasia. In this report, the role of biomarkers in the diagnosis and assessment of prognosis of renal tumors is addressed. In particular we focused upon the use of immunohistochemical markers and the approach to specific differential diagnostic scenarios. We enquired whether cytogenetic and molecular tools were applied in practice and asked for views on the perceived prognostic role of biomarkers. Both the survey and conference voting results demonstrated a high degree of consensus in participants’ responses regarding prognostic/predictive markers and molecular techniques, whereas it was apparent that biomarkers for these purposes remained outside the diagnostic realm pending clinical validation. Although no individual antibody or panel of antibodies reached consensus for classifying renal tumors, or for confirming renal metastatic disease, it was noted from the online survey that 87% of respondents used immunohistochemistry to subtype renal tumors sometimes or occasionally, and a majority (87%) used immunohistochemical markers (Pax 2 or Pax 8, renal cell carcinoma [RCC] marker, panel of pan-CK, CK7, vimentin, and CD10) in confirming the diagnosis of metastatic RCC. There was consensus that immunohistochemistry should be used for histologic subtyping and applied before reaching a diagnosis of unclassified RCC. At the conference, there was consensus that TFE3 and TFEB analysis ought to be requested when RCC was diagnosed in a young patient or when histologic appearances were suggestive of the translocation subtype; whereas Pax 2 and/or Pax 8 were considered to be the most useful markers in the diagnosis of a renal primary. PMID:24025522

Analyses of integrated aircraft cabin contaminant monitoring network based on Kalman consensus filter.

PubMed

Wang, Rui; Li, Yanxiao; Sun, Hui; Chen, Zengqiang

2017-11-01

The modern civil aircrafts use air ventilation pressurized cabins subject to the limited space. In order to monitor multiple contaminants and overcome the hypersensitivity of the single sensor, the paper constructs an output correction integrated sensor configuration using sensors with different measurement theories after comparing to other two different configurations. This proposed configuration works as a node in the contaminant distributed wireless sensor monitoring network. The corresponding measurement error models of integrated sensors are also proposed by using the Kalman consensus filter to estimate states and conduct data fusion in order to regulate the single sensor measurement results. The paper develops the sufficient proof of the Kalman consensus filter stability when considering the system and the observation noises and compares the mean estimation and the mean consensus errors between Kalman consensus filter and local Kalman filter. The numerical example analyses show the effectiveness of the algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

[X-ray endoscopic semiotics and diagnostic algorithm of radiation studies of preneoplastic gastric mucosa changes].

PubMed

Akberov, R F; Gorshkov, A N

1997-01-01

The X-ray endoscopic semiotics of precancerous gastric mucosal changes (epithelial dysplasia, intestinal epithelial rearrangement) was examined by the results of 1574 gastric examination. A diagnostic algorithm was developed for radiation studies in the diagnosis of the above pathology.

2012 HIV Diagnostics Conference: the molecular diagnostics perspective.

PubMed

Branson, Bernard M; Pandori, Mark

2013-04-01

2012 HIV Diagnostic Conference Atlanta, GA, USA, 12-14 December 2012. This report highlights the presentations and discussions from the 2012 National HIV Diagnostic Conference held in Atlanta (GA, USA), on 12-14 December 2012. Reflecting changes in the evolving field of HIV diagnostics, the conference provided a forum for evaluating developments in molecular diagnostics and their role in HIV diagnosis. In 2010, the HIV Diagnostics Conference concluded with the proposal of a new diagnostic algorithm which included nucleic acid testing to resolve discordant screening and supplemental antibody test results. The 2012 meeting, picking up where the 2010 meeting left off, focused on scientific presentations that assessed this new algorithm and the role played by RNA testing and new developments in molecular diagnostics, including detection of total and integrated HIV-1 DNA, detection and quantification of HIV-2 RNA, and rapid formats for detection of HIV-1 RNA.

Diagnostic depressive symptoms of the mixed bipolar episode.

PubMed

Cassidy, F; Ahearn, E; Murry, E; Forest, K; Carroll, B J

2000-03-01

There is not yet consensus on the best diagnostic definition of mixed bipolar episodes. Many have suggested the DSM-III-R/-IV definition is too rigid. We propose alternative criteria using data from a large patient cohort. We evaluated 237 manic in-patients using DSM-III-R criteria and the Scale for Manic States (SMS). A bimodally distributed factor of dysphoric mood has been reported from the SMS data. We used both the factor and the DSM-III-R classifications to identify candidate depressive symptoms and then developed three candidate depressive symptom sets. Using ROC analysis we determined the optimal threshold number of symptoms in each set and compared the three ROC solutions. The optimal solution was tested against the DSM-III-R classification for crossvalidation. The optimal ROC solution was a set, derived from both the DSM-III-R and the SMS, and the optimal threshold for diagnosis was two or more symptoms. Applying this set iteratively to the DSM-III-R classification produced the identical ROC solution. The prevalence of mixed episodes in the cohort was 13.9% by DSM-III-R, 20.2% by the dysphoria factor and 27.4% by the new ROC solution. A diagnostic set of six dysphoric symptoms (depressed mood, anhedonia, guilt, suicide, fatigue and anxiety), with a threshold of two symptoms, is proposed for a mixed episode. This new definition has a foundation in clinical data, in the proved diagnostic performance of the qualifying symptoms, and in ROC validation against two previous definitions that each have face validity.

Comparison of STR profiling from low template DNA extracts with and without the consensus profiling method

PubMed Central

2012-01-01

Background The consensus profiling method was introduced to overcome the exaggerated stochastic effects associated with low copy number DNA typing. However, little empirical evidence has been provided which shows that a consensus profile, derived from dividing a sample into separate aliquots and including only alleles seen at least twice, gives the most informative profile, compared to a profile obtained by amplifying the entire low template DNA extract in one reaction. Therefore, this study aimed to investigate the quality of consensus profiles compared to profiles obtained using the whole low template extract for amplification. Methods A total of 100 pg and 25 pg DNA samples were amplified with the PowerPlex® ESI 16 Kits using 30 or 34 PCR cycles. A total of 100 pg and 25 pg DNA samples were then divided into three aliquots for a 34-cycle PCR and a consensus profile derived that included alleles that appeared in at least two of the replicates. Profiles from the non-split samples were compared to the consensus profiles focusing on peak heights, allele drop out, locus drop out and allele drop in. Results Performing DNA profiling on non-split extracts produced profiles with a higher percentage of correct loci compared to the consensus profiling technique. Consensus profiling did eliminate any spurious alleles from the final profile. However, there was a notable increase in allele and locus drop out when a LTDNA sample was divided prior to amplification. Conclusions The loss of information that occurs when a sample is split for amplification indicates that consensus profiling may not be producing the most informative DNA profile for samples where the template amount is limited. PMID:22748106

Combination of culture, antigen and toxin detection, and cytotoxin neutralization assay for optimal Clostridium difficile diagnostic testing

PubMed Central

Alfa, Michelle J; Sepehri, Shadi

2013-01-01

BACKGROUND: There has been a growing interest in developing an appropriate laboratory diagnostic algorithm for Clostridium difficile, mainly as a result of increases in both the number and severity of cases of C difficile infection in the past decade. A C difficile diagnostic algorithm is necessary because diagnostic kits, mostly for the detection of toxins A and B or glutamate dehydrogenase (GDH) antigen, are not sufficient as stand-alone assays for optimal diagnosis of C difficile infection. In addition, conventional reference methods for C difficile detection (eg, toxigenic culture and cytotoxin neutralization [CTN] assays) are not routinely practiced in diagnostic laboratory settings. OBJECTIVE: To review the four-step algorithm used at Diagnostic Services of Manitoba sites for the laboratory diagnosis of toxigenic C difficile. RESULT: One year of retrospective C difficile data using the proposed algorithm was reported. Of 5695 stool samples tested, 9.1% (n=517) had toxigenic C difficile. Sixty per cent (310 of 517) of toxigenic C difficile stools were detected following the first two steps of the algorithm. CTN confirmation of GDH-positive, toxin A- and B-negative assays resulted in detection of an additional 37.7% (198 of 517) of toxigenic C difficile. Culture of the third specimen, from patients who had two previous negative specimens, detected an additional 2.32% (12 of 517) of toxigenic C difficile samples. DISCUSSION: Using GDH antigen as the screening and toxin A and B as confirmatory test for C difficile, 85% of specimens were reported negative or positive within 4 h. Without CTN confirmation for GDH antigen and toxin A and B discordant results, 37% (195 of 517) of toxigenic C difficile stools would have been missed. Following the algorithm, culture was needed for only 2.72% of all specimens submitted for C difficile testing. CONCLUSION: The overview of the data illustrated the significance of each stage of this four-step C difficile algorithm and emphasized the value of using CTN assay and culture as parts of an algorithm that ensures accurate diagnosis of toxigenic C difficile. PMID:24421808

Autism Diagnostic Interview-Revised (ADI-R) Algorithms for Toddlers and Young Preschoolers: Application in a Non-US Sample of 1,104 Children

ERIC Educational Resources Information Center

de Bildt, Annelies; Sytema, Sjoerd; Zander, Eric; Bölte, Sven; Sturm, Harald; Yirmiya, Nurit; Yaari, Maya; Charman, Tony; Salomone, Erica; LeCouteur, Ann; Green, Jonathan; Bedia, Ricardo Canal; Primo, Patricia García; van Daalen, Emma; de Jonge, Maretha V.; Guðmundsdóttir, Emilía; Jóhannsdóttir, Sigurrós; Raleva, Marija; Boskovska, Meri; Rogé, Bernadette; Baduel, Sophie; Moilanen, Irma; Yliherva, Anneli; Buitelaar, Jan; Oosterling, Iris J.

2015-01-01

The current study aimed to investigate the Autism Diagnostic Interview-Revised (ADI-R) algorithms for toddlers and young preschoolers (Kim and Lord, "J Autism Dev Disord" 42(1):82-93, 2012) in a non-US sample from ten sites in nine countries (n = 1,104). The construct validity indicated a good fit of the algorithms. The diagnostic…

Classification of a large microarray data set: Algorithm comparison and analysis of drug signatures

PubMed Central

Natsoulis, Georges; El Ghaoui, Laurent; Lanckriet, Gert R.G.; Tolley, Alexander M.; Leroy, Fabrice; Dunlea, Shane; Eynon, Barrett P.; Pearson, Cecelia I.; Tugendreich, Stuart; Jarnagin, Kurt

2005-01-01

A large gene expression database has been produced that characterizes the gene expression and physiological effects of hundreds of approved and withdrawn drugs, toxicants, and biochemical standards in various organs of live rats. In order to derive useful biological knowledge from this large database, a variety of supervised classification algorithms were compared using a 597-microarray subset of the data. Our studies show that several types of linear classifiers based on Support Vector Machines (SVMs) and Logistic Regression can be used to derive readily interpretable drug signatures with high classification performance. Both methods can be tuned to produce classifiers of drug treatments in the form of short, weighted gene lists which upon analysis reveal that some of the signature genes have a positive contribution (act as “rewards” for the class-of-interest) while others have a negative contribution (act as “penalties”) to the classification decision. The combination of reward and penalty genes enhances performance by keeping the number of false positive treatments low. The results of these algorithms are combined with feature selection techniques that further reduce the length of the drug signatures, an important step towards the development of useful diagnostic biomarkers and low-cost assays. Multiple signatures with no genes in common can be generated for the same classification end-point. Comparison of these gene lists identifies biological processes characteristic of a given class. PMID:15867433

Implementation and testing of a sensor-netting algorithm for early warning and high confidence C/B threat detection

NASA Astrophysics Data System (ADS)

Gruber, Thomas; Grim, Larry; Fauth, Ryan; Tercha, Brian; Powell, Chris; Steinhardt, Kristin

2011-05-01

Large networks of disparate chemical/biological (C/B) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. Sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A data fusion algorithm design was completed in a Phase I SBIR effort and development continues in the Phase II SBIR effort. The initial implementation and testing of the algorithm has produced some performance results. The algorithm accepts point and/or standoff sensor data, and event detection data (e.g., the location of an explosion) from various ISR sensors (e.g., acoustic, infrared cameras, etc.). These input data are preprocessed to assign estimated uncertainty to each incoming piece of data. The data are then sent to a weighted tomography process to obtain a consensus threat map, including estimated threat concentration level uncertainty. The threat map is then tested for consistency and the overall confidence for the map result is estimated. The map and confidence results are displayed on a COP. The benefits of a modular implementation of the algorithm and comparisons of fused / un-fused data results will be presented. The metrics for judging the sensor-netting algorithm performance are warning time, threat map accuracy (as compared to ground truth), false alarm rate, and false alarm rate v. reported threat confidence level.

Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

PubMed

Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

2009-09-01

Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.

Flexible Multi agent Algorithm for Distributed Decision Making

DTIC Science & Technology

2015-01-01

How, J. P. Consensus - Based Auction Approaches for Decentralized task Assignment. Proceedings of the AIAA Guidance, Navigation, and Control...G. ; Kim, Y. Market- based Decentralized Task Assignment for Cooperative UA V Mission Including Rendezvous. Proceedings of the AIAA Guidance...scalable and adaptable to a variety of specific mission tasks . Additionally, the algorithm could easily be adapted for use on land or sea- based systems

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

PubMed

Ehteshami Bejnordi, Babak; Veta, Mitko; Johannes van Diest, Paul; van Ginneken, Bram; Karssemeijer, Nico; Litjens, Geert; van der Laak, Jeroen A W M; Hermsen, Meyke; Manson, Quirine F; Balkenhol, Maschenka; Geessink, Oscar; Stathonikos, Nikolaos; van Dijk, Marcory Crf; Bult, Peter; Beca, Francisco; Beck, Andrew H; Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Zhong, Aoxiao; Dou, Qi; Li, Quanzheng; Chen, Hao; Lin, Huang-Jing; Heng, Pheng-Ann; Haß, Christian; Bruni, Elia; Wong, Quincy; Halici, Ugur; Öner, Mustafa Ümit; Cetin-Atalay, Rengul; Berseth, Matt; Khvatkov, Vitali; Vylegzhanin, Alexei; Kraus, Oren; Shaban, Muhammad; Rajpoot, Nasir; Awan, Ruqayya; Sirinukunwattana, Korsuk; Qaiser, Talha; Tsang, Yee-Wah; Tellez, David; Annuscheit, Jonas; Hufnagl, Peter; Valkonen, Mira; Kartasalo, Kimmo; Latonen, Leena; Ruusuvuori, Pekka; Liimatainen, Kaisa; Albarqouni, Shadi; Mungal, Bharti; George, Ami; Demirci, Stefanie; Navab, Nassir; Watanabe, Seiryo; Seno, Shigeto; Takenaka, Yoichi; Matsuda, Hideo; Ahmady Phoulady, Hady; Kovalev, Vassili; Kalinovsky, Alexander; Liauchuk, Vitali; Bueno, Gloria; Fernandez-Carrobles, M Milagro; Serrano, Ismael; Deniz, Oscar; Racoceanu, Daniel; Venâncio, Rui

2017-12-12

Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

Improving Consensus Scoring of Crowdsourced Data Using the Rasch Model: Development and Refinement of a Diagnostic Instrument.

PubMed

Brady, Christopher John; Mudie, Lucy Iluka; Wang, Xueyang; Guallar, Eliseo; Friedman, David Steven

2017-06-20

Diabetic retinopathy (DR) is a leading cause of vision loss in working age individuals worldwide. While screening is effective and cost effective, it remains underutilized, and novel methods are needed to increase detection of DR. This clinical validation study compared diagnostic gradings of retinal fundus photographs provided by volunteers on the Amazon Mechanical Turk (AMT) crowdsourcing marketplace with expert-provided gold-standard grading and explored whether determination of the consensus of crowdsourced classifications could be improved beyond a simple majority vote (MV) using regression methods. The aim of our study was to determine whether regression methods could be used to improve the consensus grading of data collected by crowdsourcing. A total of 1200 retinal images of individuals with diabetes mellitus from the Messidor public dataset were posted to AMT. Eligible crowdsourcing workers had at least 500 previously approved tasks with an approval rating of 99% across their prior submitted work. A total of 10 workers were recruited to classify each image as normal or abnormal. If half or more workers judged the image to be abnormal, the MV consensus grade was recorded as abnormal. Rasch analysis was then used to calculate worker ability scores in a random 50% training set, which were then used as weights in a regression model in the remaining 50% test set to determine if a more accurate consensus could be devised. Outcomes of interest were the percent correctly classified images, sensitivity, specificity, and area under the receiver operating characteristic (AUROC) for the consensus grade as compared with the expert grading provided with the dataset. Using MV grading, the consensus was correct in 75.5% of images (906/1200), with 75.5% sensitivity, 75.5% specificity, and an AUROC of 0.75 (95% CI 0.73-0.78). A logistic regression model using Rasch-weighted individual scores generated an AUROC of 0.91 (95% CI 0.88-0.93) compared with 0.89 (95% CI 0.86-92) for a model using unweighted scores (chi-square P value<.001). Setting a diagnostic cut-point to optimize sensitivity at 90%, 77.5% (465/600) were graded correctly, with 90.3% sensitivity, 68.5% specificity, and an AUROC of 0.79 (95% CI 0.76-0.83). Crowdsourced interpretations of retinal images provide rapid and accurate results as compared with a gold-standard grading. Creating a logistic regression model using Rasch analysis to weight crowdsourced classifications by worker ability improves accuracy of aggregated grades as compared with simple majority vote. ©Christopher John Brady, Lucy Iluka Mudie, Xueyang Wang, Eliseo Guallar, David Steven Friedman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.06.2017.

