kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

PubMed Central

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

2013-01-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

Meta-analysis of the predictive factors of postpartum fatigue.

PubMed

Badr, Hanan A; Zauszniewski, Jaclene A

2017-08-01

Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes. We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes. Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (r range =0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (r range =0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (r range =0.50+) for depression. Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue. Copyright © 2017 Elsevier

Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

PubMed

Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

2018-01-01

The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

Use of clinical risk factors to identify postmenopausal women with vertebral fractures.

PubMed

Tobias, J H; Hutchinson, A P; Hunt, L P; McCloskey, E V; Stone, M D; Martin, J C; Thompson, P W; Palferman, T G; Bhalla, A K

2007-01-01

Previous studies have been unable to identify risk factors for prevalent vertebral fractures (VF), which are suitable for use in selection strategies intended to target high-risk sub-groups for diagnostic assessment. However, these studies generally consisted of large epidemiology surveys based on questionnaires and were only able to evaluate a limited number of risk factors. Here, we investigated whether a stronger relationship exists with prevalent VF when conventional risk factors are combined with additional information obtained from detailed one-to-one assessment. Women aged 65-75 registered at four geographically distinct GP practices were invited to participate (n=1,518), of whom 540 attended for assessment as follows: a questionnaire asking about risk factors for osteoporosis such as height loss compared to age 25 and history of non-vertebral fracture (NVF), the get-up-and-go test, Margolis back pain score, measurement of wall-tragus and rib-pelvis distances, and BMD as measured by the distal forearm BMD. A lateral thoraco-lumbar spine X-ray was obtained, which was subsequently scored for the presence of significant vertebral deformities. Of the 509 subjects who underwent spinal radiographs, 37 (7.3%) were found to have one or more VF. Following logistic regression analysis, the four most predictive clinical risk factors for prevalent VF were: height loss (P=0.006), past NVF (P=0.004), history of back pain (P=0.075) and age (P=0.05). BMD was also significantly associated with prevalent VF (P=0.002), but its inclusion did not affect associations with other variables. Factors elicited from detailed one-to-one assessment were not related to the risk of one or more prevalent VFs. The area under ROC curves derived from these regressions, which suggested that models for prevalent VF had modest predictive accuracy, were as follows: 0.68 (BMD), 0.74 (four clinical risk factors above) and 0.78 (clinical risk factors + BMD). Analyses were repeated in relation to the

Development and Preliminary Performance of a Risk Factor Screen to Predict Posttraumatic Psychological Disorder After Trauma Exposure

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Spain, David A.

2017-01-01

Objective We examined data from a prospective study of risk factors that increase vulnerability or resilience, exacerbate distress, or foster recovery to determine whether risk factors accurately predict which individuals will later have high posttraumatic (PT) symptom levels and whether brief measures of risk factors also accurately predict later symptom elevations. Method Using data from 129 adults exposed to traumatic injury of self or a loved one, we conducted receiver operating characteristic (ROC) analyses of 14 risk factors assessed by full-length measures, determined optimal cutoff scores and calculated predictive performance for the nine that were most predictive. For five risk factors, we identified sets of items that accounted for 90% of variance in total scores and calculated predictive performance for sets of brief risk measures. Results A set of nine risk factors assessed by full measures identified 89% of those who later had elevated PT symptoms (sensitivity) and 78% of those who did not (specificity). A set of four brief risk factor measures assessed soon after injury identified 86% of those who later had elevated PT symptoms and 72% of those who did not. Conclusions Use of sets of brief risk factor measures shows promise of accurate prediction of PT psychological disorder and probable PTSD or depression. Replication of predictive accuracy is needed in a new and larger sample. PMID:28622811

Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens

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

Park, Min-Sun; Park, Sung Yong; Miller, Keith R.

2013-11-01

Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformationalmore » changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.« less

Predictive factors of dropout from inpatient treatment for anorexia nervosa.

PubMed

Roux, H; Ali, A; Lambert, S; Radon, L; Huas, C; Curt, F; Berthoz, S; Godart, Nathalie

2016-09-30

Patients with severe Anorexia Nervosa (AN) whose condition is life-threatening or who are not receiving adequate ambulatory care are hospitalized. However, 40 % of these patients leave the hospital prematurely, without reaching the target weight set in the treatment plan, and this can compromise outcome. This study set out to explore factors predictive of dropout from hospital treatment among patients with AN, in the hope of identifying relevant therapeutic targets. From 2009 to 2011, 180 women hospitalized for AN (DSM-IV diagnosis) in 10 centres across France were divided into two groups: those under 18 years (when the decision to discharge belongs to the parents) and those aged 18 years and over (when the patient can legally decide to leave the hospital). Both groups underwent clinical assessment using the Morgan & Russell Global Outcome State questionnaire and the Eating Disorders Examination Questionnaire (EDE-Q) for assessment of eating disorder symptoms and outcome. Psychological aspects were assessed via the evaluation of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS). Socio-demographic data were also collected. A number of factors identified in previous research as predictive of dropout from hospital treatment were tested using stepwise descending Cox regressions. We found that factors predictive of dropout varied according to age groups (being under 18 as opposed to 18 and over). For participants under 18, predictive factors were living in a single-parent family, severe intake restriction as measured on the "dietary restriction" subscale of the Morgan & Russell scale, and a low patient-reported score on the EDE-Q "restraint concerns" subscale. For those over 18, dropout was predicted from a low depression score on the HADS, low level of concern about weight on the EDE-Q subscale, and lower educational status. To prevent dropout from hospitalization for AN, the appropriate therapeutic measures vary according to whether

Predictive Factors for Death After Snake Envenomation in Myanmar.

PubMed

Aye, Kyi-Phyu; Thanachartwet, Vipa; Soe, Chit; Desakorn, Varunee; Chamnanchanunt, Supat; Sahassananda, Duangjai; Supaporn, Thanom; Sitprija, Visith

2018-06-01

Factors predictive for death from snake envenomation vary between studies, possibly due to variation in host genetic factors and venom composition. This study aimed to evaluate predictive factors for death from snake envenomation in Myanmar. A prospective study was performed among adult patients with snakebite admitted to tertiary hospitals in Yangon, Myanmar, from May 2015 to August 2016. Data including clinical variables and laboratory parameters, management, and outcomes were evaluated. Multivariate regression analysis was performed to evaluate factors predictive for death at the time of presentation to the hospital. Of the 246 patients with snake envenomation recruited into the study, 225 (92%) survived and 21 (8%) died during hospitalization. The snake species responsible for a bite was identified in 74 (30%) of the patients; the majority of bites were from Russell's vipers (63 patients, 85%). The independent factors predictive for death included 1) duration from bite to arrival at the hospital >1 h (odds ratio [OR]: 9.0, 95% confidence interval [CI]: 1.1-75.2; P=0.04); 2) white blood cell counts >20 ×10 3 cells·μL -1 (OR: 8.9, 95% CI: 2.3-33.7; P=0.001); and 3) the presence of capillary leakage (OR: 3.7, 95% CI: 1.2-11.2; P=0.02). A delay in antivenom administration >4 h increases risk of death (11/21 deaths). Patients who present with these independent predictive factors should be recognized and provided with early appropriate intervention to reduce the mortality rate among adults with snake envenomation in Myanmar. Copyright © 2018 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

Evaluating predictive models for solar energy growth in the US states and identifying the key drivers

NASA Astrophysics Data System (ADS)

Chakraborty, Joheen; Banerji, Sugata

2018-03-01

Driven by a desire to control climate change and reduce the dependence on fossil fuels, governments around the world are increasing the adoption of renewable energy sources. However, among the US states, we observe a wide disparity in renewable penetration. In this study, we have identified and cleaned over a dozen datasets representing solar energy penetration in each US state, and the potentially relevant socioeconomic and other factors that may be driving the growth in solar. We have applied a number of predictive modeling approaches - including machine learning and regression - on these datasets over a 17-year period and evaluated the relative performance of the models. Our goals were: (1) identify the most important factors that are driving the growth in solar, (2) choose the most effective predictive modeling technique for solar growth, and (3) develop a model for predicting next year’s solar growth using this year’s data. We obtained very promising results with random forests (about 90% efficacy) and varying degrees of success with support vector machines and regression techniques (linear, polynomial, ridge). We also identified states with solar growth slower than expected and representing a potential for stronger growth in future.

Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury

PubMed Central

2016-01-01

Return to work (RTW) for people with acquired brain injury (ABI) represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology) in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state) at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery) between admission and discharge was assessed by Functional Independent Measure (FIM) gain, through the Montebello Rehabilitation Factor Score (MRFS), which was obtained as follows: (discharge FIM—admission FIM)/(Maximum possible FIM—Admission FIM) x 100. The cut-off value (criterion) deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%). Considering the Mini Mental State Examination (MMSE) and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself. PMID:27780215

Return to Work: A Cut-Off of FIM Gain with Montebello Rehabilitation Factor Score in Order to Identify Predictive Factors in Subjects with Acquired Brain Injury.

PubMed

Franceschini, Marco; Massimiani, Maria Pia; Paravati, Stefano; Agosti, Maurizio

2016-01-01

Return to work (RTW) for people with acquired brain injury (ABI) represents a main objective of rehabilitation: this work presents a strong correlation between personal well-being and quality of life. The aim of this study is to investigate the prognostic factors that can predict RTW after ABI (traumatic or non- traumatic aetiology) in patients without disorders of consciousness (e.g. coma, vegetative or minimally conscious state) at the beginning of their admission to rehabilitation. At the end of a 6-month follow-up after discharge, data were successfully collected in 69 patients. The rehabilitation effectiveness (functional Recovery) between admission and discharge was assessed by Functional Independent Measure (FIM) gain, through the Montebello Rehabilitation Factor Score (MRFS), which was obtained as follows: (discharge FIM-admission FIM)/(Maximum possible FIM-Admission FIM) x 100. The cut-off value (criterion) deriving from MRFS, which helped identify RTW patients, resulted in .659 (sn 88.9%; sp 52.4%). Considering the Mini Mental State Examination (MMSE) and the MRFS data, the multivariable binary logistic regression analysis presented 62.96% of correct RTW classification cases, 80.95% of non-RTW leading to an overall satisfactory predictability of 73.91%. The results of the present study suggest that occupational therapy intervention could modify cut-off in patients with an MFRS close to target at the end of an in-hospital rehabilitative program thus developing their capabilities and consequently surpassing cut-off itself.

Predictive factors for poor prognosis febrile neutropenia.

PubMed

Ahn, Shin; Lee, Yoon-Seon

2012-07-01

Most patients with chemotherapy-induced febrile neutropenia recover rapidly without serious complications. However, it still remains a life-threatening treatment-related toxicity, and is associated with dose reductions and delays of chemotherapeutic agents that may compromise treatment outcomes. Recent developments of risk stratification enabled early discharge with oral antibiotics for low-risk patients. However, even in low-risk patients, medical complications including bacteremia could happen. The authors reviewed recent literature to provide an update on research regarding predictive factors for poor prognosis in patients with febrile neutropenia. Various prognostic factors have been suggested with controversies. Hematological parameters, prophylactic measurements and patient-specific risk factors showed inconsistent results. MASCC risk-index score, which was originally developed to identify low-risk patients, in turn showed that the lower the MASCC score, the poorer the prognosis of febrile neutropenia, with very low levels (<15), the rate of complications was high. Patients with severe sepsis and septic shock commonly had procalcitonin concentration above 2.0 ng/ml, and this level should be considered at high risk of poor prognosis. Lower MASCC score and higher procalcitonin concentration can predict poor outcomes in febrile neutropenia. More research is required with regard to the other factors showing controversies.

Using decision tree analysis to identify risk factors for relapse to smoking

PubMed Central

Piper, Megan E.; Loh, Wei-Yin; Smith, Stevens S.; Japuntich, Sandra J.; Baker, Timothy B.

2010-01-01

This research used classification tree analysis and logistic regression models to identify risk factors related to short- and long-term abstinence. Baseline and cessation outcome data from two smoking cessation trials, conducted from 2001 to 2002, in two Midwestern urban areas, were analyzed. There were 928 participants (53.1% women, 81.8% white) with complete data. Both analyses suggest that relapse risk is produced by interactions of risk factors and that early and late cessation outcomes reflect different vulnerability factors. The results illustrate the dynamic nature of relapse risk and suggest the importance of efficient modeling of interactions in relapse prediction. PMID:20397871

Regulatory element-based prediction identifies new susceptibility regulatory variants for osteoporosis.

PubMed

Yao, Shi; Guo, Yan; Dong, Shan-Shan; Hao, Ruo-Han; Chen, Xiao-Feng; Chen, Yi-Xiao; Chen, Jia-Bin; Tian, Qing; Deng, Hong-Wen; Yang, Tie-Lin

2017-08-01

Despite genome-wide association studies (GWASs) have identified many susceptibility genes for osteoporosis, it still leaves a large part of missing heritability to be discovered. Integrating regulatory information and GWASs could offer new insights into the biological link between the susceptibility SNPs and osteoporosis. We generated five machine learning classifiers with osteoporosis-associated variants and regulatory features data. We gained the optimal classifier and predicted genome-wide SNPs to discover susceptibility regulatory variants. We further utilized Genetic Factors for Osteoporosis Consortium (GEFOS) and three in-house GWASs samples to validate the associations for predicted positive SNPs. The random forest classifier performed best among all machine learning methods with the F1 score of 0.8871. Using the optimized model, we predicted 37,584 candidate SNPs for osteoporosis. According to the meta-analysis results, a list of regulatory variants was significantly associated with osteoporosis after multiple testing corrections and contributed to the expression of known osteoporosis-associated protein-coding genes. In summary, combining GWASs and regulatory elements through machine learning could provide additional information for understanding the mechanism of osteoporosis. The regulatory variants we predicted will provide novel targets for etiology research and treatment of osteoporosis.

Predictive factors for pharyngocutaneous fistulization after total laryngectomy: a Dutch Head and Neck Society audit.

PubMed

Lansaat, Liset; van der Noort, Vincent; Bernard, Simone E; Eerenstein, Simone E J; Plaat, Boudewijn E C; Langeveld, Ton A P M; Lacko, Martin; Hilgers, Frans J M; de Bree, Remco; Takes, Robert P; van den Brekel, Michiel W M

2018-03-01

Incidences of pharyngocutaneous fistulization (PCF) after total laryngectomy (TL) reported in the literature vary widely, ranging from 2.6 to 65.5%. Comparison between different centers might identify risk factors, but also might enable improvements in quality of care. To enable this on a national level, an audit in the 8 principle Dutch Head and Neck Centers (DHNC) was initiated. A retrospective chart review of all 324 patients undergoing laryngectomy in a 2-year (2012 and 2013) period was performed. Overall PCF%, PCF% per center and factors predictive for PCF were identified. Furthermore, a prognostic model predicting the PCF% per center was developed. To provide additional data, a survey among the head and neck surgeons of the participating centers was carried out. Overall PCF% was 25.9. The multivariable prediction model revealed that previous treatment with (chemo)radiotherapy in combination with a long interval between primary treatment and TL, previous tracheotomy, near total pharyngectomy, neck dissection, and BMI < 18 were the best predictors for PCF. Early oral intake did not influence PCF rate. PCF% varied quite widely between centers, but for a large extend this could be explained with the prediction model. PCF performance rate (difference between the PCF% and the predicted PCF%) per DHNC, though, shows that not all differences are explained by factors established in the prediction model. However, these factors explain enough of the differences that, compensating for these factors, hospital is no longer independently predictive for PCF. This nationwide audit has provided valid comparative PCF data confirming the known risk factors from the literature which are important for counseling on PCF risks. Data show that variations in PCF% in the DHNCs (in part) are explainable by the variations in these predictive factors. Since elective neck dissection is a major risk factor for PCF, it only should be performed on well funded indication.

[Predictive factors of mortality in extremely preterm infants].

PubMed

Lin, L; Fang, M C; Jiang, H; Zhu, M L; Chen, S Q; Lin, Z L

2018-04-02

Objective: To investigate the predictive factors of mortality in extremely preterm infants. Methods: The retrospective case-control study was accomplished in the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University. A total of 268 extremely preterm infants seen from January 1, 1999 to December 31, 2015 were divided into survival group (192 cases) and death group (76 cases). The potential predictive factors of mortality were identified by univariate analysis, and then analyzed by multivariate unconditional Logistic regression analysis. The mortality and predictive factors were also compared between two time periods, which were January 1, 1999 to December 31, 2007 (65 cases) and January 1, 2008 to December 31, 2015 (203 cases). Results: The median gestational age (GA) of extremely preterm infants was 27 weeks (23 +3 -27 +6 weeks). The mortality was higher in infants with GA of 25-<26 weeks ( OR= 2.659, 95% CI: 1.211-5.840) and<25 weeks ( OR= 10.029, 95% CI: 3.266-30.792) compared to that in infants with GA> 26 weeks. From January 1, 2008 to December 31, 2015, the number of extremely preterm infants was increased significantly compared to the previous 9 years, while the mortality decreased significantly ( OR= 0.490, 95% CI: 0.272-0.884). Multivariate unconditional Logistic regression analysis showed that GA below 25 weeks ( OR= 6.033, 95% CI: 1.393-26.133), lower birth weight ( OR= 0.997, 95% CI: 0.995-1.000), stage Ⅲ necrotizing enterocolitis (NEC) ( OR= 15.907, 95% CI: 3.613-70.033), grade Ⅰ and Ⅱ intraventricular hemorrhage (IVH) ( OR= 0.260, 95% CI: 0.117-0.575) and dependence on invasive mechanical ventilation ( OR= 3.630, 95% CI: 1.111-11.867) were predictive factors of mortality in extremely preterm infants. Conclusions: GA below 25 weeks, lower birth weight, stage Ⅲ NEC and dependence on invasive mechanical ventilation are risk factors of mortality in extremely preterm infants. But grade ⅠandⅡ IVH is protective

Identifying environmental factors harmful to reproduction.

PubMed Central

Palmer, A K

1993-01-01

Reproduction is essential for the continuation of the species and for life itself. In biological terms, living and reproducing are essentially one and the same. There is, therefore, no sharp division between identifying factors harmful to reproduction and identifying factors harmful to life or vice versa. Detection of harmful factors requires balanced use of a variety of methodologies from databases on structure-activity relationships through in vitro and in vivo test systems of varying complexity to surveys of wildlife and human populations. Human surveys provide the only assured means of discriminating between real and imagined harmful factors, but they are time consuming and provide information after the harm has been done. Test systems with whole animals provide the best prospects for identifying harmful factors quickly, but currently available methods used for testing agrochemicals and drugs need a thorough overhaul before they can provide a role model. Whether there is a need for new methodology is doubtful. More certain is the need to use existing methodology more wisely. We need a better understanding of the environment--whatever it is--and a more thoughtful approach to investigation of multifactorial situations. PMID:8243390

[Predictive factors of anxiety disorders].

PubMed

Domschke, K

2014-10-01

Anxiety disorders are among the most frequent mental disorders in Europe (12-month prevalence 14%) and impose a high socioeconomic burden. The pathogenesis of anxiety disorders is complex with an interaction of biological, environmental and psychosocial factors contributing to the overall disease risk (diathesis-stress model). In this article, risk factors for anxiety disorders will be presented on several levels, e.g. genetic factors, environmental factors, gene-environment interactions, epigenetic mechanisms, neuronal networks ("brain fear circuit"), psychophysiological factors (e.g. startle response and CO2 sensitivity) and dimensional/subclinical phenotypes of anxiety (e.g. anxiety sensitivity and behavioral inhibition), and critically discussed regarding their potential predictive value. The identification of factors predictive of anxiety disorders will possibly allow for effective preventive measures or early treatment interventions, respectively, and reduce the individual patient's suffering as well as the overall socioeconomic burden of anxiety disorders.

Predictive factors for the Nursing Diagnoses in people living with Acquired Immune Deficiency Syndrome 1

PubMed Central

da Silva, Richardson Augusto Rosendo; Costa, Romanniny Hévillyn Silva; Nelson, Ana Raquel Cortês; Duarte, Fernando Hiago da Silva; Prado, Nanete Caroline da Costa; Rodrigues, Eduardo Henrique Fagundes

2016-01-01

Abstract Objective: to identify the predictive factors for the nursing diagnoses in people living with Acquired Immune Deficiency Syndrome. Method: a cross-sectional study, undertaken with 113 people living with AIDS. The data were collected using an interview script and physical examination. Logistic regression was used for the data analysis, considering a level of significance of 10%. Results: the predictive factors identified were: for the nursing diagnosis of knowledge deficit-inadequate following of instructions and verbalization of the problem; for the nursing diagnosis of failure to adhere - years of study, behavior indicative of failure to adhere, participation in the treatment and forgetfulness; for the nursing diagnosis of sexual dysfunction - family income, reduced frequency of sexual practice, perceived deficit in sexual desire, perceived limitations imposed by the disease and altered body function. Conclusion: the predictive factors for these nursing diagnoses involved sociodemographic and clinical characteristics, defining characteristics, and related factors, which must be taken into consideration during the assistance provided by the nurse. PMID:27384466

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

Identifying pollution sources and predicting urban air quality using ensemble learning methods

NASA Astrophysics Data System (ADS)

Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

2013-12-01

In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

Factors predicting weight-bearing asymmetry 1month after unilateral total knee arthroplasty: a cross-sectional study.

PubMed

Christiansen, Cory L; Bade, Michael J; Weitzenkamp, David A; Stevens-Lapsley, Jennifer E

2013-03-01

Factors predicting weight-bearing asymmetry (WBA) after unilateral total knee arthroplasty (TKA) are not known. However, identifying modifiable and non-modifiable predictors of WBA is needed to optimize rehabilitation, especially since WBA is negatively correlated to poor functional performance. The purpose of this study was to identify factors predictive of WBA during sit-stand transitions for people 1month following unilateral TKA. Fifty-nine people were tested preoperatively and 1month following unilateral TKA for WBA using average vertical ground reaction force under each foot during the Five Times Sit-to-Stand Test. Candidate variables tested in the regression analysis represented physical impairments (strength, muscle activation, pain, and motion), demographics, anthropometrics, and movement compensations. WBA, measured as the ratio of surgical/non-surgical limb vertical ground reaction force, was 0.69 (0.18) (mean (SD)) 1month after TKA. Regression analysis identified preoperative WBA (β=0.40), quadriceps strength ratio (β=0.31), and hamstrings strength ratio (β=0.19) as factors predictive of WBA 1month after TKA (R(2)=0.30). Greater amounts of WBA 1month after TKA are predicted by modifiable factors including habitual movement pattern and asymmetry in quadriceps and hamstrings strength. Copyright © 2012 Elsevier B.V. All rights reserved.

Predicting risk for childhood asthma by pre-pregnancy, perinatal, and postnatal factors.

PubMed

Wen, Hui-Ju; Chiang, Tung-Liang; Lin, Shio-Jean; Guo, Yue Leon

2015-05-01

Symptoms of atopic disease start early in human life. Predicting risk for childhood asthma by early-life exposure would contribute to disease prevention. A birth cohort study was conducted to investigate early-life risk factors for childhood asthma and to develop a predictive model for the development of asthma. National representative samples of newborn babies were obtained by multistage stratified systematic sampling from the 2005 Taiwan Birth Registry. Information on potential risk factors and children's health was collected by home interview when babies were 6 months old and 5 yr old, respectively. Backward stepwise regression analysis was used to identify the risk factors of childhood asthma for predictive models that were used to calculate the probability of childhood asthma. A total of 19,192 children completed the study satisfactorily. Physician-diagnosed asthma was reported in 6.6% of 5-yr-old children. Pre-pregnancy factors (parental atopy and socioeconomic status), perinatal factors (place of residence, exposure to indoor mold and painting/renovations during pregnancy), and postnatal factors (maternal postpartum depression and the presence of atopic dermatitis before 6 months of age) were chosen for the predictive models, and the highest predicted probability of asthma in 5-yr-old children was 68.1% in boys and 78.1% in girls; the lowest probability in boys and girls was 4.1% and 3.2%, respectively. This investigation provides a technique for predicting risk of childhood asthma that can be used to developing a preventive strategy against asthma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Treatment-Related Predictive and Prognostic Factors in Trimodality Approach in Stage IIIA/N2 Non-Small Cell Lung Cancer.

PubMed

Jeremić, Branislav; Casas, Francesc; Dubinsky, Pavol; Gomez-Caamano, Antonio; Čihorić, Nikola; Videtic, Gregory; Igrutinovic, Ivan

2018-01-01

While there are no established pretreatment predictive and prognostic factors in patients with stage IIIA/pN2 non-small cell lung cancer (NSCLC) indicating a benefit to surgery as a part of trimodality approach, little is known about treatment-related predictive and prognostic factors in this setting. A literature search was conducted to identify possible treatment-related predictive and prognostic factors for patients for whom trimodality approach was reported on. Overall survival was the primary endpoint of this study. Of 30 identified studies, there were two phase II studies, 5 "prospective" studies, and 23 retrospective studies. No study was found which specifically looked at treatment-related predictive factors of improved outcomes in trimodality treatment. Of potential treatment-related prognostic factors, the least frequently analyzed factors among 30 available studies were overall pathologic stage after preoperative treatment and UICC downstaging. Evaluation of treatment response before surgery and by pathologic tumor stage after induction therapy were analyzed in slightly more than 40% of studies and found not to influence survival. More frequently studied factors-resection status, degree of tumor regression, and pathologic nodal stage after induction therapy as well as the most frequently studied factor, the treatment (in almost 75% studies)-showed no discernible impact on survival, due to conflicting results. Currently, it is impossible to identify any treatment-related predictive or prognostic factors for selecting surgery in the treatment of patients with stage IIIA/pN2 NSCLC.

Shoulder dystocia: risk factors, predictability, and preventability.

PubMed

Mehta, Shobha H; Sokol, Robert J

2014-06-01

Shoulder dystocia remains an unpredictable obstetric emergency, striking fear in the hearts of obstetricians both novice and experienced. While outcomes that lead to permanent injury are rare, almost all obstetricians with enough years of practice have participated in a birth with a severe shoulder dystocia and are at least aware of cases that have resulted in significant neurologic injury or even neonatal death. This is despite many years of research trying to understand the risk factors associated with it, all in an attempt primarily to characterize when the risk is high enough to avoid vaginal delivery altogether and prevent a shoulder dystocia, whose attendant morbidities are estimated to be at a rate as high as 16-48%. The study of shoulder dystocia remains challenging due to its generally retrospective nature, as well as dependence on proper identification and documentation. As a result, the prediction of shoulder dystocia remains elusive, and the cost of trying to prevent one by performing a cesarean delivery remains high. While ultimately it is the injury that is the key concern, rather than the shoulder dystocia itself, it is in the presence of an identified shoulder dystocia that occurrence of injury is most common. The majority of shoulder dystocia cases occur without major risk factors. Moreover, even the best antenatal predictors have a low positive predictive value. Shoulder dystocia therefore cannot be reliably predicted, and the only preventative measure is cesarean delivery. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictive factor and antihypertensive usage of tyrosine kinase inhibitor-induced hypertension in kidney cancer patients

PubMed Central

IZUMI, KOUJI; ITAI, SHINGO; TAKAHASHI, YOSHIKO; MAOLAKE, AERKEN; NAMIKI, MIKIO

2014-01-01

Hypertension (HT) is the common adverse event associated with vascular endothelial growth factor receptor-tyrosine kinase inhibitors (VEGFR-TKI). The present study was performed to identify the predictive factors of TKI-induced HT and to determine the classes of antihypertensive agents (AHTA) that demonstrate optimal efficacy against this type of HT. The charts of 50 cases of patients that had received VEGFR-TKI treatment were retrospectively examined. The association between patient background and TKI-induced HT, and the effect of administering AHTA were analyzed. High systolic blood pressure at baseline was identified to be a predictive factor for HT. In addition, there was no difference observed between calcium channel blockers (CCBs) and angiotensin receptor II blockers (ARBs) as first-line AHTA for the control of HT. The findings of the present study may aid with predicting the onset of TKI-induced HT, as well as for its management via the primary use of either CCBs or ARBs. PMID:24959266

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Factors predicting the success of trabeculectomy bleb enhancement with needling.

PubMed

Than, Jonathan Y-X L; Al-Mugheiry, Toby S; Gale, Jesse; Martin, Keith R

2018-02-09

Bleb needling is widely used to restore flow and lower intraocular pressure (IOP) in a failing trabeculectomy. We aimed to measure the safety and efficacy of needling in a large cohort and identify factors that were associated with success and failure. This retrospective audit included all patients who underwent needling at Addenbrooke's Hospital, Cambridge over a 10-year period. Data were available on 91 patients (98% of patients identified), including 191 needlings on 96 eyes. Success was defined as IOP below 21 mm Hg or 16 mm Hg or 13 mm Hg consistently, without reoperation or glaucoma medication. Risk factors for failure were assessed by Cox proportional hazard regression and Kaplan-Meier curves. Success defined as IOP <16 mm Hg was 66.6% at 12 months and 53% at 3 years and success defined as IOP <21 mm Hg was 77.1% at 12 months and 73.1% at 3 years. Failure after needling was most common in the first 6 months. Factors that predicted failure were flat or fibrotic blebs (non-functional) and no longer injected, while success was predicted by achieving a low IOP immediately after needling. No significant complications were identified. Needling was most successful soon after trabeculectomy, but resuscitation of a long-failed trabeculectomy had lower likelihood of success. The safety and efficacy compare favourably with alternative treatment approaches. © 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.

Factors that Predict How Women Label Their Own Childhood Sexual Abuse

ERIC Educational Resources Information Center

Katerndahl, David; Burge, Sandra; Kellogg, Nancy

2006-01-01

Despite the psychological impact of child sexual abuse, many victims do not acknowledge that their experiences were "abuse." This study sought to identify factors that predict how women label their own experiences of childhood sexual abuse. This cross-sectional study was conducted in a family medicine clinic with adult female patients. Subjects…

Factors associated with diabetes mellitus prediction among pregnant Arab subjects with gestational diabetes.

PubMed

Aljohani, Naji; Al Serehi, Amal; Ahmed, Amjad M; Buhary, Badr Aldin M; Alzahrani, Saad; At-Taras, Eeman; Almujally, Najla; Alsharqi, Maha; Alqahtani, Mohammed; Almalki, Mussa

2015-01-01

There is scarcity of available information on the possible significant risk factors related to diabetes mellitus (DM) prediction among expectant Saudi mothers with gestational diabetes mellitus (GDM). The present study is the first to identify such risk factors in the Arab cohort. A total of 300 pregnant subjects (mean age 33.45 ± 6.5 years) were randomly selected from all the deliveries registered at the Obstetrics Department of King Fahad Medical City, Riyadh Saudi Arabia from April 2011 to March 2013. Demographic and baseline glycemic information were collected. A total of 7 highly significant and independent risk factors were identified: age, obesity, and family history of DM, GDM < 20 weeks, macrosomia, insulin therapy and recurrent GDM. Among these factors, subjects who had insulin therapy use are 5 times more likely to develop DMT2 (p-value 3.94 × 10(-14)) followed by recurrent GDM [odds-ratio 4.69 (Confidence Interval 2.34-4.84); P = 1.24 × 10(-13)). The identification of the risk factors mentioned with their respective predictive powers in the detection of DMT2 needs to be taken seriously in the post-partum assessment of Saudi pregnant patients at highest risk.

Artificial neural networks identify the predictive values of risk factors on the conversion of amnestic mild cognitive impairment.

PubMed

Tabaton, Massimo; Odetti, Patrizio; Cammarata, Sergio; Borghi, Roberta; Monacelli, Fiammetta; Caltagirone, Carlo; Bossù, Paola; Buscema, Massimo; Grossi, Enzo

2010-01-01

The search for markers that are able to predict the conversion of amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) is crucial for early mechanistic therapies. Using artificial neural networks (ANNs), 22 variables that are known risk factors of AD were analyzed in 80 patients with aMCI, for a period spanning at least 2 years. The cases were chosen from 195 aMCI subjects recruited by four Italian Alzheimer's disease units. The parameters of glucose metabolism disorder, female gender, and apolipoprotein E epsilon3/epsilon4 genotype were found to be the biological variables with high relevance for predicting the conversion of aMCI. The scores of attention and short term memory tests also were predictors. Surprisingly, the plasma concentration of amyloid-beta (42) had a low predictive value. The results support the utility of ANN analysis as a new tool in the interpretation of data from heterogeneous and distinct sources.

A Regression Model with a New Tool: IDB Analyzer for Identifying Factors Predicting Mathematics Performance Using PISA 2012 Indices

ERIC Educational Resources Information Center

Arikan, Serkan

2014-01-01

There are many studies that focus on factors affecting achievement. However, there is limited research that used student characteristics indices reported by the Programme for International Student Assessment (PISA). Therefore, this study investigated the predictive effects of student characteristics on mathematics performance of Turkish students.…

Predictive Factors for Differentiating Between Septic Arthritis and Lyme Disease of the Knee in Children.

PubMed

Baldwin, Keith D; Brusalis, Christopher M; Nduaguba, Afamefuna M; Sankar, Wudbhav N

2016-05-04

Differentiating between septic arthritis and Lyme disease of the knee in endemic areas can be challenging and has major implications for patient management. The purpose of this study was to identify a prediction rule to differentiate septic arthritis from Lyme disease in children presenting with knee pain and effusion. We retrospectively reviewed the records of patients younger than 18 years of age with knee effusions who underwent arthrocentesis at our institution from 2005 to 2013. Patients with either septic arthritis (positive joint fluid culture or synovial white blood-cell count of >60,000 white blood cells/mm(3) with negative Lyme titer) or Lyme disease (positive Lyme immunoglobulin G on Western blot analysis) were included. To avoid misclassification bias, undiagnosed knee effusions and joints with both a positive culture and positive Lyme titers were excluded. Historical, clinical, and laboratory data were compared between groups to identify variables for comparison. Binary logistic regression analysis was used to identify independent predictive variables. One hundred and eighty-nine patients were studied: 23 with culture-positive septic arthritis, 26 with culture-negative septic arthritis, and 140 with Lyme disease. Multivariate binary logistic regression identified pain with short arc motion, history of fever reported by the patient or a family member, C-reactive protein of >4 mg/L, and age younger than 2 years as independent predictive factors for septic arthritis. A simpler model was developed that showed that the risk of septic arthritis with none of these factors was 2%, with 1 of these factors was 18%, with 2 of these factors was 45%, with 3 of these factors was 84%, or with all 4 of these factors was 100%. Although septic arthritis of the knee and Lyme monoarthritis share common features that can make them difficult to distinguish clinically, the presence of pain with short arc motion, C-reactive protein of >4.0 mg/L, patient-reported history of

Profiling healthy eaters. Determining factors that predict healthy eating practices among Dutch adults.