Recommendations for the inclusion of Fabry disease as a rare febrile condition in existing algorithms for fever of unknown origin.

PubMed

Manna, Raffaele; Cauda, Roberto; Feriozzi, Sandro; Gambaro, Giovanni; Gasbarrini, Antonio; Lacombe, Didier; Livneh, Avi; Martini, Alberto; Ozdogan, Huri; Pisani, Antonio; Riccio, Eleonora; Verrecchia, Elena; Dagna, Lorenzo

2017-10-01

Fever of unknown origin (FUO) is a rather rare clinical syndrome representing a major diagnostic challenge. The occurrence of more than three febrile attacks with fever-free intervals of variable duration during 6 months of observation has recently been proposed as a subcategory of FUO, Recurrent FUO (RFUO). A substantial number of patients with RFUO have auto-inflammatory genetic fevers, but many patients remain undiagnosed. We hypothesize that this undiagnosed subgroup may be comprised of, at least in part, a number of rare genetic febrile diseases such as Fabry disease. We aimed to identify key features or potential diagnostic clues for Fabry disease as a model of rare genetic febrile diseases causing RFUO, and to develop diagnostic guidelines for RFUO, using Fabry disease as an example of inserting other rare diseases in the existing FUO algorithms. An international panel of specialists in recurrent fevers and rare diseases, including internists, infectious disease specialists, rheumatologists, gastroenterologists, nephrologists, and medical geneticists convened to review the existing diagnostic algorithms, and to suggest recommendations for arriving at accurate diagnoses on the basis of available literature and clinical experience. By combining specific features of rare diseases with other diagnostic considerations, guidelines have been designed to raise awareness and identify rare diseases among other causes of FUO. The proposed guidelines may be useful for the inclusion of rare diseases in the diagnostic algorithms for FUO. A wide spectrum of patients will be needed to validate the algorithm in different clinical settings.

A WAO - ARIA - GA²LEN consensus document on molecular-based allergy diagnostics

PubMed Central

2013-01-01

Molecular-based allergy (MA) diagnostics is an approach used to map the allergen sensitization of a patient at a molecular level, using purified natural or recombinant allergenic molecules (allergen components) instead of allergen extracts. Since its introduction, MA diagnostics has increasingly entered routine care, with currently more than 130 allergenic molecules commercially available for in vitro specific IgE (sIgE) testing. MA diagnostics allows for an increased accuracy in allergy diagnosis and prognosis and plays an important role in three key aspects of allergy diagnosis: (1) resolving genuine versus cross-reactive sensitization in poly-sensitized patients, thereby improving the understanding of triggering allergens; (2) assessing, in selected cases, the risk of severe, systemic versus mild, local reactions in food allergy, thereby reducing unnecessary anxiety for the patient and the need for food challenge testing; and (3) identifying patients and triggering allergens for specific immunotherapy (SIT). Singleplex and multiplex measurement platforms are available for MA diagnostics. The Immuno-Solid phase Allergen Chip (ISAC) is the most comprehensive platform currently available, which involves a biochip technology to measure sIgE antibodies against more than one hundred allergenic molecules in a single assay. As the field of MA diagnostics advances, future work needs to focus on large-scale, population-based studies involving practical applications, elucidation and expansion of additional allergenic molecules, and support for appropriate test interpretation. With the rapidly expanding evidence-base for MA diagnosis, there is a need for allergists to keep abreast of the latest information. The aim of this consensus document is to provide a practical guide for the indications, determination, and interpretation of MA diagnostics for clinicians trained in allergology. PMID:24090398

A WAO - ARIA - GA²LEN consensus document on molecular-based allergy diagnostics.

PubMed

Canonica, Giorgio Walter; Ansotegui, Ignacio J; Pawankar, Ruby; Schmid-Grendelmeier, Peter; van Hage, Marianne; Baena-Cagnani, Carlos E; Melioli, Giovanni; Nunes, Carlos; Passalacqua, Giovanni; Rosenwasser, Lanny; Sampson, Hugh; Sastre, Joaquin; Bousquet, Jean; Zuberbier, Torsten

2013-10-03

Molecular-based allergy (MA) diagnostics is an approach used to map the allergen sensitization of a patient at a molecular level, using purified natural or recombinant allergenic molecules (allergen components) instead of allergen extracts. Since its introduction, MA diagnostics has increasingly entered routine care, with currently more than 130 allergenic molecules commercially available for in vitro specific IgE (sIgE) testing.MA diagnostics allows for an increased accuracy in allergy diagnosis and prognosis and plays an important role in three key aspects of allergy diagnosis: (1) resolving genuine versus cross-reactive sensitization in poly-sensitized patients, thereby improving the understanding of triggering allergens; (2) assessing, in selected cases, the risk of severe, systemic versus mild, local reactions in food allergy, thereby reducing unnecessary anxiety for the patient and the need for food challenge testing; and (3) identifying patients and triggering allergens for specific immunotherapy (SIT).Singleplex and multiplex measurement platforms are available for MA diagnostics. The Immuno-Solid phase Allergen Chip (ISAC) is the most comprehensive platform currently available, which involves a biochip technology to measure sIgE antibodies against more than one hundred allergenic molecules in a single assay. As the field of MA diagnostics advances, future work needs to focus on large-scale, population-based studies involving practical applications, elucidation and expansion of additional allergenic molecules, and support for appropriate test interpretation. With the rapidly expanding evidence-base for MA diagnosis, there is a need for allergists to keep abreast of the latest information. The aim of this consensus document is to provide a practical guide for the indications, determination, and interpretation of MA diagnostics for clinicians trained in allergology.

Development of an Adaptable Display and Diagnostic System for the Evaluation of Tropical Cyclone Forecasts

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Burek, T.; Halley-Gotway, J.

2015-12-01

NCAR's Joint Numerical Testbed Program (JNTP) focuses on the evaluation of experimental forecasts of tropical cyclones (TCs) with the goal of developing new research tools and diagnostic evaluation methods that can be transitioned to operations. Recent activities include the development of new TC forecast verification methods and the development of an adaptable TC display and diagnostic system. The next generation display and diagnostic system is being developed to support evaluation needs of the U.S. National Hurricane Center (NHC) and broader TC research community. The new hurricane display and diagnostic capabilities allow forecasters and research scientists to more deeply examine the performance of operational and experimental models. The system is built upon modern and flexible technology that includes OpenLayers Mapping tools that are platform independent. The forecast track and intensity along with associated observed track information are stored in an efficient MySQL database. The system provides easy-to-use interactive display system, and provides diagnostic tools to examine forecast track stratified by intensity. Consensus forecasts can be computed and displayed interactively. The system is designed to display information for both real-time and for historical TC cyclones. The display configurations are easily adaptable to meet the needs of the end-user preferences. Ongoing enhancements include improving capabilities for stratification and evaluation of historical best tracks, development and implementation of additional methods to stratify and compute consensus hurricane track and intensity forecasts, and improved graphical display tools. The display is also being enhanced to incorporate gridded forecast, satellite, and sea surface temperature fields. The presentation will provide an overview of the display and diagnostic system development and demonstration of the current capabilities.

Clinical reasoning in unimodal interventions in patients with non-specific neck pain in daily physiotherapy practice, a Delphi study.

PubMed

Maissan, Francois; Pool, Jan; Stutterheim, Eric; Wittink, Harriet; Ostelo, Raymond

2018-06-02

Neck pain is the fourth major cause of disability worldwide but sufficient evidence regarding treatment is not available. This study is a first exploratory attempt to gain insight into and consensus on the clinical reasoning of experts in patients with non-specific neck pain. First, we aimed to inventory expert opinions regarding the indication for physiotherapy when, other than neck pain, no positive signs and symptoms and no positive diagnostic tests are present. Secondly, we aimed to determine which measurement instruments are being used and when they are used to support and objectify the clinical reasoning process. Finally, we wanted to establish consensus among experts regarding the use of unimodal interventions in patients with non-specific neck pain, i.e. their sequential linear clinical reasoning. A Delphi study. A Web-based Delphi study was conducted. Fifteen experts (teachers and researchers) participated. Pain alone was deemed not be an indication for physiotherapy treatment. PROMs are mainly used for evaluative purposes and physical tests for diagnostic and evaluative purposes. Eighteen different variants of sequential linear clinical reasoning were investigated within our Delphi study. Only 6 out of 18 variants of sequential linear clinical reasoning reached more than 50% consensus. Pain alone is not an indication for physiotherapy. Insight has been obtained into which measurement instruments are used and when they are used. Consensus about sequential linear lines of clinical reasoning was poor. Copyright © 2018 Elsevier Ltd. All rights reserved.

Expert consensus document: Clinical and molecular diagnosis, screening and management of Beckwith-Wiedemann syndrome: an international consensus statement.

PubMed

Brioude, Frédéric; Kalish, Jennifer M; Mussa, Alessandro; Foster, Alison C; Bliek, Jet; Ferrero, Giovanni Battista; Boonen, Susanne E; Cole, Trevor; Baker, Robert; Bertoletti, Monica; Cocchi, Guido; Coze, Carole; De Pellegrin, Maurizio; Hussain, Khalid; Ibrahim, Abdulla; Kilby, Mark D; Krajewska-Walasek, Malgorzata; Kratz, Christian P; Ladusans, Edmund J; Lapunzina, Pablo; Le Bouc, Yves; Maas, Saskia M; Macdonald, Fiona; Õunap, Katrin; Peruzzi, Licia; Rossignol, Sylvie; Russo, Silvia; Shipster, Caroleen; Skórka, Agata; Tatton-Brown, Katrina; Tenorio, Jair; Tortora, Chiara; Grønskov, Karen; Netchine, Irène; Hennekam, Raoul C; Prawitt, Dirk; Tümer, Zeynep; Eggermann, Thomas; Mackay, Deborah J G; Riccio, Andrea; Maher, Eamonn R

2018-04-01

Beckwith-Wiedemann syndrome (BWS), a human genomic imprinting disorder, is characterized by phenotypic variability that might include overgrowth, macroglossia, abdominal wall defects, neonatal hypoglycaemia, lateralized overgrowth and predisposition to embryonal tumours. Delineation of the molecular defects within the imprinted 11p15.5 region can predict familial recurrence risks and the risk (and type) of embryonal tumour. Despite recent advances in knowledge, there is marked heterogeneity in clinical diagnostic criteria and care. As detailed in this Consensus Statement, an international consensus group agreed upon 72 recommendations for the clinical and molecular diagnosis and management of BWS, including comprehensive protocols for the molecular investigation, care and treatment of patients from the prenatal period to adulthood. The consensus recommendations apply to patients with Beckwith-Wiedemann spectrum (BWSp), covering classical BWS without a molecular diagnosis and BWS-related phenotypes with an 11p15.5 molecular anomaly. Although the consensus group recommends a tumour surveillance programme targeted by molecular subgroups, surveillance might differ according to the local health-care system (for example, in the United States), and the results of targeted and universal surveillance should be evaluated prospectively. International collaboration, including a prospective audit of the results of implementing these consensus recommendations, is required to expand the evidence base for the design of optimum care pathways.

Current state of the art, multimodality research and future visions for the treatment of patients with prostate cancer: consensus results from "Challenges and Chances in Prostate Cancer Research Meeting 2013".

PubMed

Combs, Stephanie E; Debus, Jürgen; Feick, Günter; Hadaschik, Boris; Hohenfellner, Markus; Schüle, Roland; Zacharias, Jens-Peter; Schwardt, Malte

2014-11-04

A brainstorming and consensus meeting organized by the German Cancer Aid focused on modern treatment of prostate cancer and promising innovative techniques and research areas. Besides optimization of screening algorithms, molecular-based stratification and individually tailored treatment regimens will be the future of multimodal prostate cancer management. Effective interdisciplinary structures, including biobanking and data collection mechanisms are the basis for such developments.

Bipartite consensus for multi-agent systems with antagonistic interactions and communication delays

NASA Astrophysics Data System (ADS)

Guo, Xing; Lu, Jianquan; Alsaedi, Ahmed; Alsaadi, Fuad E.

2018-04-01

This paper studies the consensus problems over signed digraphs with arbitrary finite communication delays. For the considered system, the information flow is directed and only locally delayed information can be used for each node. We derive that bipartite consensus of this system can be realized when the associated signed digraph is strongly connected. Furthermore, for structurally balanced networks, this paper studies the pinning partite consensus for the considered system. we design a pinning scheme to pin any one agent in the signed network, and obtain that the network achieves pinning bipartite consensus with any initial conditions. Finally, two examples are provided to demonstrate the effectiveness of our main results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yongzheng, E-mail: yzsung@gmail.com; Li, Wang; Zhao, Donghua

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of itsmore » graph Laplacian. The influence of network topologies on the consensus time is also investigated.« less

Qualitative Event-Based Diagnosis: Case Study on the Second International Diagnostic Competition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil

2010-01-01

We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach

An ontology-driven, diagnostic modeling system.

PubMed

Haug, Peter J; Ferraro, Jeffrey P; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Dean, Nathan; Jones, Jason

2013-06-01

To present a system that uses knowledge stored in a medical ontology to automate the development of diagnostic decision support systems. To illustrate its function through an example focused on the development of a tool for diagnosing pneumonia. We developed a system that automates the creation of diagnostic decision-support applications. It relies on a medical ontology to direct the acquisition of clinic data from a clinical data warehouse and uses an automated analytic system to apply a sequence of machine learning algorithms that create applications for diagnostic screening. We refer to this system as the ontology-driven diagnostic modeling system (ODMS). We tested this system using samples of patient data collected in Salt Lake City emergency rooms and stored in Intermountain Healthcare's enterprise data warehouse. The system was used in the preliminary development steps of a tool to identify patients with pneumonia in the emergency department. This tool was compared with a manually created diagnostic tool derived from a curated dataset. The manually created tool is currently in clinical use. The automatically created tool had an area under the receiver operating characteristic curve of 0.920 (95% CI 0.916 to 0.924), compared with 0.944 (95% CI 0.942 to 0.947) for the manually created tool. Initial testing of the ODMS demonstrates promising accuracy for the highly automated results and illustrates the route to model improvement. The use of medical knowledge, embedded in ontologies, to direct the initial development of diagnostic computing systems appears feasible.

Deformed Palmprint Matching Based on Stable Regions.

PubMed

Wu, Xiangqian; Zhao, Qiushi

2015-12-01

Palmprint recognition (PR) is an effective technology for personal recognition. A main problem, which deteriorates the performance of PR, is the deformations of palmprint images. This problem becomes more severe on contactless occasions, in which images are acquired without any guiding mechanisms, and hence critically limits the applications of PR. To solve the deformation problems, in this paper, a model for non-linearly deformed palmprint matching is derived by approximating non-linear deformed palmprint images with piecewise-linear deformed stable regions. Based on this model, a novel approach for deformed palmprint matching, named key point-based block growing (KPBG), is proposed. In KPBG, an iterative M-estimator sample consensus algorithm based on scale invariant feature transform features is devised to compute piecewise-linear transformations to approximate the non-linear deformations of palmprints, and then, the stable regions complying with the linear transformations are decided using a block growing algorithm. Palmprint feature extraction and matching are performed over these stable regions to compute matching scores for decision. Experiments on several public palmprint databases show that the proposed models and the KPBG approach can effectively solve the deformation problem in palmprint verification and outperform the state-of-the-art methods.

ICD-11 Gaming Disorder: Needed and just in time or dangerous and much too early?

PubMed Central

van den Brink, Wim

2017-01-01

In their debate contribution, Aarseth et al. (2016) strongly argue against the proposal of WHO ICD-11 (International Classification of Diseases, 11th revision) to include Gaming Disorder as a new diagnostic category emphasizing the fact that no consensus exists on the definition and the risk that gaming will be demonized and gamers stigmatized resulting in a tsunami of false positive referrals to treatment. In this commentary, it is argued that gaming is indeed just another relatively innocent recreational activity with only a small minority losing control resulting in gaming-related problems. It is also argued that – despite a lack of full consensus on the diagnostic criteria – there are clear indications that Gaming Disorder is a relevant clinical entity worldwide and that official recognition as a mental disorder is urgently needed to facilitate the further development, accessibility, and reimbursement of the treatment. PMID:28816496

ICD-11 Gaming Disorder: Needed and just in time or dangerous and much too early?

PubMed

van den Brink, Wim

2017-09-01

In their debate contribution, Aarseth et al. (2016) strongly argue against the proposal of WHO ICD-11 (International Classification of Diseases, 11th revision) to include Gaming Disorder as a new diagnostic category emphasizing the fact that no consensus exists on the definition and the risk that gaming will be demonized and gamers stigmatized resulting in a tsunami of false positive referrals to treatment. In this commentary, it is argued that gaming is indeed just another relatively innocent recreational activity with only a small minority losing control resulting in gaming-related problems. It is also argued that - despite a lack of full consensus on the diagnostic criteria - there are clear indications that Gaming Disorder is a relevant clinical entity worldwide and that official recognition as a mental disorder is urgently needed to facilitate the further development, accessibility, and reimbursement of the treatment.

Diagnosis, monitoring, and treatment of primary ciliary dyskinesia: PCD foundation consensus recommendations based on state of the art review

PubMed Central

Zariwala, Maimoona A.; Ferkol, Thomas; Davis, Stephanie D.; Sagel, Scott D.; Dell, Sharon D.; Rosenfeld, Margaret; Olivier, Kenneth N.; Milla, Carlos; Daniel, Sam J.; Kimple, Adam J.; Manion, Michele; Knowles, Michael R.; Leigh, Margaret W.

2015-01-01

Summary Primary ciliary dyskinesia (PCD) is a genetically heterogeneous, rare lung disease resulting in chronic oto‐sino‐pulmonary disease in both children and adults. Many physicians incorrectly diagnose PCD or eliminate PCD from their differential diagnosis due to inexperience with diagnostic testing methods. Thus far, all therapies used for PCD are unproven through large clinical trials. This review article outlines consensus recommendations from PCD physicians in North America who have been engaged in a PCD centered research consortium for the last 10 years. These recommendations have been adopted by the governing board of the PCD Foundation to provide guidance for PCD clinical centers for diagnostic testing, monitoring, and appropriate short and long‐term therapeutics in PCD patients. Pediatr Pulmonol. 2016;51:115–132. © 2015 The Authors. Pediatric Pulmonology Published by Wiley Periodicals, Inc. PMID:26418604

A Framework to Debug Diagnostic Matrices

NASA Technical Reports Server (NTRS)

Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

2013-01-01

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement.

PubMed

McInnes, Matthew D F; Moher, David; Thombs, Brett D; McGrath, Trevor A; Bossuyt, Patrick M; Clifford, Tammy; Cohen, Jérémie F; Deeks, Jonathan J; Gatsonis, Constantine; Hooft, Lotty; Hunt, Harriet A; Hyde, Christopher J; Korevaar, Daniël A; Leeflang, Mariska M G; Macaskill, Petra; Reitsma, Johannes B; Rodin, Rachel; Rutjes, Anne W S; Salameh, Jean-Paul; Stevens, Adrienne; Takwoingi, Yemisi; Tonelli, Marcello; Weeks, Laura; Whiting, Penny; Willis, Brian H

2018-01-23

Systematic reviews of diagnostic test accuracy synthesize data from primary diagnostic studies that have evaluated the accuracy of 1 or more index tests against a reference standard, provide estimates of test performance, allow comparisons of the accuracy of different tests, and facilitate the identification of sources of variability in test accuracy. To develop the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagnostic test accuracy guideline as a stand-alone extension of the PRISMA statement. Modifications to the PRISMA statement reflect the specific requirements for reporting of systematic reviews and meta-analyses of diagnostic test accuracy studies and the abstracts for these reviews. Established standards from the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network were followed for the development of the guideline. The original PRISMA statement was used as a framework on which to modify and add items. A group of 24 multidisciplinary experts used a systematic review of articles on existing reporting guidelines and methods, a 3-round Delphi process, a consensus meeting, pilot testing, and iterative refinement to develop the PRISMA diagnostic test accuracy guideline. The final version of the PRISMA diagnostic test accuracy guideline checklist was approved by the group. The systematic review (produced 64 items) and the Delphi process (provided feedback on 7 proposed items; 1 item was later split into 2 items) identified 71 potentially relevant items for consideration. The Delphi process reduced these to 60 items that were discussed at the consensus meeting. Following the meeting, pilot testing and iterative feedback were used to generate the 27-item PRISMA diagnostic test accuracy checklist. To reflect specific or optimal contemporary systematic review methods for diagnostic test accuracy, 8 of the 27 original PRISMA items were left unchanged, 17 were modified, 2 were added, and 2 were omitted. The 27-item PRISMA diagnostic test accuracy checklist provides specific guidance for reporting of systematic reviews. The PRISMA diagnostic test accuracy guideline can facilitate the transparent reporting of reviews, and may assist in the evaluation of validity and applicability, enhance replicability of reviews, and make the results from systematic reviews of diagnostic test accuracy studies more useful.

IV Brazilian Consensus on Rhinitis - an update on allergic rhinitis.

PubMed

Sakano, Eulalia; Sarinho, Emanuel S C; Cruz, Alvaro A; Pastorino, Antonio C; Tamashiro, Edwin; Kuschnir, Fábio; Castro, Fábio F M; Romano, Fabrizio R; Wandalsen, Gustavo F; Chong-Neto, Herberto J; Mello, João F de; Silva, Luciana R; Rizzo, Maria Cândida; Miyake, Mônica A M; Rosário Filho, Nelson A; Rubini, Norma de Paula M; Mion, Olavo; Camargos, Paulo A; Roithmann, Renato; Godinho, Ricardo N; Pignatari, Shirley Shizue N; Sih, Tania; Anselmo-Lima, Wilma T; Solé, Dirceu

2017-11-02

The guidelines on allergic rhinitis aim to update knowledge about the disease and care for affected patients. The initiative called "Allergic Rhinitis and its Impact on Asthma", initially published in 2001 and updated in 2008 and 2010, has been very successful in disseminating information and evidence, as well as providing a classification of severity and proposing a systemized treatment protocol. In order to include the participation of other medical professionals in the treatment of allergic rhinitis, it is important to develop algorithms that accurately indicate what should and can be done regionally. To update the III Brazilian Consensus on Rhinitis - 2012, with the creation of an algorithm for allergic rhinitis management. We invited 24 experts nominated by the Brazilian Association of Allergy and Immunology, Brazilian Association of Otorhinolaryngology and Head and Neck Surgery and Brazilian Society of Pediatrics to update the 2012 document. The update of the last Brazilian Consensus on Rhinitis incorporated and adapted the relevant information published in all "Allergic Rhinitis and its Impact on Asthma" Initiative documents to the Brazilian scenario, bringing new concepts such as local allergic rhinitis, new drugs and treatment evaluation methods. A flowchart for allergic rhinitis treatment has been proposed. Copyright © 2017. Published by Elsevier Editora Ltda.

Accurate construction of consensus genetic maps via integer linear programming.

PubMed

Wu, Yonghui; Close, Timothy J; Lonardi, Stefano

2011-01-01

We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely, local reshuffles and global displacements. The resulting combinatorial optimization problem is, in turn, expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speedup heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments shows that MERGEMAP consistently outperforms JOINMAP, which is the most popular tool currently available for this task, both in terms of accuracy and running time. MERGEMAP is available for download at http://www.cs.ucr.edu/~yonghui/mgmap.html.

Predicting the transmembrane secondary structure of ligand-gated ion channels.

PubMed

Bertaccini, E; Trudell, J R

2002-06-01

Recent mutational analyses of ligand-gated ion channels (LGICs) have demonstrated a plausible site of anesthetic action within their transmembrane domains. Although there is a consensus that the transmembrane domain is formed from four membrane-spanning segments, the secondary structure of these segments is not known. We utilized 10 state-of-the-art bioinformatics techniques to predict the transmembrane topology of the tetrameric regions within six members of the LGIC family that are relevant to anesthetic action. They are the human forms of the GABA alpha 1 receptor, the glycine alpha 1 receptor, the 5HT3 serotonin receptor, the nicotinic AChR alpha 4 and alpha 7 receptors and the Torpedo nAChR alpha 1 receptor. The algorithms utilized were HMMTOP, TMHMM, TMPred, PHDhtm, DAS, TMFinder, SOSUI, TMAP, MEMSAT and TOPPred2. The resulting predictions were superimposed on to a multiple sequence alignment of the six amino acid sequences created using the CLUSTAL W algorithm. There was a clear statistical consensus for the presence of four alpha helices in those regions experimentally thought to span the membrane. The consensus of 10 topology prediction techniques supports the hypothesis that the transmembrane subunits of the LGICs are tetrameric bundles of alpha helices.

Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination.

PubMed

Duraipandian, Shiyamala; Sylvest Bergholt, Mads; Zheng, Wei; Yu Ho, Khek; Teh, Ming; Guan Yeoh, Khay; Bok Yan So, Jimmy; Shabbir, Asim; Huang, Zhiwei

2012-08-01

Optical spectroscopic techniques including reflectance, fluorescence and Raman spectroscopy have shown promising potential for in vivo precancer and cancer diagnostics in a variety of organs. However, data-analysis has mostly been limited to post-processing and off-line algorithm development. In this work, we develop a fully automated on-line Raman spectral diagnostics framework integrated with a multimodal image-guided Raman technique for real-time in vivo cancer detection at endoscopy. A total of 2748 in vivo gastric tissue spectra (2465 normal and 283 cancer) were acquired from 305 patients recruited to construct a spectral database for diagnostic algorithms development. The novel diagnostic scheme developed implements on-line preprocessing, outlier detection based on principal component analysis statistics (i.e., Hotelling's T2 and Q-residuals) for tissue Raman spectra verification as well as for organ specific probabilistic diagnostics using different diagnostic algorithms. Free-running optical diagnosis and processing time of < 0.5 s can be achieved, which is critical to realizing real-time in vivo tissue diagnostics during clinical endoscopic examination. The optimized partial least squares-discriminant analysis (PLS-DA) models based on the randomly resampled training database (80% for learning and 20% for testing) provide the diagnostic accuracy of 85.6% [95% confidence interval (CI): 82.9% to 88.2%] [sensitivity of 80.5% (95% CI: 71.4% to 89.6%) and specificity of 86.2% (95% CI: 83.6% to 88.7%)] for the detection of gastric cancer. The PLS-DA algorithms are further applied prospectively on 10 gastric patients at gastroscopy, achieving the predictive accuracy of 80.0% (60/75) [sensitivity of 90.0% (27/30) and specificity of 73.3% (33/45)] for in vivo diagnosis of gastric cancer. The receiver operating characteristics curves further confirmed the efficacy of Raman endoscopy together with PLS-DA algorithms for in vivo prospective diagnosis of gastric cancer. This work successfully moves biomedical Raman spectroscopic technique into real-time, on-line clinical cancer diagnosis, especially in routine endoscopic diagnostic applications.

Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination

NASA Astrophysics Data System (ADS)

Duraipandian, Shiyamala; Sylvest Bergholt, Mads; Zheng, Wei; Yu Ho, Khek; Teh, Ming; Guan Yeoh, Khay; Bok Yan So, Jimmy; Shabbir, Asim; Huang, Zhiwei

2012-08-01

Optical spectroscopic techniques including reflectance, fluorescence and Raman spectroscopy have shown promising potential for in vivo precancer and cancer diagnostics in a variety of organs. However, data-analysis has mostly been limited to post-processing and off-line algorithm development. In this work, we develop a fully automated on-line Raman spectral diagnostics framework integrated with a multimodal image-guided Raman technique for real-time in vivo cancer detection at endoscopy. A total of 2748 in vivo gastric tissue spectra (2465 normal and 283 cancer) were acquired from 305 patients recruited to construct a spectral database for diagnostic algorithms development. The novel diagnostic scheme developed implements on-line preprocessing, outlier detection based on principal component analysis statistics (i.e., Hotelling's T2 and Q-residuals) for tissue Raman spectra verification as well as for organ specific probabilistic diagnostics using different diagnostic algorithms. Free-running optical diagnosis and processing time of < 0.5 s can be achieved, which is critical to realizing real-time in vivo tissue diagnostics during clinical endoscopic examination. The optimized partial least squares-discriminant analysis (PLS-DA) models based on the randomly resampled training database (80% for learning and 20% for testing) provide the diagnostic accuracy of 85.6% [95% confidence interval (CI): 82.9% to 88.2%] [sensitivity of 80.5% (95% CI: 71.4% to 89.6%) and specificity of 86.2% (95% CI: 83.6% to 88.7%)] for the detection of gastric cancer. The PLS-DA algorithms are further applied prospectively on 10 gastric patients at gastroscopy, achieving the predictive accuracy of 80.0% (60/75) [sensitivity of 90.0% (27/30) and specificity of 73.3% (33/45)] for in vivo diagnosis of gastric cancer. The receiver operating characteristics curves further confirmed the efficacy of Raman endoscopy together with PLS-DA algorithms for in vivo prospective diagnosis of gastric cancer. This work successfully moves biomedical Raman spectroscopic technique into real-time, on-line clinical cancer diagnosis, especially in routine endoscopic diagnostic applications.

The Autism Diagnostic Observation Schedule, Module 4: Application of the Revised Algorithms in an Independent, Well-Defined, Dutch Sample (n = 93).

PubMed

de Bildt, Annelies; Sytema, Sjoerd; Meffert, Harma; Bastiaansen, Jojanneke A C J

2016-01-01

This study examined the discriminative ability of the revised Autism Diagnostic Observation Schedule module 4 algorithm (Hus and Lord in J Autism Dev Disord 44(8):1996-2012, 2014) in 93 Dutch males with Autism Spectrum Disorder (ASD), schizophrenia, psychopathy or controls. Discriminative ability of the revised algorithm ASD cut-off resembled the original algorithm ASD cut-off: highly specific for psychopathy and controls, lower sensitivity than Hus and Lord (2014; i.e. ASD .61, AD .53). The revised algorithm AD cut-off improved sensitivity over the original algorithm. Discriminating ASD from schizophrenia was still challenging, but the better-balanced sensitivity (.53) and specificity (.78) of the revised algorithm AD cut-off may aide clinicians' differential diagnosis. Findings support using the revised algorithm, being conceptually conform the other modules, thus improving comparability across the lifespan.

Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application.

PubMed

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Hajj, Hazem; Kobeissy, Firas H

2017-01-01

Degradomics is a novel discipline that involves determination of the proteases/substrate fragmentation profile, called the substrate degradome, and has been recently applied in different disciplines. A major application of degradomics is its utility in the field of biomarkers where the breakdown products (BDPs) of different protease have been investigated. Among the major proteases assessed, calpain and caspase proteases have been associated with the execution phases of the pro-apoptotic and pro-necrotic cell death, generating caspase/calpain-specific cleaved fragments. The distinction between calpain and caspase protein fragments has been applied to distinguish injury mechanisms. Advanced proteomics technology has been used to identify these BDPs experimentally. However, it has been a challenge to identify these BDPs with high precision and efficiency, especially if we are targeting a number of proteins at one time. In this chapter, we present a novel bioinfromatic detection method that identifies BDPs accurately and efficiently with validation against experimental data. This method aims at predicting the consensus sequence occurrences and their variants in a large set of experimentally detected protein sequences based on state-of-the-art sequence matching and alignment algorithms. After detection, the method generates all the potential cleaved fragments by a specific protease. This space and time-efficient algorithm is flexible to handle the different orientations that the consensus sequence and the protein sequence can take before cleaving. It is O(mn) in space complexity and O(Nmn) in time complexity, with N number of protein sequences, m length of the consensus sequence, and n length of each protein sequence. Ultimately, this knowledge will subsequently feed into the development of a novel tool for researchers to detect diverse types of selected BDPs as putative disease markers, contributing to the diagnosis and treatment of related disorders.

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2002-01-01

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

Simple Estimation of Incident HIV Infection Rates in Notification Cohorts Based on Window Periods of Algorithms for Evaluation of Line-Immunoassay Result Patterns

PubMed Central

Schüpbach, Jörg; Gebhardt, Martin D.; Scherrer, Alexandra U.; Bisset, Leslie R.; Niederhauser, Christoph; Regenass, Stephan; Yerly, Sabine; Aubert, Vincent; Suter, Franziska; Pfister, Stefan; Martinetti, Gladys; Andreutti, Corinne; Klimkait, Thomas; Brandenberger, Marcel; Günthard, Huldrych F.

2013-01-01

Background Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. Methods We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship ‘Prevalence  =  Incidence x Duration’ in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship ‘incident  =  true incident + false incident’ and also to the IIR derived from the BED incidence assay. Results Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R2 = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. Conclusions IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts. PMID:23990968

Artificial Neural Networks for differential diagnosis of breast lesions in MR-Mammography: a systematic approach addressing the influence of network architecture on diagnostic performance using a large clinical database.

PubMed

Dietzel, Matthias; Baltzer, Pascal A T; Dietzel, Andreas; Zoubi, Ramy; Gröschel, Tobias; Burmeister, Hartmut P; Bogdan, Martin; Kaiser, Werner A

2012-07-01

Differential diagnosis of lesions in MR-Mammography (MRM) remains a complex task. The aim of this MRM study was to design and to test robustness of Artificial Neural Network architectures to predict malignancy using a large clinical database. For this IRB-approved investigation standardized protocols and study design were applied (T1w-FLASH; 0.1 mmol/kgBW Gd-DTPA; T2w-TSE; histological verification after MRM). All lesions were evaluated by two experienced (>500 MRM) radiologists in consensus. In every lesion, 18 previously published descriptors were assessed and documented in the database. An Artificial Neural Network (ANN) was developed to process this database (The-MathWorks/Inc., feed-forward-architecture/resilient back-propagation-algorithm). All 18 descriptors were set as input variables, whereas histological results (malignant vs. benign) was defined as classification variable. Initially, the ANN was optimized in terms of "Training Epochs" (TE), "Hidden Layers" (HL), "Learning Rate" (LR) and "Neurons" (N). Robustness of the ANN was addressed by repeated evaluation cycles (n: 9) with receiver operating characteristics (ROC) analysis of the results applying 4-fold Cross Validation. The best network architecture was identified comparing the corresponding Area under the ROC curve (AUC). Histopathology revealed 436 benign and 648 malignant lesions. Enhancing the level of complexity could not increase diagnostic accuracy of the network (P: n.s.). The optimized ANN architecture (TE: 20, HL: 1, N: 5, LR: 1.2) was accurate (mean-AUC 0.888; P: <0.001) and robust (CI: 0.885-0.892; range: 0.880-0.898). The optimized neural network showed robust performance and high diagnostic accuracy for prediction of malignancy on unknown data. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The PHQ-8 as a measure of current depression in the general population.