PubMed

Swan, Emily; Bouwman, Laura; Hiddink, Gerrit Jan; Aarts, Noelle; Koelen, Maria

2015-06-01

Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's salutogenic framework for health development to examine a set of factors that predict healthy eating in a cross-sectional study of Dutch adults. Data were analyzed from participants (n = 703) who completed the study's survey in January 2013. Logistic regression analysis was performed to test the association of survey factors on the outcome variable high dietary score. In the multivariate logistic regression model, five factors contributed significantly (p < .05) to the predictive ability of the overall model: being female; living with a partner; a strong sense of coherence (construct from the salutogenic framework), flexible restraint of eating, and self-efficacy for healthy eating. Findings complement what is already known of the factors that relate to poor eating practices. This can provide nutrition promotion with a more comprehensive picture of the factors that both support and hinder healthy eating practices. Future research should explore these factors to better understand their origins and mechanisms in relation to healthy eating practices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Antipsychotic therapeutic drug monitoring: psychiatrists’ attitudes and factors predicting likely future use

PubMed Central

Law, Suzanne; Haddad, Peter M.; Chaudhry, Imran B.; Husain, Nusrat; Drake, Richard J.; Flanagan, Robert J.; David, Anthony S.

2015-01-01

Background: This study aimed to explore predictive factors for future use of therapeutic drug monitoring (TDM) and to further examine psychiatrists’ current prescribing practices and perspectives regarding antipsychotic TDM using plasma concentrations. Method: A cross-sectional study for consultant psychiatrists using a postal questionnaire was conducted in north-west England. Data were combined with those of a previous London-based study and principal axis factor analysis was conducted to identify predictors of future use of TDM. Results: Most of the 181 participants (82.9%, 95% confidence interval 76.7–87.7%) agreed that ‘if TDM for antipsychotics were readily available, I would use it’. Factor analysis identified five factors from the original 35 items regarding TDM. Four of the factors significantly predicted likely future use of antipsychotic TDM and together explained 40% of the variance in a multivariate linear regression model. Likely future use increased with positive attitudes and expectations, and decreased with potential barriers, negative attitudes and negative expectations. Scientific perspectives of TDM and psychiatrist characteristics were not significant predictors. Conclusion: Most senior psychiatrists indicated that they would use antipsychotic TDM if available. However, psychiatrists’ attitudes and expectations and the potential barriers need to be addressed, in addition to the scientific evidence, before widespread use of antipsychotic TDM is likely in clinical practice. PMID:26301077

Children's First Experience of Taking Anabolic-Androgenic Steroids can Occur before Their 10th Birthday: A Systematic Review Identifying 9 Factors That Predicted Doping among Young People

PubMed Central

Nicholls, Adam R.; Cope, Ed; Bailey, Richard; Koenen, Katrin; Dumon, Detlef; Theodorou, Nikolaos C.; Chanal, Benoit; Saint Laurent, Delphine; Müller, David; Andrés, Mar P.; Kristensen, Annemarie H.; Thompson, Mark A.; Baumann, Wolfgang; Laurent, Jean-Francois

2017-01-01

Taking performance-enhancing drugs (PEDs) can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping (e.g., self-esteem, resisting social pressure, and perfectionist strivings), whereas other were positively associated with doping (e.g., suicide risk, anticipated regret, and aggression). Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping. PMID:28676778

Children's First Experience of Taking Anabolic-Androgenic Steroids can Occur before Their 10th Birthday: A Systematic Review Identifying 9 Factors That Predicted Doping among Young People.

PubMed

Nicholls, Adam R; Cope, Ed; Bailey, Richard; Koenen, Katrin; Dumon, Detlef; Theodorou, Nikolaos C; Chanal, Benoit; Saint Laurent, Delphine; Müller, David; Andrés, Mar P; Kristensen, Annemarie H; Thompson, Mark A; Baumann, Wolfgang; Laurent, Jean-Francois

2017-01-01

Taking performance-enhancing drugs (PEDs) can cause serious and irreversible health consequences, which can ultimately lead to premature death. Some young people may take PEDs without fully understanding the ramifications of their actions or based on the advice from others. The purpose of this systematic review was to identify the main factors that predicted doping among young people. The literature was systematically reviewed using search engines, manually searching specialist journals, and pearl growing. Fifty-two studies, which included 187,288 young people aged between 10 and 21 years of age, 883 parents of adolescent athletes, and 11 adult coaches, who were interviewed regarding young athletes, were included in this review. Nine factors predicted doping among young people: gender; age; sports participation; sport type; psychological variables; entourage; ethnicity; nutritional supplements; and health harming behaviors. In regards to psychological variables, 22 different constructs were associated with doping among young people. Some psychological constructs were negatively associated with doping (e.g., self-esteem, resisting social pressure, and perfectionist strivings), whereas other were positively associated with doping (e.g., suicide risk, anticipated regret, and aggression). Policy makers and National Anti-Doping Organizations could use these findings to help identify athletes who are more at risk of doping and then expose these individuals to anti-doping education. Based on the current findings, it also appears that education programs should commence at the onset of adolescence or even late childhood, due to the young age in which some individuals start doping.

Implementation of predictive data mining techniques for identifying risk factors of early AVF failure in hemodialysis patients.

PubMed

Rezapour, Mohammad; Khavanin Zadeh, Morteza; Sepehri, Mohammad Mehdi

2013-01-01

Arteriovenous fistula (AVF) is an important vascular access for hemodialysis (HD) treatment but has 20-60% rate of early failure. Detecting association between patient's parameters and early AVF failure is important for reducing its prevalence and relevant costs. Also predicting incidence of this complication in new patients is a beneficial controlling procedure. Patient safety and preservation of early AVF failure is the ultimate goal. Our research society is Hasheminejad Kidney Center (HKC) of Tehran, which is one of Iran's largest renal hospitals. We analyzed data of 193 HD patients using supervised techniques of data mining approach. There were 137 male (70.98%) and 56 female (29.02%) patients introduced into this study. The average of age for all the patients was 53.87 ± 17.47 years. Twenty eight patients had smoked and the number of diabetic patients and nondiabetics was 87 and 106, respectively. A significant relationship was found between "diabetes mellitus," "smoking," and "hypertension" with early AVF failure in this study. We have found that these mentioned risk factors have important roles in outcome of vascular surgery, versus other parameters such as "age." Then we predicted this complication in future AVF surgeries and evaluated our designed prediction methods with accuracy rates of 61.66%-75.13%.

Factors predicting labor induction success: a critical analysis.

PubMed

Crane, Joan M G

2006-09-01

Because of the risk of failed induction of labor, a variety of maternal and fetal factors as well as screening tests have been suggested to predict labor induction success. Certain characteristics of the woman (including parity, age, weight, height and body mass index), and of the fetus (including birth weight and gestational age) are associated with the success of labor induction; with parous, young women who are taller and lower weight having a higher rate of induction success. Fetuses with a lower birth weight or increased gestational age are also associated with increased induction success. The condition of the cervix at the start of induction is an important predictor, with the modified Bishop score being a widely used scoring system. The most important element of the Bishop score is dilatation. Other predictors, including transvaginal ultrasound (TVUS) and biochemical markers [including fetal fibronectin (fFN)] have been suggested. Meta-analyses of studies identified from MEDLINE, PubMed, and EMBASE and published from 1990 to October 2005 were performed evaluating the use of TVUS and fFN in predicting labor induction success in women at term with singleton gestations. Both TVUS and Bishop score predicted successful induction [likelihood ratio (LR)=1.82, 95% confidence interval (CI)=1.51-2.20 and LR=2.10, 95%CI=1.67-2.64, respectively]. As well, fFN and Bishop score predicted successful induction (LR=1.49, 95%CI=1.20-1.85, and LR=2.62, 95%CI=1.88-3.64, respectively). Although TVUS and fFN predicted successful labor induction, neither has been shown to be superior to Bishop score. Further research is needed to evaluate these potential predictors and insulin-like growth factor binding protein-1 (IGFBP-1), another potential biochemical marker.

Identifying risk factors for refractory febrile neutropenia in patients with lung cancer.

PubMed

Fujita, Masaki; Tokunaga, Shoji; Ikegame, Satoshi; Harada, Eiji; Matsumoto, Takemasa; Uchino, Junji; Watanabe, Kentaro; Nakanishi, Yoichi

2012-02-01

Information about the development of febrile neutropenia in patients with solid tumors remains insufficient. In this study, we tried to identify the risk factors for refractory febrile neutropenia in patients with lung cancer. A total of 59 neutropenic fever episodes associated with anti-tumor chemotherapy for lung cancer were retrospectively analyzed. We compared patient characteristics according to their initial response to treatment with antibiotics. For 34 of 59 (58%) episodes a response to initial antibiotics was obtained whereas 25 of 59 (42%) were refractory to treatment. Multivariate analysis demonstrated independent risk factors for refractory febrile neutropenia with lung cancer. These risk factors were the severity of febrile neutropenia (odds ratio (OR) 6.11; 95% confidence interval (CI) 1.85-20.14) and C-reactive protein more than 10 mg/dl (OR 4.39; 95% CI 1.22-15.74). These factors could predict outcome for patients with lung cancer who develop refractory febrile neutropenia.

Sequence-based predictive modeling to identify cancerlectins

PubMed Central

Lai, Hong-Yan; Chen, Xin-Xin; Chen, Wei; Tang, Hua; Lin, Hao

2017-01-01

Lectins are a diverse type of glycoproteins or carbohydrate-binding proteins that have a wide distribution to various species. They can specially identify and exclusively bind to a certain kind of saccharide groups. Cancerlectins are a group of lectins that are closely related to cancer and play a major role in the initiation, survival, growth, metastasis and spread of tumor. Several computational methods have emerged to discriminate cancerlectins from non-cancerlectins, which promote the study on pathogenic mechanisms and clinical treatment of cancer. However, the predictive accuracies of most of these techniques are very limited. In this work, by constructing a benchmark dataset based on the CancerLectinDB database, a new amino acid sequence-based strategy for feature description was developed, and then the binomial distribution was applied to screen the optimal feature set. Ultimately, an SVM-based predictor was performed to distinguish cancerlectins from non-cancerlectins, and achieved an accuracy of 77.48% with AUC of 85.52% in jackknife cross-validation. The results revealed that our prediction model could perform better comparing with published predictive tools. PMID:28423655

Consumer factors predicting level of treatment response to illness management and recovery.

PubMed

White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

2017-12-01

This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p < .001, R2 = .248, R2 change = .05. Additionally, we found that higher levels of maladaptive coping at baseline were predictive of higher levels of adaptive coping at follow-up, F(2, 180) = 5.29, p < .02, R2 = .38, R2 change = .02. Evidence did not support additional predictors. Previously, consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predictive factors for red blood cell transfusion in children undergoing noncomplex cardiac surgery.

PubMed

Mulaj, Muj; Faraoni, David; Willems, Ariane; Sanchez Torres, Cristel; Van der Linden, Philippe

2014-08-01

Red blood cell (RBC) transfusion is frequently required in pediatric cardiac surgery and is associated with altered outcome and increased costs. Determining which factors predict transfusion in this context will enable clinicians to adopt strategies that will reduce the risk of RBC transfusion. This study aimed to assess predictive factors associated with RBC transfusion in children undergoing low-risk cardiac surgery with cardiopulmonary bypass (CPB). Children undergoing surgery to repair ventricular septal defect or atrioventricular septal defect from 2006 to 2011 were included in this retrospective study. Demography, preoperative laboratory testing, intraoperative data, and RBC transfusion were reviewed. Univariate and multivariate logistic regression analysis were used to define factors that were able to predict RBC transfusion. Then, we employed receiver operating characteristic analysis to design a predictive score. Among the 334 children included, 261 (78%) were transfused. Age (<18 months), priming volume of the CPB (>43 mL/kg), type of oxygenator used, minimal temperature reached during CPB (<32°C), and preoperative hematocrit (<34%) were independently associated with RBC transfusion in the studied population. A predictive score 2 or greater was the best predictor of RBC transfusion. The present study identified several factors that were significantly associated with perioperative RBC transfusion. Based on these factors, we designed a predictive score that can be used to develop a patient-based blood management program with the aim of reducing the incidence of RBC transfusion. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Predictive factors for moderate or severe exacerbations in asthma patients receiving outpatient care.

PubMed

Gutiérrez, Francisco Javier Álvarez; Galván, Marta Ferrer; Gallardo, Juan Francisco Medina; Mancera, Marta Barrera; Romero, Beatriz Romero; Falcón, Auxiliadora Romero

2017-05-02

Asthma exacerbations are important events that affect disease control, but predictive factors for severe or moderate exacerbations are not known. The objective was to study the predictive factors for moderate (ME) and severe (SE) exacerbations in asthma patients receiving outpatient care. Patients aged > 12 years with asthma were included in the study and followed-up at 4-monthly intervals over a 12-month period. Clinical (severity, level of control, asthma control test [ACT]), atopic, functional, inflammatory, SE and ME parameters were recorded. Univariate analysis was used to compare data from patients presenting at least 1 SE or ME during the follow-up period vs no exacerbations. Statistically significant (p <0.1) factors were then subjected to multiple analysis by binary logistic regression. A total of 330 patients completed the study, most of whom were atopic (76%), women (nearly 70%), with moderate and mild persistent asthma (>80%). Twenty-seven patients (8%) had a SE and 183 had a ME (58.5%) during follow-up. In the case of SEs, the only predictive factor identified in the multiple analysis was previous SE (baseline visit OR 4.218 95% CI 1.53-11.58, 4-month follow-up OR 6.88 95% CI 2.018-23.51) and inhalation technique (OR 3.572 95% CI 1.324-9.638). In the case of MEs, the only predictive factor found in the multiple analysis were previous ME (baseline visit OR 2.90 95% CI 1.54-5.48, 4-month follow- up OR 1.702 95% CI 1.146-2.529). The primary predictive factor for SE or ME is prior SE or ME, respectively. SEs seem to constitute a specific patient "phenotype", in which the sole predictive factor is prior SEs.

Beyond Engagement Analytics: Which Online Mixed-Data Factors Predict Student Learning Outcomes?

ERIC Educational Resources Information Center

Strang, Kenneth David

2017-01-01

This mixed-method study focuses on online learning analytics, a research area of importance. Several important student attributes and their online activities are examined to identify what seems to work best to predict higher grades. The purpose is to explore the relationships between student grade and key learning engagement factors using a large…

Predictive factors of tumor control and survival after radiosurgery for local failures of nasopharyngeal carcinoma.

PubMed

Chua, Daniel T T; Sham, Jonathan S T; Hung, Kwan-Ngai; Leung, Lucullus H T; Au, Gordon K H

2006-12-01

Stereotactic radiosurgery has been employed as a salvage treatment of local failures of nasopharyngeal carcinoma (NPC). To identify patients that would benefit from radiosurgery, we reviewed our data with emphasis on factors that predicted treatment outcome. A total of 48 patients with local failures of NPC were treated by stereotactic radiosurgery between March 1996 and February 2005. Radiosurgery was administered using a modified linear accelerator with single or multiple isocenters to deliver a median dose of 12.5 Gy to the target periphery. Median follow-up was 54 months. Five-year local failure-free probability after radiosurgery was 47.2% and 5-year overall survival rate was 46.9%. Neuroendocrine complications occurred in 27% of patients but there were no treatment-related deaths. Time interval from primary radiotherapy, retreatment T stage, prior local failures and tumor volume were significant predictive factors of local control and/or survival whereas age was of marginal significance in predicting survival. A radiosurgery prognostic scoring system was designed based on these predictive factors. Five-year local failure-free probabilities in patients with good, intermediate and poor prognostic scores were 100%, 42.5%, and 9.6%. The corresponding five-year overall survival rates were 100%, 51.1%, and 0%. Important factors that predicted tumor control and survival after radiosurgery were identified. Patients with good prognostic score should be treated by radiosurgery in view of the excellent results. Patients with intermediate prognostic score may also be treated by radiosurgery but those with poor prognostic score should receive other salvage treatments.

Developing Predictive Models for Algal Bloom Occurrence and Identifying Factors Controlling their Occurrence in the Charlotte County and Surroundings

NASA Astrophysics Data System (ADS)

Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.

2017-12-01

Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.

CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes

PubMed Central

Hestand, Matthew S; van Galen, Michiel; Villerius, Michel P; van Ommen, Gert-Jan B; den Dunnen, Johan T; 't Hoen, Peter AC

2008-01-01

Background The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false positives and false negatives in current approaches. Computational methods to reduce false positives are to look for over-representation of transcription factor binding sites in a set of similarly regulated promoters or to look for conservation in orthologous promoter alignments. Results We have developed a novel tool, "CORE_TF" (Conserved and Over-REpresented Transcription Factor binding sites) that identifies common transcription factor binding sites in promoters of co-regulated genes. To improve upon existing binding site predictions, the tool searches for position weight matrices from the TRANSFACR database that are over-represented in an experimental set compared to a random set of promoters and identifies cross-species conservation of the predicted transcription factor binding sites. The algorithm has been evaluated with expression and chromatin-immunoprecipitation on microarray data. We also implement and demonstrate the importance of matching the random set of promoters to the experimental promoters by GC content, which is a unique feature of our tool. Conclusion The program CORE_TF is accessible in a user friendly web interface at . It provides a table of over-represented transcription factor binding sites in the users input genes' promoters and a graphical view of evolutionary conserved transcription factor binding sites. In our test data sets it successfully predicts target transcription factors and their binding sites. PMID:19036135

Remission of Intermediate Uveitis: Incidence and Predictive Factors.

PubMed

Kempen, John H; Gewaily, Dina Y; Newcomb, Craig W; Liesegang, Teresa L; Kaçmaz, R Oktay; Levy-Clarke, Grace A; Nussenblatt, Robert B; Rosenbaum, James T; Sen, H Nida; Suhler, Eric B; Thorne, Jennifer E; Foster, C Stephen; Jabs, Douglas A; Payal, Abhishek; Fitzgerald, Tonetta D

2016-04-01

To evaluate the incidence of remission among patients with intermediate uveitis; to identify factors potentially predictive of remission. Retrospective cohort study. Involved eyes of patients with primary noninfectious intermediate uveitis at 4 academic ocular inflammation subspecialty practices, followed sufficiently long to meet the remission outcome definition, were studied retrospectively by standardized chart review data. Remission of intermediate uveitis was defined as a lack of inflammatory activity at ≥2 visits spanning ≥90 days in the absence of any corticosteroid or immunosuppressant medications. Factors potentially predictive of intermediate uveitis remission were evaluated using survival analysis. Among 849 eyes (of 510 patients) with intermediate uveitis followed over 1934 eye-years, the incidence of intermediate uveitis remission was 8.6/100 eye-years (95% confidence interval [CI], 7.4-10.1). Factors predictive of disease remission included prior pars plana vitrectomy (PPV) (hazard ratio [HR] [vs no PPV] = 2.39; 95% CI, 1.42-4.00), diagnosis of intermediate uveitis within the last year (HR [vs diagnosis >5 years ago] =3.82; 95% CI, 1.91-7.63), age ≥45 years (HR [vs age <45 years] = 1.79; 95% CI, 1.03-3.11), female sex (HR = 1.61; 95% CI, 1.04-2.49), and Hispanic race/ethnicity (HR [vs white race] = 2.81; 95% CI, 1.23-6.41). Presence/absence of a systemic inflammatory disease, laterality of uveitis, and smoking status were not associated with differential incidence. Our results suggest that intermediate uveitis is a chronic disease with an overall low rate of remission. Recently diagnosed patients and older, female, and Hispanic patients were more likely to remit. With regard to management, pars plana vitrectomy was associated with increased probability of remission. Copyright © 2016 Elsevier Inc. All rights reserved.

Remission of Intermediate Uveitis: Incidence and Predictive Factors

PubMed Central

Kempen, John H.; Gewaily, Dina Y.; Newcomb, Craig W.; Liesegang, Teresa L.; Kaçmaz, R. Oktay; Levy-Clarke, Grace A.; Nussenblatt, Robert B.; Rosenbaum, James T.; Sen, H. Nida; Suhler, Eric B.; Thorne, Jennifer E.; Foster, C. Stephen; Jabs, Douglas A.; Payal, Abhishek; Fitzgerald, Tonetta D.

2016-01-01

Purpose To evaluate the incidence of remission among patients with intermediate uveitis; to identify factors potentially predictive of remission. Design Retrospective cohort study. Methods Involved eyes of patients with primary non-infectious intermediate uveitis at 4 academic ocular inflammation subspecialty practices, followed sufficiently long to meet the remission outcome definition, were studied retrospectively by standardized chart review data. Remission of intermediate uveitis was defined as a lack of inflammatory activity at ≥2 visits spanning ≥90 days in the absence of any corticosteroid or immunosuppressant medications. Factors potentially predictive of intermediate uveitis remission were evaluated using survival analysis. Results Among 849 eyes (of 510 patients) with intermediate uveitis followed over 1,934 eye-years, the incidence of intermediate uveitis remission was 8.6/100 eye-years (95% confidence interval (CI), 7.4–10.1). Factors predictive of disease remission included prior pars plana vitrectomy (PPV) (HR (vs. no PPV)=2.39; 95% CI, 1.42–4.00), diagnosis of intermediate uveitis within the last year (vs. diagnosis >5 years ago)=3.82; 95% CI, 1.91–7.63), age ≥45 years (HR (vs. age <45 years)=1.79; 95% CI, 1.03–3.11), female sex (HR=1.61; 95% CI, 1.04–2.49), and Hispanic race/ethnicity (HR (vs. white race)=2.81; 95% CI, 1.23–6.41). Presence/absence of a systemic inflammatory disease, laterality of uveitis, and smoking status were not associated with differential incidence. Conclusions Our results suggest that intermediate uveitis is a chronic disease with an overall low rate of remission. Recently diagnosed cases, and older, female and Hispanic cases were more likely to remit. With regards to management, pars plana vitrectomy was associated with increased probability of remission. PMID:26772874

CisMapper: predicting regulatory interactions from transcription factor ChIP-seq data

PubMed Central

O'Connor, Timothy; Bodén, Mikael

2017-01-01

Abstract Identifying the genomic regions and regulatory factors that control the transcription of genes is an important, unsolved problem. The current method of choice predicts transcription factor (TF) binding sites using chromatin immunoprecipitation followed by sequencing (ChIP-seq), and then links the binding sites to putative target genes solely on the basis of the genomic distance between them. Evidence from chromatin conformation capture experiments shows that this approach is inadequate due to long-distance regulation via chromatin looping. We present CisMapper, which predicts the regulatory targets of a TF using the correlation between a histone mark at the TF's bound sites and the expression of each gene across a panel of tissues. Using both chromatin conformation capture and differential expression data, we show that CisMapper is more accurate at predicting the target genes of a TF than the distance-based approaches currently used, and is particularly advantageous for predicting the long-range regulatory interactions typical of tissue-specific gene expression. CisMapper also predicts which TF binding sites regulate a given gene more accurately than using genomic distance. Unlike distance-based methods, CisMapper can predict which transcription start site of a gene is regulated by a particular binding site of the TF. PMID:28204599

Morbidity predicting factors of penetrating colon injuries.

PubMed

Mickevicius, A; Valeikaite, G; Tamelis, A; Saladzinskas, Z; Svagzdys, S; Pavalkis, D

2010-01-01

To analyze patients suffering from penetrating colon injuries management, clinical outcomes and factors, which predict higher morbidity and complications rate. this was a retrospective analysis of prospectively collected data from patients with injured colon from 1995 to 2008. Age, time till operation, systolic blood pressure, part of injured colon, fecal contamination, PATI were registered. Monovariate and multivariate logistic regression was performed to determine higher morbidity predictive factors. 61 patients had penetrating colon injuries. Major fecal contamination of the peritoneal cavity and systolic blood pressure lower than 90 mmHg are independent factors determining the fecal diversion operation. Primary repair group analysis establish that major fecal contamination and systolic blood pressure lower than 90 mmHg OR = 4.2 and 0.96 were significant risk factors, which have contributed to the development of postoperative complications. And systolic blood pressure lower than 90 mmHg and PATI 20 predict OR = 0.05 and 2.61 higher morbidity. Fecal contamination of the peritoneal cavity and hypotension were determined to be crucial in choice of performing fecal diversion or primary repair. But the same criteria and PATI predict higher rate of postoperative complications and higher morbidity.

Factors Predictive of Healing in Large Rotator Cuff Tears: Is It Possible to Predict Retear Preoperatively?

PubMed

Jeong, Ho Yeon; Kim, Hwan Jin; Jeon, Yoon Sang; Rhee, Yong Girl

2018-03-01

Many studies have identified risk factors that cause retear after rotator cuff repair. However, it is still questionable whether retears can be predicted preoperatively. To determine the risk factors related to retear after arthroscopic rotator cuff repair and to evaluate whether it is possible to predict the occurrence of retear preoperatively. Case-control study; Level of evidence, 3. This study enrolled 112 patients who underwent arthroscopic rotator cuff repair with single-row technique for a large-sized tear, defined as a tear with a mediolateral length of 3 to 5 cm. All patients underwent routine magnetic resonance imaging (MRI) at 9 months postoperatively to assess tendon integrity. The sample included 61 patients (54.5%) in the healed group and 51 (45.5%) in the retear group. In multivariate analysis, the independent predictors of retears were supraspinatus muscle atrophy ( P < .001) and fatty infiltration of the infraspinatus ( P = .027), which could be preoperatively measured by MRI. A significant difference was found between the two groups in sex, the acromiohumeral interval, tendon tension, and preoperative or intraoperative mediolateral tear length and musculotendinous junction position in univariate analysis. However, these variables were not independent predictors in multivariate analysis. The cutoff values of occupation ratio of supraspinatus and fatty infiltration of the infraspinatus were 43% and grade 2, respectively. The occupation ratio of supraspinatus <43% and grade ≥2 fatty infiltration of the infraspinatus were the strongest predictors of retear, with an area under the curve of 0.908, sensitivity of 98.0%, and specificity of 83.6% (accuracy = 90.2%). In patients with large rotator cuff tears, it was possible to predict the retear before rotator cuff repair regardless of intraoperative factors. The retear could be predicted most effectively when the occupation ratio of supraspinatus was <43% or the fatty infiltration of infraspinatus was

Predicting College Success: The Relative Contributions of Five Social/Personality Factors, Five Cognitive/Learning Factors, and SAT Scores

PubMed Central

Hannon, Brenda

2014-01-01

To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results revealed many significant predictors of GPA for both freshmen and non-freshmen. However, subsequent regressions showed that only academic self-efficacy, epistemic belief of learning, and high-knowledge integration explained unique variance in GPA (19%-freshmen, 23.2%-non-freshmen). Further for freshmen, SAT scores explained an additional unique 10.6% variance after the influences attributed to these three predictors was removed whereas for non-freshmen, SAT scores failed to explain any additional variance. These results highlight the unique and important contributions of academic self-efficacy, epistemic belief of learning and high-knowledge integration to GPA beyond other previously-identified predictors. PMID:25568884

Nightmares in the general population: identifying potential causal factors.

PubMed

Rek, Stephanie; Sheaves, Bryony; Freeman, Daniel

2017-09-01

Nightmares are inherently distressing, prevent restorative sleep, and are associated with a number of psychiatric problems, but have rarely been the subject of empirical study. Negative affect, linked to stressful events, is generally considered the key trigger of nightmares; hence nightmares have most often been considered in the context of post-traumatic stress disorder (PTSD). However, many individuals with heightened negative affect do not have nightmares. The objective of this study was to identify mechanistically plausible factors, beyond negative affect, that may explain why individuals experience nightmares. 846 participants from the UK general population completed an online survey about nightmare occurrence and severity (pre-occupation, distress, and impairment), negative affect, worry, depersonalisation, hallucinatory experiences, paranoia, alcohol use, sleep duration, physical activity levels, PTSD symptoms, and stressful life events. Associations of nightmares with the putative predictive factors were tested controlling for levels of negative affect. Analyses were also repeated controlling for levels of PTSD and the recent occurrence of stressful life events. Nightmare occurrence, adjusting for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, paranoia, and sleep duration (odds ratios 1.25-1.45). Nightmare severity, controlling for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, and paranoia (R 2 s: 0.33-0.39). Alcohol use and physical activity levels were not associated with nightmares. The study identifies a number of potential predictors of the occurrence and severity of nightmares. Causal roles require testing in future longitudinal, experimental, and treatment studies.

Factors predictive for incidence and remission of internet addiction in young adolescents: a prospective study.

PubMed

Ko, Chih-Hung; Yen, Ju-Yu; Yen, Cheng-Fang; Lin, Huang-Chi; Yang, Ming-Jen

2007-08-01

The aim of the study is to determine the incidence and remission rates for Internet addiction and the associated predictive factors in young adolescents over a 1-year follow-up. This was a prospective, population-based investigation. Five hundred seventeen students (267 male and 250 female) were recruited from three junior high schools in southern Taiwan. The factors examined included gender, personality, mental health, self-esteem, family function, life satisfaction, and Internet activities. The result revealed that the 1-year incidence and remission rates for Internet addiction were 7.5% and 49.5% respectively. High exploratory excitability, low reward dependence, low self-esteem, low family function, and online game playing predicted the emergency of the Internet addiction. Further, low hostility and low interpersonal sensitivity predicted remission of Internet addiction. The factors predictive incidence and remission of Internet addiction identified in this study could be provided for prevention and promoting remission of Internet addiction in adolescents.

Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification.

PubMed

Baker, Erich J; Walter, Nicole A R; Salo, Alex; Rivas Perea, Pablo; Moore, Sharon; Gonzales, Steven; Grant, Kathleen A

2017-03-01

The Monkey Alcohol Tissue Research Resource (MATRR) is a repository and analytics platform for detailed data derived from well-documented nonhuman primate (NHP) alcohol self-administration studies. This macaque model has demonstrated categorical drinking norms reflective of human drinking populations, resulting in consumption pattern classifications of very heavy drinking (VHD), heavy drinking (HD), binge drinking (BD), and low drinking (LD) individuals. Here, we expand on previous findings that suggest ethanol drinking patterns during initial drinking to intoxication can reliably predict future drinking category assignment. The classification strategy uses a machine-learning approach to examine an extensive set of daily drinking attributes during 90 sessions of induction across 7 cohorts of 5 to 8 monkeys for a total of 50 animals. A Random Forest classifier is employed to accurately predict categorical drinking after 12 months of self-administration. Predictive outcome accuracy is approximately 78% when classes are aggregated into 2 groups, "LD and BD" and "HD and VHD." A subsequent 2-step classification model distinguishes individual LD and BD categories with 90% accuracy and between HD and VHD categories with 95% accuracy. Average 4-category classification accuracy is 74%, and provides putative distinguishing behavioral characteristics between groupings. We demonstrate that data derived from the induction phase of this ethanol self-administration protocol have significant predictive power for future ethanol consumption patterns. Importantly, numerous predictive factors are longitudinal, measuring the change of drinking patterns through 3 stages of induction. Factors during induction that predict future heavy drinkers include being younger at the time of first intoxication and developing a shorter latency to first ethanol drink. Overall, this analysis identifies predictive characteristics in future very heavy drinkers that optimize intoxication, such as having

Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

PubMed

Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

2018-05-01

Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

PubMed

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Identifying Factors for Worker Motivation in Zambia's Rural Health Facilities.

PubMed

Cross, Samuel S; Baernholdt, Dr Marianne

2017-01-01

Within Zambia there is a shortage of health workers in rural areas. This study aims to identify motivating factors for retaining rural health workers. Sixty rural health workers completed surveys and 46 were interviewed. They rated the importance of six motivating factors and discussed these and other factors in interviews. An interview was conducted with a Government Human Resources Manager (HR Manager) to elicit contextual information. All six factors were identified as being very important motivators, as were two additional factors. Additional career training was identified by many as the most important factor. Comparison of results and the HR Manager interview revealed that workers lacked knowledge about opportunities and that the HR manager was aware of barriers to career development. The Zambian government might better motivate and retain rural health workers by offering them any combination of identified factors, and by addressing the barriers to career development.

Intrinsic Predictive Factors of Noncontact Lateral Ankle Sprain in Collegiate Athletes

PubMed Central

Kobayashi, Takumi; Yoshida, Masahiro; Yoshida, Makoto; Gamada, Kazuyoshi

2013-01-01

Background: Lateral ankle sprain (LAS) is one of the most common injuries in sports. Despite extensive research, intrinsic factors that predict initial and recurrent noncontact LAS remain undefined. Purpose: To identify the predictive factors of initial and recurrent noncontact LAS, focusing on ankle flexibility and/or alignment in collegiate athletes. Study Design: Case-control study; Level of evidence, 3. Methods: A total of 191 athletes were assessed during the preseason for factors predictive of noncontact LAS. The baseline measurements included weightbearing dorsiflexion range of motion (ROM), leg-heel angle, foot internal rotation angle in plantar flexion, classification according to the mortise test, and navicular–medial malleolus (NMM) distance. Occurrence of noncontact LAS and participation in practice and games were prospectively recorded for 11 months. Results: Of the 191 athletes assessed, 169 (145 males, 24 females) completed the study; 125 athletes had a history of ankle sprain. During the observational period, 16 athletes suffered noncontact LAS (0.58 per 1000 athlete-exposures) consisting of 4 initial sprains and 12 recurrences. The hazard ratio estimated by a Cox regression analysis showed that athletes with an NMM distance ≥4.65 cm were 4.14 times more likely to suffer an initial noncontact LAS than were athletes with a shorter NMM distance (95% confidence interval, 1.12-14.30) and that athletes with a weightbearing dorsiflexion ROM >49.5° were 1.12 times as likely to suffer a recurrent noncontact LAS compared with athletes with a lower ROM (95% confidence interval, 1.05-1.20). Conclusion: NMM distance predicts initial noncontact LAS, and weightbearing dorsiflexion ROM predicts recurrent noncontact LAS. PMID:26535263

Factors predicting mortality in severe acute pancreatitis.

PubMed

Compañy, L; Sáez, J; Martínez, J; Aparicio, J R; Laveda, R; Griñó, P; Pérez-Mateo, M

2003-01-01

Acute pancreatitis (AP) is a common disorder in which ensuing serious complications may lead to a fatal outcome in patients. To describe a large series of patients with severe AP (SAP) who were admitted to our hospital and to identify factors predicting mortality. In a retrospective study, all patients with SAP diagnosed between February 1996 and October 2000 according to the Atlanta criteria were studied. Out of a total of 363 AP patients, 67 developed SAP. The mean age of the patients was 69; the commonest etiology was biliary; 55.2% developed necrosis; the commonest systemic complication was respiratory failure (44.7%), followed by acute renal failure (35.8%) and shock (20.9%). A total of 31.3% of the patients died. Factors significantly related to mortality were age, upper digestive tract bleeding, acute renal failure, respiratory failure and shock by univariate analysis. However, pseudocysts seemed to have a protective effect. By multivariate analysis, independent prognostic factors were age, acute renal failure and respiratory failure. Patients with SAP mainly died due to systemic complications, especially acute renal failure and respiratory failure. Necrosis (in the absence or presence of infection) was not correlated with increased mortality. A pseudocyst was found to be a protective factor, probably because the definition itself led to the selection of patients who had survived multiorgan failure. Copyright 2003 S. Karger AG, Basel and IAP

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

PubMed

Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

2017-02-01

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Contextual Predictive Factors of Child Sexual Abuse: The Role of Parent-Child Interaction

ERIC Educational Resources Information Center

Ramirez, Clemencia; Pinzon-Rondon, Angela Maria; Botero, Juan Carlos

2011-01-01

Objectives: To determine the prevalence of child sexual abuse in the Colombian coasts, as well as to assess the role of parent-child interactions on its occurrence and to identify factors from different environmental levels that predict it. Methods: This cross-sectional study explores the results of 1,089 household interviews responded by mothers.…

Predictive factors for postoperative severe hypocalcaemia after parathyroidectomy for primary hyperparathyroidism.

PubMed

Crea, Nicola; Pata, Giacomo; Casella, Claudio; Cappelli, Carlo; Salerni, Bruno

2012-03-01

Hypocalcaemia is a complication of parathyroidectomy. We retrospectively analyzed data on patients who underwent parathyroidectomy for primary hyperparathyroidism (pHPT) to identify predictive factors for severe postoperative hypocalcaemia. Since 2004 we performed 87 parathyroidectomies for pHPT. We divided the patients into two groups: subjects who presented with postoperative hypocalcaemia (group B) or otherwise (group A). We looked for a correlation between several variables and the incidence of postoperative hypocalcaemia. The median calcemia in group B (19 patients) was 6.9 mg/dL on the first postoperative day and 7.6 mg/dL on the third day. We observed hypocalcemia related clinical symptoms in every patient. In all 19 cases the reduction of intraoperative parathyroid hormone above 85 per cent after parathyroidectomy was related to the development of severe postoperative hypocalcaemia (P = 0.042). We found that the reduction of intraoperative parathyroid hormone over 85 per cent after parathyroidectomy can be considered a reliable predictive factor of postoperative hypocalcaemia after parathyroidectomy for primary hyperparathyroidism.

Can the big five factors of personality predict lymphocyte counts?

PubMed

Ožura, Ana; Ihan, Alojz; Musek, Janek

2012-03-01

Psychological stress is known to affect the immune system. The Limbic Hypothalamic Pituitary Adrenal (LHPA) axis has been identified as the principal path of the bidirectional communication between the immune system and the central nervous system with significant psychological activators. Personality traits acted as moderators of the relationship between life conflicts and psychological distress. This study focuses on the relationship between the Big Five factors of personality and immune regulation as indicated by Lymphocyte counts. Our study included 32 professional soldiers from the Slovenian Army that completed the Big Five questionnaire (Goldberg IPIP-300). We also assessed their white blood cell counts with a detailed lymphocyte analysis using flow cytometry. The correlations between personality variables and immune system parameters were calculated. Furthermore, regression analyses were performed using personality variables as predictors and immune parameters as criteria. The results demonstrated that the model using the Big Five factors as predictors of Lymphocyte counts is significant in predicting the variance in NK and B cell counts. Agreeableness showed the strongest predictive function. The results offer support for the theoretical models that stressed the essential links between personality and immune regulation. Further studies with larger samples examining the Big five factors and immune system parameters are needed.

Factors Predictive Of Alcohol Consumption Among Elderly People In A Rural Community: A Case Study In Phayao Province Thailand.

PubMed

Hongthong, Donnapa; Somrongthong, Ratana; Wongchaiya, Pimpimon; Kumar, Ramesh

2016-01-01

Alcohol consumption is recognized as a public health issue. Study objectives were to identify factors predictive of alcohol consumption among elderly people in Phayao province Thailand, where there was high prevalence of alcohol consumption. This was a cross-sectional study. Four hundred elderly people participated in a survey. Data was collected by face-to-face interviews. Chi-square and multivariate logistic regression were used to determine the factors predictive of alcohol consumption among the study subjects. One thirds of elderly (31.7%) had consumed alcohol in their lifetime, and (15.7%) of them were current drinkers. Following univariate analysis, seven factors included gender, working, sickness, smoking, quality of life (QOL), daily activities and economic recession - were identified as being significantly associated with drinking (p<0.05). Multivariate analysis revealed four factors to be predictive of alcohol among elderly people: gender (OR=6.02, 95% CI=3.58-10.13), smoking (OR=4.34, 95% CI=2.57-7.34), economic recession (OR=2.79, 95%, CI=1.66-4.71), and QOL (OR=1.86, 95%, CI=1.09-3.16). Gender (male) and smoking were strongly predictive factors of elderly alcohol consumption. Hence, an effort to reduce alcohol consumption should be placed on male elderly and those who smoke.

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

PubMed

Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David

2015-12-01

We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p < 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion

Increasing organizational energy conservation behaviors: Comparing the theory of planned behavior and reasons theory for identifying specific motivational factors to target for change

NASA Astrophysics Data System (ADS)

Finlinson, Scott Michael

Social scientists frequently assess factors thought to underlie behavior for the purpose of designing behavioral change interventions. Researchers commonly identify these factors by examining relationships between specific variables and the focal behaviors being investigated. Variables with the strongest relationships to the focal behavior are then assumed to be the most influential determinants of that behavior, and therefore often become the targets for change in a behavioral change intervention. In the current proposal, multiple methods are used to compare the effectiveness of two theoretical frameworks for identifying influential motivational factors. Assessing the relative influence of all factors and sets of factors for driving behavior should clarify which framework and methodology is the most promising for identifying effective change targets. Results indicated each methodology adequately predicted the three focal behaviors examined. However, the reasons theory approach was superior for predicting factor influence ratings compared to the TpB approach. While common method variance contamination had minimal impact on the results or conclusions derived from the present study's findings, there were substantial differences in conclusions depending on the questionnaire design used to collect the data. Examples of applied uses of the present study are discussed.

Evaluation of easily measured risk factors in the prediction of osteoporotic fractures

PubMed Central

Bensen, Robert; Adachi, Jonathan D; Papaioannou, Alexandra; Ioannidis, George; Olszynski, Wojciech P; Sebaldt, Rolf J; Murray, Timothy M; Josse, Robert G; Brown, Jacques P; Hanley, David A; Petrie, Annie; Puglia, Mark; Goldsmith, Charlie H; Bensen, W

2005-01-01

Background Fracture represents the single most important clinical event in patients with osteoporosis, yet remains under-predicted. As few premonitory symptoms for fracture exist, it is of critical importance that physicians effectively and efficiently identify individuals at increased fracture risk. Methods Of 3426 postmenopausal women in CANDOO, 40, 158, 99, and 64 women developed a new hip, vertebral, wrist or rib fracture, respectively. Seven easily measured risk factors predictive of fracture in research trials were examined in clinical practice including: age (<65, 65–69, 70–74, 75–79, 80+ years), rising from a chair with arms (yes, no), weight (< 57, ≥ 57kg), maternal history of hip facture (yes, no), prior fracture after age 50 (yes, no), hip T-score (>-1, -1 to >-2.5, ≤-2.5), and current smoking status (yes, no). Multivariable logistic regression analysis was conducted. Results The inability to rise from a chair without the use of arms (3.58; 95% CI: 1.17, 10.93) was the most significant risk factor for new hip fracture. Notable risk factors for predicting new vertebral fractures were: low body weight (1.57; 95% CI: 1.04, 2.37), current smoking (1.95; 95% CI: 1.20, 3.18) and age between 75–79 years (1.96; 95% CI: 1.10, 3.51). New wrist fractures were significantly identified by low body weight (1.71, 95% CI: 1.01, 2.90) and prior fracture after 50 years (1.96; 95% CI: 1.19, 3.22). Predictors of new rib fractures include a maternal history of a hip facture (2.89; 95% CI: 1.04, 8.08) and a prior fracture after 50 years (2.16; 95% CI: 1.20, 3.87). Conclusion This study has shown that there exists a variety of predictors of future fracture, besides BMD, that can be easily assessed by a physician. The significance of each variable depends on the site of incident fracture. Of greatest interest is that an inability to rise from a chair is perhaps the most readily identifiable significant risk factor for hip fracture and can be easily incorporated into

Predictive factors of telemedicine service acceptance and behavioral intention of physicians.

PubMed

Rho, Mi Jung; Choi, In Young; Lee, Jaebeom

2014-08-01

Despite the proliferation of telemedicine technology, telemedicine service acceptance has been slow in actual healthcare settings. The purpose of this research is to develop a theoretical model for explaining the predictive factors influencing physicians' willingness to use telemedicine technology to provide healthcare services. We developed the Telemedicine Service Acceptance model based on the technology acceptance model (TAM) with the inclusion of three predictive constructs from the previously published telemedicine literature: (1) accessibility of medical records and of patients as clinical factors, (2) self-efficacy as an individual factor and (3) perceived incentives as regulatory factors. A survey was conducted, and structural equation modeling was applied to evaluate the empirical validity of the model and causal relationships within the model using the data collected from 183 physicians. Our results confirmed the validity of the original TAM constructs: the perceived usefulness of telemedicine directly impacted the behavioral intention to use it, and the perceived ease of use directly impacted both the perceived usefulness and the behavioral intention to use it. In addition, new predictive constructs were found to have ramifications on TAM variables: the accessibility of medical records and of patients directly impacted the perceived usefulness of telemedicine, self-efficacy had a significant positive effect on both the perceived ease of use and the perceived usefulness of telemedicine, and perceived incentives were found to be important with respect to the intention to use telemedicine technology. This study demonstrated that the Telemedicine Service Acceptance model was feasible and could explain the acceptance of telemedicine services by physicians. These results identified important factors for increasing the involvement of physicians in telemedicine practice. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Factors which predict violence victimization in Nigeria

PubMed Central

Fry, Lincoln J.

2014-01-01

Background: Violence is a major public health issue, globally as well as in the African continent. This paper looks at Nigeria and begins the process of identifying the factors that predict interpersonal violence in that country. The purpose is to interpret the implications of the results presented here for violence prevention programmes in Nigeria. Materials and Methods: The study is based on the responses of 2324 Nigerians included in Round Four of the Afrobarometer surveys. The study concentrates on 579 respondents who reported either they or someone else in their family had been the victim of violence, defined as being physically attacked, in the past year. Results: A logistical regression analysis revealed five significant factors that predicted interpersonal violence: being the victim of a property crime, the fear of crime, the respondents faith, whethera police station was in the local area and poverty. The findings revealed that 43.7% of the sample had been victimised within the past year and 18.8% had been the victim of both violent and property crimes. One surprising findingwas the number of respondents who were re-victimised; 75% of violence victims also had been property crime victims. Conclusions: These findings suggest that target hardening should be the basis to plan, implement and evaluate violence prevention programmes in Nigeria. Prevention personnel and/or law enforcement need to respond to reported incidents of property and/or violence victimisation and attempt to prepare victims to protect both their premises and their persons in the future. PMID:24970968

Gankyrin is a predictive and oncogenic factor in well-differentiated and dedifferentiated liposarcoma.

PubMed

Hwang, Ju-Ae; Yang, Heung-Mo; Hong, Doo-Pyo; Joo, Sung-Yeon; Choi, Yoon-La; Park, Joo-Hung; Lazar, Alexander J; Pollock, Raphael E; Lev, Dina; Kim, Sung Joo

2014-10-15

Liposarcoma is one of the most common histologic types of soft tissue sarcoma and is frequently an aggressive cancer with poor outcome. Hence, alternative approaches other than surgical excision are necessary to improve treatment of well-differentiated/dedifferentiated liposarcoma (WDLPS/DDLPS). For this reason, we performed a two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry/mass spectrometry (MALDI-TOF/MS) analysis to identify new factors for WDLPS and DDLPS. Among the selected candidate proteins, gankyrin, known to be an oncoprotein, showed a significantly high level of expression pattern and inversely low expression of p53/p21 in WDLPS and DDLPS tissues, suggesting possible utility as a new predictive factor. Moreover, inhibition of gankyrin not only led to reduction of in vitro cell growth ability including cell proliferation, colony-formation, and migration, but also in vivo DDLPS cell tumorigenesis, perhaps via downregulation of the p53 tumor suppressor gene and its p21 target and also reduction of AKT/mTOR signal activation. This study identifies gankyrin, for the first time, as new potential predictive and oncogenic factor of WDLPS and DDLPS, suggesting the potential for service as a future LPS therapeutic approach.

Gankyrin is a predictive and oncogenic factor in well-differentiated and dedifferentiated liposarcoma

PubMed Central

Hong, Doo-Pyo; Joo, Sung-Yeon; Choi, Yoon-La; Park, Joo-Hung; Lazar, Alexander J.; Pollock, Raphael E.; Lev, Dina; Kim, Sung Joo

2014-01-01

Liposarcoma is one of the most common histologic types of soft tissue sarcoma and is frequently an aggressive cancer with poor outcome. Hence, alternative approaches other than surgical excision are necessary to improve treatment of well-differentiated/dedifferentiated liposarcoma (WDLPS/DDLPS). For this reason, we performed a two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry/mass spectrometry (MALDI-TOF/MS) analysis to identify new factors for WDLPS and DDLPS. Among the selected candidate proteins, gankyrin, known to be an oncoprotein, showed a significantly high level of expression pattern and inversely low expression of p53/p21 in WDLPS and DDLPS tissues, suggesting possible utility as a new predictive factor. Moreover, inhibition of gankyrin not only led to reduction of in vitro cell growth ability including cell proliferation, colony-formation, and migration, but also in vivo DDLPS cell tumorigenesis, perhaps via downregulation of the p53 tumor suppressor gene and its p21 target and also reduction of AKT/mTOR signal activation. This study identifies gankyrin, for the first time, as new potential predictive and oncogenic factor of WDLPS and DDLPS, suggesting the potential for service as a future LPS therapeutic approach. PMID:25238053

What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil p

A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

PubMed

Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

2018-03-06

Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

Predicting Factors of Chronic Subdural Hematoma Following Surgical Clipping in Unruptured and Ruptured Intracranial Aneurysm.

PubMed

Kwon, Min-Yong; Kim, Chang-Hyun; Lee, Chang-Young

2016-09-01

The aim of this study is to analyze the differences in the incidence, predicting factors, and clinical course of chronic subdural hematoma (CSDH) following surgical clipping between unruptured (UIA) and ruptured intracranial aneurysm (RIA). We conducted a retrospective analysis of 752 patients (UIA : 368 and RIA : 384) who underwent surgical clipping during 8 years. The incidence and predicting factors of CSDH development in the UIA and RIA were compared according to medical records and radiological data. The incidence of postoperative CSDH was higher in the UIA (10.9%) than in the RIA (3.1%) (p=0.000). In multivariate analysis, a high Hounsfield (HF) unit (blood clots) for subdural fluid collection (SFC), persistence of SFC ≥5 mm and male sex in the UIA and A high HF unit for SFC and SFC ≥5 mm without progression to hydrocephalus in the RIA were identified as the independent predicting factors for CSDH development (p<0.05). There were differences in the incidence and predicting factors for CSDH following surgical clipping between UIA and RIA. Blood clots in the subdural space and persistence of SFC ≥5 mm were predicting factors in both UIA and RIA. However, progression to hydrocephalus may have in part contributed to low CSDH development in the RIA. We suggest that cleaning of blood clots in the subdural space and efforts to minimize SFC ≥5 mm at the end of surgery is helpful to prevent CSDH following aneurysmal clipping.

Evaluation of the Predictive Validity of Thermography in Identifying Extravasation With Intravenous Chemotherapy Infusions.

PubMed

Matsui, Yuko; Murayama, Ryoko; Tanabe, Hidenori; Oe, Makoto; Motoo, Yoshiharu; Wagatsuma, Takanori; Michibuchi, Michiko; Kinoshita, Sachiko; Sakai, Keiko; Konya, Chizuko; Sugama, Junko; Sanada, Hiromi

Early detection of extravasation is important, but conventional methods of detection lack objectivity and reliability. This study evaluated the predictive validity of thermography for identifying extravasation during intravenous antineoplastic therapy. Of 257 patients who received chemotherapy through peripheral veins, extravasation was identified in 26. Thermography was performed every 15 to 30 minutes during the infusions. Sensitivity, specificity, positive predictive value, and negative predictive value using thermography were 84.6%, 94.8%, 64.7%, and 98.2%, respectively. This study showed that thermography offers an accurate prediction of extravasation.

Evaluation of the Predictive Validity of Thermography in Identifying Extravasation With Intravenous Chemotherapy Infusions

PubMed Central

Murayama, Ryoko; Tanabe, Hidenori; Oe, Makoto; Motoo, Yoshiharu; Wagatsuma, Takanori; Michibuchi, Michiko; Kinoshita, Sachiko; Sakai, Keiko; Konya, Chizuko; Sugama, Junko; Sanada, Hiromi

2017-01-01

Early detection of extravasation is important, but conventional methods of detection lack objectivity and reliability. This study evaluated the predictive validity of thermography for identifying extravasation during intravenous antineoplastic therapy. Of 257 patients who received chemotherapy through peripheral veins, extravasation was identified in 26. Thermography was performed every 15 to 30 minutes during the infusions. Sensitivity, specificity, positive predictive value, and negative predictive value using thermography were 84.6%, 94.8%, 64.7%, and 98.2%, respectively. This study showed that thermography offers an accurate prediction of extravasation. PMID:29112585

Factors predicting survival in amyotrophic lateral sclerosis patients on non-invasive ventilation.

PubMed

Gonzalez Calzada, Nuria; Prats Soro, Enric; Mateu Gomez, Lluis; Giro Bulta, Esther; Cordoba Izquierdo, Ana; Povedano Panades, Monica; Dorca Sargatal, Jordi; Farrero Muñoz, Eva

2016-01-01

Non invasive ventilation (NIV) improves quality of life and extends survival in amyotrophic lateral sclerosis (ALS) patients. However, few data exist about the factors related to survival. We intended to assess the predictive factors that influence survival in patients after NIV initiation. Patients who started NIV from 2000 to 2014 and were tolerant (compliance ≥ 4 hours) were included; demographic, disease related and respiratory variables at NIV initiation were analysed. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. 213 patients were included with median survival from NIV initiation of 13.5 months. In univariate analysis, the identified risk factors for mortality were severity of bulbar involvement (HR 2), Forced Vital Capacity (FVC) % (HR 0.99) and ALSFRS-R (HR 0.97). Multivariate analysis showed that bulbar involvement (HR 1.92) and ALSFRS-R (HR 0.97) were independent predictive factors of survival in patients on NIV. In our study, the two prognostic factors in ALS patients following NIV were the severity of bulbar involvement and ALSFRS-R at the time on NIV initiation. A better assessment of bulbar involvement, including evaluation of the upper airway, and a careful titration on NIV are necessary to optimize treatment efficacy.

Epigenetic priors for identifying active transcription factor binding sites.

PubMed

Cuellar-Partida, Gabriel; Buske, Fabian A; McLeay, Robert C; Whitington, Tom; Noble, William Stafford; Bailey, Timothy L

2012-01-01

Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcriptional regulation. Using epigenetic data such as histone modification and DNase I, accessibility data has been shown to improve motif-based in silico methods for predicting such binding, but this approach has not yet been fully explored. We describe a probabilistic method for combining one or more tracks of epigenetic data with a standard DNA sequence motif model to improve our ability to identify active transcription factor binding sites (TFBSs). We convert each data type into a position-specific probabilistic prior and combine these priors with a traditional probabilistic motif model to compute a log-posterior odds score. Our experiments, using histone modifications H3K4me1, H3K4me3, H3K9ac and H3K27ac, as well as DNase I sensitivity, show conclusively that the log-posterior odds score consistently outperforms a simple binary filter based on the same data. We also show that our approach performs competitively with a more complex method, CENTIPEDE, and suggest that the relative simplicity of the log-posterior odds scoring method makes it an appealing and very general method for identifying functional TFBSs on the basis of DNA and epigenetic evidence. FIMO, part of the MEME Suite software toolkit, now supports log-posterior odds scoring using position-specific priors for motif search. A web server and source code are available at http://meme.nbcr.net. Utilities for creating priors are at http://research.imb.uq.edu.au/t.bailey/SD/Cuellar2011. t.bailey@uq.edu.au Supplementary data are available at Bioinformatics online.

Identifying Clinical Factors Which Predict for Early Failure Patterns Following Resection for Pancreatic Adenocarcinoma in Patients Who Received Adjuvant Chemotherapy Without Chemoradiation.

PubMed

Walston, Steve; Salloum, Joseph; Grieco, Carmine; Wuthrick, Evan; Diaz, Dayssy A; Barney, Christian; Manilchuk, Andrei; Schmidt, Carl; Dillhoff, Mary; Pawlik, Timothy M; Williams, Terence M

2018-05-04

The role of radiation therapy (RT) in resected pancreatic cancer (PC) remains incompletely defined. We sought to determine clinical variables which predict for local-regional recurrence (LRR) to help select patients for adjuvant RT. We identified 73 patients with PC who underwent resection and adjuvant gemcitabine-based chemotherapy alone. We performed detailed radiologic analysis of first patterns of failure. LRR was defined as recurrence of PC within standard postoperative radiation volumes. Univariate analyses (UVA) were conducted using the Kaplan-Meier method and multivariate analyses (MVA) utilized the Cox proportional hazard ratio model. Factors significant on UVA were used for MVA. At median follow-up of 20 months, rates of local-regional recurrence only (LRRO) were 24.7%, LRR as a component of any failure 68.5%, metastatic recurrence (MR) as a component of any failure 65.8%, and overall disease recurrence (OR) 90.5%. On UVA, elevated postoperative CA 19-9 (>90 U/mL), pathologic lymph node positive (pLN+) disease, and higher tumor grade were associated with increased LRR, MR, and OR. On MVA, elevated postoperative CA 19-9 and pLN+ were associated with increased MR and OR. In addition, positive resection margin was associated with increased LRRO on both UVA and MVA. About 25% of patients with PC treated without adjuvant RT develop LRRO as initial failure. The only independent predictor of LRRO was positive margin, while elevated postoperative CA 19-9 and pLN+ were associated with predicting MR and overall survival. These data may help determine which patients benefit from intensification of local therapy with radiation.

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

Predictive factors of clinical response in steroid-refractory ulcerative colitis treated with granulocyte-monocyte apheresis

PubMed Central

D'Ovidio, Valeria; Meo, Donatella; Viscido, Angelo; Bresci, Giampaolo; Vernia, Piero; Caprilli, Renzo

2011-01-01

AIM: To identify factors predicting the clinical response of ulcerative colitis patients to granulocyte-monocyte apheresis (GMA). METHODS: Sixty-nine ulcerative colitis patients (39 F, 30 M) dependent upon/refractory to steroids were treated with GMA. Steroid dependency, clinical activity index (CAI), C reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), values at baseline, use of immunosuppressant, duration of disease, and age and extent of disease were considered for statistical analysis as predictive factors of clinical response. Univariate and multivariate logistic regression models were used. RESULTS: In the univariate analysis, CAI (P = 0.039) and ESR (P = 0.017) levels at baseline were singled out as predictive of clinical remission. In the multivariate analysis steroid dependency [Odds ratio (OR) = 0.390, 95% Confidence interval (CI): 0.176-0.865, Wald 5.361, P = 0.0160] and low CAI levels at baseline (4 < CAI < 7) (OR = 0.770, 95% CI: 0.425-1.394, Wald 3.747, P = 0.028) proved to be effective as factors predicting clinical response. CONCLUSION: GMA may be a valid therapeutic option for steroid-dependent ulcerative colitis patients with mild-moderate disease and its clinical efficacy seems to persist for 12 mo. PMID:21528055

Identification of the Predictive Power of Five Factor Personality Traits for Individual Instrument Performance Anxiety

ERIC Educational Resources Information Center

Özdemir, Gökhan; Dalkiran, Esra

2017-01-01

This study, with the aim of identifying the predictive power of the five-factor personality traits of music teacher candidates on individual instrument performance anxiety, was designed according to the relational screening model. The study population was students attending the Music Education branch of Fine Arts Education Departments in…

Predicting Factors of Chronic Subdural Hematoma Following Surgical Clipping in Unruptured and Ruptured Intracranial Aneurysm

PubMed Central

Kwon, Min-Yong; Kim, Chang-Hyun

2016-01-01

Objective The aim of this study is to analyze the differences in the incidence, predicting factors, and clinical course of chronic subdural hematoma (CSDH) following surgical clipping between unruptured (UIA) and ruptured intracranial aneurysm (RIA). Methods We conducted a retrospective analysis of 752 patients (UIA : 368 and RIA : 384) who underwent surgical clipping during 8 years. The incidence and predicting factors of CSDH development in the UIA and RIA were compared according to medical records and radiological data. Results The incidence of postoperative CSDH was higher in the UIA (10.9%) than in the RIA (3.1%) (p=0.000). In multivariate analysis, a high Hounsfield (HF) unit (blood clots) for subdural fluid collection (SFC), persistence of SFC ≥5 mm and male sex in the UIA and A high HF unit for SFC and SFC ≥5 mm without progression to hydrocephalus in the RIA were identified as the independent predicting factors for CSDH development (p<0.05). Conclusion There were differences in the incidence and predicting factors for CSDH following surgical clipping between UIA and RIA. Blood clots in the subdural space and persistence of SFC ≥5 mm were predicting factors in both UIA and RIA. However, progression to hydrocephalus may have in part contributed to low CSDH development in the RIA. We suggest that cleaning of blood clots in the subdural space and efforts to minimize SFC ≥5 mm at the end of surgery is helpful to prevent CSDH following aneurysmal clipping. PMID:27651863

Patterns of Functioning and Predictive Factors in Children Born Moderately Preterm or at Term

ERIC Educational Resources Information Center

Cserjesi, Renata; van Braeckel, Koenraad N. J. A.; Timmerman, Marieke; Butcher, Phillipa R.; Kerstjens, Jorien M.; Reijneveld, Sijmen A.; Bouma, Anke; Bos, Arend F.; Geuze, Reint H.

2012-01-01

Aim: The aim of this study was to identify subgroups of children born moderately preterm (MPT) and term with distinctive levels and patterns of functioning, and the perinatal and demographic factors that predict subgroup membership. Method: A total of 378 children aged 7 years, 248 MPT (138 males, 110 females; gestational age 32-36 wks) and a…

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

PubMed

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Can Childhood Factors Predict Workplace Deviance?

PubMed Central

Piquero, Nicole Leeper; Moffitt, Terrie E.

2013-01-01

Compared to the more common focus on street crime, empirical research on workplace deviance has been hampered by highly select samples, cross-sectional research designs, and limited inclusion of relevant predictor variables that bear on important theoretical debates. A key debate concerns the extent to which childhood conduct-problem trajectories influence crime over the life-course, including adults’ workplace crime, whether childhood low self-control is a more important determinant than trajectories, and/or whether each or both of these childhood factors relate to later criminal activity. This paper provides evidence on this debate by examining two types of workplace deviance: production and property deviance separately for males and females. We use data from the Dunedin Multidisciplinary Health and Development Study, a birth cohort followed into adulthood, to examine how childhood factors (conduct-problem trajectories and low self-control) and then adult job characteristics predict workplace deviance at age 32. Analyses revealed that none of the childhood factors matter for predicting female deviance in the workplace but that conduct-problem trajectories did account for male workplace deviance. PMID:24882937

Temporal effects in trend prediction: identifying the most popular nodes in the future.

PubMed

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail.

Temporal Effects in Trend Prediction: Identifying the Most Popular Nodes in the Future

PubMed Central

Zhou, Yanbo; Zeng, An; Wang, Wei-Hong

2015-01-01

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes’ recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail. PMID:25806810

Predictive factors for bleeding during treatment with rivaroxaban and warfarin in Japanese patients with atrial fibrillation - Subgroup analysis of J-ROCKET AF.

PubMed

Hori, Masatsugu; Matsumoto, Masayasu; Tanahashi, Norio; Momomura, Shin-Ichi; Uchiyama, Shinichiro; Goto, Shinya; Izumi, Tohru; Koretsune, Yukihiro; Kajikawa, Mariko; Kato, Masaharu; Cavaliere, Mary; Iekushi, Kazuma; Yamanaka, Satoshi

2016-12-01

Results from the J-ROCKET AF study revealed that rivaroxaban was non-inferior to warfarin with respect to the principal safety outcomes in patients with non-valvular atrial fibrillation. This subgroup analysis evaluated whether non-major clinically relevant bleeding (NMCRB) could be a predictive factor for major bleeding (MB). Other predictive factors for MB were also obtained in both rivaroxaban and warfarin treatment groups. The temporal incidence of MB was compared between the rivaroxaban and warfarin treatment groups. Assessment was made whether MB events were often preceded by NMCRB. Univariate and multivariate analyses were carried out to identify any independent predictive factors for MB in both treatment groups. The incidences of MB and NMCRB were 18.04% (138/639 patients) in the rivaroxaban arm, and 16.42% in the warfarin arm (124/639 patients). NMCRB preceded MB in only four patients in each treatment group (rivaroxaban: 4/117 and warfarin: 4/98). Multivariate analysis identified predictive factors for bleeding events: anemia with warfarin treatment and concomitant use of antiplatelet agents with rivaroxaban treatment. Results from this subgroup analysis, particularly the fact that there was no repeated or sequential pattern between NMCRB and MB occurrences in both treatment groups, suggests that NMCRB might not be a predictive factor for MB. On the contrary, anemia and concomitant use of antiplatelet therapy were likely predictive factors for bleeding with warfarin and rivaroxaban treatment, respectively. Copyright © 2016 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Can theory predict the process of suicide on entry to prison? Predicting dynamic risk factors for suicide ideation in a high-risk prison population.

PubMed

Slade, Karen; Edelman, Robert

2014-01-01

Each year approximately 110,000 people are imprisoned in England and Wales and new prisoners remain one of the highest risk groups for suicide across the world. The reduction of suicide in prisoners remains difficult as assessments and interventions tend to rely on static risk factors with few theoretical or integrated models yet evaluated. To identify the dynamic factors that contribute to suicide ideation in this population based on Williams and Pollock's (2001) Cry of Pain (CoP) model. New arrivals (N = 198) into prison were asked to complete measures derived from the CoP model plus clinical and prison-specific factors. It was hypothesized that the factors of the CoP model would be predictive of suicide ideation. Support was provided for the defeat and entrapment aspects of the CoP model with previous self-harm, repeated times in prison, and suicide-permissive cognitions also key in predicting suicide ideation for prisoners on entry to prison. An integrated and dynamic model was developed that has utility in predicting suicide in early-stage prisoners. Implications for both theory and practice are discussed along with recommendations for future research.

Factors influencing speech and language outcomes of children with early identified severe/profound hearing loss: Clinician-identified facilitators and barriers.

PubMed

Fulcher, Anne Nivelles; Purcell, Alison; Baker, Elise; Munro, Natalie

2015-06-01

Early identification of severe/profound childhood hearing loss (HL) gives these children access to hearing devices and early intervention to facilitate improved speech and language outcomes. Predicting which infants will go on to achieve such outcomes remains difficult. This study describes clinician identified malleable and non-malleable factors that may influence speech and language outcomes for children with severe/profound HL. Semi-structured interviews were conducted with six experienced auditory verbal clinicians. A collective case study design was implemented. The interviews were transcribed and coded into themes using constant comparative analysis. Clinicians identified that, for children with severe/profound HL, early identification, early amplification and commencing auditory-verbal intervention under 6 months of age may facilitate child progress. Possible barriers were living in rural/remote areas, the clinicians' lack of experience and confidence in providing intervention for infants under age 6-months and belonging to a family with a culturally and linguistically diverse (CALD) background. The results indicate that multiple factors need to be considered by clinicians working with children with HL and their families to determine how each child functions within their own environment and personal contexts, consistent with the International Classification of Functioning, Disability and Health (ICF) framework. Such an approach is likely to empower clinicians to carefully balance potential barriers to, and facilitators of, optimal speech and language outcomes for all children with HL.

Perceived participation and autonomy: aspects of functioning and contextual factors predicting participation after stroke.

PubMed

Fallahpour, Mandana; Tham, Kerstin; Joghataei, Mohammad Taghi; Jonsson, Hans

2011-04-01

To describe perceived participation and autonomy among a sample of persons with stroke in Iran and to identify different aspects of functioning and contextual factors predicting participation after stroke. A cross-sectional study. A total of 102 persons, between 27 and 75 years of age, diagnosed with first-ever stroke. Participants were assessed for different aspects of functioning, contextual factors and health conditions. Participation was assessed using the Persian version of the Impact on Participation and Autonomy questionnaire. This study demonstrated that the majority of the study population perceived their participation and autonomy to be good to fair in the different domains of their participation, but not with respect to the autonomy outdoors domain. In addition, physical function was found to be the most important variable predicting performance-based participation, whereas mood state was the most important variable predicting social-based participation. The results emphasize the importance of physical function, mood state and access to caregiving services as predictors of participation in everyday life after stroke. Whilst there are two dimensions of participation in this Persian sample of persons with stroke, the factors explaining participation seem to be the same across the cultures.

Clinicopathological factors predictive of postoperative seizures in patients with gliomas.

PubMed

Yang, Pei; Liang, Tingyu; Zhang, Chuanbao; Cai, Jinquan; Zhang, Wei; Chen, Baoshi; Qiu, Xiaoguang; Yao, Kun; Li, Guilin; Wang, Haoyuan; Jiang, Chuanlu; You, Gan; Jiang, Tao

2016-02-01

Epilepsy is one of the most common manifestations in gliomas and has a severe effect on the life expectancy and quality of life of patients. The aim of our study was to assess the potential connections between clinicopathological factors and postoperative seizure. We retrospectively investigated a group of 147 Chinese high-grade glioma (HGG) patients with preoperative seizure to examine the correlation between postoperative seizure and clinicopathological factors and prognosis. Univariate analyses and multivariate logistic regression analyses were performed to identify factors associated with postoperative seizures. Survival function curves were calculated using the Kaplan-Meier method. 53 patients (36%) were completely seizure-free (Engel class I), and 94 (64%) experienced a postoperative seizure (Engel classes II, III, and IV). A Chi-squared analysis showed that anaplastic oligodendroglioma/anaplastic oligoastrocytoma (AO/AOA) (P=0.05), epidermal growth factor receptor (EGFR) expression (P=0.0004), O(6)-methylguanine DNA methyltransferase (MGMT) expression (P=0.011), and phosphatase and tensin homolog (PTEN) expression (P=0.045) were all significantly different. A logistic regression analysis showed that MGMT expression (P=0.05), EGFR expression (P=0.001), and AO/AOA (P=0.038) are independent factors of postoperative seizure. Patients with lower MGMT and EGFR expression and AO/AOA showed more frequent instances of postoperative seizure. Postoperative seizure showed no statistical significance on overall survival (OS) and progression-free survival (PFS). Our study identified clinicopathological factors related to postoperative seizure in HGGs and found two predictive biomarkers of postoperative seizure: MGMT and EGFR. These findings provided insight treatment strategies aimed at prolonging survival and improving quality of life. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Predictive Factors of Headache Resolution After Chiari Type 1 Malformation Surgery.

PubMed

Grangeon, Lou; Puy, Laurent; Gilard, Vianney; Hebant, Benjamin; Langlois, Olivier; Derrey, Stephane; Gerardin, Emmanuel; Maltete, David; Guegan-Massardier, Evelyne; Magne, Nicolas

2018-02-01

Headache is the main and often isolated symptom of patients with Chiari type 1 malformation (CM1). Classically described as occipital and exacerbated by cough, headaches may be poorly characterized, making it difficult to establish CM1 as the underlying cause. Current guidelines for surgical posterior fossa decompression are undefined. The challenge is to distinguish headaches related to CM1 from headaches coincidentally coexisting with CM1. We aimed to determine predictive factors of headache resolution after surgery and applied to our cohort the Chiari Severity Index, a recently developed predictive prognostic score. This retrospective study enrolled 49 patients with CM1 and preoperative headache. Standardized telephone interviews regarding headaches before and after surgery were conducted by the same neurologist; magnetic resonance imaging morphometric analyses were performed by an independent neuroradiologist. Headache resolution was defined as ≥50% reduction in frequency of headache days. Preoperative factors of headache resolution after multivariate analysis were attack duration <5 minutes (P = 0.001), triggering by Valsalva maneuvers (P = 0.003), severe intensity of attack (P = 0.05), occipital location (P = 0.05), and greater number of headache days per month (P = 0.04). These characteristics are part of International Headache Society diagnostic criteria for headache attributed to CM1. No radiologic predictive factor was demonstrated. Postoperative improvement was inversely correlated with Chiari Severity Index. This study confirms the relevance of International Headache Society criteria to identify headaches related to CM1. We propose their systematic use in a preoperative questionnaire. Copyright © 2017 Elsevier Inc. All rights reserved.