PubMed

Kroenke, Kurt; Strine, Tara W; Spitzer, Robert L; Williams, Janet B W; Berry, Joyce T; Mokdad, Ali H

2009-04-01

The eight-item Patient Health Questionnaire depression scale (PHQ-8) is established as a valid diagnostic and severity measure for depressive disorders in large clinical studies. Our objectives were to assess the PHQ-8 as a depression measure in a large, epidemiological population-based study, and to determine the comparability of depression as defined by the PHQ-8 diagnostic algorithm vs. a PHQ-8 cutpoint > or = 10. Random-digit-dialed telephone survey of 198,678 participants in the 2006 Behavioral Risk Factor Surveillance Survey (BRFSS), a population-based survey in the United States. Current depression as defined by either the DSM-IV based diagnostic algorithm (i.e., major depressive or other depressive disorder) of the PHQ-8 or a PHQ-8 score > or = 10; respondent sociodemographic characteristics; number of days of impairment in the past 30 days in multiple domains of health-related quality of life (HRQoL). The prevalence of current depression was similar whether defined by the diagnostic algorithm or a PHQ-8 score > or = 10 (9.1% vs. 8.6%). Depressed patients had substantially more days of impairment across multiple domains of HRQoL, and the impairment was nearly identical in depressed groups defined by either method. Of the 17,040 respondents with a PHQ-8 score > or = 10, major depressive disorder was present in 49.7%, other depressive disorder in 23.9%, depressed mood or anhedonia in another 22.8%, and no evidence of depressive disorder or depressive symptoms in only 3.5%. The PHQ-8 diagnostic algorithm rather than an independent structured psychiatric interview was used as the criterion standard. The PHQ-8 is a useful depression measure for population-based studies, and either its diagnostic algorithm or a cutpoint > or = 10 can be used for defining current depression.

An Efficient Reachability Analysis Algorithm

NASA Technical Reports Server (NTRS)

Vatan, Farrokh; Fijany, Amir

2008-01-01

A document discusses a new algorithm for generating higher-order dependencies for diagnostic and sensor placement analysis when a system is described with a causal modeling framework. This innovation will be used in diagnostic and sensor optimization and analysis tools. Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in-situ platforms. This algorithm will serve as a power tool for technologies that satisfy a key requirement of autonomous spacecraft, including science instruments and in-situ missions.

Prosthetic joint infection development of an evidence-based diagnostic algorithm.

PubMed

Mühlhofer, Heinrich M L; Pohlig, Florian; Kanz, Karl-Georg; Lenze, Ulrich; Lenze, Florian; Toepfer, Andreas; Kelch, Sarah; Harrasser, Norbert; von Eisenhart-Rothe, Rüdiger; Schauwecker, Johannes

2017-03-09

Increasing rates of prosthetic joint infection (PJI) have presented challenges for general practitioners, orthopedic surgeons and the health care system in the recent years. The diagnosis of PJI is complex; multiple diagnostic tools are used in the attempt to correctly diagnose PJI. Evidence-based algorithms can help to identify PJI using standardized diagnostic steps. We reviewed relevant publications between 1990 and 2015 using a systematic literature search in MEDLINE and PUBMED. The selected search results were then classified into levels of evidence. The keywords were prosthetic joint infection, biofilm, diagnosis, sonication, antibiotic treatment, implant-associated infection, Staph. aureus, rifampicin, implant retention, pcr, maldi-tof, serology, synovial fluid, c-reactive protein level, total hip arthroplasty (THA), total knee arthroplasty (TKA) and combinations of these terms. From an initial 768 publications, 156 publications were stringently reviewed. Publications with class I-III recommendations (EAST) were considered. We developed an algorithm for the diagnostic approach to display the complex diagnosis of PJI in a clear and logically structured process according to ISO 5807. The evidence-based standardized algorithm combines modern clinical requirements and evidence-based treatment principles. The algorithm provides a detailed transparent standard operating procedure (SOP) for diagnosing PJI. Thus, consistently high, examiner-independent process quality is assured to meet the demands of modern quality management in PJI diagnosis.

Prescribed performance distributed consensus control for nonlinear multi-agent systems with unknown dead-zone input

NASA Astrophysics Data System (ADS)

Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang

2018-05-01

In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

A randomized controlled trial of a diagnostic algorithm for symptoms of uncomplicated cystitis at an out-of-hours service

PubMed Central

Grude, Nils; Lindbaek, Morten

2015-01-01

Objective. To compare the clinical outcome of patients presenting with symptoms of uncomplicated cystitis who were seen by a doctor, with patients who were given treatment following a diagnostic algorithm. Design. Randomized controlled trial. Setting. Out-of-hours service, Oslo, Norway. Intervention. Women with typical symptoms of uncomplicated cystitis were included in the trial in the time period September 2010–November 2011. They were randomized into two groups. One group received standard treatment according to the diagnostic algorithm, the other group received treatment after a regular consultation by a doctor. Subjects. Women (n = 441) aged 16–55 years. Mean age in both groups 27 years. Main outcome measures. Number of days until symptomatic resolution. Results. No significant differences were found between the groups in the basic patient demographics, severity of symptoms, or percentage of urine samples with single culture growth. A median of three days until symptomatic resolution was found in both groups. By day four 79% in the algorithm group and 72% in the regular consultation group were free of symptoms (p = 0.09). The number of patients who contacted a doctor again in the follow-up period and received alternative antibiotic treatment was insignificantly higher (p = 0.08) after regular consultation than after treatment according to the diagnostic algorithm. There were no cases of severe pyelonephritis or hospital admissions during the follow-up period. Conclusion. Using a diagnostic algorithm is a safe and efficient method for treating women with symptoms of uncomplicated cystitis at an out-of-hours service. This simplification of treatment strategy can lead to a more rational use of consultation time and a stricter adherence to National Antibiotic Guidelines for a common disorder. PMID:25961367

A randomized controlled trial of a diagnostic algorithm for symptoms of uncomplicated cystitis at an out-of-hours service.

PubMed

Bollestad, Marianne; Grude, Nils; Lindbaek, Morten

2015-06-01

To compare the clinical outcome of patients presenting with symptoms of uncomplicated cystitis who were seen by a doctor, with patients who were given treatment following a diagnostic algorithm. Randomized controlled trial. Out-of-hours service, Oslo, Norway. Women with typical symptoms of uncomplicated cystitis were included in the trial in the time period September 2010-November 2011. They were randomized into two groups. One group received standard treatment according to the diagnostic algorithm, the other group received treatment after a regular consultation by a doctor. Women (n = 441) aged 16-55 years. Mean age in both groups 27 years. Number of days until symptomatic resolution. No significant differences were found between the groups in the basic patient demographics, severity of symptoms, or percentage of urine samples with single culture growth. A median of three days until symptomatic resolution was found in both groups. By day four 79% in the algorithm group and 72% in the regular consultation group were free of symptoms (p = 0.09). The number of patients who contacted a doctor again in the follow-up period and received alternative antibiotic treatment was insignificantly higher (p = 0.08) after regular consultation than after treatment according to the diagnostic algorithm. There were no cases of severe pyelonephritis or hospital admissions during the follow-up period. Using a diagnostic algorithm is a safe and efficient method for treating women with symptoms of uncomplicated cystitis at an out-of-hours service. This simplification of treatment strategy can lead to a more rational use of consultation time and a stricter adherence to National Antibiotic Guidelines for a common disorder.

Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistics and Model Explorer.

PubMed

Giancarlo, Raffaele; Scaturro, Davide; Utro, Filippo

2008-10-29

Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster Sum-of-Squares) and KL (Krzanowski and Lai index). We perform extensive experiments on six benchmark microarray datasets, using both Hierarchical and K-means clustering algorithms, and we provide an analysis assessing both the intrinsic ability of a measure to predict the correct number of clusters in a dataset and its merit relative to the other measures. We pay particular attention both to precision and speed. Moreover, we also provide various fast approximation algorithms for the computation of Gap, FOM and WCSS. The main result is a hierarchy of those measures in terms of precision and speed, highlighting some of their merits and limitations not reported before in the literature. Based on our analysis, we draw several conclusions for the use of those internal measures on microarray data. We report the main ones. Consensus is by far the best performer in terms of predictive power and remarkably algorithm-independent. Unfortunately, on large datasets, it may be of no use because of its non-trivial computer time demand (weeks on a state of the art PC). FOM is the second best performer although, quite surprisingly, it may not be competitive in this scenario: it has essentially the same predictive power of WCSS but it is from 6 to 100 times slower in time, depending on the dataset. The approximation algorithms for the computation of FOM, Gap and WCSS perform very well, i.e., they are faster while still granting a very close approximation of FOM and WCSS. The approximation algorithm for the computation of Gap deserves to be singled-out since it has a predictive power far better than Gap, it is competitive with the other measures, but it is at least two order of magnitude faster in time with respect to Gap. Another important novel conclusion that can be drawn from our analysis is that all the measures we have considered show severe limitations on large datasets, either due to computational demand (Consensus, as already mentioned, Clest and Gap) or to lack of precision (all of the other measures, including their approximations). The software and datasets are available under the GNU GPL on the supplementary material web page.

An opinion formation based binary optimization approach for feature selection

NASA Astrophysics Data System (ADS)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

The Geological Susceptibility of Induced Earthquakes in the Duvernay Play

NASA Astrophysics Data System (ADS)

Pawley, Steven; Schultz, Ryan; Playter, Tiffany; Corlett, Hilary; Shipman, Todd; Lyster, Steven; Hauck, Tyler

2018-02-01

Presently, consensus on the incorporation of induced earthquakes into seismic hazard has yet to be established. For example, the nonstationary, spatiotemporal nature of induced earthquakes is not well understood. Specific to the Western Canada Sedimentary Basin, geological bias in seismogenic activation potential has been suggested to control the spatial distribution of induced earthquakes regionally. In this paper, we train a machine learning algorithm to systemically evaluate tectonic, geomechanical, and hydrological proxies suspected to control induced seismicity. Feature importance suggests that proximity to basement, in situ stress, proximity to fossil reef margins, lithium concentration, and rate of natural seismicity are among the strongest model predictors. Our derived seismogenic potential map faithfully reproduces the current distribution of induced seismicity and is suggestive of other regions which may be prone to induced earthquakes. The refinement of induced seismicity geological susceptibility may become an important technique to identify significant underlying geological features and address induced seismic hazard forecasting issues.

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot.

PubMed

Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Kikuchi, Kazufumi; Yoshimoto, Koji; Mizoguchi, Masahiro; Suzuki, Satoshi O; Yoshiura, Takashi; Honda, Hiroshi

2016-07-01

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas. This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis. Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529). CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Professional Acceptance Of Electronic Images In Radiologic Practice

NASA Astrophysics Data System (ADS)

Gitlin, Joseph N.; Curtis, David J.; Kerlin, Barbara D.; Olmsted, William W.

1983-05-01

During the past four years, a large number of radiographic images have been interpreted in both film and video modes in an effort to determine the utility of digital/analogue systems in general practice. With the cooperation of the Department of Defense, the MITRE Corporation, and several university-based radiology departments, the Public Health Service has participated in laboratory experiments and a teleradiology field trial to meet this objective. During the field trial, 30 radiologists participated in the interpretation of more than 4,000 diagnostic x-ray examinations that were performed at distant clinics, digitized, and transmitted to a medical center for interpretation on video monitors. As part of the evaluation, all of the participating radiologists and the attending physicians at the clinics were queried regarding the teleradiology system, particularly with respect to the diagnostic quality of the electronic images. The original films for each of the 4,000 examinations were read independently, and the findings and impressions from each mode were compared to identify discrepancies. In addition, a sample of 530 cases was reviewed and interpreted by a consensus panel to measure the accuracy of findings and impressions of both film and video readings. The sample has been retained in an automated archive for future study at the National Center of Devices and Radiological Health facilities in Rockville, Maryland. The studies include a comparison of diagnostic findings and impressions from 1024 x 1024 matrices with those obtained from the 512 x 512 format used in the field trial. The archive also provides a database for determining the effect of data compression techniques on diagnostic interpretations and establishing the utility of image processing algorithms. The paper will include an analysis of the final results of the field trial and preliminary findings from the ongoing studies using the archive of cases at the National Center for Devices and Radiological Health. This paper was not available at the time of printing of the Proceedings.

Optimizing Patient-centered Communication and Multidisciplinary Care Coordination in Emergency Diagnostic Imaging: A Research Agenda.

PubMed

Sabbatini, Amber K; Merck, Lisa H; Froemming, Adam T; Vaughan, William; Brown, Michael D; Hess, Erik P; Applegate, Kimberly E; Comfere, Nneka I

2015-12-01

Patient-centered emergency diagnostic imaging relies on efficient communication and multispecialty care coordination to ensure optimal imaging utilization. The construct of the emergency diagnostic imaging care coordination cycle with three main phases (pretest, test, and posttest) provides a useful framework to evaluate care coordination in patient-centered emergency diagnostic imaging. This article summarizes findings reached during the patient-centered outcomes session of the 2015 Academic Emergency Medicine consensus conference "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The primary objective was to develop a research agenda focused on 1) defining component parts of the emergency diagnostic imaging care coordination process, 2) identifying gaps in communication that affect emergency diagnostic imaging, and 3) defining optimal methods of communication and multidisciplinary care coordination that ensure patient-centered emergency diagnostic imaging. Prioritized research questions provided the framework to define a research agenda for multidisciplinary care coordination in emergency diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

PubMed Central

Veta, Mitko; Johannes van Diest, Paul; van Ginneken, Bram; Karssemeijer, Nico; Litjens, Geert; van der Laak, Jeroen A. W. M.; Hermsen, Meyke; Manson, Quirine F; Balkenhol, Maschenka; Geessink, Oscar; Stathonikos, Nikolaos; van Dijk, Marcory CRF; Bult, Peter; Beca, Francisco; Beck, Andrew H; Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Zhong, Aoxiao; Dou, Qi; Li, Quanzheng; Chen, Hao; Lin, Huang-Jing; Heng, Pheng-Ann; Haß, Christian; Bruni, Elia; Wong, Quincy; Halici, Ugur; Öner, Mustafa Ümit; Cetin-Atalay, Rengul; Berseth, Matt; Khvatkov, Vitali; Vylegzhanin, Alexei; Kraus, Oren; Shaban, Muhammad; Rajpoot, Nasir; Awan, Ruqayya; Sirinukunwattana, Korsuk; Qaiser, Talha; Tsang, Yee-Wah; Tellez, David; Annuscheit, Jonas; Hufnagl, Peter; Valkonen, Mira; Kartasalo, Kimmo; Latonen, Leena; Ruusuvuori, Pekka; Liimatainen, Kaisa; Albarqouni, Shadi; Mungal, Bharti; George, Ami; Demirci, Stefanie; Navab, Nassir; Watanabe, Seiryo; Seno, Shigeto; Takenaka, Yoichi; Matsuda, Hideo; Ahmady Phoulady, Hady; Kovalev, Vassili; Kalinovsky, Alexander; Liauchuk, Vitali; Bueno, Gloria; Fernandez-Carrobles, M. Milagro; Serrano, Ismael; Deniz, Oscar; Racoceanu, Daniel; Venâncio, Rui

2017-01-01

Importance Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists’ diagnoses in a diagnostic setting. Design, Setting, and Participants Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting. PMID:29234806

[Fool's gold standards in language screening. Sensitivity and specificity of the Hessian child language screening test (Kindersprachscreening, KiSS)].

PubMed

Neumann, K; Holler-Zittlau, I; van Minnen, S; Sick, U; Zaretsky, Y; Euler, H A

2011-01-01

The German Kindersprachscreening (KiSS) is a universal speech and language screening test for large-scale identification of Hessian kindergarten children requiring special educational language training or clinical speech/language therapy. To calculate the procedural screening validity, 257 children (aged 4.0 to 4.5 years) were tested using KiSS and four language tests (Reynell Development Language Scales III, Patholinguistische Diagnostik, PLAKSS, AWST-R). The majority or consensus judgements of three speech-language professionals, based on the language test results, served as a reference criterion. The base (fail) rates of the professionals were either self-determined or preset based on known prevalence rates. Screening validity was higher for preset than for self-determined base rates due to higher inter-judge agreement. The confusion matrices of the overall index classification of the KiSS (speech-language abnormalities with educational or clinical needs) with the fixed base rate expert judgement about language impairment, including fluency or voice disorders, yielded a sensitivity of 88% and a specificity of 78%, for just language impairment 84% and 75%, respectively. Specificities for disorders requiring clinical diagnostics in the KiSS (language impairment alone or combined with fluency/voice disorders) related to the test-based consensus expert judgment was about 93%. Sensitivities were unsatisfactory because the differentiation between educational and clinical needs requires improvement. Since the judgement concordances between the speech-language professionals was only moderate, the development of a comprehensive German reference test for speech and language disorders with evidence-based algorithmic decision rules rather than subjective clinical judgement is advocated.

Management of neonatal cholestasis: consensus statement of the Pediatric Gastroenterology Chapter of Indian Academy of Pediatrics.

PubMed

Bhatia, Vidyut; Bavdekar, Ashish; Matthai, John; Waikar, Yogesh; Sibal, Anupam

2014-03-01

Neonatal cholestasis is an important cause of chronic liver disease in young children. Late referral and lack of precise etiological diagnosis are reasons for poor outcome in substantial number of cases in India. There is a need to create better awareness among the pediatricians, obstetricians and primary care physicians on early recognition, prompt evaluation and referral to regional centers. Eminent national faculty members were invited to participate in the process of forming a consensus statement. Selected members were requested to prepare guidelines on specific issues, which were reviewed by two other members. These guidelines were then incorporated into a draft statement, which was circulated to all members. A round table conference was organized; presentations, ensuing discussions, and opinions expressed by the participants were incorporated into the final draft. To review available published data on the subject from India and the West, to discuss current diagnostic and management practices in major centers in India, and to identify various problems in effective diagnosis and ways to improve the overall outcome. Current problems faced in different areas were discussed and possible remedial measures were identified. The ultimate aim would be to achieve results comparable to the West. Early recognition, prompt evaluation and algorithm-based management will improve outcome in neonatal cholestasis. Inclusion of stool/urine color charts in well baby cards and sensitizing pediatricians about differentiating conjugated from the more common unconjugated hyperbilirubinemia are possible effective steps. Considering the need for specific expertise and the poor outcome in sub- optimally managed cases, referral to regional centers is warranted.