Family Factors Predicting Categories of Suicide Risk

ERIC Educational Resources Information Center

Randell, Brooke P.; Wang, Wen-Ling; Herting, Jerald R.; Eggert, Leona L.

2006-01-01

We compared family risk and protective factors among potential high school dropouts with and without suicide-risk behaviors (SRB) and examined the extent to which these factors predict categories of SRB. Subjects were randomly selected from among potential dropouts in 14 high schools. Based upon suicide-risk status, 1,083 potential high school…

Identifying risk profiles for childhood obesity using recursive partitioning based on individual, familial, and neighborhood environment factors.

PubMed

Van Hulst, Andraea; Roy-Gagnon, Marie-Hélène; Gauvin, Lise; Kestens, Yan; Henderson, Mélanie; Barnett, Tracie A

2015-02-15

Few studies consider how risk factors within multiple levels of influence operate synergistically to determine childhood obesity. We used recursive partitioning analysis to identify unique combinations of individual, familial, and neighborhood factors that best predict obesity in children, and tested whether these predict 2-year changes in body mass index (BMI). Data were collected in 2005-2008 and in 2008-2011 for 512 Quebec youth (8-10 years at baseline) with a history of parental obesity (QUALITY study). CDC age- and sex-specific BMI percentiles were computed and children were considered obese if their BMI was ≥95th percentile. Individual (physical activity and sugar-sweetened beverage intake), familial (household socioeconomic status and measures of parental obesity including both BMI and waist circumference), and neighborhood (disadvantage, prestige, and presence of parks, convenience stores, and fast food restaurants) factors were examined. Recursive partitioning, a method that generates a classification tree predicting obesity based on combined exposure to a series of variables, was used. Associations between resulting varying risk group membership and BMI percentile at baseline and 2-year follow up were examined using linear regression. Recursive partitioning yielded 7 subgroups with a prevalence of obesity equal to 8%, 11%, 26%, 28%, 41%, 60%, and 63%, respectively. The 2 highest risk subgroups comprised i) children not meeting physical activity guidelines, with at least one BMI-defined obese parent and 2 abdominally obese parents, living in disadvantaged neighborhoods without parks and, ii) children with these characteristics, except with access to ≥1 park and with access to ≥1 convenience store. Group membership was strongly associated with BMI at baseline, but did not systematically predict change in BMI. Findings support the notion that obesity is predicted by multiple factors in different settings and provide some indications of potentially

Clinical Factors Predict Atezolizumab Response.

PubMed

2018-04-01

Researchers have presented a new model that uses six readily available clinical factors to predict whether a patient with advanced bladder cancer who has already received platinum chemotherapy will respond to treatment with the PD-L1 inhibitor atezolizumab. The results may help patients and their doctors decide how to proceed with treatment. ©2018 American Association for Cancer Research.

Predictive factors of thyroid cancer in patients with Graves' disease.

PubMed

Ren, Meng; Wu, Mu Chao; Shang, Chang Zhen; Wang, Xiao Yi; Zhang, Jing Lu; Cheng, Hua; Xu, Ming Tong; Yan, Li

2014-01-01

The best preoperative examination in Graves' disease with thyroid cancer still remains uncertain. The objectives of the present study were to investigate the prevalence of thyroid cancer in Graves' disease patients, and to identify the predictive factors and ultrasonographic features of thyroid cancer that may aid the preoperative diagnosis in Graves' disease. This retrospective study included 423 patients with Graves' disease who underwent surgical treatment from 2002 to 2012 at our institution. The clinical features and ultrasonographic findings of thyroid nodules were recorded. The diagnosis of thyroid cancer was determined according to the pathological results. Thyroid cancer was discovered in 58 of the 423 (13.7 %) surgically treated Graves' disease patients; 46 of those 58 patients had thyroid nodules, and the other 12 patients were diagnosed with incidentally discovered thyroid carcinomas without thyroid nodules. Among the 58 patients with thyroid cancer, papillary microcarcinomas were discovered in 50 patients, and multifocality and lymph node involvement were detected in the other 8 patients. Multivariate regression analysis showed younger age was the only significant factor predictive of metastatic thyroid cancer. Ultrasonographic findings of calcification and intranodular blood flow in thyroid nodules indicate that they are more likely to harbor thyroid cancers. Because the influencing factor of metastatic thyroid cancers in Graves' disease is young age, every suspicious nodule in Graves' disease patients should be evaluated and treated carefully, especially in younger patients because of the potential for metastasis.

Predictive factors of weight regain following laparoscopic Roux-en-Y gastric bypass.

PubMed

Keith, Charles J; Gullick, Allison A; Feng, Katey; Richman, Joshua; Stahl, Richard; Grams, Jayleen

2018-05-01

Strategies to address weight recidivism following Roux-en-Y gastric bypass (RYGB) could be developed if patients at risk were identified in advance. This study aimed to determine factors that predict weight regain. Retrospective review was performed of patients who underwent laparoscopic RYGB at a single institution over 10 years. Group-based modeling was used to estimate trajectories of weight regain after nadir and stratify patients based on percent weight change (%WC). Three trajectories were identified from 586 patients: 121 had ongoing weight loss, 343 were weight stable, and 122 regained weight. Male sex (p = 0.020) and white race (p < 0.001) were associated with stable weight or weight regain. Being from a neighborhood of socioeconomic advantage (p = 0.035) was associated with weight regain. Patients with weight regain experienced improved percent weight loss (%WL) at nadir (p < 0.001) and ΔBMI (p = 0.002), yet they had higher weight and BMI and lower %WL and ΔBMI than the other two groups during long-term follow-up. On multivariate analyses, those who regained weight were more likely from socioeconomically advantaged neighborhoods (OR 1.82, CI 1.18-2.79). Several patient-related characteristics predicted an increased likelihood of weight regain. Further studies are needed to elucidate how these factors contribute to weight recidivism following bariatric surgery.

Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: the PALMS study protocol.

PubMed

Jerosch-Herold, Christina; Shepstone, Lee; Wilson, Edward C F; Dyer, Tony; Blake, Julian

2014-02-07

Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions.

Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: the PALMS study protocol

PubMed Central

2014-01-01

Background Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. Methods/Design In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. Discussion This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions. PMID:24507749

[Predictive factors associated with severity of asthma exacerbations].

PubMed

Atiş, Sibel; Kaplan, Eylem Sercan; Ozge, Cengiz; Bayindir, Suzan

2008-01-01

Several factors have been accused for asthma exacerbations, however, very few studies have evaluated whether different factors predict severity of asthma exacerbation. We aimed to determine the predictive factors for severity of asthma exacerbation. Retrospective analysis of data on 93 patients visited our emergency-department because of asthma exacerbation was reviewed. Hospitalization in intensive care unit and/or intubation because of asthma was accepted as the criteria for severe exacerbation. Logistic regression analysis estimated the strength of association of each variable, potentially related to severe asthmatic exacerbation, with severe/very severe as compared to mild/moderate asthmatic exacerbation. Independent variables included in the analysis were age, sex, smoking history, inhaler steroid using, compliance with medication, chronic asthma severity, presence of additional atopic diseases, prick test positivity, provocative factors, number of short-acting beta(2)-agonist using, number of visits to emergency department for asthma over one year period, previous severe exacerbation, pulmonary functions, and blood eosinophil count. 20 were severe/very severe and 73 mild/moderate asthmatic exacerbation. Frequent using of short-acting beta(2)-agonist (OR= 1.5, 95% CI= 1.08-5.3, p= 0.003), noncompliance with medication (OR= 3.6, 95% CI= 1.3-9.9, p= 0.013), previous severe asthmatic exacerbation (OR= 3.8, 95% CI= 1.48-10.01, p= 0.005) and recent admission to hospital (OR= 2.9, 95% CI= 1.07-8.09, p= 0.037) were found to be predictive factors for severe asthmatic exacerbation. Different predictive factors, in particular frequent using of short-acting beta(2)-agonist and noncompliance with medication may be associated with severe asthma exacerbations compared to milder exacerbations. This suggests different mechanisms are responsible for severity of asthma exacerbation.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting

Predictive factors for cosmetic surgery: a hospital-based investigation.

PubMed

Li, Jun; Li, Qian; Zhou, Bei; Gao, Yanli; Ma, Jiehua; Li, Jingyun

2016-01-01

Cosmetic surgery is becoming increasingly popular in China. However, reports on the predictive factors for cosmetic surgery in Chinese individuals are scarce in the literature. We retrospectively analyzed 4550 cosmetic surgeries performed from January 2010 to December 2014 at a single center in China. Data collection included patient demographics and type of cosmetic surgery. Predictive factors were age, sex, marital status, occupational status, educational degree, and having had children. Predictive factors for the three major cosmetic surgeries were determined using a logistic regression analysis. Patients aged 19-34 years accounted for the most popular surgical procedures (76.9 %). The most commonly requested procedures were eye surgery, Botox injection, and nevus removal. Logistic regression analysis showed that higher education level (college, P = 0.01, OR 1.21) was predictive for eye surgery. Age (19-34 years, P = 0.00, OR 33.39; 35-50, P = 0.00, OR 31.34; ≥51, P = 0.00, OR 16.42), female sex (P = 0.00, OR 9.19), employment (service occupations, P = 0.00, OR 2.31; non-service occupations, P = 0.00, OR 1.76), and higher education level (college, P = 0.00, OR 1.39) were independent predictive factors for Botox injection. Married status (P = 0.00, OR 1.57), employment (non-service occupations, P = 0.00, OR 1.50), higher education level (masters, P = 0.00, OR 6.61), and having children (P = 0.00, OR 1.45) were independent predictive factors for nevus removal. The principal three cosmetic surgeries (eye surgery, Botox injection, and nevus removal) were associated with multiple variables. Patients employed in non-service occupations were more inclined to undergo Botox injection and nevus removal. Cohort study, Level III.

Risk factors for the treatment outcome of retreated pulmonary tuberculosis patients in China: an optimized prediction model.

PubMed

Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J

2017-07-01

Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.

Evaluation of an inpatient fall risk screening tool to identify the most critical fall risk factors in inpatients.

PubMed

Hou, Wen-Hsuan; Kang, Chun-Mei; Ho, Mu-Hsing; Kuo, Jessie Ming-Chuan; Chen, Hsiao-Lien; Chang, Wen-Yin

2017-03-01

To evaluate the accuracy of the inpatient fall risk screening tool and to identify the most critical fall risk factors in inpatients. Variations exist in several screening tools applied in acute care hospitals for examining risk factors for falls and identifying high-risk inpatients. Secondary data analysis. A subset of inpatient data for the period from June 2011-June 2014 was extracted from the nursing information system and adverse event reporting system of an 818-bed teaching medical centre in Taipei. Data were analysed using descriptive statistics, receiver operating characteristic curve analysis and logistic regression analysis. During the study period, 205 fallers and 37,232 nonfallers were identified. The results revealed that the inpatient fall risk screening tool (cut-off point of ≥3) had a low sensitivity level (60%), satisfactory specificity (87%), a positive predictive value of 2·0% and a negative predictive value of 99%. The receiver operating characteristic curve analysis revealed an area under the curve of 0·805 (sensitivity, 71·8%; specificity, 78%). To increase the sensitivity values, the Youden index suggests at least 1·5 points to be the most suitable cut-off point for the inpatient fall risk screening tool. Multivariate logistic regression analysis revealed a considerably increased fall risk in patients with impaired balance and impaired elimination. The fall risk factor was also significantly associated with days of hospital stay and with admission to surgical wards. The findings can raise awareness about the two most critical risk factors for falls among future clinical nurses and other healthcare professionals and thus facilitate the development of fall prevention interventions. This study highlights the needs for redefining the cut-off points of the inpatient fall risk screening tool to effectively identify inpatients at a high risk of falls. Furthermore, inpatients with impaired balance and impaired elimination should be closely

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Systematic Review: Predisposing, Precipitating, Perpetuating, and Present Factors Predicting Anticipatory Distress to Painful Medical Procedures in Children

PubMed Central

Pillai Riddell, Rebecca R.; Khan, Maria; Calic, Masa; Taddio, Anna; Tablon, Paula

2016-01-01

Objective To conduct a systematic review of the factors predicting anticipatory distress to painful medical procedures in children. Methods A systematic search was conducted to identify studies with factors related to anticipatory distress to painful medical procedures in children aged 0–18 years. The search retrieved 7,088 articles to review against inclusion criteria. A total of 77 studies were included in the review. Results 31 factors were found to predict anticipatory distress to painful medical procedures in children. A narrative synthesis of the evidence was conducted, and a summary figure is presented. Conclusions Many factors were elucidated that contribute to the occurrence of anticipatory distress to painful medical procedures. The factors that appear to increase anticipatory distress are child psychopathology, difficult child temperament, parent distress promoting behaviors, parent situational distress, previous pain events, parent anticipation of distress, and parent anxious predisposition. Longitudinal and experimental research is needed to further elucidate these factors. PMID:26338981

Factors Affecting Retention Behavior: A Model To Predict At-Risk Students. AIR 1997 Annual Forum Paper.

ERIC Educational Resources Information Center

Sadler, William E.; Cohen, Frederic L.; Kockesen, Levent

This paper describes a methodology used in an on-going retention study at New York University (NYU) to identify a series of easily measured factors affecting student departure decisions. Three logistic regression models for predicting student retention were developed, each containing data available at three distinct times during the first…

Vocal fold hemorrhage: factors predicting recurrence.

PubMed

Lennon, Christen J; Murry, Thomas; Sulica, Lucian

2014-01-01

Vocal fold hemorrhage is an acute phonotraumatic injury treated with voice rest; recurrence is a generally accepted indication for surgical intervention. This study aims to identify factors predictive of recurrence based on outcomes of a large clinical series. Retrospective cohort. Retrospective review of cases of vocal fold hemorrhage presenting to a university laryngology service. Demographic information was compiled. Videostroboscopic exams were evaluated for hemorrhage extent, presence of varix, mucosal lesion, and/or vocal fold paresis. Vocal fold hemorrhage recurrence was the main outcome measure. Follow-up telephone survey was used to complement clinical data. Forty-seven instances of vocal fold hemorrhage were evaluated (25M:22F; 32 professional voice users). Twelve of the 47 (26%) patients experienced recurrence. Only the presence of varix demonstrated significant association with recurrence (P = 0.0089) on multivariate logistic regression. Vocal fold hemorrhage recurred in approximately 26% of patients. Varix was a predictor of recurrence, with 48% of those with varix experiencing recurrence. Monitoring, behavioral management and/or surgical intervention may be indicated to treat patients with such characteristics. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

[Predictive factors of contamination in a blood culture with bacterial growth in an Emergency Department].

PubMed

Hernández-Bou, S; Trenchs Sainz de la Maza, V; Esquivel Ojeda, J N; Gené Giralt, A; Luaces Cubells, C

2015-06-01

The aim of this study is to identify predictive factors of bacterial contamination in positive blood cultures (BC) collected in an emergency department. A prospective, observational and analytical study was conducted on febrile children aged on to 36 months, who had no risk factors of bacterial infection, and had a BC collected in the Emergency Department between November 2011 and October 2013 in which bacterial growth was detected. The potential BC contamination predicting factors analysed were: maximum temperature, time to positivity, initial Gram stain result, white blood cell count, absolute neutrophil count, band count, and C-reactive protein (CRP). Bacteria grew in 169 BC. Thirty (17.8%) were finally considered true positives and 139 (82.2%) false positives. All potential BC contamination predicting factors analysed, except maximum temperature, showed significant differences between true positives and false positives. CRP value, time to positivity, and initial Gram stain result are the best predictors of false positives in BC. The positive predictive values of a CRP value≤30mg/L, BC time to positivity≥16h, and initial Gram stain suggestive of a contaminant in predicting a FP, are 95.1, 96.9 and 97.5%, respectively. When all 3 conditions are applied, their positive predictive value is 100%. Four (8.3%) patients with a false positive BC and discharged to home were revaluated in the Emergency Department. The majority of BC obtained in the Emergency Department that showed positive were finally considered false positives. Initial Gram stain, time to positivity, and CRP results are valuable diagnostic tests in distinguishing between true positives and false positives in BC. The early detection of false positives will allow minimising their negative consequences. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Sinusoidal obstruction syndrome (SOS) related to chemotherapy for colorectal liver metastases: factors predictive of severe SOS lesions and protective effect of bevacizumab.

PubMed

Hubert, Catherine; Sempoux, Christine; Humblet, Yves; van den Eynde, Marc; Zech, Francis; Leclercq, Isabelle; Gigot, Jean-François

2013-11-01

The most frequent presentation of chemotherapy-related toxicity in colorectal liver metastases (CRLM) is sinusoidal obstruction syndrome (SOS). The purpose of the present study was to identify preoperative factors predictive of SOS and to establish associations between type of chemotherapy and severity of SOS. A retrospective study was carried out in a tertiary academic referral hospital. Patients suffering from CRLM who had undergone resection of at least one liver segment were included. Grading of SOS on the non-tumoral liver parenchyma was accomplished according to the Rubbia-Brandt criteria. A total of 151 patients were enrolled and divided into four groups according to the severity of SOS (grades 0-3). Multivariate analysis identified oxaliplatin and 5-fluorouracil as chemotherapeutic agents responsible for severe SOS lesions (P < 0.001 and P = 0.005, respectively). Bevacizumab was identified as having a protective effect against the occurrence of SOS lesions (P = 0.005). Univariate analysis identified the score on the aspartate aminotransferase : platelets ratio index (APRI) as the most significant biological factor predictive of severe SOS lesions. Splenomegaly is also significantly associated with the occurrence of severe SOS lesions. The APRI score and splenomegaly are effective as factors predictive of SOS. Bevacizumab has a protective effect against SOS. © 2013 International Hepato-Pancreato-Biliary Association.

Subarachnoid hemorrhage admissions retrospectively identified using a prediction model

PubMed Central

McIntyre, Lauralyn; Fergusson, Dean; Turgeon, Alexis; dos Santos, Marlise P.; Lum, Cheemun; Chassé, Michaël; Sinclair, John; Forster, Alan; van Walraven, Carl

2016-01-01

Objective: To create an accurate prediction model using variables collected in widely available health administrative data records to identify hospitalizations for primary subarachnoid hemorrhage (SAH). Methods: A previously established complete cohort of consecutive primary SAH patients was combined with a random sample of control hospitalizations. Chi-square recursive partitioning was used to derive and internally validate a model to predict the probability that a patient had primary SAH (due to aneurysm or arteriovenous malformation) using health administrative data. Results: A total of 10,322 hospitalizations with 631 having primary SAH (6.1%) were included in the study (5,122 derivation, 5,200 validation). In the validation patients, our recursive partitioning algorithm had a sensitivity of 96.5% (95% confidence interval [CI] 93.9–98.0), a specificity of 99.8% (95% CI 99.6–99.9), and a positive likelihood ratio of 483 (95% CI 254–879). In this population, patients meeting criteria for the algorithm had a probability of 45% of truly having primary SAH. Conclusions: Routinely collected health administrative data can be used to accurately identify hospitalized patients with a high probability of having a primary SAH. This algorithm may allow, upon validation, an easy and accurate method to create validated cohorts of primary SAH from either ruptured aneurysm or arteriovenous malformation. PMID:27629096

A Global Genomic and Genetic Strategy to Identify, Validate and Use Gene Signatures of Xenobiotic-Responsive Transcription Factors in Prediction of Pathway Activation in the Mouse Liver

EPA Science Inventory

Many drugs and environmentally-relevant chemicals activate xenobiotic-responsive transcription factors. Identification of target genes of these factors would be useful in predicting pathway activation in in vitro chemical screening as well as their involvement in disease states. ...

Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in Rheumatoid Arthritis.

PubMed

Nguyen, Minh Vu Chuong; Baillet, Athan; Romand, Xavier; Trocmé, Candice; Courtier, Anaïs; Marotte, Hubert; Thomas, Thierry; Soubrier, Martin; Miossec, Pierre; Tébib, Jacques; Grange, Laurent; Toussaint, Bertrand; Lequerré, Thierry; Vittecoq, Olivier; Gaudin, Philippe

2018-06-06

Tumour necrosis factor-alpha inhibitors (TNFi) are effective treatments for Rheumatoid Arthritis (RA). Responses to treatment are barely predictable. As these treatments are costly and may induce a number of side effects, we aimed at identifying a panel of protein biomarkers that could be used to predict clinical response to TNFi for RA patients. Baseline blood levels of C-reactive protein, platelet factor 4, apolipoprotein A1, prealbumin, α1-antitrypsin, haptoglobin, S100A8/A9 and S100A12 proteins in bDMARD naive patients at the time of TNFi treatment initiation were assessed in a multicentric prospective French cohort. Patients fulfilling good EULAR response at 6 months were considered as responders. Logistic regression was used to determine best biomarker set that could predict good clinical response to TNFi. A combination of biomarkers (prealbumin, platelet factor 4 and S100A12) was identified and could predict response to TNFi in RA with sensitivity of 78%, specificity of 77%, positive predictive values (PPV) of 72%, negative predictive values (NPV) of 82%, positive likelihood ratio (LR+) of 3.35 and negative likelihood ratio (LR-) of 0.28. Lower levels of prealbumin and S100A12 and higher level of platelet factor 4 than the determined cutoff at baseline in RA patients are good predictors for response to TNFi treatment globally as well as to Infliximab, Etanercept and Adalimumab individually. A multivariate model combining 3 biomarkers (prealbumin, platelet factor 4 and S100A12) accurately predicted response of RA patients to TNFi and has potential in a daily practice personalized treatment. Copyright © 2018. Published by Elsevier Masson SAS.

Predictive factors of mortality within 30 days in patients with nonvariceal upper gastrointestinal bleeding.

PubMed

Lee, Yoo Jin; Min, Bo Ram; Kim, Eun Soo; Park, Kyung Sik; Cho, Kwang Bum; Jang, Byoung Kuk; Chung, Woo Jin; Hwang, Jae Seok; Jeon, Seong Woo

2016-01-01

Nonvariceal upper gastrointestinal bleeding (NVUGIB) is a common medical emergency that can be life threatening. This study evaluated predictive factors of 30-day mortality in patients with this condition. A prospective observational study was conducted at a single hospital between April 2010 and November 2012, and 336 patients with symptoms and signs of gastrointestinal bleeding were consecutively enrolled. Clinical characteristics and endoscopic findings were reviewed to identify potential factors associated with 30-day mortality. Overall, 184 patients were included in the study (men, 79.3%; mean age, 59.81 years), and 16 patients died within 30 days (8.7%). Multivariate analyses revealed that comorbidity of diabetes mellitus (DM) or metastatic malignancy, age ≥ 65 years, and hypotension (systolic pressure < 90 mmHg) during hospitalization were significant predictive factors of 30-day mortality. Comorbidity of DM or metastatic malignancy, age ≥ 65 years, and hemodynamic instability during hospitalization were predictors of 30-day mortality in patients with NVUGIB. These results will help guide the management of patients with this condition.

Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status.

PubMed

Hüsing, Anika; Canzian, Federico; Beckmann, Lars; Garcia-Closas, Montserrat; Diver, W Ryan; Thun, Michael J; Berg, Christine D; Hoover, Robert N; Ziegler, Regina G; Figueroa, Jonine D; Isaacs, Claudine; Olsen, Anja; Viallon, Vivian; Boeing, Heiner; Masala, Giovanna; Trichopoulos, Dimitrios; Peeters, Petra H M; Lund, Eiliv; Ardanaz, Eva; Khaw, Kay-Tee; Lenner, Per; Kolonel, Laurence N; Stram, Daniel O; Le Marchand, Loïc; McCarty, Catherine A; Buring, Julie E; Lee, I-Min; Zhang, Shumin; Lindström, Sara; Hankinson, Susan E; Riboli, Elio; Hunter, David J; Henderson, Brian E; Chanock, Stephen J; Haiman, Christopher A; Kraft, Peter; Kaaks, Rudolf

2012-09-01

There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.

Examining Factors Predicting Students' Digital Competence

ERIC Educational Resources Information Center

Hatlevik, Ove Edvard; Guðmundsdóttir, Gréta Björk; Loi, Massimo

2015-01-01

The purpose of this study was to examine factors predicting lower secondary school students' digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what…

Predictive and Prognostic Factors in Definition of Risk Groups in Endometrial Carcinoma

PubMed Central

Sorbe, Bengt

2012-01-01

Background. The aim was to evaluate predictive and prognostic factors in a large consecutive series of endometrial carcinomas and to discuss pre- and postoperative risk groups based on these factors. Material and Methods. In a consecutive series of 4,543 endometrial carcinomas predictive and prognostic factors were analyzed with regard to recurrence rate and survival. The patients were treated with primary surgery and adjuvant radiotherapy. Two preoperative and three postoperative risk groups were defined. DNA ploidy was included in the definitions. Eight predictive or prognostic factors were used in multivariate analyses. Results. The overall recurrence rate of the complete series was 11.4%. Median time to relapse was 19.7 months. In a multivariate logistic regression analysis, FIGO grade, myometrial infiltration, and DNA ploidy were independent and statistically predictive factors with regard to recurrence rate. The 5-year overall survival rate was 73%. Tumor stage was the single most important factor with FIGO grade on the second place. DNA ploidy was also a significant prognostic factor. In the preoperative risk group definitions three factors were used: histology, FIGO grade, and DNA ploidy. Conclusions. DNA ploidy was an important and significant predictive and prognostic factor and should be used both in preoperative and postoperative risk group definitions. PMID:23209924

What Factors Predict Differences in CLAST Performance among Community Colleges? Research Report No. 90-12R.

ERIC Educational Resources Information Center

Morris, Cathy; Belcher, Marcia J.

In 1990, a study was conducted at Florida's Miami-Dade Community College (MDCC) to identify institutional factors that predict pass rates on the College-Level Academic Skills Test (CLAST). Statewide results of the October 1989 administration of the CLAST were used for the study, including the scores of all students who indicated that they had…

Prediction of Mass Spectral Response Factors from Predicted Chemometric Data for Druglike Molecules

NASA Astrophysics Data System (ADS)

Cramer, Christopher J.; Johnson, Joshua L.; Kamel, Amin M.

2017-02-01

A method is developed for the prediction of mass spectral ion counts of drug-like molecules using in silico calculated chemometric data. Various chemometric data, including polar and molecular surface areas, aqueous solvation free energies, and gas-phase and aqueous proton affinities were computed, and a statistically significant relationship between measured mass spectral ion counts and the combination of aqueous proton affinity and total molecular surface area was identified. In particular, through multilinear regression of ion counts on predicted chemometric data, we find that log10(MS ion counts) = -4.824 + c 1•PA + c 2•SA, where PA is the aqueous proton affinity of the molecule computed at the SMD(aq)/M06-L/MIDI!//M06-L/MIDI! level of electronic structure theory, SA is the total surface area of the molecule in its conjugate base form, and c 1 and c 2 have values of -3.912 × 10-2 mol kcal-1 and 3.682 × 10-3 Å-2. On a 66-molecule training set, this regression exhibits a multiple R value of 0.791 with p values for the intercept, c 1, and c 2 of 1.4 × 10-3, 4.3 × 10-10, and 2.5 × 10-6, respectively. Application of this regression to an 11-molecule test set provides a good correlation of prediction with experiment ( R = 0.905) albeit with a systematic underestimation of about 0.2 log units. This method may prove useful for semiquantitative analysis of drug metabolites for which MS response factors or authentic standards are not readily available.

Predictive factors for intrauterine growth restriction.

PubMed

Albu, A R; Anca, A F; Horhoianu, V V; Horhoianu, I A

2014-06-15

Reduced fetal growth is seen in about 10% of the pregnancies but only a minority has a pathological background and is known as intrauterine growth restriction or fetal growth restriction (IUGR / FGR). Increased fetal and neonatal mortality and morbidity as well as adult pathologic conditions are often associated to IUGR. Risk factors for IUGR are easy to assess but have poor predictive value. For the diagnostic purpose, biochemical serum markers, ultrasound and Doppler study of uterine and spiral arteries, placental volume and vascularization, first trimester growth pattern are object of assessment today. Modern evaluations propose combined algorithms using these strategies, all with the goal of a better prediction of risk pregnancies.

Predictive Factors for Fatal Tick-Borne Spotted Fever in Brazil.

PubMed

de Oliveira, S V; Willemann, M C A; Gazeta, G S; Angerami, R N; Gurgel-Gonçalves, R

2017-11-01

In Brazil, two pathogenic Rickettsia species have been identified causing tick-borne spotted fever (SF). The aetiological agent Rickettsia rickettsii causes serious illness, particularly in the south-eastern region of the country. Moreover, the Rickettsia sp. strain Atlantic Rainforest cause milder clinical manifestations in south-eastern, south and north-east regions. This study has sought to analyse predictive factors for fatal SF. A case-control study was performed using disease notification records in Brazil. The cases included were individuals with laboratory confirmation and fatal progression of SF, while the controls included individuals with SF who were cured. A total of 386 cases and 415 controls were identified (1 : 1.1), and the cases and controls were similar in age. The factors identified as being protective against death were reported presence of ticks (odds ratio [OR], 0.60; 95% confidence interval [CI], 0.41-0.88), residing in urban areas (OR, 0.47, 95% CI, 0.31-0.74) and presenting lymphadenopathy (OR, 0.43; 95% CI, 0.23-0.82). Males exhibited a greater chance of death (OR, 1.57; 95% CI, 1.13-2.18), as did patients who were hospitalized (OR, 10.82; 95% CI, 6.38-18.35) and who presented hypotension or shock (OR, 10.80; 95% CI, 7.33-15.93), seizures (OR, 11.24; 95% CI, 6.49-19.45) and coma (OR of 15.16; 95% CI, 8.51-27.02). The study demonstrates the severity profile of the SF cases, defined either as the frequency of hospitalization (even in cases that were cured) or as the increased frequency of the clinical complications typically found in critical patients. Opportune clinical diagnosis, a careful evaluation of the epidemiological aspects of the disease and adequate care for patients are determining factors for reducing SF fatality rates. © 2017 Blackwell Verlag GmbH.

Predictive factors of functional capacity and real-world functioning in patients with schizophrenia.

PubMed

Menendez-Miranda, I; Garcia-Portilla, M P; Garcia-Alvarez, L; Arrojo, M; Sanchez, P; Sarramea, F; Gomar, J; Bobes-Bascaran, M T; Sierra, P; Saiz, P A; Bobes, J

2015-07-01

This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia. Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores. Functional capacity: scores on the PSP and PANSS-GP entered first and second at P<0.0001 and accounted for 21% of variance (R(2)=0.208, model df=2, F=15.724, P<0.0001). Real-world functioning: scores on the CGI-S (B=-5.406), PANSS-N (B=-0.657) and Sp-UPSA (B=0.230) entered first, second and third, and accounted for 51% of variance (model df=3, F=37.741, P<0.0001). In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Identified state-space prediction model for aero-optical wavefronts

NASA Astrophysics Data System (ADS)

Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

2013-07-01

A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Systematic Review: Predisposing, Precipitating, Perpetuating, and Present Factors Predicting Anticipatory Distress to Painful Medical Procedures in Children.

PubMed

Racine, Nicole M; Riddell, Rebecca R Pillai; Khan, Maria; Calic, Masa; Taddio, Anna; Tablon, Paula

2016-03-01

To conduct a systematic review of the factors predicting anticipatory distress to painful medical procedures in children. A systematic search was conducted to identify studies with factors related to anticipatory distress to painful medical procedures in children aged 0-18 years. The search retrieved 7,088 articles to review against inclusion criteria. A total of 77 studies were included in the review. 31 factors were found to predict anticipatory distress to painful medical procedures in children. A narrative synthesis of the evidence was conducted, and a summary figure is presented. Many factors were elucidated that contribute to the occurrence of anticipatory distress to painful medical procedures. The factors that appear to increase anticipatory distress are child psychopathology, difficult child temperament, parent distress promoting behaviors, parent situational distress, previous pain events, parent anticipation of distress, and parent anxious predisposition. Longitudinal and experimental research is needed to further elucidate these factors. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identifying critical success factors for designing selection processes into postgraduate specialty training: the case of UK general practice.

PubMed

Plint, Simon; Patterson, Fiona

2010-06-01

The UK national recruitment process into general practice training has been developed over several years, with incremental introduction of stages which have been piloted and validated. Previously independent processes, which encouraged multiple applications and produced inconsistent outcomes, have been replaced by a robust national process which has high reliability and predictive validity, and is perceived to be fair by candidates and allocates applicants equitably across the country. Best selection practice involves a job analysis which identifies required competencies, then designs reliable assessment methods to measure them, and over the long term ensures that the process has predictive validity against future performance. The general practitioner recruitment process introduced machine markable short listing assessments for the first time in the UK postgraduate recruitment context, and also adopted selection centre workplace simulations. The key success factors have been identified as corporate commitment to the goal of a national process, with gradual convergence maintaining locus of control rather than the imposition of change without perceived legitimate authority.

Predictive factors for intrauterine growth restriction

PubMed Central

Albu, AR; Anca, AF; Horhoianu, VV; Horhoianu, IA

2014-01-01

Abstract Reduced fetal growth is seen in about 10% of the pregnancies but only a minority has a pathological background and is known as intrauterine growth restriction or fetal growth restriction (IUGR / FGR). Increased fetal and neonatal mortality and morbidity as well as adult pathologic conditions are often associated to IUGR. Risk factors for IUGR are easy to assess but have poor predictive value. For the diagnostic purpose, biochemical serum markers, ultrasound and Doppler study of uterine and spiral arteries, placental volume and vascularization, first trimester growth pattern are object of assessment today. Modern evaluations propose combined algorithms using these strategies, all with the goal of a better prediction of risk pregnancies. Abbreviations: SGA = small for gestational age; IUGR = intrauterine growth restriction; FGR = fetal growth restriction; IUFD = intrauterine fetal demise; HIV = human immunodeficiency virus; PAPP-A = pregnancy associated plasmatic protein A; β-hCG = beta human chorionic gonadotropin; MoM = multiple of median; ADAM-12 = A-disintegrin and metalloprotease 12; PP-13 = placental protein 13; VEGF = vascular endothelial growth factor; PlGF = placental growth factor; sFlt-1 = soluble fms-like tyrosine kinase-1; UAD = uterine arteries Doppler ultrasound; RI = resistence index; PI = pulsatility index; VOCAL = Virtual Organ Computer–Aided Analysis software; VI = vascularization index; FI = flow index; VFI = vascularization flow index; PQ = placental quotient PMID:25408721

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

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

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

Using machine learning to identify factors that govern amorphization of irradiated pyrochlores

DOE PAGES

Pilania, Ghanshyam; Whittle, Karl R.; Jiang, Chao; ...

2017-02-10

Structure–property relationships are a key materials science concept that enables the design of new materials. In the case of materials for application in radiation environments, correlating radiation tolerance with fundamental structural features of a material enables materials discovery. Here, we use a machine learning model to examine the factors that govern amorphization resistance in the complex oxide pyrochlore (A 2B 2O 7) in a regime in which amorphization occurs as a consequence of defect accumulation. We examine the fidelity of predictions based on cation radii and electronegativities, the oxygen positional parameter, and the energetics of disordering and amorphizing the material.more » No one factor alone adequately predicts amorphization resistance. We find that when multiple families of pyrochlores (with different B cations) are considered, radii and electronegativities provide the best prediction, but when the machine learning model is restricted to only the B = Ti pyrochlores, the energetics of disordering and amorphization are critical factors. We discuss how these static quantities provide insight into an inherently kinetic property such as amorphization resistance at finite temperature. Lastly, this work provides new insight into the factors that govern the amorphization susceptibility and highlights the ability of machine learning approaches to generate that insight.« less

Prediction and Informative Risk Factor Selection of Bone Diseases.

PubMed

Li, Hui; Li, Xiaoyi; Ramanathan, Murali; Zhang, Aidong

2015-01-01

With the booming of healthcare industry and the overwhelming amount of electronic health records (EHRs) shared by healthcare institutions and practitioners, we take advantage of EHR data to develop an effective disease risk management model that not only models the progression of the disease, but also predicts the risk of the disease for early disease control or prevention. Existing models for answering these questions usually fall into two categories: the expert knowledge based model or the handcrafted feature set based model. To fully utilize the whole EHR data, we will build a framework to construct an integrated representation of features from all available risk factors in the EHR data and use these integrated features to effectively predict osteoporosis and bone fractures. We will also develop a framework for informative risk factor selection of bone diseases. A pair of models for two contrast cohorts (e.g., diseased patients versus non-diseased patients) will be established to discriminate their characteristics and find the most informative risk factors. Several empirical results on a real bone disease data set show that the proposed framework can successfully predict bone diseases and select informative risk factors that are beneficial and useful to guide clinical decisions.

Molecular factor computing for predictive spectroscopy.

PubMed

Dai, Bin; Urbas, Aaron; Douglas, Craig C; Lodder, Robert A

2007-08-01

The concept of molecular factor computing (MFC)-based predictive spectroscopy was demonstrated here with quantitative analysis of ethanol-in-water mixtures in a MFC-based prototype instrument. Molecular computing of vectors for transformation matrices enabled spectra to be represented in a desired coordinate system. New coordinate systems were selected to reduce the dimensionality of the spectral hyperspace and simplify the mechanical/electrical/computational construction of a new MFC spectrometer employing transmission MFC filters. A library search algorithm was developed to calculate the chemical constituents of the MFC filters. The prototype instrument was used to collect data from 39 ethanol-in-water mixtures (range 0-14%). For each sample, four different voltage outputs from the detector (forming two factor scores) were measured by using four different MFC filters. Twenty samples were used to calibrate the instrument and build a multivariate linear regression prediction model, and the remaining samples were used to validate the predictive ability of the model. In engineering simulations, four MFC filters gave an adequate calibration model (r2 = 0.995, RMSEC = 0.229%, RMSECV = 0.339%, p = 0.05 by f test). This result is slightly better than a corresponding PCR calibration model based on corrected transmission spectra (r2 = 0.993, RMSEC = 0.359%, RMSECV = 0.551%, p = 0.05 by f test). The first actual MFC prototype gave an RMSECV = 0.735%. MFC was a viable alternative to conventional spectrometry with the potential to be more simply implemented and more rapid and accurate.

Baseline factors predictive of patient satisfaction with sacral neuromodulation for idiopathic fecal incontinence.

PubMed

Duelund-Jakobsen, Jakob; van Wunnik, Bart; Buntzen, Steen; Lundby, Lilli; Laurberg, Søren; Baeten, Cor

2014-07-01

Sacral neuromodulation (SNM) is an established treatment for fecal incontinence (FI). A recent study from our group found that the relationship between patient satisfaction and clinical outcome is complex and does not match the traditional used success criteria. Therefore, the ability to predict patient satisfaction must be given priority. The aim of the present study is to identify baseline factors predictive of patient satisfaction, with SNM, for idiopathic FI. We analyzed data from patients treated with SNM for idiopathic FI in Aarhus, Denmark, and Maastricht, The Netherlands. A questionnaire considering self-reported satisfaction was mailed to these patients and compared to baseline characteristics. Logistic regression was used to determine the predictive value of baseline demographic and diagnostic variables. In total, 131 patients were included in the analysis. Patient satisfaction with the current treatment result was reported in 75 patients. Fifty-six patients were dissatisfied with SNM treatment, after median 46 months (range 11-122) with permanent implantation. Pudendal nerve terminal motor latency (PNTML) was the solely identified predictor for long-term patient satisfaction. A subgroup univariate-logistic regression analysis showed that PNTML ≤ 2.3 ms at the side of lead implantation was a statistically significant predictor for patient satisfaction (odds ratio (OR) 2.3, 95% confidence interval (CI) 1.01-5.24, p = 0.048). Baseline PNTML measurement may be predictive of long-term satisfaction with SNM therapy for idiopathic FI. Further studies are needed to confirm this result.

Molecular modelling of the Norrie disease protein predicts a cystine knot growth factor tertiary structure.

PubMed

Meitinger, T; Meindl, A; Bork, P; Rost, B; Sander, C; Haasemann, M; Murken, J

1993-12-01

The X-lined gene for Norrie disease, which is characterized by blindness, deafness and mental retardation has been cloned recently. This gene has been thought to code for a putative extracellular factor; its predicted amino acid sequence is homologous to the C-terminal domain of diverse extracellular proteins. Sequence pattern searches and three-dimensional modelling now suggest that the Norrie disease protein (NDP) has a tertiary structure similar to that of transforming growth factor beta (TGF beta). Our model identifies NDP as a member of an emerging family of growth factors containing a cystine knot motif, with direct implications for the physiological role of NDP. The model also sheds light on sequence related domains such as the C-terminal domain of mucins and of von Willebrand factor.

Predictive factors for somatization in a trauma sample

PubMed Central

2009-01-01

Background Unexplained somatic symptoms are common among trauma survivors. The relationship between trauma and somatization appears to be mediated by posttraumatic stress disorder (PTSD). However, only few studies have focused on what other psychological risk factors may predispose a trauma victim towards developing somatoform symptoms. Methods The present paper examines the predictive value of PTSD severity, dissociation, negative affectivity, depression, anxiety, and feeling incompetent on somatization in a Danish sample of 169 adult men and women who were affected by a series of explosions in a firework factory settled in a residential area. Results Negative affectivity and feelings of incompetence significantly predicted somatization, explaining 42% of the variance. PTSD was significant until negative affectivity was controlled for. Conclusion Negative affectivity and feelings of incompetence significantly predicted somatization in the trauma sample whereas dissociation, depression, and anxiety were not associated with degree of somatization. PTSD as a risk factor was mediated by negative affectivity. PMID:19126224

Factors predicting high estimated 10-year stroke risk: thai epidemiologic stroke study.

PubMed

Hanchaiphiboolkul, Suchat; Puthkhao, Pimchanok; Towanabut, Somchai; Tantirittisak, Tasanee; Wangphonphatthanasiri, Khwanrat; Termglinchan, Thanes; Nidhinandana, Samart; Suwanwela, Nijasri Charnnarong; Poungvarin, Niphon

2014-08-01

The purpose of the study was to determine the factors predicting high estimated 10-year stroke risk based on a risk score, and among the risk factors comprising the risk score, which factors had a greater impact on the estimated risk. Thai Epidemiologic Stroke study was a community-based cohort study, which recruited participants from the general population from 5 regions of Thailand. Cross-sectional baseline data of 16,611 participants aged 45-69 years who had no history of stroke were included in this analysis. Multiple logistic regression analysis was used to identify the predictors of high estimated 10-year stroke risk based on the risk score of the Japan Public Health Center Study, which estimated the projected 10-year risk of incident stroke. Educational level, low personal income, occupation, geographic area, alcohol consumption, and hypercholesterolemia were significantly associated with high estimated 10-year stroke risk. Among these factors, unemployed/house work class had the highest odds ratio (OR, 3.75; 95% confidence interval [CI], 2.47-5.69) followed by illiterate class (OR, 2.30; 95% CI, 1.44-3.66). Among risk factors comprising the risk score, the greatest impact as a stroke risk factor corresponded to age, followed by male sex, diabetes mellitus, systolic blood pressure, and current smoking. Socioeconomic status, in particular, unemployed/house work and illiterate class, might be good proxy to identify the individuals at higher risk of stroke. The most powerful risk factors were older age, male sex, diabetes mellitus, systolic blood pressure, and current smoking. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Identifying influential factors of business process performance using dependency analysis

NASA Astrophysics Data System (ADS)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

[Doppler ultrasonography of the renal artery: Guidelines and predictive factors for the presence of a tight stenosis. Retrospective analysis of 450 consecutive examinations].

PubMed

Dejerome, C; Grange, C; De Laforcade, L; Bonin, O; Laville, M; Lermusiaux, P; Long, A

2018-05-01

Duplex ultrasonography screening for renal artery stenosis has been the object of guidelines published by four societies designed to optimize the cost-effectiveness of the examination. To determine how well guideline indications for ultrasonography matched with requests and results in our university hospital; to determine whether compliance with guidelines was predictive of renal artery stenosis; to identify guidelines predictive of presence of stenosis; and to determine whether other predictive factors can be recognized. Requests and results of 450 Duplex ultrasonography examinations of the renal arteries performed from January 1st 2014 to December 31st 2015 were compared with published guidelines. At least one guideline indication was identified for 212 of the 450 examinations performed (47.1%). Among these examinations, renal artery stenosis≥70% was identified in 18 patients (8.0%). No case of stenosis was identified during examinations performed outside guideline indications. Factors predictive of stenosis were: compliance with guidelines (OR=21.86 [2.88; 165.8]). Predictive guidelines were: resistant hypertension in spite of appropriate treatment (OR=3.85, [1.44; 10.33], P=0.011), accelerated hypertension (OR=7.30, [1.40; 37.99], P=0.049), sudden unexplained pulmonary edema (OR=7.30, [1.40; 37.99], P=0.049), unexplained renal insufficiency (OR=3.58, [1.37; 9.37], P=0.011), unexplained renal hypotrophy (OR=16.69, [4.38; 63.69], P<0.001), renal asymmetry (OR=4.32, [1.45; 12.85], P<0.016). No other factor was predictive of renal stenosis. These examinations had therapeutic consequences in only 50% of patients. This study confirms the relevance of published guidelines. The diagnostic-effectiveness of Duplex ultrasonography examinations to search for renal artery stenosis depends upon compliance with these guidelines. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Factors Predicting Ethiopian Anesthetists' Intention to Leave Their Job.

PubMed

Kols, Adrienne; Kibwana, Sharon; Molla, Yohannes; Ayalew, Firew; Teshome, Mihereteab; van Roosmalen, Jos; Stekelenburg, Jelle

2018-05-01

Ethiopia has rapidly expanded training programs for associate clinician anesthetists in order to address shortages of anesthesia providers. However, retaining them in the public health sector has proven challenging. This study aimed to determine anesthetists' intentions to leave their jobs and identify factors that predict turnover intentions. A nationally representative, cross-sectional survey of 251 anesthetists working in public-sector hospitals in Ethiopia was conducted in 2014. Respondents were asked whether they planned to leave the job in the next year and what factors they considered important when making decisions to quit. Bivariate and multivariable logistic regressions were conducted to investigate 16 potential predictors of turnover intentions, including personal and facility characteristics as well as decision-making factors. Almost half (n = 120; 47.8%) of anesthetists planned to leave their jobs in the next year, and turnover intentions peaked among those with 2-5 years of experience. Turnover intentions were not associated with the compulsory service obligation. Anesthetists rated salary and opportunities for professional development as the most important factors in decisions to quit. Five predictors of turnover intentions were significant in the multivariable model: younger age, working at a district rather than regional or referral hospital, the perceived importance of living conditions, opportunities for professional development, and conditions at the workplace. Human resources strategies focused on improving living conditions for anesthetists and expanding professional development opportunities may increase retention. Special attention should be focused on younger anesthetists and those posted at district hospitals.

Predicting missing links and identifying spurious links via likelihood analysis

NASA Astrophysics Data System (ADS)

Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

2016-03-01

Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network’s probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms.

Predicting missing links and identifying spurious links via likelihood analysis

PubMed Central

Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

2016-01-01

Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network’s probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms. PMID:26961965

PAMPA--critical factors for better predictions of absorption.

PubMed

Avdeef, Alex; Bendels, Stefanie; Di, Li; Faller, Bernard; Kansy, Manfred; Sugano, Kiyohiko; Yamauchi, Yukinori

2007-11-01

PAMPA, log P(OCT), and Caco-2 are useful tools in drug discovery for the prediction of oral absorption, brain penetration and for the development of structure-permeability relationships. Each approach has its advantages and limitations. Selection criteria for methods are based on many different factors: predictability, throughput, cost and personal preferences (people factor). The PAMPA concerns raised by Galinis-Luciani et al. (Galinis-Luciani et al., 2007, J Pharm Sci, this issue) are answered by experienced PAMPA practitioners, inventors and developers from diverse research organizations. Guidelines on how to use PAMPA are discussed. PAMPA and PAMPA-BBB have much better predictivity for oral absorption and brain penetration than log P(OCT) for real-world drug discovery compounds. PAMPA and Caco-2 have similar predictivity for passive oral absorption. However, it is not advisable to use PAMPA to predict absorption involving transporter-mediated processes, such as active uptake or efflux. Measurement of PAMPA is much more rapid and cost effective than Caco-2 and log P(OCT). PAMPA assay conditions are critical in order to generate high quality and relevant data, including permeation time, assay pH, stirring, use of cosolvents and selection of detection techniques. The success of using PAMPA in drug discovery depends on careful data interpretation, use of optimal assay conditions, implementation and integration strategies, and education of users. Copyright 2007 Wiley-Liss, Inc.

[Predictive factors of virological response in chronically HCV infected].

PubMed

Lapiński, Tadeusz Wojciech; Flisiak, Robert

2012-09-01

Research on new antivirals drugs applied in the treatment of chronically HCV infected indicate that even the most perfect therapeutic molecules do not guarantee 100% efficacy. Since the beginning of the history of HCV infection treatment clinicians looked for predictors of treatment efficacy. Numerous studies confirm the high probability of cure in patients who cleared HCVinfectional 4 and 12 weeks of therapy. However despite of viral factors, recent research demonstrated predictive role of some host dependent factors. The most important role seems to play genetic factors including polymorphism rs12979860, as well as chemokins including first of all CXCL10 (IP-10). Very interesting seems to be also results of studies on association between vitamine D concentration and treatment efficacy. However in the future the most important predictive factor remain probably early on-treatment viral response.

[Predictive factors of complications during CT-guided transthoracic biopsy].

PubMed

Fontaine-Delaruelle, C; Souquet, P-J; Gamondes, D; Pradat, E; de Leusse, A; Ferretti, G R; Couraud, S

2017-04-01

CT-guided transthoracic core-needle biopsy (TTNB) is frequently used for the diagnosis of lung nodules. The aim of this study is to describe TTNBs' complications and to investigate predictive factors of complications. All consecutive TTNBs performed in three centers between 2006 and 2012 were included. Binary logistic regression was used for multivariate analysis. Overall, 970 TTNBs were performed in 929 patients. The complication rate was 34% (life-threatening complication in 6%). The most frequent complications were pneumothorax (29% included 4% which required chest-tube) and hemoptysis (5%). The mortality rate was 0.1% (n=1). In multivariate analysis, predictive factor for a complication was small target size (AOR=0.984; 95% CI [0.976-0.992]; P<0.001). This predictive factor was also found for occurrence of life-threatening complication (AOR=0.982; [0.965-0.999]; P=0.037), of pneumothorax (AOR=0.987; [0.978-0.995]; P=0.002) and of hemoptysis (AOR=0.973; [0.951-0.997]; P=0.024). One complication occurred in one-third of TTNBs. The proportion of life-threatening complication was 6%. A small lesion size was predictive of complication occurrence. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Early Recurrence After Hepatectomy for Colorectal Liver Metastases: What Optimal Definition and What Predictive Factors?

PubMed Central

Imai, Katsunori; Allard, Marc-Antoine; Benitez, Carlos Castro; Vibert, Eric; Sa Cunha, Antonio; Cherqui, Daniel; Castaing, Denis; Bismuth, Henri; Baba, Hideo

2016-01-01

Background. The purpose of this study was to determine the optimal definition and elucidate the predictive factors of early recurrence after surgery for colorectal liver metastases (CRLM). Methods. Among 987 patients who underwent curative surgery for CRLM from 1990 to 2012, 846 with a minimum follow-up period of 24 months were eligible for this study. The minimum p value approach of survival after initial recurrence was used to determine the optimal cutoff for the definition of early recurrence. The predictive factors of early recurrence and prognostic factors of survival were analyzed. Results. For 667 patients (79%) who developed recurrence, the optimal cutoff point of early recurrence was determined to be 8 months after surgery. The impact of early recurrence on survival was demonstrated mainly in patients who received preoperative chemotherapy. Among the 691 patients who received preoperative chemotherapy, recurrence was observed in 562 (81%), and survival in patients with early recurrence was significantly worse than in those with late recurrence (5-year survival 18.5% vs. 53.4%, p < .0001). Multivariate logistic analysis identified age ≤57 years (p = .0022), >1 chemotherapy line (p = .03), disease progression during last-line chemotherapy (p = .024), >3 tumors (p = .0014), and carbohydrate antigen 19-9 >60 U/mL (p = .0003) as independent predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. Conclusion. The optimal cutoff point of early recurrence was determined to be 8 months. The preoperative prediction of early recurrence is possible and crucial for designing effective perioperative chemotherapy regimens. Implications for Practice: In this study, the optimal cutoff point of early recurrence was determined to be 8 months after surgery based on the minimum p value approach, and its prognostic impact was demonstrated mainly in patients who received preoperative chemotherapy

A Python Analytical Pipeline to Identify Prohormone Precursors and Predict Prohormone Cleavage Sites

PubMed Central

Southey, Bruce R.; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.

2008-01-01

Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides. PMID:19169350

Factors Predicting Smoking in a Laboratory-Based Smoking-Choice Task

PubMed Central

Bold, Krysten W.; Yoon, Haewon; Chapman, Gretchen B.; McCarthy, Danielle E.

2013-01-01

This study aimed to expand the current understanding of smoking maintenance mechanisms by examining how putative relapse risk factors relate to a single behavioral smoking choice using a novel laboratory smoking-choice task. After 12 hours of nicotine deprivation, participants were exposed to smoking cues and given the choice between smoking up to two cigarettes in a 15-minute window or waiting and receiving four cigarettes after a delay of 45 minutes. Greater nicotine dependence, higher impulsivity, and lower distress tolerance were hypothesized to predict earlier and more intensive smoking. Out of 35 participants (n=9 female), 26 chose to smoke with a median time to a first puff of 1.22 minutes (standard deviation=2.62 min, range=0.03–10.62 min). Survival analyses examined latency to first puff, and results indicated that greater pre-task craving and smoking more cigarettes per day were significantly related to smoking sooner in the task. Greater behavioral disinhibition predicted shorter smoking latency in the first two minutes of the task, but not at a delay of more than two minutes. Lower distress tolerance (reporting greater regulation efforts to alleviate distress) was related to more puffs smoked and greater nicotine dependence was related to more time spent smoking in the task. This novel laboratory smoking-choice paradigm may be a useful laboratory analog for the choices smokers make during cessation attempts and may help identify factors that influence smoking lapses. PMID:23421357

Ecological Factors Predict Transition Readiness/Self-Management in Youth With Chronic Conditions.

PubMed

Javalkar, Karina; Johnson, Meredith; Kshirsagar, Abhijit V; Ocegueda, Sofia; Detwiler, Randal K; Ferris, Maria

2016-01-01

Health care transition readiness or self-management among adolescents and young adults (AYA) with chronic conditions may be influenced by factors related to their surrounding environment. Study participants were AYA diagnosed with a chronic condition and evaluated at pediatric- and adult-focused subspecialty clinics at the University of North Carolina Hospital Systems. All participants were administered a provider-administered self-management/transition-readiness tool, the UNC TRxANSITION Scale. Geographic area and associated characteristics (ecological factors) were identified for each participant's ZIP code using the published U.S. Census data. The Level 1 model of the hierarchical linear regression used individual-level predictors of transition readiness/self-management. The Level 2 model incorporated the ecological factors. We enrolled 511 AYA with different chronic conditions aged 12-31 years with the following characteristics: mean age of 20± 4 years, 45% white, 42% black, and 54% female. Participants represented 214 ZIP codes in or around North Carolina, USA. The Level 1 model showed that age, gender, and race were significant predictors of transition readiness/self-management. On adding the ecological factors in the Level 2 model, race was no longer significant. Participants from a geographic area with a greater percentage of females (β = .114, p = .005) and a higher median income (β = .126, p = .002) had greater overall transition readiness. Ecological factors also predicted subdomains of transition readiness/self-management. In this cohort of adolescents and young adults with different chronic conditions, ecological disparities such as sex composition, median income, and language predict self-management/transition readiness. It is important to take ecological risk factors into consideration when preparing patients for health self-management or transition. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All

Predictive factors for birth weight of newborns of mothers with gestational diabetes mellitus.

PubMed

Silva, Sara de Oliveira Corrêa da; Saunders, Cláudia; Zajdenverg, Lenita; Moreira, Luciana Novaes; Heidelmann, Sonaly Petronilho; Pereira, Ariane Cristine Dos Santos; Padilha, Patricia de Carvalho

2018-04-01

To evaluate the predictive factors of birth weight (BW) of newborns of women with gestational diabetes mellitus (GDM). A cross-sectional study was performed among pregnant women with GDM treated in a public maternity unit, Brazil. We selected 283 pregnant women, with nutritional follow-up initiated till the 28th gestational week, singleton pregnancy, without chronic diseases and with birth weight information of the newborns. The predictive factors of BW were identified by multivariate linear regression. Mean maternal age was 31.2 ± 5.8 years; 64.4% were non-white; 70.1% were pre-gestational overweight or obese. Mean BW was 3234.3 ± 478.8 g. An increase of 1 kg of weight in the first and third trimesters increased BW by 21 g (p = 0.01) and 27 g (p = 0.03), respectively. Similarly, the other predictive factors of BW were pre-gestational body mass index (β = 17.16, p = 0.02) and postprandial plasma glucose in the third trimester (β = 4.14, p = 0.008), in the model adjusted by gestational age at delivery (β = 194.68, p < 0.001). The best predictors of BW were gestational age at birth, and maternal pre-gestational and gestational anthropometric characteristics. Maternal glycaemic levels may also influence BW. The results may contribute to a review of prenatal routines for pregnant women with GDM. Copyright © 2018 Elsevier B.V. All rights reserved.

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

Breastfeeding at 6 weeks and predictive factors.

PubMed

Chye, J K; Zain, Z; Lim, W L; Lim, C T

1997-10-01

Despite the numerous changes made in accordance with the Baby Friendly Hospital Initiative at the University Hospital, Kuala Lumpur, the low rates of breastfeeding have persisted. This study aims to examine the current trend in infant feeding, and the influences of some perinatal and sociodemographic factors on breastfeeding. Five-hundred mothers with singleton pregnancies and healthy infants were interviewed at 6 weeks post-partum. Only 124 (25 per cent) mothers were practising exclusive breastfeeding (EBF), and 132 (26 per cent) mothers were using exclusive infant formula feeding (EIF). On logistic regression analyses, mothers who followed EBF were more likely to have had antenatal plans to breastfeed (Odds ratio 2.44, 95 per cent confidence interval 1.75-3.45), not in paid employment post-natally (OR 1.76, 95 per cent CI 1.31-2.36), of older age group (> 27 years) (OR 1.48, 95 per cent CI 1.13-1.93), had female infants (OR 1.38, 95 per cent CI 1.05-1.80) and of Indian ethnicity (compared to Chinese) (OR 3.87, 95 per cent CI 2.16-6.89). Breastfeeding difficulties were associated with decreased odds of EBF (OR 0.21, 95 per cent CI 0.13-0.34). Parental education, fathers' ages and incomes, primigravida status, Caesarean section, present of episiotomy, late first breastfeed, phototherapy, and length of hospital stay were not significant predictors of failure of EBF. In comparison, predictive factors for increased use of EIF were mothers who have had breastfeeding difficulties, < or = 9 years of schooling, and of Chinese descent. In conclusions, the overall rate of EBF by 6 weeks of age in infants born in this urban hospital had remained poor. The adverse factors for EBF identified in this study warrant further in-depth studies to determine effective ways of improving EBF rates.

Predictive factors of the nursing diagnosis sedentary lifestyle in people with high blood pressure.

PubMed

Guedes, Nirla Gomes; Lopes, Marcos Venícios de Oliveira; Araujo, Thelma Leite de; Moreira, Rafaella Pessoa; Martins, Larissa Castelo Guedes

2011-01-01

To verify the reproducibility of defining the characteristics and related factors in order to identify a sedentary lifestyle in patients with high blood pressure. A cross-sectional study. 310 patients diagnosed with high blood pressure. Socio-demographics and variables related to defining the characteristics and related factors of a sedentary lifestyle. The coefficient Kappa was utilized to analyze the reproducibility. The sensitivity, specificity, and predictive value of the defining characteristics were also analyzed. Logistic regression was applied in the analysis of possible predictors. The defining characteristic with the greatest sensitivity was demonstrates physical deconditioning (98.92%). The characteristics chooses a daily routine lacking physical exercise and verbalizes preference for activities low in physical activity presented higher values of specificity (99.21% and 95.97%, respectively). The following indicators were identified as powerful predictors (85.2%) for the identification of a sedentary lifestyle: demonstrates physical deconditioning, verbalizes preference for activities low in physical activity, and lack of training for accomplishment of physical exercise. © 2010 Wiley Periodicals, Inc.

Identifying factors that influence pregnancy intentions: evidence from South Africa and Malawi.

PubMed

Evens, Emily; Tolley, Elizabeth; Headley, Jennifer; McCarraher, Donna R; Hartmann, Miriam; Mtimkulu, Vuyelwa T; Manenzhe, Kgahlisho Nozibele; Hamela, Gloria; Zulu, Fatima

2015-01-01

In developing-country settings, pregnancy intentions are often assessed using a series of questions from the Demographic and Health Surveys, yet research conducted in several countries yields conflicting results regarding these questions' ability to predict pregnancy. Conducted in Malawi and South Africa, this study identified individual, partner and societal factors that influence desire for pregnancy, and women's ability to achieve their intentions. Data come from interviews and focus-group discussions conducted prior to the FEM-PrEP HIV-prevention trial with women from communities at high risk of HIV infection. Cultural norms regarding contraceptive use and childbearing influenced both women's desire for pregnancy and ability to achieve those goals. Partner's expectations for pregnancy, financial concerns, family composition and contraceptive experiences were additional influences. Actively planning for pregnancy was not a salient concept to the majority of participants. Results support the call for a multidimensional measure of pregnancy intention that reflects the variety of factors that influence intentions, highlight the fluid nature of many women's reproductive health decision making and challenge the notion that all fertility decisions are the result of conscious action. Additional work on how women's plans for pregnancy are achieved would be programmatically more useful than current measures of intention.

Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

PubMed

Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, T; Tanizawa, Y

2018-04-29

To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin <1.1. Decision-curve analysis showed that combining insulinogenic index/fasting immunoreactive insulin <1.1 with basic clinical information resulted in superior net benefits for prediction of postpartum glucose intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. © 2018 Diabetes UK.

Use of a twin dataset to identify AMD-related visual patterns controlled by genetic factors

NASA Astrophysics Data System (ADS)

Quellec, Gwénolé; Abràmoff, Michael D.; Russell, Stephen R.

2010-03-01

The mapping of genotype to the phenotype of age-related macular degeneration (AMD) is expected to improve the diagnosis and treatment of the disease in a near future. In this study, we focused on the first step to discover this mapping: we identified visual patterns related to AMD which seem to be controlled by genetic factors, without explicitly relating them to the genes. For this purpose, we used a dataset of eye fundus photographs from 74 twin pairs, either monozygotic twins, who have the same genotype, or dizygotic twins, whose genes responsible for AMD are less likely to be identical. If we are able to differentiate monozygotic twins from dizygotic twins, based on a given visual pattern, then this pattern is likely to be controlled by genetic factors. The main visible consequence of AMD is the apparition of drusen between the retinal pigment epithelium and Bruch's membrane. We developed two automated drusen detectors based on the wavelet transform: a shape-based detector for hard drusen, and a texture- and color- based detector for soft drusen. Forty visual features were evaluated at the location of the automatically detected drusen. These features characterize the texture, the shape, the color, the spatial distribution, or the amount of drusen. A distance measure between twin pairs was defined for each visual feature; a smaller distance should be measured between monozygotic twins for visual features controlled by genetic factors. The predictions of several visual features (75.7% accuracy) are comparable or better than the predictions of human experts.

Preoperative serum alkaline phosphatase: a predictive factor for early hypocalcaemia following parathyroidectomy of primary hyperparathyroidism.

PubMed

Sun, Longhao; He, Xianghui; Liu, Tong

2014-01-01

Postoperative hypocalcemia is one of the most common complications following parathyroidectomy for primary hyperparathyroidism (PHPT). The aim of this study was to analyze the predictive value of biochemical parameters as indicators for episodes of hypocalcemia in patients undergoing parathyroidectomy for PHPT. The patients with PHPT who underwent parathyroidectomy between February 2004 and February 2014 were studied retrospectively at a single medical center. The patients were divided into biochemical, clinical, and no postoperative hypocalcemia groups, based on different clinical manifestations. Potential risk factors for postoperative hypocalcemia were identified and investigated by univariate and multivariate Logistic regression analysis. Of the 139 cases, 25 patients (18.0%) were diagnosed with postoperative hypocalcemia according to the traditional criterion. Univariate analysis revealed only alkaline phosphatase (ALP) and the small area under the curve (AUC) of receiver operating characteristics (ROC) curve for ALP demonstrates low accuracy in predicting the occurrence of postoperative hypocalcemia. Based on new criteria, 22 patients were added to the postoperative hypocalcemia group and similar biochemical parameters were compared. The serum ALP was a significant independent risk factor for postoperative hypocalcemia (P = 0.000) and its AUC of ROC curve was 0.783. The optimal cutoff point was 269 U/L and the sensitivity and specificity for prediction were 89.2% and 64.3%, respectively. The risk of postoperative hypocalcemia after parathyroidectomy should be emphasized for patients with typical symptoms of hypocalcemia despite their serum calcium level is in normal or a little higher range. Serum ALP is a predictive factor for the occurrence of postoperative hypocalcemia.

Genome wide predictions of miRNA regulation by transcription factors.

PubMed

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predictive factors of cytomegalovirus seropositivity among pregnant women in Paris, France.

PubMed

N'Diaye, Dieynaba S; Yazdanpanah, Yazdan; Krivine, Anne; Andrieu, Thibaut; Rozenberg, Flore; Picone, Olivier; Tsatsaris, Vassilis; Goffinet, François; Launay, Odile

2014-01-01

Cytomegalovirus (CMV) is the most frequent cause of congenital infection. The objective of this study was to evaluate predictive factors for CMV seronegativity in a cohort of pregnant women in Paris, France. Pregnant women enrolled in a prospective cohort during the 2009 A/H1N1 pandemic were tested for CMV IgG antibodies. Variables collected were age, geographic origin, lifestyle, work characteristics, socioeconomic status, gravidity, parity and number of children at home. A multivariate logistic regression model was used to identify independent predictive factors for CMV seropositivity. Among the 826 women enrolled, 389 (47.1%) were primiparous, and 552 (67.1%) had Metropolitan France as a geographic origin. Out of these, 355 (i.e. 57.0%, 95% confidence interval (CI): [53.6%-60.4%]) were CMV seropositive: 43.7% (95% CI:[39.5%-47.9%]) in those whose geographic origin was Metropolitan France and 84.1% in those with other origins (95% CI:[79.2%-88.3%]). Determinants associated with CMV seropositivity in a multivariate logistic regression model were: (i) geographic origin (p<0.001(compared with Metropolitan France, geographic origins of Africa adjusted odds ratio (aOR) 21.2, 95% CI:[9.7-46.5], French overseas departments and territories and other origin, aOR 7.5, 95% CI:[3.9-14.6], and Europe or Asia, aOR 2.2, 95% CI: [1.3-3.7]); and (ii) gravidity (p = 0.019), (compared with gravidity = 1, if gravidity≥3, aOR = 1.5, 95% CI: [1.1-2.2]; if gravidity = 2, aOR = 1.0, 95% CI: [0.7-1.4]). Work characteristics and socioeconomic status were not independently associated with CMV seropositivity. In this cohort of pregnant women, a geographic origin of Metropolitan France and a low gravidity were predictive factors for CMV low seropositivity. Such women are therefore the likely target population for prevention of CMV infection during pregnancy in France.

Predictive Factors of Cytomegalovirus Seropositivity among Pregnant Women in Paris, France

PubMed Central

N’Diaye, Dieynaba S.; Yazdanpanah, Yazdan; Krivine, Anne; Andrieu, Thibaut; Rozenberg, Flore; Picone, Olivier; Tsatsaris, Vassilis; Goffinet, François; Launay, Odile

2014-01-01

Background Cytomegalovirus (CMV) is the most frequent cause of congenital infection. The objective of this study was to evaluate predictive factors for CMV seronegativity in a cohort of pregnant women in Paris, France. Methods Pregnant women enrolled in a prospective cohort during the 2009 A/H1N1 pandemic were tested for CMV IgG antibodies. Variables collected were age, geographic origin, lifestyle, work characteristics, socioeconomic status, gravidity, parity and number of children at home. A multivariate logistic regression model was used to identify independent predictive factors for CMV seropositivity. Results Among the 826 women enrolled, 389 (47.1%) were primiparous, and 552 (67.1%) had Metropolitan France as a geographic origin. Out of these, 355 (i.e. 57.0%, 95% confidence interval (CI): [53.6%–60.4%]) were CMV seropositive: 43.7% (95% CI:[39.5%–47.9%]) in those whose geographic origin was Metropolitan France and 84.1% in those with other origins (95% CI:[79.2%–88.3%]). Determinants associated with CMV seropositivity in a multivariate logistic regression model were: (i) geographic origin (p<0.001(compared with Metropolitan France, geographic origins of Africa adjusted odds ratio (aOR) 21.2, 95% CI:[9.7–46.5], French overseas departments and territories and other origin, aOR 7.5, 95% CI:[3.9–14.6], and Europe or Asia, aOR 2.2, 95% CI: [1.3–3.7]); and (ii) gravidity (p = 0.019), (compared with gravidity = 1, if gravidity≥3, aOR = 1.5, 95% CI: [1.1–2.2]; if gravidity = 2, aOR = 1.0, 95% CI: [0.7–1.4]). Work characteristics and socioeconomic status were not independently associated with CMV seropositivity. Conclusions In this cohort of pregnant women, a geographic origin of Metropolitan France and a low gravidity were predictive factors for CMV low seropositivity. Such women are therefore the likely target population for prevention of CMV infection during pregnancy in France. PMID:24587077

Identifying depression severity risk factors in persons with traumatic spinal cord injury.