Patent Ductus Arteriosus in the Preterm Infant: Diagnostic and Treatment Options.

PubMed

Prescott, Stephanie; Keim-Malpass, Jessica

2017-02-01

The incidence of hemodynamically significant patent ductus arteriosus (hsPDA) increases with decreasing gestational age and is associated with many common morbidities of extreme prematurity. Controversies remain surrounding the definition of hsPDA, the population of infants requiring treatment, the appropriate timing and method of treatment, and the outcomes associated with PDA and its therapies. This integrative literature review focuses on diagnostic and treatment recommendations derived from the highest levels of evidence. PubMed and CINAHL were searched using key words "neonatal" and "patent ductus arteriosus" to discover the highest levels of evidence surrounding diagnosis, treatment methods, and outcomes. The lack of consensus surrounding the diagnosis and clinical significance of PDA hinders meta-analysis across studies and confounds understanding of appropriate management strategies. Novel biomarkers, pharmaceutical choices, and transcatheter closure methods are expanding diagnostic and treatment options. Infants weighing less than 1000 g are at highest risk. Prophylactic closure is no longer recommended, although early asymptomatic therapy is still preferred by some to avoid prolonged pulmonary overcirculation or decreased renal and gut perfusion. Conservative treatment measures such as fluid restriction and diuretic administration have not consistently proven effective and are in some instances detrimental. Cyclooxygenase inhibitors are effective but have adverse renal and mesenteric effects. Oral ibuprofen is associated with lower instance of necrotizing enterocolitis. Well-defined staging criteria would aid in comparison and meta-analysis. Trials that include a control group that receives no therapy may help separate the outcomes associated with prematurity from those associated with PDA.

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

PubMed

Hotz, Christine S; Templeton, Steven J; Christopher, Mary M

2005-03-01

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

PubMed

Martinelli, Eugenio; Mencattini, Arianna; Daprati, Elena; Di Natale, Corrado

2016-01-01

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present 'intelligent personal assistants', and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants' emotional state, selective/differential data collection based on emotional content, etc.).

Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images.

PubMed

Karim, Rashed; Bhagirath, Pranav; Claus, Piet; James Housden, R; Chen, Zhong; Karimaghaloo, Zahra; Sohn, Hyon-Mok; Lara Rodríguez, Laura; Vera, Sergio; Albà, Xènia; Hennemuth, Anja; Peitgen, Heinz-Otto; Arbel, Tal; Gonzàlez Ballester, Miguel A; Frangi, Alejandro F; Götte, Marco; Razavi, Reza; Schaeffter, Tobias; Rhode, Kawal

2016-05-01

Studies have demonstrated the feasibility of late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging for guiding the management of patients with sequelae to myocardial infarction, such as ventricular tachycardia and heart failure. Clinical implementation of these developments necessitates a reproducible and reliable segmentation of the infarcted regions. It is challenging to compare new algorithms for infarct segmentation in the left ventricle (LV) with existing algorithms. Benchmarking datasets with evaluation strategies are much needed to facilitate comparison. This manuscript presents a benchmarking evaluation framework for future algorithms that segment infarct from LGE CMR of the LV. The image database consists of 30 LGE CMR images of both humans and pigs that were acquired from two separate imaging centres. A consensus ground truth was obtained for all data using maximum likelihood estimation. Six widely-used fixed-thresholding methods and five recently developed algorithms are tested on the benchmarking framework. Results demonstrate that the algorithms have better overlap with the consensus ground truth than most of the n-SD fixed-thresholding methods, with the exception of the Full-Width-at-Half-Maximum (FWHM) fixed-thresholding method. Some of the pitfalls of fixed thresholding methods are demonstrated in this work. The benchmarking evaluation framework, which is a contribution of this work, can be used to test and benchmark future algorithms that detect and quantify infarct in LGE CMR images of the LV. The datasets, ground truth and evaluation code have been made publicly available through the website: https://www.cardiacatlas.org/web/guest/challenges. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Classifying syndromes in Chinese medicine using multi-label learning algorithm with relevant features for each label.

PubMed

Xu, Jin; Xu, Zhao-Xia; Lu, Ping; Guo, Rui; Yan, Hai-Xia; Xu, Wen-Jie; Wang, Yi-Qin; Xia, Chun-Ming

2016-11-01

To develop an effective Chinese Medicine (CM) diagnostic model of coronary heart disease (CHD) and to confifirm the scientifific validity of CM theoretical basis from an algorithmic viewpoint. Four types of objective diagnostic data were collected from 835 CHD patients by using a self-developed CM inquiry scale for the diagnosis of heart problems, a tongue diagnosis instrument, a ZBOX-I pulse digital collection instrument, and the sound of an attending acquisition system. These diagnostic data was analyzed and a CM diagnostic model was established using a multi-label learning algorithm (REAL). REAL was employed to establish a Xin (Heart) qi defificiency, Xin yang defificiency, Xin yin defificiency, blood stasis, and phlegm fifive-card CM diagnostic model, which had recognition rates of 80.32%, 89.77%, 84.93%, 85.37%, and 69.90%, respectively. The multi-label learning method established using four diagnostic models based on mutual information feature selection yielded good recognition results. The characteristic model parameters were selected by maximizing the mutual information for each card type. The four diagnostic methods used to obtain information in CM, i.e., observation, auscultation and olfaction, inquiry, and pulse diagnosis, can be characterized by these parameters, which is consistent with CM theory.

Achieving Routine Submillisievert CT Scanning: Report from the Summit on Management of Radiation Dose in CT

PubMed Central

Chen, Guang Hong; Kalender, Willi; Leng, Shuai; Samei, Ehsan; Taguchi, Katsuyuki; Wang, Ge; Yu, Lifeng; Pettigrew, Roderic I.

2012-01-01

This Special Report presents the consensus of the Summit on Management of Radiation Dose in Computed Tomography (CT) (held in February 2011), which brought together participants from academia, clinical practice, industry, and regulatory and funding agencies to identify the steps required to reduce the effective dose from routine CT examinations to less than 1 mSv. The most promising technologies and methods discussed at the summit include innovations and developments in x-ray sources; detectors; and image reconstruction, noise reduction, and postprocessing algorithms. Access to raw projection data and standard data sets for algorithm validation and optimization is a clear need, as is the need for new, clinically relevant metrics of image quality and diagnostic performance. Current commercially available techniques such as automatic exposure control, optimization of tube potential, beam-shaping filters, and dynamic z-axis collimators are important, and education to successfully implement these methods routinely is critically needed. Other methods that are just becoming widely available, such as iterative reconstruction, noise reduction, and postprocessing algorithms, will also have an important role. Together, these existing techniques can reduce dose by a factor of two to four. Technical advances that show considerable promise for additional dose reduction but are several years or more from commercial availability include compressed sensing, volume of interest and interior tomography techniques, and photon-counting detectors. This report offers a strategic roadmap for the CT user and research and manufacturer communities toward routinely achieving effective doses of less than 1 mSv, which is well below the average annual dose from naturally occurring sources of radiation. © RSNA, 2012 PMID:22692035

First European consensus for diagnosis, management, and treatment of transthyretin familial amyloid polyneuropathy

PubMed Central

Adams, David; Suhr, Ole B.; Hund, Ernst; Obici, Laura; Tournev, Ivailo; Campistol, Josep M.; Slama, Michel S.; Hazenberg, Bouke P.; Coelho, Teresa

2016-01-01

Purpose of review Early and accurate diagnosis of transthyretin familial amyloid polyneuropathy (TTR-FAP) represents one of the major challenges faced by physicians when caring for patients with idiopathic progressive neuropathy. There is little consensus in diagnostic and management approaches across Europe. Recent findings The low prevalence of TTR-FAP across Europe and the high variation in both genotype and phenotypic expression of the disease means that recognizing symptoms can be difficult outside of a specialized diagnostic environment. The resulting delay in diagnosis and the possibility of misdiagnosis can misguide clinical decision-making and negatively impact subsequent treatment approaches and outcomes. Summary This review summarizes the findings from two meetings of the European Network for TTR-FAP (ATTReuNET). This is an emerging group comprising representatives from 10 European countries with expertise in the diagnosis and management of TTR-FAP, including nine National Reference Centres. The current review presents management strategies and a consensus on the gold standard for diagnosis of TTR-FAP as well as a structured approach to ongoing multidisciplinary care for the patient. Greater communication, not just between members of an individual patient's treatment team, but also between regional and national centres of expertise, is the key to the effective management of TTR-FAP. PMID:26734952

Expert consensus document: Advances in the evaluation of anorectal function.

PubMed

Carrington, Emma V; Scott, S Mark; Bharucha, Adil; Mion, François; Remes-Troche, Jose M; Malcolm, Allison; Heinrich, Henriette; Fox, Mark; Rao, Satish S

2018-05-01

Faecal incontinence and evacuation disorders are common, impair quality of life and incur substantial economic costs worldwide. As symptoms alone are poor predictors of underlying pathophysiology and aetiology, diagnostic tests of anorectal function could facilitate patient management in those cases that are refractory to conservative therapies. In the past decade, several major technological advances have improved our understanding of anorectal structure, coordination and sensorimotor function. This Consensus Statement provides the reader with an appraisal of the current indications, study performance characteristics, clinical utility, strengths and limitations of the most widely available tests of anorectal structure (ultrasonography and MRI) and function (anorectal manometry, neurophysiological investigations, rectal distension techniques and tests of evacuation, including defecography). Additionally, this article provides our consensus on the clinical relevance of these tests.

Seizures in the elderly: development and validation of a diagnostic algorithm.

PubMed

Dupont, Sophie; Verny, Marc; Harston, Sandrine; Cartz-Piver, Leslie; Schück, Stéphane; Martin, Jennifer; Puisieux, François; Alecu, Cosmin; Vespignani, Hervé; Marchal, Cécile; Derambure, Philippe

2010-05-01

Seizures are frequent in the elderly, but their diagnosis can be challenging. The objective of this work was to develop and validate an expert-based algorithm for the diagnosis of seizures in elderly people. A multidisciplinary group of neurologists and geriatricians developed a diagnostic algorithm using a combination of selected clinical, electroencephalographical and radiological criteria. The algorithm was validated by multicentre retrospective analysis of data of patients referred for specific symptoms and classified by the experts as epileptic patients or not. The algorithm was applied to all the patients, and the diagnosis provided by the algorithm was compared to the clinical diagnosis of the experts. Twenty-nine clinical, electroencephalographical and radiological criteria were selected for the algorithm. According to criteria combination, seizures were classified in four levels of diagnosis: certain, highly probable, possible or improbable. To validate the algorithm, the medical records of 269 elderly patients were analyzed (138 with epileptic seizures, 131 with non-epileptic manifestations). Patients were mainly referred for a transient focal deficit (40%), confusion (38%), unconsciousness (27%). The algorithm best classified certain and probable seizures versus possible and improbable seizures, with 86.2% sensitivity and 67.2% specificity. Using logistical regression, 2 simplified models were developed, the first with 13 criteria (Se 85.5%, Sp 90.1%), and the second with 7 criteria only (Se 84.8%, Sp 88.6%). In conclusion, the present study validated the use of a revised diagnostic algorithm to help diagnosis epileptic seizures in the elderly. A prospective study is planned to further validate this algorithm. Copyright 2010 Elsevier B.V. All rights reserved.

Inaccuracy of Wolff-Parkinson-white accessory pathway localization algorithms in children and patients with congenital heart defects.

PubMed

Bar-Cohen, Yaniv; Khairy, Paul; Morwood, James; Alexander, Mark E; Cecchin, Frank; Berul, Charles I

2006-07-01

ECG algorithms used to localize accessory pathways (AP) in patients with Wolff-Parkinson-White (WPW) syndrome have been validated in adults, but less is known of their use in children, especially in patients with congenital heart disease (CHD). We hypothesize that these algorithms have low diagnostic accuracy in children and even lower in those with CHD. Pre-excited ECGs in 43 patients with WPW and CHD (median age 5.4 years [0.9-32 years]) were evaluated and compared to 43 consecutive WPW control patients without CHD (median age 14.5 years [1.8-18 years]). Two blinded observers predicted AP location using 2 adult and 1 pediatric WPW algorithms, and a third blinded observer served as a tiebreaker. Predicted locations were compared with ablation-verified AP location to identify (a) exact match for AP location and (b) match for laterality (left-sided vs right-sided AP). In control children, adult algorithms were accurate in only 56% and 60%, while the pediatric algorithm was correct in 77%. In 19 patients with Ebstein's anomaly, diagnostic accuracy was similar to controls with at times an even better ability to predict laterality. In non-Ebstein's CHD, however, the algorithms were markedly worse (29% for the adult algorithms and 42% for the pediatric algorithms). A relatively large degree of interobserver variability was seen (kappa values from 0.30 to 0.58). Adult localization algorithms have poor diagnostic accuracy in young patients with and without CHD. Both adult and pediatric algorithms are particularly misleading in non-Ebstein's CHD patients and should be interpreted with caution.

Comparison of Diagnostic Algorithms for Detecting Toxigenic Clostridium difficile in Routine Practice at a Tertiary Referral Hospital in Korea.

PubMed

Moon, Hee-Won; Kim, Hyeong Nyeon; Hur, Mina; Shim, Hee Sook; Kim, Heejung; Yun, Yeo-Min

2016-01-01

Since every single test has some limitations for detecting toxigenic Clostridium difficile, multistep algorithms are recommended. This study aimed to compare the current, representative diagnostic algorithms for detecting toxigenic C. difficile, using VIDAS C. difficile toxin A&B (toxin ELFA), VIDAS C. difficile GDH (GDH ELFA, bioMérieux, Marcy-l'Etoile, France), and Xpert C. difficile (Cepheid, Sunnyvale, California, USA). In 271 consecutive stool samples, toxigenic culture, toxin ELFA, GDH ELFA, and Xpert C. difficile were performed. We simulated two algorithms: screening by GDH ELFA and confirmation by Xpert C. difficile (GDH + Xpert) and combined algorithm of GDH ELFA, toxin ELFA, and Xpert C. difficile (GDH + Toxin + Xpert). The performance of each assay and algorithm was assessed. The agreement of Xpert C. difficile and two algorithms (GDH + Xpert and GDH+ Toxin + Xpert) with toxigenic culture were strong (Kappa, 0.848, 0.857, and 0.868, respectively). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of algorithms (GDH + Xpert and GDH + Toxin + Xpert) were 96.7%, 95.8%, 85.0%, 98.1%, and 94.5%, 95.8%, 82.3%, 98.5%, respectively. There were no significant differences between Xpert C. difficile and two algorithms in sensitivity, specificity, PPV and NPV. The performances of both algorithms for detecting toxigenic C. difficile were comparable to that of Xpert C. difficile. Either algorithm would be useful in clinical laboratories and can be optimized in the diagnostic workflow of C. difficile depending on costs, test volume, and clinical needs.

A Cognitive Machine Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis from Restrictive Cardiomyopathy

PubMed Central

Sengupta, Partho P.; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

2016-01-01

Background Associating a patient’s profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography (STE) data sets derived from patients with known constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods and Results Clinical and echocardiographic data of 50 patients with CP and 44 with RCM were used for developing an associative memory classifier (AMC) based machine learning algorithm. The STE data was normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve (AUC) of the AMC was evaluated for differentiating CP from RCM. Using only STE variables, AMC achieved a diagnostic AUC of 89·2%, which improved to 96·2% with addition of 4 echocardiographic variables. In comparison, the AUC of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63·7%, respectively. Furthermore, AMC demonstrated greater accuracy and shorter learning curves than other machine learning approaches with accuracy asymptotically approaching 90% after a training fraction of 0·3 and remaining flat at higher training fractions. Conclusions This study demonstrates feasibility of a cognitive machine learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. PMID:27266599

Complex interferometry potential in case of sufficiently stable diagnostic system

NASA Astrophysics Data System (ADS)

Kalal, M.

2016-06-01

Classical interferometry is one of the key methods among active optical diagnostics. Its more advanced version, which allows recording and subsequent reconstruction of up to three sets of data using just one data object —a complex interferogram—was developed in the past and became known as complex interferometry. Employing this diagnostics, not only the usual phase shift, but also the amplitude of the probing beam as well as the fringe contrast (leading directly to the phase shift time derivative) can be reconstructed simultaneously from such a complex interferogram. In this paper it will be demonstrated that even in the case of a not particularly good diagnostic beam quality these three quantities can be reconstructed with a high degree of accuracy provided both the diagnostic beam as well as the corresponding optical line feature a reasonable stability. Such stability requirement is important as in an ideal case four shots need to be gradually recorded (one by one): the signal complex interferogram, the reference interferogram as well as the intensity structures of the signal and reference part of the diagnostic beam. Two examples of complex interferograms obtained in experiments will be analyzed: the laser produced plasma (spark in the air) and the high pressure gas jet. A general ray-tracing based iterative algorithm will be outlined in order to increase a precision of the index of refraction spatial profile taking into account refraction effects (omitted in the Abel inversion) and employing the original reconstructed phase shift and amplitude.

Diagnostic tests and algorithms used in the investigation of haematuria: systematic reviews and economic evaluation.