PubMed

Williams, Ryan T; Wilson, Catherine S; Heinemann, Allen W; Lazowski, Linda E; Fann, Jesse R; Bombardier, Charles H

2014-02-01

Examine the relationship between demographic characteristics, health-, and injury-related characteristics, and substance misuse across multiple levels of depression severity. 204 persons with traumatic spinal cord injury (SCI) volunteered as part of screening efforts for a randomized controlled trial of venlafaxine extended release for major depressive disorder (MDD). Instruments included the Patient Health Questionnaire-9 (PHQ-9) depression scale, the Alcohol Use Disorders Identification Test (AUDIT), and the Substance Abuse in Vocational Rehabilitation-Screener (SAVR-S), which contains 3 subscales: drug misuse, alcohol misuse, and a subtle items scale. Each of the SAVR-S subscales contributes to an overall substance use disorder (SUD) outcome. Three proportional odds models were specified, varying the substance misuse measure included in each model. 44% individuals had no depression symptoms, 31% had mild symptoms, 16% had moderate symptoms, 6% had moderately severe symptoms, and 3% had severe depression symptoms. Alcohol misuse, as indicated by the AUDIT and the SAVR-S drug misuse subscale scores were significant predictors of depression symptom severity. The SAVR-S substance use disorder (SUD) screening outcome was the most predictive variable. Level of education was only significantly predictive of depression severity in the model using the AUDIT alcohol misuse indicator. Likely SUD as measured by the SAVR-S was most predictive of depression symptom severity in this sample of persons with traumatic SCI. Drug and alcohol screening are important for identifying individuals at risk for depression, but screening for both may be optimal. Further research is needed on risk and protective factors for depression, including psychosocial characteristics. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Integrating the ICF with positive psychology: Factors predicting role participation for mothers with multiple sclerosis.

PubMed

Farber, Ruth S; Kern, Margaret L; Brusilovsky, Eugene

2015-05-01

Being a mother has become a realizable life role for women with disabilities and chronic illnesses, including multiple sclerosis (MS). Identifying psychosocial factors that facilitate participation in important life roles-including motherhood-is essential to help women have fuller lives despite the challenge of their illness. By integrating the International Classification of Functioning, Disability, and Health (ICF) and a positive psychology perspective, this study examined how environmental social factors and positive personal factors contribute to daily role participation and satisfaction with parental participation. One hundred and 11 community-dwelling mothers with MS completed Ryff's Psychological Well-Being Scales, the Medical Outcome Study Social Support Survey, the Short Form-36, and the Parental Participation Scale. Hierarchical regression analyses examined associations between social support and positive personal factors (environmental mastery, self-acceptance, purpose in life) with daily role participation (physical and emotional) and satisfaction with parental participation. One-way ANOVAs tested synergistic combinations of social support and positive personal factors. Social support predicted daily role participation (fewer limitations) and greater satisfaction with parental participation. Positive personal factors contributed additional unique variance. Positive personal factors and social support synergistically predicted better function and greater satisfaction than either alone. Integrating components of the ICF and positive psychology provides a useful model for understanding how mothers with MS can thrive despite challenge or impairment. Both positive personal factors and environmental social factors were important contributors to positive role functioning. Incorporating these paradigms into treatment may help mothers with MS participate more fully in meaningful life roles. (c) 2015 APA, all rights reserved).

Using Emotional and Social Factors To Predict Student Success.

ERIC Educational Resources Information Center

Pritchard, Mary E.; Wilson, Gregory S.

2003-01-01

College academic success and retention have traditionally been predicted using demographic and academic variables. This study moved beyond traditional predictors. A survey of 218 undergraduate students revealed that emotional and social factors (e.g., stress, frequency of alcohol consumption) related to GPA and emotional factors (e.g.,…

Identifying molecular subtypes related to clinicopathologic factors in pancreatic cancer

PubMed Central

2014-01-01

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal tumors and usually presented with locally advanced and distant metastasis disease, which prevent curative resection or treatments. In this regard, we considered identifying molecular subtypes associated with clinicopathological factor as prognosis factors to stratify PDAC for appropriate treatment of patients. Results In this study, we identified three molecular subtypes which were significant on survival time and metastasis. We also identified significant genes and enriched pathways represented for each molecular subtype. Considering R0 resection patients included in each subtype, metastasis and survival times are significantly associated with subtype 1 and subtype 2. Conclusions We observed three PDAC molecular subtypes and demonstrated that those subtypes were significantly related with metastasis and survival time. The study may have utility in stratifying patients for cancer treatment. PMID:25560450

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics.

PubMed

Rho, Mi Jung; Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Jung, Dong Jin; Kim, Dai-Jin; Choi, In Young

2017-12-27

Background : Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods : Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results : The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions : These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.

Screening for violence risk factors identifies young adults at risk for return emergency department visit for injury.

PubMed

Hankin, Abigail; Wei, Stanley; Foreman, Juron; Houry, Debra

2014-08-01

Homicide is the second leading cause of death among youth aged 15-24. Prior cross-sectional studies, in non-healthcare settings, have reported exposure to community violence, peer behavior, and delinquency as risk factors for violent injury. However, longitudinal cohort studies have not been performed to evaluate the temporal or predictive relationship between these risk factors and emergency department (ED) visits for injuries among at-risk youth. The objective was to assess whether self-reported exposure to violence risk factors in young adults can be used to predict future ED visits for injuries over a 1-year period. This prospective cohort study was performed in the ED of a Southeastern US Level I trauma center. Eligible participants were patients aged 18-24, presenting for any chief complaint. We excluded patients if they were critically ill, incarcerated, or could not read English. Initial recruitment occurred over a 6-month period, by a research assistant in the ED for 3-5 days per week, with shifts scheduled such that they included weekends and weekdays, over the hours from 8AM-8PM. At the time of initial contact in the ED, patients were asked to complete a written questionnaire, consisting of previously validated instruments measuring the following risk factors: a) aggression, b) perceived likelihood of violence, c) recent violent behavior, d) peer behavior, e) community exposure to violence, and f) positive future outlook. At 12 months following the initial ED visit, the participants' medical records were reviewed to identify any subsequent ED visits for injury-related complaints. We analyzed data with chi-square and logistic regression analyses. Three hundred thirty-two patients were approached, of whom 300 patients consented. Participants' average age was 21.1 years, with 60.1% female, 86.0% African American. After controlling for participant gender, ethnicity, or injury complaint at time of first visit, return visits for injuries were significantly

Neutrophil-to-lymphocyte ratio and mural nodule height as predictive factors for malignant intraductal papillary mucinous neoplasms.

PubMed

Watanabe, Yusuke; Niina, Yusuke; Nishihara, Kazuyoshi; Okayama, Takafumi; Tamiya, Sadafumi; Nakano, Toru

2018-01-15

Accurate preoperative prediction for malignant IPMN is still challenging. The aim of this study was to investigate the validity of neutrophil-to-lymphocyte ratio (NLR) and mural nodule height (MNH) for predicting malignant intraductal papillary mucinous neoplasm (IPMN). The medical records of 60 patients who underwent pancreatectomy for IPMN were retrospectively reviewed. NLR tended to be higher in malignant IPMN (median: 2.23) than in benign IPMN (median: 2.04; p = .14). MNH was significantly greater in malignant IPMN (median: 16 mm) than in benign IPMN (median: 8 mm; p < .01). The optimal cutoff values for the NLR and MNH were 3.60 and 11 mm, respectively. The sensitivity and specificity of NLR ≥3.60 for predicting malignant IPMN were 40% and 93%, and those of MNH ≥11 mm were 73% and 77%, respectively. Univariate analysis revealed that NLR ≥3.60 (p < .01) and MNH ≥11 mm (p < .01) were significant predictive factors. On multivariate analysis, enhanced solid component was identified as an independent factor, but NLR ≥3.60 and MNH ≥11 mm were not. NLR and MNH are suboptimal tests in predicting malignant IPMN; however, they can be useful to assist in clinical decision-making.

Predicting Gender-Role Attitudes in Adolescent Females: Ability, Agency, and Parental Factors.

ERIC Educational Resources Information Center

Ahrens, Julia A.; O'Brien, Karen M.

1996-01-01

Investigated the contribution of ability, agency, and parental factors to the prediction of gender-role attitudes of 409 adolescent females in a private, college-preparatory high school. Findings indicate that ability and agency were predictive of gender-role attitudes, whereas parental factors were not significant contributors. Recommendations…

Suicide risk among prisoners in French Guiana: prevalence and predictive factors.

PubMed

Ayhan, Gülen; Arnal, Romain; Basurko, Célia; About, Vincent; Pastre, Agathe; Pinganaud, Eric; Sins, Dominique; Jehel, Louis; Falissard, Bruno; Nacher, Mathieu

2017-05-02

Suicide rates in prison are high and their risk factors are incompletely understood. The objective of the present study is to measure the risk of suicide and its predictors in the only prison of multicultural French Guiana. All new prisoners arriving between September 2013 and December 2014 were included. The Mini International Neuropsychiatric Interview (MINI) was used and socio-demographic data was collected. In order to identify the predictors of suicide risk multivariate logistic regression was used. Of the 707 prisoners included 13.2% had a suicidal risk, 14.0% of whom had a high risk, 15.1% a moderate risk and 41.9% a low risk. Predictive factors were depression (OR 7.44, 95% CI: 3.50-15.87), dysthymia (OR 4.22, 95% CI: 1.34-13.36), panic disorder (OR 3.47, 95% CI: 1.33-8.99), general anxiety disorder (GAD) (OR 2.19, 95% CI: 1.13-4.22), men having been abused during childhood (OR 21.01, 95%, CI: 3.26-135.48), having been sentenced for sexual assault (OR 7.12, 95% CI: 1.98-25.99) and smoking (OR 2.93, 95%, CI 1.30-6.63). The suicide risk was lower than in mainland France, possibly reflecting the differences in the social stigma attached to incarceration because of migrant populations and the importance and trivialization of drug trafficking among detainees. However, there were no differences between nationalities. The results reemphasize the importance of promptly identifying and treating psychiatric disorders, which were the main suicide risk factors.

Predictive factors of relapse in low-risk gestational trophoblastic neoplasia patients successfully treated with methotrexate alone.

PubMed

Couder, Florence; Massardier, Jérôme; You, Benoît; Abbas, Fatima; Hajri, Touria; Lotz, Jean-Pierre; Schott, Anne-Marie; Golfier, François

2016-07-01

Patients with 2000 FIGO low-risk gestational trophoblastic neoplasia are commonly treated with single-agent chemotherapy. Methotrexate is widely used in this indication in Europe. Analysis of relapse after treatment and identification of factors associated with relapse would help understand their potential impacts on 2000 FIGO score evolution and chemotherapy management of gestational trophoblastic neoplasia patients. This retrospective study analyzes the predictive factors of relapse in low-risk gestational trophoblastic neoplasia patients whose hormone chorionic gonadotropin (hCG) normalized with methotrexate alone. Between 1999 and 2014, 993 patients with gestational trophoblastic neoplasia were identified in the French Trophoblastic Disease Reference Center database, of which 465 were low-risk patients whose hCG normalized with methotrexate alone. Using univariate and multivariate analysis we identified significant predictive factors for relapse after methotrexate. The Kaplan-Meier method was used to plot the outcome of patients. The 5-year recurrence rate of low-risk gestational trophoblastic neoplasia patients whose hCG normalized with methotrexate alone was 5.7% (confidence interval [IC], 3.86-8.46). Univariate analysis identified an antecedent pregnancy resulting in a delivery (HR = 5.96; 95% CI, 1.40-25.4, P = .016), a number of methotrexate courses superior to 5 courses (5-8 courses vs 1-4: HR = 6.19; 95% CI, 1.43-26.8, P = .015; 9 courses and more vs 1-4: HR = 6.80; 95% CI, 1.32-35.1, P = .022), and hCG normalization delay centered to the mean as predictive factors of recurrence (HR = 1.27; 95% CI, 1.09-1.49, P = .003). Multivariate analysis confirmed the type of antecedent pregnancy and the number of methotrexate courses as independent predictive factors of recurrence. A low-risk gestational trophoblastic neoplasia arising after a normal delivery had an 8.66 times higher relapse risk than that of a postmole gestational trophoblastic neoplasia

Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

EPA Science Inventory

Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease.

PubMed

Noyce, Alastair J; R'Bibo, Lea; Peress, Luisa; Bestwick, Jonathan P; Adams-Carr, Kerala L; Mencacci, Niccolo E; Hawkes, Christopher H; Masters, Joseph M; Wood, Nicholas; Hardy, John; Giovannoni, Gavin; Lees, Andrew J; Schrag, Anette

2017-02-01

A number of early features can precede the diagnosis of Parkinson's disease (PD). To test an online, evidence-based algorithm to identify risk indicators of PD in the UK population. Participants aged 60 to 80 years without PD completed an online survey and keyboard-tapping task annually over 3 years, and underwent smell tests and genotyping for glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 (LRRK2) mutations. Risk scores were calculated based on the results of a systematic review of risk factors and early features of PD, and individuals were grouped into higher (above 15th centile), medium, and lower risk groups (below 85th centile). Previously defined indicators of increased risk of PD ("intermediate markers"), including smell loss, rapid eye movement-sleep behavior disorder, and finger-tapping speed, and incident PD were used as outcomes. The correlation of risk scores with intermediate markers and movement of individuals between risk groups was assessed each year and prospectively. Exploratory Cox regression analyses with incident PD as the dependent variable were performed. A total of 1323 participants were recruited at baseline and >79% completed assessments each year. Annual risk scores were correlated with intermediate markers of PD each year and baseline scores were correlated with intermediate markers during follow-up (all P values < 0.001). Incident PD diagnoses during follow-up were significantly associated with baseline risk score (hazard ratio = 4.39, P = .045). GBA variants or G2019S LRRK2 mutations were found in 47 participants, and the predictive power for incident PD was improved by the addition of genetic variants to risk scores. The online PREDICT-PD algorithm is a unique and simple method to identify indicators of PD risk. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder

Perforated Peptic Ulcer Repair: Factors Predicting Conversion in Laparoscopy and Postoperative Septic Complications.

PubMed

Muller, Markus K; Wrann, Simon; Widmer, Jeannette; Klasen, Jennifer; Weber, Markus; Hahnloser, Dieter

2016-09-01

The surgical treatment for perforated peptic ulcers can be safely performed laparoscopically. The aim of the study was to define simple predictive factors for conversion and septic complications. This retrospective case-control study analyzed patients treated with either laparoscopic surgery or laparotomy for perforated peptic ulcers. A total of 71 patients were analyzed. Laparoscopically operated patients had a shorter hospital stay (13.7 vs. 15.1 days). In an intention-to-treat analysis, patients with conversion to open surgery (analyzed as subgroup from laparoscopic approach group) showed no prolonged hospital stay (15.3 days) compared to patients with a primary open approach. Complication and mortality rates were not different between the groups. The statistical analysis identified four intraoperative risk factors for conversion: Mannheim peritonitis index (MPI) > 21 (p = 0.02), generalized peritonitis (p = 0.04), adhesions, and perforations located in a region other than the duodenal anterior wall. We found seven predictive factors for septic complications: age >70 (p = 0.02), cardiopulmonary disease (p = 0.04), ASA > 3 (p = 0.002), CRP > 100 (p = 0.005), duration of symptoms >24 h (p = 0.02), MPI > 21(p = 0.008), and generalized peritonitis (p = 0.02). Our data suggest that a primary laparoscopic approach has no disadvantages. Factors necessitating conversions emerged during the procedure inhibiting a preoperative selection. Factors suggesting imminent septic complications can be assessed preoperatively. An assessment of the proposed parameters may help optimize the management of possible septic complications.

Psychological factors that predict reaction to abortion.

PubMed

Moseley, D T; Follingstad, D R; Harley, H; Heckel, R V

1981-04-01

Investigated demographic and psychological factors related to positive or negative reactions to legal abortions performed during the first trimester of pregnancy in 62 females in an urban southern community. Results suggest that the social context and the degree of support from a series of significant persons rather than demographic variables were most predictive of a positive reaction.

[Predicting individual risk of high healthcare cost to identify complex chronic patients].

PubMed

Coderch, Jordi; Sánchez-Pérez, Inma; Ibern, Pere; Carreras, Marc; Pérez-Berruezo, Xavier; Inoriza, José M

2014-01-01

To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Factors that predict adolescent motivation for substance abuse treatment.

PubMed

Battjes, Robert J; Gordon, Michael S; O'Grady, Kevin E; Kinlock, Timothy W; Carswell, Melissa A

2003-04-01

Many adolescent substance abusers enter treatment because of external pressures and thus lack motivation to change their behavior and engage in treatment. Because an understanding of adolescent motivation may contribute to improved treatment, an investigation of factors that predict motivation was undertaken with youth admitted to an adolescent outpatient substance abuse treatment program (N=196). At admission, these subjects received a comprehensive biopsychosocial assessment. Using multiple regression analysis, factors considered to potentially predict motivation were assessed. Of the factors examined, those that involved experiencing various negative consequences of substance use emerged as important predictors of motivation, whereas severity of substance use did not. Diminished awareness of negative consequences of use was consonant with lower motivation, suggesting the importance of interventions to help youth recognize negative consequences of their substance use. Interventions to enhance motivation are likely to become more important as the juvenile justice system increasingly refers troubled youth to treatment.

A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks.

PubMed

Peng, Wei; Lan, Wei; Zhong, Jiancheng; Wang, Jianxin; Pan, Yi

2017-07-15

MicroRNAs have been reported to have close relationship with diseases due to their deregulation of the expression of target mRNAs. Detecting disease-related microRNAs is helpful for disease therapies. With the development of high throughput experimental techniques, a large number of microRNAs have been sequenced. However, it is still a big challenge to identify which microRNAs are related to diseases. Recently, researchers are interesting in combining multiple-biological information to identify the associations between microRNAs and diseases. In this work, we have proposed a novel method to predict the microRNA-disease associations based on four biological properties. They are microRNA, disease, gene and environment factor. Compared with previous methods, our method makes predictions not only by using the prior knowledge of associations among microRNAs, disease, environment factors and genes, but also by using the internal relationship among these biological properties. We constructed four biological networks based on the similarity of microRNAs, diseases, environment factors and genes, respectively. Then random walking was implemented on the four networks unequally. In the walking course, the associations can be inferred from the neighbors in the same networks. Meanwhile the association information can be transferred from one network to another. The results of experiment showed that our method achieved better prediction performance than other existing state-of-the-art methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Delayed neuropsychological sequelae after carbon monoxide poisoning: predictive risk factors in the Emergency Department. A retrospective study.

PubMed

Pepe, Giuseppe; Castelli, Matteo; Nazerian, Peiman; Vanni, Simone; Del Panta, Massimo; Gambassi, Francesco; Botti, Primo; Missanelli, Andrea; Grifoni, Stefano

2011-03-17

Delayed neuropsychological sequelae (DNS) commonly occur after recovery from acute carbon monoxide (CO) poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department. We retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy) from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS. Three hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%). Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission) were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS) score <9, seizures, systolic blood pressure <90 mmHg, elevated creatine phosphokinase concentration and leukocytosis. There was no significant correlation with age, sex, voluntary exposure, headache, transient loss of consciousness, GCS between 14 and 9, arterial lactate and carboxyhemoglobin concentration. The multivariate analysis confirmed as independent prognostic factors GCS <9 (OR 7.15; CI 95%: 1.04-48.8) and leukocytosis (OR 3.31; CI 95%: 1

Delayed neuropsychological sequelae after carbon monoxide poisoning: predictive risk factors in the Emergency Department. A retrospective study

PubMed Central

2011-01-01

Background Delayed neuropsychological sequelae (DNS) commonly occur after recovery from acute carbon monoxide (CO) poisoning. The preventive role and the indications for hyperbaric oxygen therapy in the acute setting are still controversial. Early identification of patients at risk in the Emergency Department might permit an improvement in quality of care. We conducted a retrospective study to identify predictive risk factors for DNS development in the Emergency Department. Methods We retrospectively considered all CO-poisoned patients admitted to the Emergency Department of Careggi University General Hospital (Florence, Italy) from 1992 to 2007. Patients were invited to participate in three follow-up visits at one, six and twelve months from hospital discharge. Clinical and biohumoral data were collected; univariate and multivariate analysis were performed to identify predictive risk factors for DNS. Results Three hundred forty seven patients were admitted to the Emergency Department for acute CO poisoning from 1992 to 2007; 141/347 patients participated in the follow-up visit at one month from hospital discharge. Thirty four/141 patients were diagnosed with DNS (24.1%). Five/34 patients previously diagnosed as having DNS presented to the follow-up visit at six months, reporting a complete recovery. The following variables (collected before or upon Emergency Department admission) were associated to DNS development at one month from hospital discharge in the univariate analysis: CO exposure duration >6 hours, a Glasgow Coma Scale (GCS) score <9, seizures, systolic blood pressure <90 mmHg, elevated creatine phosphokinase concentration and leukocytosis. There was no significant correlation with age, sex, voluntary exposure, headache, transient loss of consciousness, GCS between 14 and 9, arterial lactate and carboxyhemoglobin concentration. The multivariate analysis confirmed as independent prognostic factors GCS <9 (OR 7.15; CI 95%: 1.04-48.8) and leukocytosis (OR 3

Predictive Success Factors in Selective Upper Airway Stimulation.

PubMed

Heiser, Clemens; Hofauer, Benedikt

2017-01-01

Obstructive sleep apnea is one of the most common diseases in Western industrialized countries. A variety of conservative and surgical treatment options are available for its treatment. In recent years, selective upper airway stimulation (sUAS) has been shown to be effective and safe. Different biomarkers have been investigated as predictive clinical success factors in a number of clinical trials. Age does not matter in sUAS, as compared to its predictive role in other therapies. Weight seems to play a limited role, depending on drug-induced sleep endoscopy to rule out a complete concentric collapse with an increased body mass index. For surgical success and the related postoperative tongue motions, a nerve integrity monitoring methodology has been developed for predicting correct cuff placement. Postoperative sonography remains a promising method for the future assessment of predictive markers in sUAS. © 2017 S. Karger AG, Basel.

BFH-OST, a new predictive screening tool for identifying osteoporosis in postmenopausal Han Chinese women

PubMed Central

Ma, Zhao; Yang, Yong; Lin, JiSheng; Zhang, XiaoDong; Meng, Qian; Wang, BingQiang; Fei, Qi

2016-01-01

Purpose To develop a simple new clinical screening tool to identify primary osteoporosis by dual-energy X-ray absorptiometry (DXA) in postmenopausal women and to compare its validity with the Osteoporosis Self-Assessment Tool for Asians (OSTA) in a Han Chinese population. Methods A cross-sectional study was conducted, enrolling 1,721 community-dwelling postmenopausal Han Chinese women. All the subjects completed a structured questionnaire and had their bone mineral density measured using DXA. Using logistic regression analysis, we assessed the ability of numerous potential risk factors examined in the questionnaire to identify women with osteoporosis. Based on this analysis, we build a new predictive model, the Beijing Friendship Hospital Osteoporosis Self-Assessment Tool (BFH-OST). Receiver operating characteristic curves were generated to compare the validity of the new model and OSTA in identifying postmenopausal women at increased risk of primary osteoporosis as defined according to the World Health Organization criteria. Results At screening, it was found that of the 1,721 subjects with DXA, 22.66% had osteoporosis and a further 47.36% had osteopenia. Of the items screened in the questionnaire, it was found that age, weight, height, body mass index, personal history of fracture after the age of 45 years, history of fragility fracture in either parent, current smoking, and consumption of three of more alcoholic drinks per day were all predictive of osteoporosis. However, age at menarche and menopause, years since menopause, and number of pregnancies and live births were irrelevant in this study. The logistic regression analysis and item reduction yielded a final tool (BFH-OST) based on age, body weight, height, and history of fracture after the age of 45 years. The BFH-OST index (cutoff =9.1), which performed better than OSTA, had a sensitivity of 73.6% and a specificity of 72.7% for identifying osteoporosis, with an area under the receiver operating

Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

PubMed

Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to

A systematic review of the factors predicting the interest in cosmetic plastic surgery.

PubMed

Milothridis, Panagiotis; Pavlidis, Leonidas; Haidich, Anna-Bettina; Panagopoulou, Efharis

2016-01-01

A systematic review of the literature was performed to clarify the psychosocial characteristics of patients who have an interest in cosmetic plastic surgery. Medical literature was reviewed by two independent researchers, and a third reviewer evaluated their results. Twelve studies addressing the predictors of interest in cosmetic surgery were finally identified and analysed. Interest in cosmetic surgery was associated with epidemiological factors, their social networks, their psychological characteristics, such as body image, self-esteem and other personality traits and for specific psychopathology and found that these may either positively or negatively predict their motivation to seek and undergo a cosmetic procedure. The review examined the psychosocial characteristics associated with an interest in cosmetic surgery. Understanding cosmetic patients' characteristics, motivation and expectation for surgery is an important aspect of their clinical care to identify those patients more likely to benefit most from the procedure.

Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.

PubMed

Evans, R Scott; Benuzillo, Jose; Horne, Benjamin D; Lloyd, James F; Bradshaw, Alejandra; Budge, Deborah; Rasmusson, Kismet D; Roberts, Colleen; Buckway, Jason; Geer, Norma; Garrett, Teresa; Lappé, Donald L

2016-09-01

Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients. Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient's risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients. The addition of NLP-identified HF patients increased the identification score's sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model's positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician's review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility. Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Factors predicting survival following noninvasive ventilation in amyotrophic lateral sclerosis.

PubMed

Peysson, S; Vandenberghe, N; Philit, F; Vial, C; Petitjean, T; Bouhour, F; Bayle, J Y; Broussolle, E

2008-01-01

The involvement of respiratory muscles is a major predicting factor for survival in amyotrophic lateral sclerosis (ALS). Recent studies show that noninvasive ventilation (NIV) can relieve symptoms of alveolar hypoventilation. However, factors predicting survival in ALS patients when treated with NIV need to be clarified. We conducted a retrospective study of 33 consecutive ALS patients receiving NIV. Ten patients had bulbar onset. We determined the median survivals from onset, diagnosis and initiation of NIV and factors predicting survival. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. The median initial and maximal total uses of NIV were 10 and 14 h/24h. The overall median survival from ALS onset was 34.2 months and worsened with increasing age and bulbar onset of the disease. The median survival from initiation of NIV was 8.4 months and was significantly poorer in patients with advanced age or with airway mucus accumulation. Survival from initiation of NIV was not influenced by respiratory parameters or bulbar symptoms. Advanced age at diagnosis and airway mucus accumulation represent poorer prognostic factors of ALS patients treated with NIV. NIV is a helpful treatment of sleep-disordered breathing, including patients with bulbar involvement. Copyright 2008 S. Karger AG, Basel.

Assessing vulnerability to drought: identifying underlying factors across Europe

NASA Astrophysics Data System (ADS)

Urquijo, Julia; Gonzalez Tánago, Itziar; Ballesteros, Mario; De Stefano, Lucia

2015-04-01

Drought is considered one of the most severe and damaging natural hazards in terms of people and sectors affected and associated losses. Drought is a normal and recurrent climatic phenomenon that occurs worldwide, although its spatial and temporal characteristics vary significantly among climates. In the case of Europe, in the last thirty years, the region has suffered several drought events that have caused estimated economic damages over a €100 billion and have affected almost 20% of its territory and population. In recent years, there has been a growing awareness among experts and authorities of the need to shift from a reactive crisis approach to a drought risk management approach, as well as of the importance of designing and implementing policies, strategies and plans at country and river basin levels to deal with drought. The identification of whom and what is vulnerable to drought is a central aspect of drought risk mitigation and planning and several authors agree that societal vulnerability often determines drought risk more than the actual precipitation shortfalls. The final aim of a drought vulnerability assessment is to identify the underlying sources of drought impact, in order to develop policy options that help to enhance coping capacity and therefore to prevent drought impact. This study identifies and maps factors underlying vulnerability to drought across Europe. The identification of factors influencing vulnerability starts from the analysis of past drought impacts in four European socioeconomic sectors. This analysis, along with an extensive literature review, led to the selection of vulnerability factors that are both relevant and adequate for the European context. Adopting the IPCC model, vulnerability factors were grouped to describe exposure, sensitivity and adaptive capacity. The aggregation of these components has resulted in the mapping of vulnerability to drought across Europe at NUTS02 level. Final results have been compared with

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics

PubMed Central

Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Kim, Dai-Jin; Choi, In Young

2017-01-01

Background: Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment. PMID:29280953

Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

PubMed

Haltigan, John D; Vaillancourt, Tracy

2016-03-01

To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

A retrospective analysis to identify the factors affecting infection in patients undergoing chemotherapy.

PubMed

Park, Ji Hyun; Kim, Hyeon-Young; Lee, Hanna; Yun, Eun Kyoung

2015-12-01

This study compares the performance of the logistic regression and decision tree analysis methods for assessing the risk factors for infection in cancer patients undergoing chemotherapy. The subjects were 732 cancer patients who were receiving chemotherapy at K university hospital in Seoul, Korea. The data were collected between March 2011 and February 2013 and were processed for descriptive analysis, logistic regression and decision tree analysis using the IBM SPSS Statistics 19 and Modeler 15.1 programs. The most common risk factors for infection in cancer patients receiving chemotherapy were identified as alkylating agents, vinca alkaloid and underlying diabetes mellitus. The logistic regression explained 66.7% of the variation in the data in terms of sensitivity and 88.9% in terms of specificity. The decision tree analysis accounted for 55.0% of the variation in the data in terms of sensitivity and 89.0% in terms of specificity. As for the overall classification accuracy, the logistic regression explained 88.0% and the decision tree analysis explained 87.2%. The logistic regression analysis showed a higher degree of sensitivity and classification accuracy. Therefore, logistic regression analysis is concluded to be the more effective and useful method for establishing an infection prediction model for patients undergoing chemotherapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of factor scores for predicting body weight from linear body measurements in three South African indigenous chicken breeds.

PubMed

Malomane, Dorcus Kholofelo; Norris, David; Banga, Cuthbert B; Ngambi, Jones W

2014-02-01

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

Carbide factor predicts rolling-element bearing fatigue life

NASA Technical Reports Server (NTRS)

Chevalier, J. L.; Zaretsky, E. V.

1973-01-01

Analysis was made to determine correlation between number and size of carbide particles and rolling-element fatigue. Correlation was established, and carbide factor was derived that can be used to predict fatigue life more effectively than such variables as heat treatment, chemical composition, and hardening mechanism.

Folate intake in a Swedish adult population: Food sources and predictive factors.

PubMed

Monteagudo, Celia; Scander, Henrik; Nilsen, Bente; Yngve, Agneta

2017-01-01

Introduction : Folate plays an important role in cell metabolism, but international studies show that intake is currently below recommendations, especially among women. The study objective was to identify folate food sources by food group, gender, and age group, and to identify factors influencing folate intake, based on food consumption data for Swedish adults in the 2010-11 Riksmaten study. M ethods : The sample included a representative Swedish population aged 18-80 years ( n  = 1657; 56.3% female). Food and nutrient intakes were estimated from self-reported food records during 4 consecutive days. Food consumption was categorized into 26 food groups. Stepwise regression was used to analyze food groups as folate sources for participants. Factors predicting the highest folate intake (third tertile) were determined by logistic regression analysis. Results : Vegetables and pulses represented the most important folate source for all age groups and both genders, especially in women aged 45-64 years (49.7% of total folate intake). The next folate source in importance was dairy products for the youngest group (18-30 years), bread for men, and fruit and berries for women. The likelihood of being in the highest tertile of folate intake (odds ratio = 1.69, 95% confidence interval 1.354-2.104) was higher for men. Influencing factors for folate intake in the highest tertile were low body mass index and high educational level in the men, and high educational level, vegetarian diet, organic product consumption, non-smoking, and alcohol consumption within recommendations in the women. Conclusion : This study describes the folate intake per food group of Swedish adults according to the 2010-11 Riksmaten survey, identifying vegetables and pulses as the most important source. Data obtained on factors related to folate consumption may be useful for the development of specific nutrition education programs to increase the intake of this vitamin in high-risk groups.

Folate intake in a Swedish adult population: Food sources and predictive factors

PubMed Central

Monteagudo, Celia; Scander, Henrik; Nilsen, Bente; Yngve, Agneta

2017-01-01

ABSTRACT Introduction: Folate plays an important role in cell metabolism, but international studies show that intake is currently below recommendations, especially among women. The study objective was to identify folate food sources by food group, gender, and age group, and to identify factors influencing folate intake, based on food consumption data for Swedish adults in the 2010–11 Riksmaten study. Methods: The sample included a representative Swedish population aged 18–80 years (n = 1657; 56.3% female). Food and nutrient intakes were estimated from self-reported food records during 4 consecutive days. Food consumption was categorized into 26 food groups. Stepwise regression was used to analyze food groups as folate sources for participants. Factors predicting the highest folate intake (third tertile) were determined by logistic regression analysis. Results: Vegetables and pulses represented the most important folate source for all age groups and both genders, especially in women aged 45–64 years (49.7% of total folate intake). The next folate source in importance was dairy products for the youngest group (18–30 years), bread for men, and fruit and berries for women. The likelihood of being in the highest tertile of folate intake (odds ratio = 1.69, 95% confidence interval 1.354–2.104) was higher for men. Influencing factors for folate intake in the highest tertile were low body mass index and high educational level in the men, and high educational level, vegetarian diet, organic product consumption, non-smoking, and alcohol consumption within recommendations in the women. Conclusion: This study describes the folate intake per food group of Swedish adults according to the 2010–11 Riksmaten survey, identifying vegetables and pulses as the most important source. Data obtained on factors related to folate consumption may be useful for the development of specific nutrition education programs to increase the intake of this vitamin in high

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

PubMed Central

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-01-01

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. PMID:25551518

Identifying environmental risk factors of cholera in a coastal area with geospatial technologies.

PubMed

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-12-29

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.

Predicting Employment in the Mental Health Treatment Study: Do Client Factors Matter?

PubMed

Metcalfe, Justin D; Drake, Robert E; Bond, Gary R

2017-05-01

For people with psychiatric disabilities, demographic characteristics and measures of clinical status are often used to allocate scarce employment services. This study examined a battery of potential client predictors of competitive employment, testing the hypothesis that evidence-based supported employment would mitigate the negative effects of poor work history, uncontrolled symptoms, substance abuse, and other client factors. In a secondary analysis of 2055 unemployed Social Security Disability Insurance beneficiaries with schizophrenia or affective disorders, we examined 20 baseline client factors as predictors of competitive employment. The analysis used logistic regression to identify significant client predictors and then examined interactions between significant predictors and receipt of evidence-based supported employment. Work history was a strong predictor of employment, and other client measures (fewer years on disability rolls, Hispanic ethnicity, and fewer physical health problems) were modestly predictive. Evidence-based supported employment mitigated negative client factors, including poor work history. Participants with a poor work history benefitted from supported employment even more than those with a recent work experience. Evidence-based supported employment helps people with serious mental illness, especially those with poor job histories, to obtain competitive employment. Factors commonly considered barriers to employment, such as diagnosis, substance use, hospitalization history, and misconceptions about disability benefits, often have little or no impact on competitive employment outcomes.