PubMed

Rodgers, M; Nixon, J; Hempel, S; Aho, T; Kelly, J; Neal, D; Duffy, S; Ritchie, G; Kleijnen, J; Westwood, M

2006-06-01

To determine the most effective diagnostic strategy for the investigation of microscopic and macroscopic haematuria in adults. Electronic databases from inception to October 2003, updated in August 2004. A systematic review was undertaken according to published guidelines. Decision analytic modelling was undertaken, based on the findings of the review, expert opinion and additional information from the literature, to assess the relative cost-effectiveness of plausible alternative tests that are part of diagnostic algorithms for haematuria. A total of 118 studies met the inclusion criteria. No studies that evaluated the effectiveness of diagnostic algorithms for haematuria or the effectiveness of screening for haematuria or investigating its underlying cause were identified. Eighteen out of 19 identified studies evaluated dipstick tests and data from these suggested that these are moderately useful in establishing the presence of, but cannot be used to rule out, haematuria. Six studies using haematuria as a test for the presence of a disease indicated that the detection of microhaematuria cannot alone be considered a useful test either to rule in or rule out the presence of a significant underlying pathology (urinary calculi or bladder cancer). Forty-eight of 80 studies addressed methods to localise the source of bleeding (renal or lower urinary tract). The methods and thresholds described in these studies varied greatly, precluding any estimate of a 'best performance' threshold that could be applied across patient groups. However, studies of red blood cell morphology that used a cut-off value of 80% dysmorphic cells for glomerular disease reported consistently high specificities (potentially useful in ruling in a renal cause for haematuria). The reported sensitivities were generally low. Twenty-eight studies included data on the accuracy of laboratory tests (tumour markers, cytology) for the diagnosis of bladder cancer. The majority of tumour marker studies evaluated nuclear matrix protein 22 or bladder tumour antigen. The sensitivity and specificity ranges suggested that neither of these would be useful either for diagnosing bladder cancer or for ruling out patients for further investigation (cystoscopy). However, the evidence remains sparse and the diagnostic accuracy estimates varied widely between studies. Fifteen studies evaluating urine cytology as a test for urinary tract malignancies were heterogeneous and poorly reported. The calculated specificity values were generally high, suggesting some possible utility in confirming malignancy. However, the evidence suggests that urine cytology has no application in ruling out malignancy or excluding patients from further investigation. Fifteen studies evaluated imaging techniques [computed tomography (CT), intravenous urography (IVU) or ultrasound scanning (US)] to detect the underlying cause of haematuria. The target condition and the reference standard varied greatly between these studies. The diagnostic accuracy data for several individual studies appeared promising but meaningful comparison of the available imaging technologies was impossible. Eight studies met the inclusion criteria but addressed different parts of the diagnostic chain (e.g. screening programmes, laboratory investigations, full urological work-up). No single study addressed the complete diagnostic process. The review also highlighted a number of methodological limitations of these studies, including their lack of generalisability to the UK context. Separate decision analytic models were therefore developed to progress estimation of the optimal strategy for the diagnostic management of haematuria. The economic model for the detection of microhaematuria found that immediate microscopy following a positive dipstick test would improve diagnostic efficiency as it eliminates the high number of false positives produced by dipstick testing. Strategies that use routine microscopy may be associated with high numbers of false results, but evidence was lacking regarding the accuracy of routine microscopy and estimates were adopted for the model. The model for imaging the upper urinary tract showed that US detects more tumours than IVU at one-third of the cost, and is also associated with fewer false results. For any cause of haematuria, CT was shown to have a mean incremental cost-effectiveness ratio of pounds sterling 9939 in comparison with the next best option, US. When US is followed up with CT for negative results with persistent haematuria, it dominates the initial use of CT alone, with a saving of pounds sterling 235,000 for the evaluation of 1000 patients. The model for investigation of the lower urinary tract showed that for low-risk patients the use of immediate cystoscopy could be avoided if cystoscopy were used for follow-up patients with a negative initial test using tumour markers and/or cytology, resulting in a saving of pounds sterling 483,000 for the evaluation of 1000 patients. The clinical and economic impact on delayed detection of both upper and lower urinary tract tumours through the use of follow-up testing should be evaluated in future studies. There are insufficient data currently available to derive an evidence-based algorithm of the diagnostic pathway for haematuria. A hypothetical algorithm based on the opinion and practice of clinical experts in the review team, other published algorithms and the results of economic modelling is presented in this report. This algorithm is presented, for comparative purposes, alongside current US and UK guidelines. The ideas contained in these algorithms and the specific questions outlined should form the basis of future research. Quality assessment of the diagnostic accuracy studies included in this review highlighted several areas of deficiency.

Finite-time consensus for controlled dynamical systems in network

NASA Astrophysics Data System (ADS)

Zoghlami, Naim; Mlayeh, Rhouma; Beji, Lotfi; Abichou, Azgal

2018-04-01

The key challenges in networked dynamical systems are the component heterogeneities, nonlinearities, and the high dimension of the formulated vector of state variables. In this paper, the emphasise is put on two classes of systems in network include most controlled driftless systems as well as systems with drift. For each model structure that defines homogeneous and heterogeneous multi-system behaviour, we derive protocols leading to finite-time consensus. For each model evolving in networks forming a homogeneous or heterogeneous multi-system, protocols integrating sufficient conditions are derived leading to finite-time consensus. Likewise, for the networking topology, we make use of fixed directed and undirected graphs. To prove our approaches, finite-time stability theory and Lyapunov methods are considered. As illustrative examples, the homogeneous multi-unicycle kinematics and the homogeneous/heterogeneous multi-second order dynamics in networks are studied.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

Distributed Finite-Time Cooperative Control of Multiple High-Order Nonholonomic Mobile Robots.

PubMed

Du, Haibo; Wen, Guanghui; Cheng, Yingying; He, Yigang; Jia, Ruting

2017-12-01

The consensus problem of multiple nonholonomic mobile robots in the form of high-order chained structure is considered in this paper. Based on the model features and the finite-time control technique, a finite-time cooperative controller is explicitly constructed which guarantees that the states consensus is achieved in a finite time. As an application of the proposed results, finite-time formation control of multiple wheeled mobile robots is studied and a finite-time formation control algorithm is proposed. To show effectiveness of the proposed approach, a simulation example is given.

Assessing Cognitive Function in Bipolar Disorder: Challenges and Recommendations for Clinical Trial Design

PubMed Central

Burdick, Katherine E.; Ketter, Terence A.; Goldberg, Joseph F.; Calabrese, Joseph R.

2015-01-01

OBJECTIVE Neurocognitive impairment in schizophrenia has been recognized for more than a century. In contrast, only recently have significant neurocognitive deficits been recognized in bipolar disorder. Converging data suggest the importance of cognitive problems in relation to quality of life in bipolar disorder, highlighting the need for treatment and prevention efforts targeting cognition in bipolar patients. Future treatment trials targeting cognitive deficits will be met with methodological challenges due to the inherent complexity and heterogeneity of the disorder, including significant diagnostic comorbidities, the episodic nature of the illness, frequent use of polypharmacy, cognitive heterogeneity, and a lack of consensus regarding measurement of cognition and outcome in bipolar patients. Guidelines for use in designing future trials are needed. PARTICIPANTS The members of the consensus panel (each of the bylined authors) were selected based upon their expertise in bipolar disorder. Dr. Burdick is a neuropsychologist who has studied cognition in this illness for 15 years; Drs. Ketter, Calabrese, and Goldberg each bring considerable expertise in the treatment of bipolar disorder both within and outside of controlled clinical trials. This consensus statement was derived from work together at scientific meetings (e.g. symposium presention at the 2014 Annual meeting of the American Society of Clinical Psychopharmacology, among others) and ongoing discussions by conference call. With the exception of the public presentations on this topic, these meetings were closed to outside participants. EVIDENCE A literature review was undertaken by the authors to identify illness-specific challenges relevant to the design and conduct of treatment trials targeting neurocognition in bipolar disorder. Expert opinion from each of the authors guided the consensus recommendations. CONSENSUS PROCESS Consensus recommendations, reached by unanimous opinion of the authors, are provided here as a preliminary guide for future trial design. Recommendations comprise exclusion of certain syndromal level comorbid diagnoses and current affective instability, restrictions on numbers and types of medications, and use of pre-screening assessment to ensure enrollment of subjects with adequate objective evidence of baseline cognitive impairment. CONCLUSIONS Clinical trials to address cognitive deficits in bipolar disorder face distinctive design challenges. As such trials move from proof-of-concept to confirmation of clinical efficacy, it will be important to incorporate distinctive design modifications to adequately address these challenges and increase the likelihood of demonstrating cognitive remediation effects. The field is now primed to address these challenges and a comprehensive effort to formalize best practice guidelines will be a critically important next step. PMID:25830456

Time for a neonatal–specific consensus definition for sepsis

PubMed Central

Wynn, James L.; Wong, Hector R.; Shanley, Thomas P.; Bizzarro, Matthew J.; Saiman, Lisa; Polin, Richard A.

2014-01-01

Objective To review the accuracy of the pediatric consensus definition of sepsis in term neonates and to determine the definition of neonatal sepsis used. Study selection The review focused primarily on pediatric literature relevant to the topic of interest. Conclusions Neonatal sepsis is variably defined based on a number of clinical and laboratory criteria that make the study of this common and devastating condition very difficult. Diagnostic challenges and uncertain disease epidemiology necessarily result from a variable definition of disease. In 2005, intensivists caring for children recognized that as new drugs became available, children would be increasingly studied and thus, pediatric-specific consensus definitions were needed. Pediatric sepsis criteria are not accurate for term neonates and have not been examined in preterm neonates for whom the developmental stage influences aberrations associated with host immune response. Thus, specific consensus definitions for both term and preterm neonates are needed. Such definitions are critical for the interpretation of observational studies, future training of scientists and practitioners, and implementation of clinical trials in neonates. PMID:24751791

Diagnostic accuracy study of anorectal manometry for diagnosis of dyssynergic defaecation

PubMed Central

Grossi, Ugo; Carrington, Emma V; Bharucha, Adil E; Horrocks, Emma J; Scott, S Mark; Knowles, Charles H

2015-01-01

Objective The diagnostic accuracy of anorectal manometry (AM), which is necessary to diagnose functional defaecatory disorders (FDD), is unknown. Using blinded analysis and standardised reporting of diagnostic accuracy (STARD), we evaluated whether AM could discriminate between asymptomatic controls and patients with functional constipation (FC). Design Derived line-plots of anorectal pressure profiles during simulated defaecation were independently analysed in random order by 3 expert observers blinded to health status in 85 women with FC and 85 age-matched asymptomatic healthy volunteers (HV). Using accepted criteria, these pressure profiles were characterized as normal (i.e. increased rectal pressure coordinated with anal relaxation) or types I-IV dyssynergia. Inter-observer agreement and diagnostic accuracy were determined. Results Blinded consensus-based assessment disclosed a normal pattern in 16/170 (9%) of all participants and only 11/85 (13%) HV. The combined frequency of dyssynergic patterns (I-IV) was very similar in FC (80/85 [94%]) and HV (74/85 [87%]). Type I dyssynergia (‘paradoxical’ contraction) was less prevalent in FC (17/85 [20%] than HV (31/85 [36.5%], p=0.03). After statistical correction, only type IV dyssynergia was moderately useful for discriminating between FC (39/85 [46%] and HV 17/85 [20%], p=0.001, PPV=70.0%, positive LR=2.3). Inter-observer agreement was substantial or moderate for identifying a normal pattern, dyssynergia types I and IV, and FDD, and fair for types II and III. Conclusions While the interpretation of AM patterns is reproducible, nearly 90% of HV have a pattern that is currently regarded as “abnormal” by AM. Hence AM is of limited utility for distinguishing between FC and HV. PMID:25765461

Multiple criteria decision-making process to derive consensus desired genetic gains for a dairy cattle breeding objective for diverse production systems.

PubMed

Kariuki, C M; van Arendonk, J A M; Kahi, A K; Komen, H

2017-06-01

Dairy cattle industries contribute to food and nutrition security and are a source of income for numerous households in many developing countries. Selective breeding can enhance efficiency in these industries. Developing dairy industries are characterized by diverse production and marketing systems. In this paper, we use weighted goal aggregating procedure to derive consensus trait preferences for different producer categories and processors. We based the study on the dairy industry in Kenya. The analytic hierarchy process was used to derive individual preferences for milk yield (MY), calving interval (CIN), production lifetime (PLT), mature body weight (MBW), and fat yield (FY). Results show that classical classification of production systems into large-scale and smallholder systems does not capture all differences in trait preferences. These differences became apparent when classification was based on productivity at the individual animal level, with high and low intensity producers and processors as the most important groups. High intensity producers had highest preferences for PLT and MY, whereas low intensity producers had highest preference for CIN and PLT; processors preferred MY and FY the most. The highest disagreements between the groups were observed for FY, PLT, and MY. Individual and group preferences were aggregated into consensus preferences using weighted goal programming. Desired gains were obtained as a product of consensus preferences and percentage genetic gains (G%). These were 2.42, 0.22, 2.51, 0.15, and 0.87 for MY, CIN, PLT, MBW, and FY, respectively. Consensus preferences can be used to derive a single compromise breeding objective for situations where the same genetic resources are used in diverse production and marketing circumstances. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Follow-up after gastrectomy for cancer: the Charter Scaligero Consensus Conference.

PubMed

Baiocchi, Gian Luca; D'Ugo, Domenico; Coit, Daniel; Hardwick, Richard; Kassab, Paulo; Nashimoto, Atsushi; Marrelli, Daniele; Allum, William; Berruti, Alfredo; Chandramohan, Servarayan Murugesan; Coburn, Natalie; Gonzàlez-Moreno, Santiago; Hoelscher, Arnulf; Jansen, Edwin; Leja, Marcis; Mariette, Christophe; Meyer, Hans-Joachim; Mönig, Stefan; Morgagni, Paolo; Ott, Katia; Preston, Shaun; Rha, Sun Young; Roviello, Franco; Sano, Takeshi; Sasako, Mitsuru; Shimada, Hideaki; Schuhmacher, Cristoph; So Bok-Yan, Jimmy; Strong, Vivian; Yoshikawa, Takaki; Terashima, Masanori; Ter-Ovanesov, Michail; Van der Velde, Cornelis; Memo, Maurizio; Castelli, Francesco; Pecorelli, Sergio; Detogni, Claudio; Kodera, Yasuhiro; de Manzoni, Giovanni

2016-01-01

Presently, there is no scientific evidence supporting a definite role for follow-up after gastrectomy for cancer, and clinical practices are quite different around the globe. The aim of this consensus conference was to present an ideal prototype of follow-up after gastrectomy for cancer, based on shared experiences and taking into account the need to rationalize the diagnostic course without losing the possibility of detecting local recurrence at a potentially curable stage. On June 19-22, 2013 in Verona (Italy), during the 10th International Gastric Cancer Congress (IGCC) of the International Gastric Cancer Association, a consensus meeting was held, concluding a 6-month, Web-based, consensus conference entitled "Rationale of oncological follow-up after gastrectomy for cancer." Forty-eight experts, with a geographical distribution reflecting different health cultures worldwide, participated in the consensus conference, and 39 attended the consensus meeting. Six statements were finally approved, displayed in a plenary session and signed by the vast majority of the 10th IGCC participants. These statements are attached as an annex to the Charter Scaligero on Gastric Cancer. After gastrectomy for cancer, oncological follow-up should be offered to patients; it should be tailored to the stage of the disease, mainly based on cross-sectional imaging, and should be discontinued after 5 years.

Consensus recommendations for improvement of unmet clinical needs--the example of chronic graft-versus-host disease: a systematic review and meta-analysis.

PubMed

Olivieri, Jacopo; Manfredi, Lucia; Postacchini, Laura; Tedesco, Silvia; Leoni, Pietro; Gabrielli, Armando; Rambaldi, Alessandro; Bacigalupo, Andrea; Olivieri, Attilio; Pomponio, Giovanni

2015-07-01

Consensus recommendations are used to improve the methodology of research about rare disorders, but their uptake is unknown. We studied the uptake of consensus recommendations in steroid-refractory chronic graft-versus-host disease (SR-cGVHD). Although in 2006 the National Institutes of Health (NIH) cGVHD consensus project produced recommendations for clinical trials, guidelines have emphasised the scarcity of valuable evidence for all tested interventions. We searched Medline (PubMed) between Jan 1, 1998, and Oct 1, 2013, for non-randomised studies of systemic treatment for SR-cGVHD. To measure adherence to NIH recommendations, we applied a 61 item checklist derived from the NIH consensus document. We did a meta-analysis to measure pooled effect size for overall response rate (ORR) and meta-regression analyses to measure the effect of deviations from NIH recommendations on pooled effect size. We included 82 studies related to nine interventions. Conformity to NIH recommendations was evenly low across the analysed timeframe (1998-2013), and did not change significantly after publication of NIH recommendations. The pooled effect size for ORR for systemic treatment of SR-cGVHD was 0.66 (95% CI 0.62-0.70). Increased adherence to NIH recommendations in a score of items defining correct response assessment was associated with a significant reduction in ORR (-4.2%, 95% CI -6.6 to -1.9; p=0.001). We recorded no significant association between ORR and sets of items related to correct diagnostic definition of SR-cGVHD (change in ORR -3.1%, 95% CI -7.7 to 1.5), specification of primary intervention (0, -3.8 to 3.6), or concomitant treatments (-1.6%, -5.4 to 2.3). The score of items defining correct response assessment increased after publication of NIH recommendations. Our findings show evidence of bias in the reported efficacy of treatment of SR-cGVHD. The overall effect of NIH recommendations in scientific literature is scarce; however, NIH recommendations improved assessment of response, possibly reducing the overestimation bias. Better implementation of NIH recommendations might reduce false expectations about new interventions, and thus prevent clinical studies with ineffective treatments. None. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lexical Morphology: Structure, Process, and Development

ERIC Educational Resources Information Center

Jarmulowicz, Linda; Taran, Valentina L.

2013-01-01

Recent work has demonstrated the importance of derivational morphology to later language development and has led to a consensus that derivation is a lexical process. In this review, derivational morphology is discussed in terms of lexical representation models from both linguistic and psycholinguistic perspectives. Input characteristics, including…

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites

PubMed Central

Kosack, Cara S.; Shanks, Leslie; Beelaert, Greet; Benson, Tumwesigye; Savane, Aboubacar; Ng’ang’a, Anne; Andre, Bita; Zahinda, Jean-Paul BN; Fransen, Katrien; Page, Anne-Laure

2017-01-01

Abstract Introduction: We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. Methods: In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. Results: Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. Conclusions: The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy. PMID:28691437

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites.

PubMed

Kosack, Cara S; Shanks, Leslie; Beelaert, Greet; Benson, Tumwesigye; Savane, Aboubacar; Ng'ang'a, Anne; Andre, Bita; Zahinda, Jean-Paul Bn; Fransen, Katrien; Page, Anne-Laure

2017-07-03

We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy.

Strategy Formulation in Small Enterprises: A Developmental Approach.

ERIC Educational Resources Information Center

Paton, Robert; Brownlie, Douglas

1991-01-01

The Small Company European Analysis Technique is a diagnostic tool that small businesses can use to analyze market opportunities in preparation for 1992. The approach uses small group consensus building as in the Delphi technique and brainstorming to formulate a strategic plan. (SK)

Mathematical detection of aortic valve opening (B point) in impedance cardiography: A comparison of three popular algorithms.

PubMed

Árbol, Javier Rodríguez; Perakakis, Pandelis; Garrido, Alba; Mata, José Luis; Fernández-Santaella, M Carmen; Vila, Jaime

2017-03-01

The preejection period (PEP) is an index of left ventricle contractility widely used in psychophysiological research. Its computation requires detecting the moment when the aortic valve opens, which coincides with the B point in the first derivative of impedance cardiogram (ICG). Although this operation has been traditionally made via visual inspection, several algorithms based on derivative calculations have been developed to enable an automatic performance of the task. However, despite their popularity, data about their empirical validation are not always available. The present study analyzes the performance in the estimation of the aortic valve opening of three popular algorithms, by comparing their performance with the visual detection of the B point made by two independent scorers. Algorithm 1 is based on the first derivative of the ICG, Algorithm 2 on the second derivative, and Algorithm 3 on the third derivative. Algorithm 3 showed the highest accuracy rate (78.77%), followed by Algorithm 1 (24.57%) and Algorithm 2 (13.82%). In the automatic computation of PEP, Algorithm 2 resulted in significantly more missed cycles (48.57%) than Algorithm 1 (6.3%) and Algorithm 3 (3.5%). Algorithm 2 also estimated a significantly lower average PEP (70 ms), compared with the values obtained by Algorithm 1 (119 ms) and Algorithm 3 (113 ms). Our findings indicate that the algorithm based on the third derivative of the ICG performs significantly better. Nevertheless, a visual inspection of the signal proves indispensable, and this article provides a novel visual guide to facilitate the manual detection of the B point. © 2016 Society for Psychophysiological Research.

Diagnostic characteristics and metabolic risk factors of cases with polycystic ovary syndrome during adolescence.

PubMed

Sıklar, Zeynep; Berberoğlu, Merih; Çamtosun, Emine; Kocaay, Pınar

2015-04-01

Polycystic ovary syndrome (PCOS) is a disorder without definite consensus on its diagnosis and management during adolescence. According to Amsterdam-2012 consensus, as physiological characteristics of adolescence may overlap with PCOS signs, it has been indicated that all Rotterdam criteria should be met. In this present study, characteristics of adolescents with different phenotypes who were diagnosed with PCOS were evaluated; and presence of differences for metabolic risk factors between phenotypes were investigated. The study was performed on adolescent females. According to phenotypic application models, individuals with all Rotterdam diagnostic criteria [hyperandrogenism (HA), polycystic ovarian morphology (PCOM), and chronic anovulation (CA) on the ultrasonography] were in Group 1 (n = 26); with HA and CA were in Group 2 (n = 10); with HA and PCOM were in Group 3 (n = 7); and with CA and PCOM were in Group 4 (n = 10). The most common application complaint (87%) among 53 cases enrolled in the study was menstrual irregularities, and 57% of cases were not obese. When PCOS was evaluated according to phenotypes, it was realized that cases that meet all 3 diagnostic Rotterdam criteria according to the current recommendation in adolescents. (Group 1) was the most common phenotype. Hyperandrogenism was associated with more metabolic abnormalities. The close monitoring of adolescents, who have 2 diagnostic criteria is advisable among PCOS phenotypes. Potentially Groups 2 and 3 which have hyperandrogenism, in particular should warrant closer follow-up although they do not meet current diagnostic criteria for adolescents. Copyright © 2015 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

Asian Consensus Report on Functional Dyspepsia

PubMed Central

Miwa, Hiroto; Ghoshal, Uday C; Gonlachanvit, Sutep; Gwee, Kok-Ann; Ang, Tiing-Leong; Chang, Full-Young; Fock, Kwong Ming; Hongo, Michio; Hou, Xiaohua; Kachintorn, Udom; Ke, Meiyun; Lai, Kwok-Hung; Lee, Kwang Jae; Lu, Ching-Liang; Mahadeva, Sanjiv; Miura, Soichiro; Park, Hyojin; Rhee, Poong-Lyul; Sugano, Kentaro; Vilaichone, Ratha-korn; Wong, Benjamin CY

2012-01-01

Background/Aims Environmental factors such as food, lifestyle and prevalence of Helicobacter pylori infection are widely different in Asian countries compared to the West, and physiological functions and genetic factors of Asians may also be different from those of Westerners. Establishing an Asian consensus for functional dyspepsia is crucial in order to attract attention to such data from Asian countries, to articulate the experience and views of Asian experts, and to provide a relevant guide on management of functional dyspepsia for primary care physicians working in Asia. Methods Consensus team members were selected from Asian experts and consensus development was carried out using a modified Delphi method. Consensus teams collected published papers on functional dyspepsia especially from Asia and developed candidate consensus statements based on the generated clinical questions. At the first face-to-face meeting, each statement was reviewed and e-mail voting was done twice. At the second face-to-face meeting, final voting on each statement was done using keypad voting system. A grade of evidence and a strength of recommendation were applied to each statement according to the method of the GRADE Working Group. Results Twenty-nine consensus statements were finalized, including 7 for definition and diagnosis, 5 for epidemiology, 9 for pathophysiology and 8 for management. Algorithms for diagnosis and management of functional dyspepsia were added. Conclusions This consensus developed by Asian experts shows distinctive features of functional dyspepsia in Asia and will provide a guide to the diagnosis and management of functional dyspepsia for Asian primary care physicians. PMID:22523724

Developmental coordination disorders: state of art.

PubMed

Vaivre-Douret, L

2014-01-01

In the literature, descriptions of children with motor coordination difficulties and clumsy movements have been discussed since the early 1900s. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), it is a marked impairment in the development of fine or global motor coordination, affecting 6% of school-age children. All these children are characterized for developmental coordination disorder (DCD) in motor learning and new motor skill acquisition, in contrast to adult apraxia which is a disorder in the execution of already learned movements. No consensus has been established about etiology of DCD. Intragroup approach through factor and cluster analysis highlights that motor impairment in DCD children varies both in severity and nature. Indeed, most studies have used screening measures of performance on some developmental milestones derived from global motor tests. A few studies have investigated different functions together with standardized assessments, such as neuromuscular tone and soft signs, qualitative and quantitative measures related to gross and fine motor coordination and the specific difficulties -academic, language, gnosic, visual motor/visual-perceptual, and attentional/executive- n order to allow a better identification of DCD subtypes with diagnostic criteria and to provide an understanding of the mechanisms and of the cerebral involvement. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Sex-specific performance of pre-imaging diagnostic algorithms for pulmonary embolism.

PubMed

van Mens, T E; van der Pol, L M; van Es, N; Bistervels, I M; Mairuhu, A T A; van der Hulle, T; Klok, F A; Huisman, M V; Middeldorp, S

2018-05-01

Essentials Decision rules for pulmonary embolism are used indiscriminately despite possible sex-differences. Various pre-imaging diagnostic algorithms have been investigated in several prospective studies. When analysed at an individual patient data level the algorithms perform similarly in both sexes. Estrogen use and male sex were associated with a higher prevalence in suspected pulmonary embolism. Background In patients suspected of pulmonary embolism (PE), clinical decision rules are combined with D-dimer testing to rule out PE, avoiding the need for imaging in those at low risk. Despite sex differences in several aspects of the disease, including its diagnosis, these algorithms are used indiscriminately in women and men. Objectives To compare the performance, defined as efficiency and failure rate, of three pre-imaging diagnostic algorithms for PE between women and men: the Wells rule with fixed or with age-adjusted D-dimer cut-off, and a recently validated algorithm (YEARS). A secondary aim was to determine the sex-specific prevalence of PE. Methods Individual patient data were obtained from six studies using the Wells rule (fixed D-dimer, n = 5; age adjusted, n = 1) and from one study using the YEARS algorithm. All studies prospectively enrolled consecutive patients with suspected PE. Main outcomes were efficiency (proportion of patients in which the algorithm ruled out PE without imaging) and failure rate (proportion of patients with PE not detected by the algorithm). Outcomes were estimated using (multilevel) logistic regression models. Results The main outcomes showed no sex differences in any of the separate algorithms. With all three, the prevalence of PE was lower in women (OR, 0.66, 0.68 and 0.74). In women, estrogen use, adjusted for age, was associated with lower efficiency and higher prevalence and D-dimer levels. Conclusions The investigated pre-imaging diagnostic algorithms for patients suspected of PE show no sex differences in performance. Male sex and estrogen use are both associated with a higher probability of having the disease. © 2018 International Society on Thrombosis and Haemostasis.

A framework for evaluating mixture analysis algorithms

NASA Astrophysics Data System (ADS)

Dasaratha, Sridhar; Vignesh, T. S.; Shanmukh, Sarat; Yarra, Malathi; Botonjic-Sehic, Edita; Grassi, James; Boudries, Hacene; Freeman, Ivan; Lee, Young K.; Sutherland, Scott

2010-04-01

In recent years, several sensing devices capable of identifying unknown chemical and biological substances have been commercialized. The success of these devices in analyzing real world samples is dependent on the ability of the on-board identification algorithm to de-convolve spectra of substances that are mixtures. To develop effective de-convolution algorithms, it is critical to characterize the relationship between the spectral features of a substance and its probability of detection within a mixture, as these features may be similar to or overlap with other substances in the mixture and in the library. While it has been recognized that these aspects pose challenges to mixture analysis, a systematic effort to quantify spectral characteristics and their impact, is generally lacking. In this paper, we propose metrics that can be used to quantify these spectral features. Some of these metrics, such as a modification of variance inflation factor, are derived from classical statistical measures used in regression diagnostics. We demonstrate that these metrics can be correlated to the accuracy of the substance's identification in a mixture. We also develop a framework for characterizing mixture analysis algorithms, using these metrics. Experimental results are then provided to show the application of this framework to the evaluation of various algorithms, including one that has been developed for a commercial device. The illustration is based on synthetic mixtures that are created from pure component Raman spectra measured on a portable device.

Detecting REM sleep from the finger: an automatic REM sleep algorithm based on peripheral arterial tone (PAT) and actigraphy.

PubMed

Herscovici, Sarah; Pe'er, Avivit; Papyan, Surik; Lavie, Peretz

2007-02-01

Scoring of REM sleep based on polysomnographic recordings is a laborious and time-consuming process. The growing number of ambulatory devices designed for cost-effective home-based diagnostic sleep recordings necessitates the development of a reliable automatic REM sleep detection algorithm that is not based on the traditional electroencephalographic, electrooccolographic and electromyographic recordings trio. This paper presents an automatic REM detection algorithm based on the peripheral arterial tone (PAT) signal and actigraphy which are recorded with an ambulatory wrist-worn device (Watch-PAT100). The PAT signal is a measure of the pulsatile volume changes at the finger tip reflecting sympathetic tone variations. The algorithm was developed using a training set of 30 patients recorded simultaneously with polysomnography and Watch-PAT100. Sleep records were divided into 5 min intervals and two time series were constructed from the PAT amplitudes and PAT-derived inter-pulse periods in each interval. A prediction function based on 16 features extracted from the above time series that determines the likelihood of detecting a REM epoch was developed. The coefficients of the prediction function were determined using a genetic algorithm (GA) optimizing process tuned to maximize a price function depending on the sensitivity, specificity and agreement of the algorithm in comparison with the gold standard of polysomnographic manual scoring. Based on a separate validation set of 30 patients overall sensitivity, specificity and agreement of the automatic algorithm to identify standard 30 s epochs of REM sleep were 78%, 92%, 89%, respectively. Deploying this REM detection algorithm in a wrist worn device could be very useful for unattended ambulatory sleep monitoring. The innovative method of optimization using a genetic algorithm has been proven to yield robust results in the validation set.

Diagnostic criteria for cryopyrin-associated periodic syndrome (CAPS).

PubMed

Kuemmerle-Deschner, Jasmin B; Ozen, Seza; Tyrrell, Pascal N; Kone-Paut, Isabelle; Goldbach-Mansky, Raphaela; Lachmann, Helen; Blank, Norbert; Hoffman, Hal M; Weissbarth-Riedel, Elisabeth; Hugle, Boris; Kallinich, Tilmann; Gattorno, Marco; Gul, Ahmet; Ter Haar, Nienke; Oswald, Marlen; Dedeoglu, Fatma; Cantarini, Luca; Benseler, Susanne M

2017-06-01

Cryopyrin-associated periodic syndrome (CAPS) is a rare, heterogeneous disease entity associated with NLRP3 gene mutations and increased interleukin-1 (IL-1) secretion. Early diagnosis and rapid initiation of IL-1 inhibition prevent organ damage. The aim of the study was to develop and validate diagnostic criteria for CAPS. An innovative process was followed including interdisciplinary team building, item generation: review of CAPS registries, systematic literature review, expert surveys, consensus conferences for item refinement, item reduction and weighting using 1000Minds decision software. Resulting CAPS criteria were tested in large cohorts of CAPS cases and controls using correspondence analysis. Diagnostic models were explored using sensitivity analyses. The international team included 16 experts. Systematic literature and registry review identified 33 CAPS-typical items; the consensus conferences reduced these to 14. 1000Minds exercises ranked variables based on importance for the diagnosis. Correspondence analysis determined variables consistently associated with the diagnosis of CAPS using 284 cases and 837 controls. Seven variables were significantly associated with CAPS (p<0.001). The best diagnosis model included: Raised inflammatory markers (C-reactive protein/serum amyloid A) plus ≥two of six CAPS-typical symptoms: urticaria-like rash, cold-triggered episodes, sensorineural hearing loss, musculoskeletal symptoms, chronic aseptic meningitis and skeletal abnormalities. Sensitivity was 81%, specificity 94%. It performed well for all CAPS subtypes and regardless of NLRP3 mutation. The novel approach integrated traditional methods of evidence synthesis with expert consensus, web-based decision tools and innovative statistical methods and may serve as model for other rare diseases. These criteria will enable a rapid diagnosis for children and adults with CAPS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

NASA Astrophysics Data System (ADS)

Chen, Jiaxi; Li, Junmin

2018-02-01

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T-S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.

Robust point matching via vector field consensus.

PubMed

Jiayi Ma; Ji Zhao; Jinwen Tian; Yuille, Alan L; Zhuowen Tu

2014-04-01

In this paper, we propose an efficient algorithm, called vector field consensus, for establishing robust point correspondences between two sets of points. Our algorithm starts by creating a set of putative correspondences which can contain a very large number of false correspondences, or outliers, in addition to a limited number of true correspondences (inliers). Next, we solve for correspondence by interpolating a vector field between the two point sets, which involves estimating a consensus of inlier points whose matching follows a nonparametric geometrical constraint. We formulate this a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables indicating whether matches in the putative set are outliers or inliers. We impose nonparametric geometrical constraints on the correspondence, as a prior distribution, using Tikhonov regularizers in a reproducing kernel Hilbert space. MAP estimation is performed by the EM algorithm which by also estimating the variance of the prior model (initialized to a large value) is able to obtain good estimates very quickly (e.g., avoiding many of the local minima inherent in this formulation). We illustrate this method on data sets in 2D and 3D and demonstrate that it is robust to a very large number of outliers (even up to 90%). We also show that in the special case where there is an underlying parametric geometrical model (e.g., the epipolar line constraint) that we obtain better results than standard alternatives like RANSAC if a large number of outliers are present. This suggests a two-stage strategy, where we use our nonparametric model to reduce the size of the putative set and then apply a parametric variant of our approach to estimate the geometric parameters. Our algorithm is computationally efficient and we provide code for others to use it. In addition, our approach is general and can be applied to other problems, such as learning with a badly corrupted training data set.