Analysis of risk factors to predict communicating hydrocephalus following gamma knife radiosurgery for intracranial schwannoma.

PubMed

Lee, Seunghoon; Seo, Seong-Wook; Hwang, Juyoung; Seol, Ho Jun; Nam, Do-Hyun; Lee, Jung-Il; Kong, Doo-Sik

2016-12-01

Communicating hydrocephalus (HCP) in vestibular schwannomas (VS) after gamma knife radiosurgery (GKRS) has been reported in the literature. However, little information about its incidence and risk factors after GKRS for intracranial schwannomas is yet available. The objective of this study was to identify the incidence and risk factors for developing communicating HCP after GKRS for intracranial schwannomas. We retrospectively reviewed a total of 702 patients with intracranial schwannomas who were treated with GKRS between January 2002 and December 2015. We investigated patients' age, gender, tumor origin, previous surgery history, tumor volume, marginal radiation dose, and presence of tumor control to identify associations with communicating HCP following GKRS. To make predictive models of communicating HCP, we performed Cox regression analyses and constructed a decision tree for risk factors. In total, 29 of the 702 patients (4.1%) developed communicating HCP following GKRS, which required ventriculo-peritoneal (VP) shunt surgery. Multivariate analyses indicated that age (P = 0.0011), tumor origin (P = 0.0438), and tumor volume (P < 0.0001) were significant predictors of communicating HCP in patients with intracranial schwannoma after GKRS. Using machine-learning methods, we fit an optimal predictive model. We found that developing communicating HCP following GKRS was most likely if the tumor was vestibular origin and had a volume ≥13.65 cm 3 . Communicating HCP is not a rare complication of GKRS for intracranial schwannomas. Under specific conditions, communicating HCP following GKRS is warranted for this patient group, and this patient group should be closely followed up. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Risk factors perceived predictive of ISA spread in Chile: applications to decision support.

PubMed

Gustafson, L; Antognoli, M; Lara Fica, M; Ibarra, R; Mancilla, J; Sandoval Del Valle, O; Enriquez Sais, R; Perez, A; Aguilar, D; Madrid, E; Bustos, P; Clement, A; Godoy, M G; Johnson, C; Remmenga, M

2014-11-01

Aquaculture is anticipated to be a critical element in future solutions to global food shortage. However, diseases can impede industry efficiency and sustainability. Consequently, diseases can and have led to dramatic re-structuring in industry or regulatory practices. The emergence of infectious salmon anemia (ISA) in Chile is one such example. As in other countries, many mitigations were instituted universally, and many incurred considerable costs as they introduced a new layer of coordination of farming activities of marine sites within common geographic areas (termed 'neighborhoods' or 'barrios'). The aggregate response led to a strong reduction in ISA incidence and impact. However, the relative value of individual mitigations is less clear, especially where response policies were universally applied and retrospective analyses are missing 'controls' (i.e., areas where a mitigation was not applied). Further, re-focusing policies around disease prevention following resolution of an outbreak is important to renew sustainable production; though, again, field data to guide this shift in purpose are often lacking. Expert panels can offer timely decision support in the absence of empirical data. We convened a panel of fish health experts to weight risk factors predictive of ISA virus (ISAV) introduction or spread between Atlantic salmon barrios in Chile. Barrios, rather than sites, were the unit of interest because many of the new mitigations operate at this level and few available studies examine their efficacy. Panelists identified barrio processing plant biosecurity, fallowing strategies, adult live fish transfers, fish and site density, smolt quality, hydrographic connection with other neighborhoods, presence of sea lice (Caligus rogercresseyi), and harvest vessel biosecurity as factors with the greatest predictive strength for ISAV virulent genotype ('HPR-deleted') occurrence. Fewer factors were considered predictive of ISAV HPR0 genotype ('HPR0') occurrence

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

PubMed

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Microarray-based SNP genotyping to identify genetic risk factors of triple-negative breast cancer (TNBC) in South Indian population.

PubMed

Aravind Kumar, M; Singh, Vineeta; Naushad, Shaik Mohammad; Shanker, Uday; Lakshmi Narasu, M

2018-05-01

In the view of aggressive nature of Triple-Negative Breast cancer (TNBC) due to the lack of receptors (ER, PR, HER2) and high incidence of drug resistance associated with it, a case-control association study was conducted to identify the contributing genetic risk factors for Triple-negative breast cancer (TNBC). A total of 30 TNBC patients and 50 age and gender-matched controls of Indian origin were screened for 9,00,000 SNP markers using microarray-based SNP genotyping approach. The initial PLINK association analysis (p < 0.01, MAF 0.14-0.44, OR 10-24) identified 28 non-synonymous SNPs and one stop gain mutation in the exonic region as possible determinants of TNBC risk. All the 29 SNPs were annotated using ANNOVAR. The interactions between these markers were evaluated using Multifactor dimensionality reduction (MDR) analysis. The interactions were in the following order: exm408776 > exm1278309 > rs316389 > rs1651654 > rs635538 > exm1292477. Recursive partitioning analysis (RPA) was performed to construct decision tree useful in predicting TNBC risk. As shown in this analysis, rs1651654 and exm585172 SNPs are found to be determinants of TNBC risk. Artificial neural network model was used to generate the Receiver operating characteristic curves (ROC), which showed high sensitivity and specificity (AUC-0.94) of these markers. To conclude, among the 9,00,000 SNPs tested, CCDC42 exm1292477, ANXA3 exm408776, SASH1 exm585172 are found to be the most significant genetic predicting factors for TNBC. The interactions among exm408776, exm1278309, rs316389, rs1651654, rs635538, exm1292477 SNPs inflate the risk for TNBC further. Targeted analysis of these SNPs and genes alone also will have similar clinical utility in predicting TNBC.

Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

PubMed Central

Siepel, Adam; Lis, John T.

2012-01-01

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

Factors predicting training transfer in health professionals participating in quality improvement educational interventions.

PubMed

Eid, Ahmed; Quinn, Doris

2017-01-31

Predictors of quality improvement (QI) training transfer are needed. This study aimed to identify these predictors among health professionals who participated in a QI training program held at a large hospital in the United States between 2005 and 2014. It also aimed to determine how these predictive factors facilitated or impeded QI training transfer. Following the Success Case Method, we used a screening survey to identify trainees with high and low levels of training transfer. We then conducted semistructured interviews with a sample of the survey respondents to document how training transfer was achieved and how lack of training transfer could be explained. The survey's response rate was 43%, with a Cronbach alpha of 0.89. We then conducted a thematic analysis of the interview transcripts of 16 physicians. The analysis revealed 3 categories of factors influencing the transfer of QI training: trainee characteristics, training course, and work environment. Relevant trainee characteristics included attitude toward change, motivation, mental processing skills, interpersonal skills, and the personality characteristics curiosity, humility, conscientiousness, resilience, wisdom, and positivity. The training project, team-based learning, and lectures were identified as relevant aspects of the training course. Work culture, work relationships, and resources were subthemes of the work environment category. We identified several QI training transfer predictors in our cohort of physicians. We hypothesize that some of these predictors may be more relevant to QI training transfer. Our results will help organizational leaders select trainees who are most likely to transfer QI training and to ensure that their work environments are conducive to QI training transfer.

A modified reverse one-hybrid screen identifies transcriptional activation in Phyochrome-Interacting Factor 3

USDA-ARS?s Scientific Manuscript database

Transcriptional activation domains (TAD) are difficult to predict and identify, since they are not conserved and have little consensus. Here, we describe a yeast-based screening method that is able to identify individual amino acid residues involved in transcriptional activation in a high throughput...

Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).

PubMed

Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T

2018-02-26

As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2  = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.

[Predictive factors of the outcomes of prenatal hydronephrosis.

PubMed

Bragagnini, Paolo; Estors, Blanca; Delgado, Reyes; Rihuete, Miguel Ángel; Gracia, Jesús

2016-12-01

To determine prenatal and postnatal independent predictors of poor outcome, spontaneous resolution, or the need for surgery in patients with prenatal hydronephrosis. We performed a retrospective study of patients with prenatal hydronephrosis. The renal pelvis APD was measured in the third prenatal trimester ultrasound, as well as in the first and second postnatal ultrasound. Other variables were taken into account, both prenatal and postnatal. For statistical analysis we used Student t-test, chi-square test, survival analysis, logrank test, and ROC curves. We included 218 patients with 293 renal units (RU). Of these, 147/293 (50.2%) RU were operated. 76/293 (25.9%) RU had spontaneous resolution and other 76/293 (25.9%) RU had poor outcome. As risk factors for surgery we found low birth weight (OR 3.84; 95% CI 1.24-11.84), prematurity (OR 4.17; 95% CI 1.35-12.88), duplication (OR 4.99; 95% CI 2.21-11.23) and the presence of nephrourological underlying pathology (OR 53.54; 95% CI 26.23-109.27). For the non-spontaneous resolution, we found as risk factors the alterations of amniotic fluid volume (RR 1.46; 95% CI 1.33-1.60) as well as the underlying nephrourological pathology and duplication. In the poor outcome, we found as risk factors the alterations of amniotic fluid volume (OR 4.54; 95% CI 1.31-15.62), the presence of nephrourological pathology (OR 4.81 95% CI 2.60-8.89) and RU that was operated (OR 4.23, 95% CI 2.35-7.60). The APD of the renal pelvis in all three ultrasounds were reliable for surgery prediction (area under the curve 0.65; 0.82; 0.71) or spontaneous resolution (area under the curve 0.80; 0.91; 0.80), only the first postnatal ultrasound has predictive value in the poor outcome (area under the curve 0.73). The higher sensitivity and specificity of the APD as predictor value was on the first postnatal ultrasound, 14.60 mm for surgery; 11.35 mm for spontaneous resolution and 15.50 mm for poor outcome. The higher APD in the renal pelvis in any of the

Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

PubMed

Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

2016-10-01

Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Clinical prediction model to identify vulnerable patients in ambulatory surgery: towards optimal medical decision-making.

PubMed

Mijderwijk, Herjan; Stolker, Robert Jan; Duivenvoorden, Hugo J; Klimek, Markus; Steyerberg, Ewout W

2016-09-01

Ambulatory surgery patients are at risk of adverse psychological outcomes such as anxiety, aggression, fatigue, and depression. We developed and validated a clinical prediction model to identify patients who were vulnerable to these psychological outcome parameters. We prospectively assessed 383 mixed ambulatory surgery patients for psychological vulnerability, defined as the presence of anxiety (state/trait), aggression (state/trait), fatigue, and depression seven days after surgery. Three psychological vulnerability categories were considered-i.e., none, one, or multiple poor scores, defined as a score exceeding one standard deviation above the mean for each single outcome according to normative data. The following determinants were assessed preoperatively: sociodemographic (age, sex, level of education, employment status, marital status, having children, religion, nationality), medical (heart rate and body mass index), and psychological variables (self-esteem and self-efficacy), in addition to anxiety, aggression, fatigue, and depression. A prediction model was constructed using ordinal polytomous logistic regression analysis, and bootstrapping was applied for internal validation. The ordinal c-index (ORC) quantified the discriminative ability of the model, in addition to measures for overall model performance (Nagelkerke's R (2) ). In this population, 137 (36%) patients were identified as being psychologically vulnerable after surgery for at least one of the psychological outcomes. The most parsimonious and optimal prediction model combined sociodemographic variables (level of education, having children, and nationality) with psychological variables (trait anxiety, state/trait aggression, fatigue, and depression). Model performance was promising: R (2)  = 30% and ORC = 0.76 after correction for optimism. This study identified a substantial group of vulnerable patients in ambulatory surgery. The proposed clinical prediction model could allow healthcare

Evaluation of non-negative matrix factorization of grey matter in age prediction.

PubMed

Varikuti, Deepthi P; Genon, Sarah; Sotiras, Aristeidis; Schwender, Holger; Hoffstaedter, Felix; Patil, Kaustubh R; Jockwitz, Christiane; Caspers, Svenja; Moebus, Susanne; Amunts, Katrin; Davatzikos, Christos; Eickhoff, Simon B

2018-06-01

The relationship between grey matter volume (GMV) patterns and age can be captured by multivariate pattern analysis, allowing prediction of individuals' age based on structural imaging. Raw data, voxel-wise GMV and non-sparse factorization (with Principal Component Analysis, PCA) show good performance but do not promote relatively localized brain components for post-hoc examinations. Here we evaluated a non-negative matrix factorization (NNMF) approach to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations. This examination was performed using three datasets: a multi-site cohort of life-span healthy adults, a single site cohort of older adults and clinical samples from the ADNI dataset with healthy subjects, participants with Mild Cognitive Impairment and patients with Alzheimer's disease (AD) subsamples. T1-weighted images were preprocessed with VBM8 standard settings to compute GMV values after normalization, segmentation and modulation for non-linear transformations only. Non-negative matrix factorization was computed on the GM voxel-wise values for a range of granularities (50-690 components) and LASSO (Least Absolute Shrinkage and Selection Operator) regression were used for age prediction. First, we compared the performance of our data compression procedure (i.e., NNMF) to various other approaches (i.e., uncompressed VBM data, PCA-based factorization and parcellation-based compression). We then investigated the impact of the granularity on the accuracy of age prediction, as well as the transferability of the factorization and model generalization across datasets. We finally validated our framework by examining age prediction in ADNI samples. Our results showed that our framework favorably compares with other approaches. They also demonstrated that the NNMF based factorization derived from one dataset could be efficiently applied to compress VBM data of another dataset and that

Individual Factors Predicting Mental Health Court Diversion Outcome

ERIC Educational Resources Information Center

Verhaaff, Ashley; Scott, Hannah

2015-01-01

Objective: This study examined which individual factors predict mental health court diversion outcome among a sample of persons with mental illness participating in a postcharge diversion program. Method: The study employed secondary analysis of existing program records for 419 persons with mental illness in a court diversion program. Results:…

Psychosocial Factors Predicting First-Year College Student Success

ERIC Educational Resources Information Center

Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

2013-01-01

This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

Learning Approaches, Demographic Factors to Predict Academic Outcomes

ERIC Educational Resources Information Center

Nguyen, Tuan Minh

2016-01-01

Purpose: The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors. Design/Methodology/Approach: ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An…

The Role of Socioeconomic Factors in the Prediction of Persistence in Puerto Rico

ERIC Educational Resources Information Center

Dika, Sandra L.

2014-01-01

While research literature suggests that socioeconomic factors play a role in predicting educational attainment, very little research has been done to examine these relationships using data from Puerto Rico. A logistic regression approach was adopted to investigate the extent to which family and school socioeconomic factors predict retention from…

Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study.

PubMed

Seyednasrollah, Fatemeh; Mäkelä, Johanna; Pitkänen, Niina; Juonala, Markus; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma; Kelly, Tanika; Li, Changwei; Bazzano, Lydia; Elo, Laura L; Raitakari, Olli T

2017-06-01

Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P <0.0001) and validation data (AUC=0.769 versus AUC=0.747, P =0.026). WGRS97 improved the accuracy in training (AUC=0.782 versus AUC=0.744, P <0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P =0.785). Higher WGRS19 associated with higher body mass index at 9 years and WGRS97 at 6 years. Replication in BHS confirmed our findings that WGRS19 and WGRS97 are associated with body mass index. WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. © 2017 American Heart Association, Inc.

Predictive value of magnetic resonance for identifying neurovascular compressions in trigeminal neuralgia.

PubMed

Ruiz-Juretschke, F; Guzmán-de-Villoria, J G; García-Leal, R; Sañudo, J R

2017-05-23

Microvascular decompression (MVD) is accepted as the only aetiological surgical treatment for refractory classic trigeminal neuralgia (TN). There is therefore increasing interest in establishing the diagnostic and prognostic value of identifying neurovascular compressions (NVC) using preoperative high-resolution three-dimensional magnetic resonance (MRI) in patients with classic TN who are candidates for surgery. This observational study includes a series of 74 consecutive patients with classic TN treated with MVD. All patients underwent a preoperative three-dimensional high-resolution MRI with DRIVE sequences to diagnose presence of NVC, as well as the degree, cause, and location of compressions. MRI results were analysed by doctors blinded to surgical findings and subsequently compared to those findings. After a minimum follow-up time of six months, we assessed the surgical outcome and graded it on the Barrow Neurological Institute pain intensity score (BNI score). The prognostic value of the preoperative MRI was estimated using binary logistic regression. Preoperative DRIVE MRI sequences showed a sensitivity of 95% and a specificity of 87%, with a 98% positive predictive value and a 70% negative predictive value. Moreover, Cohen's kappa (CK) indicated a good level of agreement between radiological and surgical findings regarding presence of NVC (CK 0.75), type of compression (CK 0.74) and the site of compression (CK 0.72), with only moderate agreement as to the degree of compression (CK 0.48). After a mean follow-up of 29 months (range 6-100 months), 81% of the patients reported pain control with or without medication (BNI score i-iiiI). Patients with an excellent surgical outcome, i.e. without pain and off medication (BNI score i), made up 66% of the total at the end of follow-up. Univariate analysis using binary logistic regression showed that a diagnosis of NVC on the preoperative MRI was a favorable prognostic factor that significantly increased the odds of

Systematic mutagenesis of genes encoding predicted autotransported proteins of Burkholderia pseudomallei identifies factors mediating virulence in mice, net intracellular replication and a novel protein conferring serum resistance.

PubMed

Lazar Adler, Natalie R; Stevens, Mark P; Dean, Rachel E; Saint, Richard J; Pankhania, Depesh; Prior, Joann L; Atkins, Timothy P; Kessler, Bianca; Nithichanon, Arnone; Lertmemongkolchai, Ganjana; Galyov, Edouard E

2015-01-01

Burkholderia pseudomallei is the causative agent of the severe tropical disease melioidosis, which commonly presents as sepsis. The B. pseudomallei K96243 genome encodes eleven predicted autotransporters, a diverse family of secreted and outer membrane proteins often associated with virulence. In a systematic study of these autotransporters, we constructed insertion mutants in each gene predicted to encode an autotransporter and assessed them for three pathogenesis-associated phenotypes: virulence in the BALB/c intra-peritoneal mouse melioidosis model, net intracellular replication in J774.2 murine macrophage-like cells and survival in 45% (v/v) normal human serum. From the complete repertoire of eleven autotransporter mutants, we identified eight mutants which exhibited an increase in median lethal dose of 1 to 2-log10 compared to the isogenic parent strain (bcaA, boaA, boaB, bpaA, bpaC, bpaE, bpaF and bimA). Four mutants, all demonstrating attenuation for virulence, exhibited reduced net intracellular replication in J774.2 macrophage-like cells (bimA, boaB, bpaC and bpaE). A single mutant (bpaC) was identified that exhibited significantly reduced serum survival compared to wild-type. The bpaC mutant, which demonstrated attenuation for virulence and net intracellular replication, was sensitive to complement-mediated killing via the classical and/or lectin pathway. Serum resistance was rescued by in trans complementation. Subsequently, we expressed recombinant proteins of the passenger domain of four predicted autotransporters representing each of the phenotypic groups identified: those attenuated for virulence (BcaA), those attenuated for virulence and net intracellular replication (BpaE), the BpaC mutant with defects in virulence, net intracellular replication and serum resistance and those displaying wild-type phenotypes (BatA). Only BcaA and BpaE elicited a strong IFN-γ response in a restimulation assay using whole blood from seropositive donors and were

Predicting the Unpredictable? Identifying High-Risk versus Low-Risk Parents with Intellectual Disabilities

ERIC Educational Resources Information Center

McGaw, Sue; Scully, Tamara; Pritchard, Colin

2010-01-01

Objectives: This study set out to identify risk factors affecting parents with intellectual disabilities (IDs) by determining: (i) whether perception of family support differs between parents with IDs, referring professionals, and a specialist parenting service; (ii) whether multivariate familial and demographic factors differentiates "high-risk"…

Predicting the Risk of Clostridium difficile Infection upon Admission: A Score to Identify Patients for Antimicrobial Stewardship Efforts.

PubMed

Kuntz, Jennifer L; Smith, David H; Petrik, Amanda F; Yang, Xiuhai; Thorp, Micah L; Barton, Tracy; Barton, Karen; Labreche, Matthew; Spindel, Steven J; Johnson, Eric S

2016-01-01

Increasing morbidity and health care costs related to Clostridium difficile infection (CDI) have heightened interest in methods to identify patients who would most benefit from interventions to mitigate the likelihood of CDI. To develop a risk score that can be calculated upon hospital admission and used by antimicrobial stewards, including pharmacists and clinicians, to identify patients at risk for CDI who would benefit from enhanced antibiotic review and patient education. We assembled a cohort of Kaiser Permanente Northwest patients with a hospital admission from July 1, 2005, through December 30, 2012, and identified CDI in the six months following hospital admission. Using Cox regression, we constructed a score to identify patients at high risk for CDI on the basis of preadmission characteristics. We calculated and plotted the observed six-month CDI risk for each decile of predicted risk. We identified 721 CDIs following 54,186 hospital admissions-a 6-month incidence of 13.3 CDIs/1000 patient admissions. Patients with the highest predicted risk of CDI had an observed incidence of 53 CDIs/1000 patient admissions. The score differentiated between patients who do and do not develop CDI, with values for the extended C-statistic of 0.75. Predicted risk for CDI agreed closely with observed risk. Our risk score accurately predicted six-month risk for CDI using preadmission characteristics. Accurate predictions among the highest-risk patient subgroups allow for the identification of patients who could be targeted for and who would likely benefit from review of inpatient antibiotic use or enhanced educational efforts at the time of discharge planning.

Are prostatic calculi independent predictive factors of lower urinary tract symptoms?

PubMed Central

Park, Sung-Woo; Nam, Jong-Kil; Lee, Sang-Don; Chung, Moon-Kee

2010-01-01

We determined the correlation between prostatic calculi and lower urinary tract symptoms (LUTS), as well as the predisposing factors of prostatic calculi. Of the 1 527 patients who presented at our clinic for LUTS, 802 underwent complete evaluations, including transrectal ultrasonography, voided bladder-3 specimen and international prostatic symptoms score (IPSS). A total of 335 patients with prostatic calculi and 467 patients without prostatic calculi were divided into calculi and no calculi groups, respectively. Predictive factors of severe LUTS and prostatic calculi were determined using uni/multivariate analysis. The overall IPSS score was 15.7 ± 9.2 and 14.1 ± 9.2 in the calculi and no calculi group, respectively (P = 0.013). The maximum flow rate was 12.1 ± 6.9 and 14.2 ± 8.2 mL s−1 in the calculi and no calculi group, respectively (P = 0.003). On univariate analysis for predicting factors of severe LUTS, differences on age (P = 0.042), prostatic calculi (P = 0.048) and prostatitis (P = 0.018) were statistically significant. However, on multivariate analysis, no factor was significant. On multivariate analysis for predisposing factors of prostatic calculi, differences on age (P < 0.001) and prostate volume (P = 0.001) were significant. To our knowledge, patients who have prostatic calculi complain of more severe LUTS. However, prostatic calculi are not an independent predictive factor of severe LUTS. Therefore, men with prostatic calculi have more severe LUTS not only because of prostatic calculi but also because of age and other factors. In addition, old age and large prostate volume are independent predisposing factors for prostatic calculi. PMID:19966831

Are prostatic calculi independent predictive factors of lower urinary tract symptoms?

PubMed

Park, Sung-Woo; Nam, Jong-Kil; Lee, Sang-Don; Chung, Moon-Kee

2010-03-01

We determined the correlation between prostatic calculi and lower urinary tract symptoms (LUTS), as well as the predisposing factors of prostatic calculi. Of the 1 527 patients who presented at our clinic for LUTS, 802 underwent complete evaluations, including transrectal ultrasonography, voided bladder-3 specimen and international prostatic symptoms score (IPSS). A total of 335 patients with prostatic calculi and 467 patients without prostatic calculi were divided into calculi and no calculi groups, respectively. Predictive factors of severe LUTS and prostatic calculi were determined using uni/multivariate analysis. The overall IPSS score was 15.7 +/- 9.2 and 14.1 +/- 9.2 in the calculi and no calculi group, respectively (P = 0.013). The maximum flow rate was 12.1 +/- 6.9 and 14.2 +/- 8.2 mL s(-1) in the calculi and no calculi group, respectively (P = 0.003). On univariate analysis for predicting factors of severe LUTS, differences on age (P = 0.042), prostatic calculi (P = 0.048) and prostatitis (P = 0.018) were statistically significant. However, on multivariate analysis, no factor was significant. On multivariate analysis for predisposing factors of prostatic calculi, differences on age (P < 0.001) and prostate volume (P = 0.001) were significant. To our knowledge, patients who have prostatic calculi complain of more severe LUTS. However, prostatic calculi are not an independent predictive factor of severe LUTS. Therefore, men with prostatic calculi have more severe LUTS not only because of prostatic calculi but also because of age and other factors. In addition, old age and large prostate volume are independent predisposing factors for prostatic calculi.

Data mining model using simple and readily available factors could identify patients at high risk for hepatocellular carcinoma in chronic hepatitis C.

PubMed

Kurosaki, Masayuki; Hiramatsu, Naoki; Sakamoto, Minoru; Suzuki, Yoshiyuki; Iwasaki, Manabu; Tamori, Akihiro; Matsuura, Kentaro; Kakinuma, Sei; Sugauchi, Fuminaka; Sakamoto, Naoya; Nakagawa, Mina; Izumi, Namiki

2012-03-01

Assessment of the risk of hepatocellular carcinoma (HCC) development is essential for formulating personalized surveillance or antiviral treatment plan for chronic hepatitis C. We aimed to build a simple model for the identification of patients at high risk of developing HCC. Chronic hepatitis C patients followed for at least 5 years (n=1003) were analyzed by data mining to build a predictive model for HCC development. The model was externally validated using a cohort of 1072 patients (472 with sustained virological response (SVR) and 600 with nonSVR to PEG-interferon plus ribavirin therapy). On the basis of factors such as age, platelet, albumin, and aspartate aminotransferase, the HCC risk prediction model identified subgroups with high-, intermediate-, and low-risk of HCC with a 5-year HCC development rate of 20.9%, 6.3-7.3%, and 0-1.5%, respectively. The reproducibility of the model was confirmed through external validation (r(2)=0.981). The 10-year HCC development rate was also significantly higher in the high-and intermediate-risk group than in the low-risk group (24.5% vs. 4.8%; p<0.0001). In the high-and intermediate-risk group, the incidence of HCC development was significantly reduced in patients with SVR compared to those with nonSVR (5-year rate, 9.5% vs. 4.5%; p=0.040). The HCC risk prediction model uses simple and readily available factors and identifies patients at a high risk of HCC development. The model allows physicians to identify patients requiring HCC surveillance and those who benefit from IFN therapy to prevent HCC. Copyright © 2011 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Father involvement: Identifying and predicting family members' shared and unique perceptions.

PubMed

Dyer, W Justin; Day, Randal D; Harper, James M

2014-08-01

Father involvement research has typically not recognized that reports of involvement contain at least two components: 1 reflecting a view of father involvement that is broadly recognized in the family, and another reflecting each reporter's unique perceptions. Using a longitudinal sample of 302 families, this study provides a first examination of shared and unique views of father involvement (engagement and warmth) from the perspectives of fathers, children, and mothers. This study also identifies influences on these shared and unique perspectives. Father involvement reports were obtained when the child was 12 and 14 years old. Mother reports overlapped more with the shared view than father or child reports. This suggests the mother's view may be more in line with broadly recognized father involvement. Regarding antecedents, for fathers' unique view, a compensatory model partially explains results; that is, negative aspects of family life were positively associated with fathers' unique view. Children's unique view of engagement may partially reflect a sentiment override with father antisocial behaviors being predictive. Mothers' unique view of engagement was predicted by father and mother work hours and her unique view of warmth was predicted by depression and maternal gatekeeping. Taken, together finding suggests a far more nuanced view of father involvement should be considered.

Can Predictive Modeling Identify Head and Neck Oncology Patients at Risk for Readmission?

PubMed

Manning, Amy M; Casper, Keith A; Peter, Kay St; Wilson, Keith M; Mark, Jonathan R; Collar, Ryan M

2018-05-01

Objective Unplanned readmission within 30 days is a contributor to health care costs in the United States. The use of predictive modeling during hospitalization to identify patients at risk for readmission offers a novel approach to quality improvement and cost reduction. Study Design Two-phase study including retrospective analysis of prospectively collected data followed by prospective longitudinal study. Setting Tertiary academic medical center. Subjects and Methods Prospectively collected data for patients undergoing surgical treatment for head and neck cancer from January 2013 to January 2015 were used to build predictive models for readmission within 30 days of discharge using logistic regression, classification and regression tree (CART) analysis, and random forests. One model (logistic regression) was then placed prospectively into the discharge workflow from March 2016 to May 2016 to determine the model's ability to predict which patients would be readmitted within 30 days. Results In total, 174 admissions had descriptive data. Thirty-two were excluded due to incomplete data. Logistic regression, CART, and random forest predictive models were constructed using the remaining 142 admissions. When applied to 106 consecutive prospective head and neck oncology patients at the time of discharge, the logistic regression model predicted readmissions with a specificity of 94%, a sensitivity of 47%, a negative predictive value of 90%, and a positive predictive value of 62% (odds ratio, 14.9; 95% confidence interval, 4.02-55.45). Conclusion Prospectively collected head and neck cancer databases can be used to develop predictive models that can accurately predict which patients will be readmitted. This offers valuable support for quality improvement initiatives and readmission-related cost reduction in head and neck cancer care.

Predictive factors of depression symptoms among adolescents in the 18-month follow-up after Wenchuan earthquake in China.

PubMed

Chui, Cheryl H K; Ran, Mao-Sheng; Li, Rong-Hui; Fan, Mei; Zhang, Zhen; Li, Yuan-Hao; Ou, Guo Jing; Jiang, Zhe; Tong, Yu-Zhen; Fang, Ding-Zhi

2017-02-01

It is unclear about the change and risk factors of depression among adolescent survivors after earthquake. This study aimed to explore the change of depression, and identify the predictive factors of depression among adolescent survivors after the 2008 Wenchuan earthquake in China. The depression among high school students at 6, 12 and 18 months after the Wenchuan earthquake were investigated. The Beck Depression Inventory (BDI) was used in this study to assess the severity of depression. Subjects included 548 student survivors in an affected high school. The rates of depression among the adolescent survivors at 6-, 12- and 18-month after the earthquake were 27.3%, 42.9% and 33.3%, respectively, for males, and 42.9%, 61.9% and 53.4%, respectively, for females. Depression symptoms, trauma-related self-injury, suicidal ideation and PTSD symptoms at the 6-month follow-up were significant predictive factors for depression at the 18-month time interval following the earthquake. This study highlights the need for considering disaster-related psychological sequela and risk factors of depression symptoms in the planning and implementation of mental health services. Long-term mental and psychological supports for victims of natural disasters are imperative.

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph

PubMed Central

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks’ price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds. PMID:27893780

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

PubMed

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

Predicting patient aggression against nurses in all hospital areas.

PubMed

Chapman, Rose; Perry, Laura; Styles, Irene; Combs, Shane

Workplace violence directed at nurses is an alarming phenomenon across the world. To intervene and manage these episodes as quickly as possible, nurses need to identify those factors that can alert them to the possibility that a violent event may occur. However, frameworks to help nurses predict episodes of workplace violence are limited. This article presents the findings of a study of nurses experience of workplace violence and identifies those factors and behaviours that nurses reported as indicating that an episode of workplace violence is likely to occur. A case study approach was used involving quantitative and qualitative data. One hundred and thirteen questionnaires were completed and 20 interviews were conducted in 2006. Nurses identified nine behaviours and factors that assist them to predict workplace violence. The first five factors comprising staring, tone of voice, anxiety, mumbling and pacing (STAMP) matched those identified in a previous study. However, the last four factors, comprising emotions, disease process, assertive/non-assertive behaviour and resources (EDAR) expand upon that study. Therefore, the acronym STAMPEDAR was used to classify the nine components. Being alert to these behaviours and factors may help nurses predict that an episode of workplace violence is likely to occur.

Definition of Failed Induction of Labor and Its Predictive Factors: Two Unsolved Issues of an Everyday Clinical Situation.

PubMed

Baños, Núria; Migliorelli, Federico; Posadas, Eduardo; Ferreri, Janisse; Palacio, Montse

2015-01-01

The objectives of this review were to identify the predictive factors of induction of labor (IOL) failure or success as well as to highlight the current heterogeneity regarding the definition and diagnosis of failed IOL. Only studies in which the main or secondary outcome was failed IOL, defined as not entering the active phase of labor after 24 h of prostaglandin administration ± 12 h of oxytocin infusion, were included in the review. The data collected were: study design, definition of failed IOL, induction method, IOL indications, failed IOL rate, cesarean section because of failed IOL and predictors of failed IOL. The database search detected 507 publications. The main reason for exclusion was that the primary or secondary outcomes were not the predetermined definition of failed IOL (not achieving active phase of labor). Finally, 7 studies were eligible. The main predictive factors identified in the review were cervical status, evaluated by the Bishop score or cervical length. Failed IOL should be defined as the inability to achieve the active phase of labor, considering that the definition of IOL is to enter the active phase of labor. A universal definition of failed IOL is an essential requisite to analyze and obtain solid results and conclusions on this issue. An important finding of this review is that only 7 of all the studies reviewed assessed achieving the active phase of labor as a primary or secondary IOL outcome. Another conclusion is that cervical status remains the most important predictor of IOL outcome, although the value of the parameters explored up to now is limited. To find or develop predictive tools to identify those women exposed to IOL who may not reach the active phase of labor is crucial to minimize the risks and costs associated with IOL failure while opening a great opportunity for investigation. Therefore, other predictive tools should be studied in order to improve IOL outcome in terms of health and economic burden. © 2015 S

Clinical factors predicting bacteremia in low-risk febrile neutropenia after anti-cancer chemotherapy.

PubMed

Ha, Young Eun; Song, Jae-Hoon; Kang, Won Ki; Peck, Kyong Ran; Chung, Doo Ryeon; Kang, Cheol-In; Joung, Mi-Kyong; Joo, Eun-Jeong; Shon, Kyung Mok

2011-11-01

Bacteremia is an important clinical condition in febrile neutropenia that can cause clinical failure of antimicrobial therapy. The purpose of this study was to investigate the clinical factors predictive of bacteremia in low-risk febrile neutropenia at initial patient evaluation. We performed a retrospective cohort study in a university hospital in Seoul, Korea, between May 1995 and May 2007. Patients who met the criteria of low-risk febrile neutropenia at the time of visit to emergency department after anti-cancer chemotherapy were included in the analysis. During the study period, 102 episodes of bacteremia were documented among the 993 episodes of low-risk febrile neutropenia. Single gram-negative bacteremia was most frequent. In multivariate regression analysis, initial body temperature ≥39°C, initial hypotension, presence of clinical sites of infection, presence of central venous catheter, initial absolute neutrophil count <50/mm(3), and the CRP ≥10 mg/dL were statistically significant predictors for bacteremia. A scoring system using these variables was derived and the likelihood of bacteremia was well correlated with the score points with AUC under ROC curve of 0.785. Patients with low score points had low rate of bacteremia, thus, would be candidates for outpatient-based or oral antibiotic therapy. We identified major clinical factors that can predict bacteremia in low-risk febrile neutropenia.