The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis

PubMed Central

Cassani, Raymundo; Falk, Tiago H.; Fraga, Francisco J.; Kanda, Paulo A. M.; Anghinah, Renato

2014-01-01

Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are susceptible to several artifacts, such as ocular, muscular, movement, and environmental. To overcome this limitation, existing diagnostic systems commonly depend on experienced clinicians to manually select artifact-free epochs from the collected multi-channel EEG data. Manual selection, however, is a tedious and time-consuming process, rendering the diagnostic system “semi-automated.” Notwithstanding, a number of EEG artifact removal algorithms have been proposed in the literature. The (dis)advantages of using such algorithms in automated AD diagnostic systems, however, have not been documented; this paper aims to fill this gap. Here, we investigate the effects of three state-of-the-art automated artifact removal (AAR) algorithms (both alone and in combination with each other) on AD diagnostic systems based on four different classes of EEG features, namely, spectral, amplitude modulation rate of change, coherence, and phase. The three AAR algorithms tested are statistical artifact rejection (SAR), blind source separation based on second order blind identification and canonical correlation analysis (BSS-SOBI-CCA), and wavelet enhanced independent component analysis (wICA). Experimental results based on 20-channel resting-awake EEG data collected from 59 participants (20 patients with mild AD, 15 with moderate-to-severe AD, and 24 age-matched healthy controls) showed the wICA algorithm alone outperforming other enhancement algorithm combinations across three tasks: diagnosis (control vs. mild vs. moderate), early detection (control vs. mild), and disease progression (mild vs. moderate), thus opening the doors for fully-automated systems that can assist clinicians with early detection of AD, as well as disease severity progression assessment. PMID:24723886

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate the feasibility and power of the proposed DCA-based profile biomarker diagnosis in achieving high sensitivity and conquering the data reproducibility issue in serum proteomics. Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction. In particular, our profile biomarker diagnosis can be generalized to other omics data for derivative component analysis (DCA)'s nature of generic data analysis.

Maximizing the sensitivity and reliability of peptide identification in large-scale proteomic experiments by harnessing multiple search engines.

PubMed

Yu, Wen; Taylor, J Alex; Davis, Michael T; Bonilla, Leo E; Lee, Kimberly A; Auger, Paul L; Farnsworth, Chris C; Welcher, Andrew A; Patterson, Scott D

2010-03-01

Despite recent advances in qualitative proteomics, the automatic identification of peptides with optimal sensitivity and accuracy remains a difficult goal. To address this deficiency, a novel algorithm, Multiple Search Engines, Normalization and Consensus is described. The method employs six search engines and a re-scoring engine to search MS/MS spectra against protein and decoy sequences. After the peptide hits from each engine are normalized to error rates estimated from the decoy hits, peptide assignments are then deduced using a minimum consensus model. These assignments are produced in a series of progressively relaxed false-discovery rates, thus enabling a comprehensive interpretation of the data set. Additionally, the estimated false-discovery rate was found to have good concordance with the observed false-positive rate calculated from known identities. Benchmarking against standard proteins data sets (ISBv1, sPRG2006) and their published analysis, demonstrated that the Multiple Search Engines, Normalization and Consensus algorithm consistently achieved significantly higher sensitivity in peptide identifications, which led to increased or more robust protein identifications in all data sets compared with prior methods. The sensitivity and the false-positive rate of peptide identification exhibit an inverse-proportional and linear relationship with the number of participating search engines.

Consensus seeking, formation keeping, and trajectory tracking in multiple vehicle cooperative control

NASA Astrophysics Data System (ADS)

Ren, Wei

Cooperative control problems for multiple vehicle systems can be categorized as either formation control problems with applications to mobile robots, unmanned air vehicles, autonomous underwater vehicles, satellites, aircraft, spacecraft, and automated highway systems, or non-formation control problems such as task assignment, cooperative transport, cooperative role assignment, air traffic control, cooperative timing, and cooperative search. The cooperative control of multiple vehicle systems poses significant theoretical and practical challenges. For cooperative control strategies to be successful, numerous issues must be addressed. We consider three important and correlated issues: consensus seeking, formation keeping, and trajectory tracking. For consensus seeking, we investigate algorithms and protocols so that a team of vehicles can reach consensus on the values of the coordination data in the presence of imperfect sensors, communication dropout, sparse communication topologies, and noisy and unreliable communication links. The main contribution of this dissertation in this area is that we show necessary and/or sufficient conditions for consensus seeking with limited, unidirectional, and unreliable information exchange under fixed and switching interaction topologies (through either communication or sensing). For formation keeping, we apply a so-called "virtual structure" approach to spacecraft formation flying and multi-vehicle formation maneuvers. As a result, single vehicle path planning and trajectory generation techniques can be employed for the virtual structure while trajectory tracking strategies can be employed for each vehicle. The main contribution of this dissertation in this area is that we propose a decentralized architecture for multiple spacecraft formation flying in deep space with formation feedback introduced. This architecture ensures the necessary precision in the presence of actuator saturation, internal and external disturbances, and stringent inter-vehicle communication limitations. A constructive approach based on the satisficing control paradigm is also applied to multi-robot coordination in hardware. For trajectory tracking, we investigate nonlinear tracking controllers for fixed wing unmanned air vehicles and nonholonomic mobile robots with velocity and heading rate constraints. The main contribution of this dissertation in this area is that our proposed tracking controllers are shown to be robust to input uncertainties and measurement noise, and are computationally simple and can be implemented with low-cost, low-power microcontrollers. In addition, our approach allows piecewise continuous reference velocity and heading rate and can be extended to derive a variety of other trajectory tracking strategies.

Gender incongruence: a comparative study using ICD-10 and DSM-5 diagnostic criteria.

PubMed

Soll, Bianca M; Robles-García, Rebeca; Brandelli-Costa, Angelo; Mori, Daniel; Mueller, Andressa; Vaitses-Fontanari, Anna M; Cardoso-da-Silva, Dhiordan; Schwarz, Karine; Abel-Schneider, Maiko; Saadeh, Alexandre; Lobato, Maria-Inês-Rodrigues

2018-01-01

To compare the presence of criteria listed in the DSM-5 and ICD-10 diagnostic manuals in a Brazilian sample of transgender persons seeking health services specifically for physical transition. This multicenter cross-sectional study included a sample of 103 subjects who sought services for gender identity disorder in two main reference centers in Brazil. The method involved a structured interview encompassing the diagnostic criteria in the two manuals. The results revealed that despite theoretical disagreement about the criteria, the manuals overlap regarding diagnosis confirmation; the DSM-5 was more inclusive (97.1%) than the ICD-10 (93.2%) in this population. Although there is no consensus on diagnostic criteria on transgenderism in the diversity of social and cultural contexts, more comprehensive diagnostic criteria are evolving due to society's increasing inclusivity.

Female androgen insufficiency: the Princeton consensus statement on definition, classification, and assessment.

PubMed

Bachmann, Gloria; Bancroft, John; Braunstein, Glenn; Burger, Henry; Davis, Susan; Dennerstein, Lorraine; Goldstein, Irwin; Guay, Andre; Leiblum, Sandra; Lobo, Rogerio; Notelovitz, Morris; Rosen, Raymond; Sarrel, Philip; Sherwin, Barbara; Simon, James; Simpson, Evan; Shifren, Jan; Spark, Richard; Traish, Abdul

2002-04-01

To evaluate the evidence for and against androgen insufficiency as a cause of sexual and other health-related problems in women and to make recommendations regarding definition, diagnosis, and assessment of androgen deficiency states in women. Evaluation of peer-review literature and consensus conference of international experts. Multinational conference in the United States. Premenopausal and postmenopausal women with androgen deficiency. Evaluation of peer-review literature and development of consensus panel guidelines. The term "female androgen insufficiency" was defined as consisting of a pattern of clinical symptoms in the presence of decreased bioavailable T and normal estrogen status. Currently available assays were found to be lacking in sensitivity and reliability at the lower ranges, and the need for an equilibrium dialysis measure was strongly emphasized. Causes of androgen insufficiency in women were classified as ovarian, adrenal, hypothalamic-pituitary, drug-related, and idiopathic. A simplified management algorithm and clinical guidelines were proposed to assist clinicians in diagnosis and assessment. Androgen replacement is currently available in several forms, although none has been approved for treatment of sexual dysfunction or other common symptoms of female androgen insufficiency. Potential risks associated with treatment were identified, and the need for informed consent and careful monitoring was noted. Finally, the panel identified key goals and priorities for future research. A new definition of androgen insufficiency in women has been proposed along with consensus-based guidelines for clinical assessment and diagnosis. A simplified management algorithm for women with low androgen in the presence of clinical symptoms and normal estrogen status has also been proposed.

N-terminal pro-B-type natriuretic peptide diagnostic algorithm versus American Heart Association algorithm for Kawasaki disease.

PubMed

Dionne, Audrey; Meloche-Dumas, Léamarie; Desjardins, Laurent; Turgeon, Jean; Saint-Cyr, Claire; Autmizguine, Julie; Spigelblatt, Linda; Fournier, Anne; Dahdah, Nagib

2017-03-01

Diagnosis of Kawasaki disease (KD) can be challenging in the absence of a confirmatory test or pathognomonic finding, especially when clinical criteria are incomplete. We recently proposed serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) as an adjunctive diagnostic test. We retrospectively tested a new algorithm to help KD diagnosis based on NT-proBNP, coronary artery dilation (CAD) at onset, and abnormal serum albumin or C-reactive protein (CRP). The goal was to assess the performance of the algorithm and compare its performance with that of the 2004 American Heart Association (AHA)/American Academy of Pediatrics (AAP) algorithm. The algorithm was tested on 124 KD patients with NT-proBNP measured on admission at the present institutions between 2007 and 2013. Age at diagnosis was 3.4 ± 3.0 years, with a median of five diagnostic criteria; and 55 of the 124 patients (44%) had incomplete KD. CA complications occurred in 64 (52%), with aneurysm in 14 (11%). Using this algorithm, 120/124 (97%) were to be treated, based on high NT-proBNP alone for 79 (64%); on onset CAD for 14 (11%); and on high CRP or low albumin for 27 (22%). Using the AHA/AAP algorithm, 22/47 (47%) of the eligible patients with incomplete KD would not have been referred for treatment, compared with 3/55 (5%) with the NT-proBNP algorithm (P < 0.001). This NT-proBNP-based algorithm is efficient to identify and treat patients with KD, including those with incomplete KD. This study paves the way for a prospective validation trial of the algorithm. © 2016 Japan Pediatric Society.

Ensemble des troubles causés par l'alcoolisation fœtale : lignes directrices canadiennes concernant le diagnostic

PubMed Central

Chudley, Albert E.; Conry, Julianne; Cook, Jocelynn L.; Loock, Christine; Rosales, Ted; LeBlanc, Nicole

2005-01-01

Résumé LE DIAGNOSTIC DE L'ENSEMBLE DES TROUBLES CAUSÉS PAR L'ALCOOLISATION FÉTALE (ETCAF) est complexe et l'élaboration de lignes directrices concernant le diagnostic est justifiée. Un sous-comité du Comité consultatif national de l'Agence de santé publique du Canada sur l'Ensemble des troubles causés par l'alcoolisation fœtale a examiné, analysé et intégré les méthodes de diagnostic actuelles afin de parvenir à une méthode de diagnostic normalisée faisant le consensus au Canada. L'objet du présent document est d'examiner et de clarifier l'utilisation des systèmes de diagnostic actuels et de formuler des recommandations quant à leur application pour le diagnostic des déficiences liées à l'ETCAF chez des individus de tous les âges. Les lignes directrices sont fondées sur un vaste consensus de praticiens et d'autres intervenants spécialisés dans le domaine. Ces lignes directrices ont été organisées en sept catégories, soit le dépistage et l'orientation vers les spécialistes, l'examen physique et le diagnostic différentiel, l'évaluation du comportement neurologique, le traitement et le suivi, les antécédents de consommation d'alcool de la mère pendant la grossesse, les critères du diagnostic pour le syndrome d'alcoolisation fœtale (SAF), SAF partiel et troubles neurologiques du développement liés à l'alcool, l'harmonisation de l'Institute of Medicine (IOM) et des approches du Code diagnostique à 4 chiffres. Le diagnostic exige une évaluation complète des antécédents, ainsi qu'un examen physique et du comportement neurologique, tout en recourant à une approche multidisciplinaire. Les présentes lignes directrices pour le diagnostic du syndrome d'alcoolisation fœtale et des déficiences qui y sont associées sont les premières à avoir été élaborées au Canada et elles sont fondées sur la consultation d'un grand éventail de spécialistes du diagnostic.

Molecular Diagnostic Analysis of Outbreak Scenarios

ERIC Educational Resources Information Center

Morsink, M. C.; Dekter, H. E.; Dirks-Mulder, A.; van Leeuwen, W. B.

2012-01-01

In the current laboratory assignment, technical aspects of the polymerase chain reaction (PCR) are integrated in the context of six different bacterial outbreak scenarios. The "Enterobacterial Repetitive Intergenic Consensus Sequence" (ERIC) PCR was used to analyze different outbreak scenarios. First, groups of 2-4 students determined optimal…

Consensus Document of the Spanish Society of Cardiology and the Spanish Society of Internal Medicine on the diagnosis and treatment of iron deficiency in heart failure.

PubMed

Manito, N; Cerqueiro, J M; Comín-Colet, J; García-Pinilla, J M; González-Franco, A; Grau-Amorós, J; Peraira, J R; Manzano, L

Iron deficiency in patients with heart failure is a medical problem of recent particular interest. This interest has resulted from the publication of several clinical trials that demonstrated that the administration of intravenous iron to such patients improved their functional capacity and even reduced the number of hospitalisations for heart failure decompensation. However, applying the evidence from these studies in clinical practice is still controversial, both in terms of the diagnostic criteria for iron deficiency (absolute and functional) and the optimal method for iron replenishment. This article is a consensus document that integrates the recommendations of the Spanish Society of Internal Medicine and the Spanish Society of Cardiology. The article reviews the scientific evidence and proposes a diagnostic and therapeutic performance protocol for iron deficiency in heart failure. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Comprehensive risk reduction in patients with atrial fibrillation: emerging diagnostic and therapeutic options—a report from the 3rd Atrial Fibrillation Competence NETwork/European Heart Rhythm Association consensus conference

PubMed Central

Kirchhof, Paulus; Lip, Gregory Y.H.; Van Gelder, Isabelle C.; Bax, Jeroen; Hylek, Elaine; Kaab, Stefan; Schotten, Ulrich; Wegscheider, Karl; Boriani, Giuseppe; Brandes, Axel; Ezekowitz, Michael; Diener, Hans; Haegeli, Laurent; Heidbuchel, Hein; Lane, Deirdre; Mont, Luis; Willems, Stephan; Dorian, Paul; Aunes-Jansson, Maria; Blomstrom-Lundqvist, Carina; Borentain, Maria; Breitenstein, Stefanie; Brueckmann, Martina; Cater, Nilo; Clemens, Andreas; Dobrev, Dobromir; Dubner, Sergio; Edvardsson, Nils G.; Friberg, Leif; Goette, Andreas; Gulizia, Michele; Hatala, Robert; Horwood, Jenny; Szumowski, Lukas; Kappenberger, Lukas; Kautzner, Josef; Leute, Angelika; Lobban, Trudie; Meyer, Ralf; Millerhagen, Jay; Morgan, John; Muenzel, Felix; Nabauer, Michael; Baertels, Christoph; Oeff, Michael; Paar, Dieter; Polifka, Juergen; Ravens, Ursula; Rosin, Ludger; Stegink, W.; Steinbeck, Gerhard; Vardas, Panos; Vincent, Alphons; Walter, Maureen; Breithardt, Günter; Camm, A. John

2012-01-01

While management of atrial fibrillation (AF) patients is improved by guideline-conform application of anticoagulant therapy, rate control, rhythm control, and therapy of accompanying heart disease, the morbidity and mortality associated with AF remain unacceptably high. This paper describes the proceedings of the 3rd Atrial Fibrillation NETwork (AFNET)/European Heart Rhythm Association (EHRA) consensus conference that convened over 60 scientists and representatives from industry to jointly discuss emerging therapeutic and diagnostic improvements to achieve better management of AF patients. The paper covers four chapters: (i) risk factors and risk markers for AF; (ii) pathophysiological classification of AF; (iii) relevance of monitored AF duration for AF-related outcomes; and (iv) perspectives and needs for implementing better antithrombotic therapy. Relevant published literature for each section is covered, and suggestions for the improvement of management in each area are put forward. Combined, the propositions formulate a perspective to implement comprehensive management in AF. PMID:21791573

[Joint endoprosthesis pathology. Histopathological diagnostics and classification].

PubMed

Krenn, V; Morawietz, L; Jakobs, M; Kienapfel, H; Ascherl, R; Bause, L; Kuhn, H; Matziolis, G; Skutek, M; Gehrke, T

2011-05-01

Prosthesis durability has steadily increased with high 10-year rates of 88-95%. However, four pathogenetic groups of diseases can decrease prosthesis durability: (1) periprosthetic wear particle disease (aseptic loosening) (2) bacterial infection (septic loosening) (3) periprosthetic ossification, and (4) arthrofibrosis. The histopathological "extended consensus classification of periprosthetic membranes" includes four types of membranes, arthrofibrosis, and osseous diseases of endoprosthetics: The four types of neosynovia are: wear particle-induced type (type I), mean prosthesis durability (MPD) in years 12.0; infectious type (type II), MPD 2.5; combined type (type III) MPD 4.2; and indeterminate type (type IV), MPD 5.5. Arthrofibrosis can be determined in three grades: grade 1 needs clinical information to be differentiated from a type IV membrane, and grades 2 & 3 can be diagnosed histopathologically. Periprosthetic ossification, osteopenia-induced fractures, and aseptic osteonecrosis can be histopathologically diagnosed safely with clinical information. The extended consensus classification of periprosthetic membranes may be a diagnostic groundwork for a future national endoprosthesis register.