Factors predicting clinical nurses' willingness to care for Ebola virus disease-infected patients: A cross-sectional, descriptive survey.

PubMed

Kim, Ji Soo; Choi, Jeong Sil

2016-09-01

The purpose of this study was to identify factors predicting clinical nurses' willingness to care for Ebola virus disease (EVD)-infected patients. Data were collected from 179 nurses employed at 10 hospitals in Korea using self-reporting questionnaires. Only 26.8% of the participants were willing to care for EVD-infected patients. Factors predicting their willingness to provide care were their belief in public service, risk perception, and age. Nurses' willingness to provide care was high when their belief in public service was high, low when their risk perception was high, and low as their age increased. In order to strengthen nurses' willingness to care for EVD-infected patients, education that targets the enhancement of belief in public service should be included in nurse training. Efforts should be directed toward lowering EVD risk perception and developing systematic responses through government-led organized support. © 2015 Wiley Publishing Asia Pty Ltd.

Predictive Factors for Beneficial Response to Interferon-alfa Therapy in Chronic Hepatitis C

PubMed Central

Yoon, Seung-Kew; Kim, Sung Soo; Park, Young Min; Shim, Kyu Sik; Lee, Chang Don; Sun, Hee Sik; Park, Doo Ho; Kim, Boo Sung; Ryu, Wang Shick; Cho, Joong Myung

1995-01-01

Objectives: Interferon is the only established teatment for chronic hepatitis C but the host-dependent or virus-related factors affecting the response rate to interferon therapy are not yet dear. The purpose of this study was to investigate the factors predictive of response to interferon-alfa therapy in chronic hepatitis C. Methods: Twenty-five consecutive patients with chronic hepatitis C were randomized to three regimens of interferon-alfa: group A (n=7, 3MU every day for 3 months), group B (n=8, 3MU every other day for 3 months) and group C (n=10, 3MU every other day for 6 months), We quantified serum HC RNA levels by competitive reverse transcription-polymerase chain reaction (RT-PCR)and performed HCV genotyping using type-specific primers deduced from the NS5 region of the HCV genome. We also attempted to identify which demographic, biochemical and histologic factors in addition to virus-related factors would significantly predict beneficial response to interferon by multivariate analysis. Results: Sustained responders were 8 (36.4%), nonsustained responders were 2 (9.1%) and nonresponders were 12 (54.5%) of 22 patients who had received complete therapy. The initial HCV RNA level (logarithmic transformed copy numbers per ml of serum)in sustained responders (5.75±0.39) was significantly lower than that of nonsustained responders (6.80±0.71)and nonresponders (6.70±0.52) (p<0.05). In multivariate multiple logistic regression analysis, the serum HCV RNA level before therapy was only the independent predictor of a sustained response to interferon-alfa therapy (p=0.001). Conclusions: Serum HCV RNA level before therapy was the most useful predictor of a sustained response to interferon-alfa therapy for chronic hepatitis C. PMID:7495780

Gender identity outcomes in children with disorders/differences of sex development: Predictive factors.

PubMed

Bakula, Dana M; Mullins, Alexandria J; Sharkey, Christina M; Wolfe-Christensen, Cortney; Mullins, Larry L; Wisniewski, Amy B

2017-06-01

Disorders/differences of sex development (DSD) comprise multiple congenital conditions in which chromosomal, gonadal, and/or anatomical sex are discordant. The prediction of future gender identity (i.e., self-identifying as male, female, or other) in children with DSD can be imprecise, and current knowledge about the development of gender identity in people with, and without DSD, is limited. However, sex of rearing is the strongest predictor of gender identity for the majority of individuals with various DSD conditions. When making decisions regarding sex of rearing biological factors (e.g., possession of a Y chromosome, degree and duration of pre- and postnatal androgen exposure, phenotypic presentation of the external genitalia, and fertility potential), social and cultural factors, as well as quality of life should be considered. Information on gender identity outcomes across a range of DSD diagnoses is presented to aid in sex of rearing assignment. Copyright © 2017 Elsevier Inc. All rights reserved.

Utility of antenatal clinical factors for prediction of postpartum outcomes in women with gestational diabetes mellitus (GDM).

PubMed

Ingram, Emily R; Robertson, Iain K; Ogden, Kathryn J; Dennis, Amanda E; Campbell, Joanne E; Corbould, Anne M

2017-06-01

Gestational diabetes mellitus (GDM) is associated with life-long increased risk of type 2 diabetes: affected women are advised to undergo oral glucose tolerance testing (OGTT) at 6-12 weeks postpartum, then glucose screening every 1-3 years. We investigated whether in women with GDM, antenatal clinical factors predicted postpartum abnormal glucose tolerance and compliance with screening. In women with GDM delivering 2007 to mid-2009 in a single hospital, antenatal/obstetric data and glucose tests at 6-12 weeks postpartum and during 5.5 years post-pregnancy were retrospectively collected. Predictors of return for testing and abnormal glucose tolerance were identified using multivariate analysis. Of 165 women, 117 (70.9%) returned for 6-12 week postpartum OGTT: 23 (19.6%) were abnormal. Smoking and parity, independent of socioeconomic status, were associated with non-return for testing. Fasting glucose ≥5.4 mmol/L on pregnancy OGTT predicted both non-return for testing and abnormal OGTT. During 5.5 years post-pregnancy, 148 (89.7%) women accessed glucose screening: nine (6.1%) developed diabetes, 33 (22.3%) had impaired fasting glucose / impaired glucose tolerance. Predictors of abnormal glucose tolerance were fasting glucose ≥5.4 mmol/L and 2-h glucose ≥9.3 mmol/L on pregnancy OGTT (~2.5-fold increased risk), and polycystic ovary syndrome (~3.4 fold increased risk). Risk score calculation, based on combined antenatal factors, did not improve predictions. Antenatal clinical factors were modestly predictive of return for testing and abnormal glucose tolerance post-pregnancy in women with GDM. Risk score calculations were ineffective in predicting outcomes: risk scores developed in other populations require validation. Ongoing glucose screening is indicated for all women with GDM. © 2016 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

Predictive and Prognostic Factors in Ovarian and Uterine Carcinosarcomas

PubMed Central

Cicin, İrfan; Özatlı, Tahsin; Türkmen, Esma; Özturk, Türkan; Özçelik, Melike; Çabuk, Devrim; Gökdurnalı, Ayşe; Balvan, Özlem; Yıldız, Yaşar; Şeker, Metin; Özdemir, Nuriye; Yapar, Burcu; Tanrıverdi, Özgür; Günaydin, Yusuf; Menekşe, Serkan; Öksüzoğlu, Berna; Aksoy, Asude; Erdogan, Bülent; Bekir Hacıoglu, M.; Arpaci, Erkan; Sevinç, Alper

2016-01-01

Background: Prognostic factors and the standard treatment approach for gynaecological carcinosarcomas have not yet been clearly defined. Although carcinosarcomas are more aggressive than pure epithelial tumours, they are treated similarly. Serous/clear cell and endometrioid components may be predictive factors for the efficacy of adjuvant chemotherapy (CT) or radiotherapy (RT) or RT in patients with uterine and ovarian carcinosarcomas. Heterologous carcinosarcomas may benefit more from adjuvant CT. Aims: We aimed to define the prognostic and predictive factors associated with treatment options in ovarian (OCS) and uterine carcinosarcoma (UCS). Study Design: Retrospective cross-sectional study Methods: We retrospectively reviewed the medical records of patients with ovarian and uterine carcinosarcoma from 2000 to 2013, and 127 women were included in this study (24 ovarian and 103 uterine). Patients admitted to seventeen oncology centres in Turkey between 2000 and December 2013 with a histologically proven diagnosis of uterine carcinosarcoma with FIGO 2009 stage I–III and patients with sufficient data obtained from well-kept medical records were included in this study. Stage IV tumours were excluded. The patient records were retrospectively reviewed. Data from 104 patients were evaluated for this study. Results: Age (≥70 years) was a poor prognostic factor for UCS (p=0.036). Pelvic±para aortic lymph node dissection did not affect overall survival (OS) (p=0.35). Macroscopic residual disease was related with OS (p<0.01). The median OS was significantly longer in stage I–II patients than stage III patients (p=0.03). Adjuvant treatment improved OS (p=0.013). Adjuvant radiotherapy tended to increase the median OS (p=0.075). However, this tendency was observed in UCS (p=0.08) rather than OCS (p=0.6).Adjuvant chemotherapy had no effect on OS (p=0.15).Adjuvant radiotherapy significantly prolonged the median OS in patients with endometrioid component (p=0.034). A

Cytokine Profiling of Ascites at Primary Surgery Identifies an Interaction of Tumor Necrosis Factor-α and Interleukin-6 in Predicting Reduced Progression-Free Survival in Epithelial Ovarian Cancer

PubMed Central

Kolomeyevskaya, Nonna; Eng, Kevin H.; Khan, Anm Nazmul H.; Grzankowski, Kassondra S.; Singel, Kelly L.; Moysich, Kirsten; Segal, Brahm H.

2015-01-01

Objectives Epithelial ovarian cancer (EOC) typically presents with advanced disease. Even with optimal debulking and response to adjuvant chemotherapy, the majority of patients will have disease relapse. We evaluated cytokine and chemokine profiles in ascites at primary surgery as biomarkers for progression-free survival (PFS) and overall survival (OS) in patients with advanced EOC. Methods Retrospective analysis of patients (n =70) who underwent surgery at Roswell Park Cancer Institute between 2002-12, followed by platinum-based chemotherapy. Results The mean age at diagnosis was 61.8 years, 85.3% had serous EOC, and 95.7% had stage IIIB, IIIC, or IV disease. Univariate analysis showed that ascites levels of tumor necrosis factor (TNF)-α were associated with reduced PFS after primary surgery. Although the ascites concentration of interleukin (IL)-6 was not by itself predictive of PFS, we found that stratifying patients by high TNF-α and high IL-6 levels identified a sub-group of patients at high risk for rapid disease relapse. This effect was largely independent of clinical prognostic variables. Conclusions The combination of high TNF-α and high IL-6 ascites levels at primary surgery predicts worse PFS in patients with advanced EOC. These results suggest an interaction between ascites TNF-α and IL-6 in driving tumor progression and resistance to chemotherapy in advanced EOC, and raise the potential for pre-treatment ascites levels of these cytokines as prognostic biomarkers. This study involved a small sample of patients and was an exploratory analysis; therefore, findings require validation in a larger independent cohort. PMID:26001328

Cytokine profiling of ascites at primary surgery identifies an interaction of tumor necrosis factor-α and interleukin-6 in predicting reduced progression-free survival in epithelial ovarian cancer.

PubMed

Kolomeyevskaya, Nonna; Eng, Kevin H; Khan, Anm Nazmul H; Grzankowski, Kassondra S; Singel, Kelly L; Moysich, Kirsten; Segal, Brahm H

2015-08-01

Epithelial ovarian cancer (EOC) typically presents with advanced disease. Even with optimal debulking and response to adjuvant chemotherapy, the majority of patients will have disease relapse. We evaluated cytokine and chemokine profiles in ascites at primary surgery as biomarkers for progression-free survival (PFS) and overall survival (OS) in patients with advanced EOC. Retrospective analysis of patients (n =70) who underwent surgery at Roswell Park Cancer Institute between 2002 and 2012, followed by platinum-based chemotherapy. The mean age at diagnosis was 61.8 years, 85.3% had serous EOC, and 95.7% had stage IIIB, IIIC, or IV disease. Univariate analysis showed that ascites levels of tumor necrosis factor (TNF)-α were associated with reduced PFS after primary surgery. Although the ascites concentration of interleukin (IL)-6 was not by itself predictive of PFS, we found that stratifying patients by high TNF-α and high IL-6 levels identified a sub-group of patients at high risk for rapid disease relapse. This effect was largely independent of clinical prognostic variables. The combination of high TNF-α and high IL-6 ascites levels at primary surgery predicts worse PFS in patients with advanced EOC. These results suggest an interaction between ascites TNF-α and IL-6 in driving tumor progression and resistance to chemotherapy in advanced EOC, and raise the potential for pre-treatment ascites levels of these cytokines as prognostic biomarkers. This study involved a small sample of patients and was an exploratory analysis; therefore, findings require validation in a larger independent cohort. Copyright © 2015 Elsevier Inc. All rights reserved.

Validating regulatory predictions from diverse bacteria with mutant fitness data

DOE PAGES

Sagawa, Shiori; Price, Morgan N.; Deutschbauer, Adam M.; ...

2017-05-24

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacterium's growth across many conditions, to test regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomicsmore » predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.« less

Validating regulatory predictions from diverse bacteria with mutant fitness data

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

Sagawa, Shiori; Price, Morgan N.; Deutschbauer, Adam M.

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacterium's growth across many conditions, to test regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomicsmore » predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.« less

Identifying dyslexia in adults: an iterative method using the predictive value of item scores and self-report questions.

PubMed

Tamboer, Peter; Vorst, Harrie C M; Oort, Frans J

2014-04-01

Methods for identifying dyslexia in adults vary widely between studies. Researchers have to decide how many tests to use, which tests are considered to be the most reliable, and how to determine cut-off scores. The aim of this study was to develop an objective and powerful method for diagnosing dyslexia. We took various methodological measures, most of which are new compared to previous methods. We used a large sample of Dutch first-year psychology students, we considered several options for exclusion and inclusion criteria, we collected as many cognitive tests as possible, we used six independent sources of biographical information for a criterion of dyslexia, we compared the predictive power of discriminant analyses and logistic regression analyses, we used both sum scores and item scores as predictor variables, we used self-report questions as predictor variables, and we retested the reliability of predictions with repeated prediction analyses using an adjusted criterion. We were able to identify 74 dyslexic and 369 non-dyslexic students. For 37 students, various predictions were too inconsistent for a final classification. The most reliable predictions were acquired with item scores and self-report questions. The main conclusion is that it is possible to identify dyslexia with a high reliability, although the exact nature of dyslexia is still unknown. We therefore believe that this study yielded valuable information for future methods of identifying dyslexia in Dutch as well as in other languages, and that this would be beneficial for comparing studies across countries.

Predicting Resident Performance from Preresidency Factors: A Systematic Review and Applicability to Neurosurgical Training.

PubMed

Zuckerman, Scott L; Kelly, Patrick D; Dewan, Michael C; Morone, Peter J; Yengo-Kahn, Aaron M; Magarik, Jordan A; Baticulon, Ronnie E; Zusman, Edie E; Solomon, Gary S; Wellons, John C

2018-02-01

Neurosurgical educators strive to identify the best applicants, yet formal study of resident selection has proved difficult. We conducted a systematic review to answer the following question: What objective and subjective preresidency factors predict resident success? PubMed, ProQuest, Embase, and the CINAHL databases were queried from 1952 to 2015 for literature reporting the impact of preresidency factors (PRFs) on outcomes of residency success (RS), among neurosurgery and all surgical subspecialties. Due to heterogeneity of specialties and outcomes, a qualitative summary and heat map of significant findings were constructed. From 1489 studies, 21 articles met inclusion criteria, which evaluated 1276 resident applicants across five surgical subspecialties. No neurosurgical studies met the inclusion criteria. Common objective PRFs included standardized testing (76%), medical school performance (48%), and Alpha Omega Alpha (43%). Common subjective PRFs included aggregate rank scores (57%), letters of recommendation (38%), research (33%), interviews (19%), and athletic or musical talent (19%). Outcomes of RS included faculty evaluations, in-training/board exams, chief resident status, and research productivity. Among objective factors, standardized test scores correlated well with in-training/board examinations but poorly correlated with faculty evaluations. Among subjective factors, aggregate rank scores, letters of recommendation, and athletic or musical talent demonstrated moderate correlation with faculty evaluations. Standardized testing most strongly correlated with future examination performance but correlated poorly with faculty evaluations. Moderate predictors of faculty evaluations were aggregate rank scores, letters of recommendation, and athletic or musical talent. The ability to predict success of neurosurgical residents using an evidence-based approach is limited, and few factors have correlated with future resident performance. Given the importance of

Angiogenic factors combined with clinical risk factors to predict preterm pre-eclampsia in nulliparous women: a predictive test accuracy study.

PubMed

Myers, J E; Kenny, L C; McCowan, L M E; Chan, E H Y; Dekker, G A; Poston, L; Simpson, N A B; North, R A

2013-09-01

To assess the performance of clinical risk factors, uterine artery Doppler and angiogenic markers to predict preterm pre-eclampsia in nulliparous women. Predictive test accuracy study. Prospective multicentre cohort study Screening for Pregnancy Endpoints (SCOPE). Low-risk nulliparous women with a singleton pregnancy were recruited. Clinical risk factor data were obtained and plasma placental growth factor (PlGF), soluble endoglin and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 14-16 weeks of gestation. Prediction models were developed using multivariable stepwise logistic regression. Preterm pre-eclampsia (delivered before 37(+0)  weeks of gestation). Of the 3529 women recruited, 187 (5.3%) developed pre-eclampsia of whom 47 (1.3%) delivered preterm. Controls (n = 188) were randomly selected from women without preterm pre-eclampsia and included women who developed other pregnancy complications. An area under a receiver operating characteristic curve (AUC) of 0.76 (95% CI 0.67-0.84) was observed using previously reported clinical risk variables. The AUC improved following the addition of PlGF measured at 14-16 weeks (0.84; 95% CI 0.77-0.91), but no further improvement was observed with the addition of uterine artery Doppler or the other angiogenic markers. A sensitivity of 45% (95% CI 0.31-0.59) (5% false-positive rate) and post-test probability of 11% (95% CI 9-13) were observed using clinical risk variables and PlGF measurement. Addition of plasma PlGF at 14-16 weeks of gestation to clinical risk assessment improved the identification of nulliparous women at increased risk of developing preterm pre-eclampsia, but the performance is not sufficient to warrant introduction as a clinical screening test. These findings are marker dependent, not assay dependent; additional markers are needed to achieve clinical utility. © 2013 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2013 RCOG.

Identifying black swans in NextGen: predicting human performance in off-nominal conditions.

PubMed

Wickens, Christopher D; Hooey, Becky L; Gore, Brian F; Sebok, Angelia; Koenicke, Corey S

2009-10-01

The objective is to validate a computational model of visual attention against empirical data--derived from a meta-analysis--of pilots' failure to notice safety-critical unexpected events. Many aircraft accidents have resulted, in part, because of failure to notice nonsalient unexpected events outside of foveal vision, illustrating the phenomenon of change blindness. A model of visual noticing, N-SEEV (noticing-salience, expectancy, effort, and value), was developed to predict these failures. First, 25 studies that reported objective data on miss rate for unexpected events in high-fidelity cockpit simulations were identified, and their miss rate data pooled across five variables (phase of flight, event expectancy, event location, presence of a head-up display, and presence of a highway-in-the-sky display). Second, the parameters of the N-SEEV model were tailored to mimic these dichotomies. The N-SEEV model output predicted variance in the obtained miss rate (r = .73). The individual miss rates of all six dichotomous conditions were predicted within 14%, and four of these were predicted within 7%. The N-SEEV model, developed on the basis of an independent data set, was able to successfully predict variance in this safety-critical measure of pilot response to abnormal circumstances, as collected from the literature. As new technology and procedures are envisioned for the future airspace, it is important to predict if these may compromise safety in terms of pilots' failing to notice unexpected events. Computational models such as N-SEEV support cost-effective means of making such predictions.

Predictive factors for successful clinical outcome 1 year after an intensive combined physical and psychological programme for chronic low back pain.

PubMed

van Hooff, Miranda L; Spruit, Maarten; O'Dowd, John K; van Lankveld, Wim; Fairbank, Jeremy C T; van Limbeek, Jacques

2014-01-01

The aim of this longitudinal study is to determine the factors which predict a successful 1-year outcome from an intensive combined physical and psychological (CPP) programme in chronic low back pain (CLBP) patients. A prospective cohort of 524 selected consecutive CLBP patients was followed. Potential predictive factors included demographic characteristics, disability, pain and cognitive behavioural factors as measured at pre-treatment assessment. The primary outcome measure was the oswestry disability index (ODI). A successful 1-year follow-up outcome was defined as a functional status equivalent to 'normal' and healthy populations (ODI ≤22). The 2-week residential programme fulfills the recommendations in international guidelines. For statistical analysis we divided the database into two equal samples. A random sample was used to develop a prediction model with multivariate logistic regression. The remaining cases were used to validate this model. The final predictive model suggested being 'in employment' at pre-treatment [OR 3.61 (95 % CI 1.80-7.26)] and an initial 'disability score' [OR 0.94 (95 % CI 0.92-0.97)] as significant predictive factors for a successful 1-year outcome (R (2) = 22 %; 67 % correctly classified). There was no predictive value from measures of psychological distress. CLBP patients who are in work and mild to moderately disabled at the start of a CPP programme are most likely to benefit from it and to have a successful treatment outcome. In these patients, the disability score falls to values seen in healthy populations. This small set of factors is easily identified, allowing selection for programme entry and triage to alternative treatment regimes.

Prospective Large-Scale Field Study Generates Predictive Model Identifying Major Contributors to Colony Losses

PubMed Central

Kielmanowicz, Merav Gleit; Inberg, Alex; Lerner, Inbar Maayan; Golani, Yael; Brown, Nicholas; Turner, Catherine Louise; Hayes, Gerald J. R.; Ballam, Joan M.

2015-01-01

Over the last decade, unusually high losses of colonies have been reported by beekeepers across the USA. Multiple factors such as Varroa destructor, bee viruses, Nosema ceranae, weather, beekeeping practices, nutrition, and pesticides have been shown to contribute to colony losses. Here we describe a large-scale controlled trial, in which different bee pathogens, bee population, and weather conditions across winter were monitored at three locations across the USA. In order to minimize influence of various known contributing factors and their interaction, the hives in the study were not treated with antibiotics or miticides. Additionally, the hives were kept at one location and were not exposed to potential stress factors associated with migration. Our results show that a linear association between load of viruses (DWV or IAPV) in Varroa and bees is present at high Varroa infestation levels (>3 mites per 100 bees). The collection of comprehensive data allowed us to draw a predictive model of colony losses and to show that Varroa destructor, along with bee viruses, mainly DWV replication, contributes to approximately 70% of colony losses. This correlation further supports the claim that insufficient control of the virus-vectoring Varroa mite would result in increased hive loss. The predictive model also indicates that a single factor may not be sufficient to trigger colony losses, whereas a combination of stressors appears to impact hive health. PMID:25875764

Frequency and predictive factors for overlap syndrome between autoimmune hepatitis and primary cholestatic liver disease.

PubMed

Gheorghe, Liana; Iacob, Speranta; Gheorghe, Cristian; Iacob, Razvan; Simionov, Iulia; Vadan, Roxana; Becheanu, Gabriel; Parvulescu, Iuliana; Toader, Cristina

2004-06-01

To evaluate the frequency of cholestatic pattern in patients with autoimmune hepatitis (AIH) and to identify predictive factors associated with the development of the overlap syndrome. Eighty-two consecutive patients diagnosed with AIH at the referral centre between January 1998 and June 2002 were included in the study. The new scoring system modified by the International Autoimmune Hepatitis Group was used to classify patients as definite/probable. Overlap syndrome was considered when the patient had clinical, serological and histological characteristics of two conditions: AIH and primary biliary cirrhosis (PBC) or AIH and primary sclerosing cholangitis (PSC). From the 82 AIH patients (76 female and six male), 84.1% presented definite AIH (> 15 points) and 15.9% probable AIH (10 - 15 points). The frequency of the overlap syndrome was 20%: 13% with PBC and 7% with PSC. In the univariate analysis the overlap syndrome was associated with male gender (P = 0.01), age < 35 years (P < 0.0001), histopathological aspect of cholestasis (P < 0.0001), suboptimal response to treatment (P < 0.0001) and probable AIH (P < 0.0001). Age < 35 years, probable AIH and the absence of anti-nuclear antibody (ANA) have been identified as independent indicators of the overlap diagnosis by the logistic regression analysis. Patients with overlap syndrome between AIH and primary cholestatic liver disease are frequently diagnosed in clinical practice, representing 20% of AIH cases in our study. The independent predictive factors associated with the diagnosis of overlap syndrome are young age, ANA(-) profile, and probable diagnosis according with the scoring system for AIH.

Adolescent Alcohol Use: Protective and Predictive Parent, Peer, and Self-Related Factors

PubMed Central

Donaldson, Candice D.; Crano, William D.

2018-01-01

Adolescent alcohol use has been linked with a multitude of problems and a trajectory predictive of problematic use in adulthood. Thus, targeting factors that enhance early prevention efforts is vital. The current study highlights variables that mitigate or predict alcohol use and heavy episodic drinking. Using Monitoring the Future (MTF) data, multiple path analytic models revealed links between parental involvement and alcohol abstinence and initiation. Parental involvement predicted enhanced self-esteem and less self-derogation and was negatively associated with peer alcohol norms for each MTF grade sampled, with stronger associations for 8th and 10th graders than 12th graders. For younger groups, self-esteem predicted increased perceptions of alcohol risk and reduced drinking. Self-derogation was associated with peers’ pro-alcohol norms, which was linked to lower risk perceptions, lower personal disapproval of use, and increased drinking. Peer influence had a stronger association with consumption for 8th and 10th graders, whereas 12th graders’ drinking was related to personal factors of alcohol risk perception and disapproval. In all grades, general alcohol use had a strong connection to heavy episodic drinking within the past 2 weeks. Across-grade variations in association of parent, peer, and personal factors suggest the desirability of tailored interventions focused on specific factors for each grade level, with the overall goal of attenuating adolescent alcohol use. PMID:27562038

Clinical Prediction Making: Examining Influential Factors Related to Clinician Predictions of Recidivism among Juvenile Offenders

ERIC Educational Resources Information Center

Calley, Nancy G.; Richardson, Emily M.

2011-01-01

This study examined factors influencing clinician predictions of recidivism for juvenile offenders, including youth age at initial juvenile justice system involvement, youth age at discharge, program completion status, clinician perception of strength of the therapeutic relationship, and clinician perception of youth commitment to treatment.…

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

EPA Science Inventory

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

Working smarter on cold cases: identifying factors associated with successful cold case investigations.

PubMed

Davis, Robert C; Jensen, Carl J; Burgette, Lane; Burnett, Kathryn

2014-03-01

Cold case squads have garnered much attention; however, they have yet to undergo significant empirical scrutiny. In the present study, the authors interviewed investigators and reviewed 189 solved and unsolved cold cases in Washington, D.C., to determine whether there are factors that can predict cold case solvability. In the interviews, new information from witnesses or information from new witnesses was cited as the most prevalent reason for case clearance. The case reviews determined that there were factors in each of the following domains that predicted whether cases would be solved during cold case investigations: Crime Context, Initial Investigation Results, Basis for Opening Cold Case, and Cold Case Investigator Actions. The results suggest that it is possible to prioritize cold case work based on the likelihood of investigations leading to clearances. © 2014 American Academy of Forensic Sciences.

Factors associated with onset timing, symptoms, and severity of depression identified in the postpartum period.

PubMed

Fisher, Sheehan D; Wisner, Katherine L; Clark, Crystal T; Sit, Dorothy K; Luther, James F; Wisniewski, Stephen

2016-10-01

Unipolar and bipolar depression identified in the postpartum period have a heterogeneous etiology. The objectives of this study are to examine the risk factors that distinguish the timing of onset for unipolar and bipolar depression and the associations between depression onset by diagnosis, and general and atypical depressive symptoms. Symptoms of depression were assessed at 4- to 6-weeks postpartum by the Structured Interview Guide for the Hamilton Depression Rating Scale-Atypical Depression Symptoms in an obstetrical sample of 727 women. Data were analyzed using ANOVA, Chi-square, and linear regression. Mothers with postpartum onset of depression were more likely to be older, Caucasian, educated, married/cohabitating, have one or no previous child, and have private insurance in contrast to mothers with pre-pregnancy and prenatal onset of depression. Mothers with bipolar depression were more likely to have a pre-pregnancy onset. Three general and two atypical depressive symptoms distinguished pre-pregnancy, during pregnancy, and postpartum depression onset, and the presence of agitation distinguished between unipolar and bipolar depression. The sample was urban, which may not be generalizable to other populations. The study was cross-sectional, which excludes potential late onset of depression (after 4-6 weeks) in the first postpartum year. A collective set of factors predicted the onset of depression identified in the postpartum for mothers distinguished by episodes of unipolar versus bipolar depression, which can inform clinical interventions. Future research on the onset of major depressive episodes could inform prophylactic and early psychiatric interventions. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying transcription factor functions and targets by phenotypic activation

PubMed Central

Chua, Gordon; Morris, Quaid D.; Sopko, Richelle; Robinson, Mark D.; Ryan, Owen; Chan, Esther T.; Frey, Brendan J.; Andrews, Brenda J.; Boone, Charles; Hughes, Timothy R.

2006-01-01

Mapping transcriptional regulatory networks is difficult because many transcription factors (TFs) are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual TFs that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast TFs that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, indicating that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5′-TCACGCAA as a binding sequence for Hms1p, a TF that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of TF activities and mapping targets that could be adapted to any organism with transgenic technology. PMID:16880382

A Predictive Model Has Identified Tick-Borne Encephalitis High-Risk Areas in Regions Where No Cases Were Reported Previously, Poland, 1999-2012.

PubMed

Stefanoff, Pawel; Rubikowska, Barbara; Bratkowski, Jakub; Ustrnul, Zbigniew; Vanwambeke, Sophie O; Rosinska, Magdalena

2018-04-04

During 1999–2012, 77% of the cases of tick-borne encephalitis (TBE) were recorded in two out of 16 Polish provinces. However, historical data, mostly from national serosurveys, suggest that the disease could be undetected in many areas. The aim of this study was to identify which routinely-measured meteorological, environmental, and socio-economic factors are associated to TBE human risk across Poland, with a particular focus on areas reporting few cases, but where serosurveys suggest higher incidence. We fitted a zero-inflated Poisson model using data on TBE incidence recorded in 108 NUTS-5 administrative units in high-risk areas over the period 1999–2012. Subsequently we applied the best fitting model to all Polish municipalities. Keeping the remaining variables constant, the predicted rate increased with the increase of air temperature over the previous 10–20 days, precipitation over the previous 20–30 days, in forestation, forest edge density, forest road density, and unemployment. The predicted rate decreased with increasing distance from forests. The map of predicted rates was consistent with the established risk areas. It predicted, however, high rates in provinces considered TBE-free. We recommend raising awareness among physicians working in the predicted high-risk areas and considering routine use of household animal surveys for risk mapping.

The Promise of Virtual Teams: Identifying Key Factors in Effectiveness and Failure

ERIC Educational Resources Information Center

Horwitz, Frank M.; Bravington, Desmond; Silvis, Ulrik

2006-01-01

Purpose: The aim of the investigation is to identify enabling and disenabling factors in the development and operation of virtual teams; to evaluate the importance of factors such as team development, cross-cultural variables, leadership, communication and social cohesion as contributors to virtual team effectiveness. Design/methodology/approach:…

Predicting the unpredictable? Identifying high-risk versus low-risk parents with intellectual disabilities.

PubMed

McGaw, Sue; Scully, Tamara; Pritchard, Colin

2010-09-01

This study set out to identify risk factors affecting parents with intellectual disabilities (IDs) by determining: (i) whether perception of family support differs between parents with IDs, referring professionals, and a specialist parenting service; (ii) whether multivariate familial and demographic factors differentiates 'high-risk' from 'low-risk' parenting; and (iii) the impact of partner relationships on parental competency and risk status. Secondary data analysis was conducted on data gathered from 101 parents with IDs and 172 of their children, all of whom had been referred to a specialist parenting service over a 5 year period. Cross-tabulations were applied to the data to examine causal processes and to improve general understanding of the risks associated with families. Contrary to popular expectations IQ levels of the main parent, relationship status, parental age, employment, amenities, valued support and parents' perception of need were not identified as contributory factors distinguishing 'high-risk' from 'low-risk' parents. Instead, 'high-risk' parenting associated more with parental reports of childhood trauma (emotional abuse and physical neglect in particular), parents' having additional special needs in addition to their IDs or parents who were raising a child with special needs. Other 'high-risk' factors identified related to the male partners of mothers with IDs, many of whom did not have IDs and/or whose histories included anti-social behaviors or criminality. The study identified some high-risk variables among parents with IDs that can distinguish them from low-risk parents with IDs. These findings generate challenges for agencies who attempt to capture the needs of parents with IDs and who endeavour to provide services to families deemed to be "at risk." These outcomes will be of special interest to the courts, especially when parents with IDs are involved in care proceedings. Copyright © 2010. Published by Elsevier Ltd.

Cognitive factors predicting intentions to search for health information: an application of the theory of planned behaviour.

PubMed

Austvoll-Dahlgren, Astrid; Falk, Ragnhild S; Helseth, Sølvi

2012-12-01

Peoples' ability to obtain health information is a precondition for their effective participation in decision making about health. However, there is limited evidence describing which cognitive factors can predict the intention of people to search for health information. To test the utility of a questionnaire in predicting intentions to search for health information, and to identify important predictors associated with this intention such that these could be targeted in an Intervention. A questionnaire was developed based on the Theory of Planned Behaviour and tested on both a mixed population sample (n=30) and a sample of parents (n = 45). The questionnaire was explored by testing for internal consistency, calculating inter-correlations between theoretically-related constructs, and by using multiple regression analysis. The reliability and validity of the questionnaire were found to be satisfactory and consistent across the two samples. The questionnaires' direct measures prediction of intention was high and accounted for 47% and 55% of the variance in behavioural intentions. Attitudes and perceived behavioural control were identified as important predictors to intention for search for health information. The questionnaire may be a useful tool for understanding and evaluating behavioural intentions and beliefs related to searches for health information. © 2012 The authors. Health Information and Libraries Journal © 2012 Health Libraries Group.

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1988-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 to + or - 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was developed to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Strengths of specimens containing crack-like slits were calculated from predicted failing strains using uniaxial stress-strain curves. Predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only + or - 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

PubMed Central

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

2017-01-01

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

Predictive Validity of Curriculum-Embedded Measures on Outcomes of Kindergarteners Identified as At Risk for Reading Difficulty

ERIC Educational Resources Information Center

Oslund, Eric L.; Hagan-Burke, Shanna; Simmons, Deborah C.; Clemens, Nathan H.; Simmons, Leslie E.; Taylor, Aaron B.; Kwok, Oi-man; Coyne, Michael D.

2017-01-01

This study examined the predictive validity of formative assessments embedded in a Tier 2 intervention curriculum for kindergarten students identified as at risk for reading difficulty. We examined when (i.e., months during the school year) measures could predict reading outcomes gathered at the end of kindergarten and whether the predictive…

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Identifying and Predicting Profiles of Medical Noncompliance: Pediatric Caregivers' Antibiotic Stewardship.

PubMed

Smith, Rachel A; Kim, Youllee; M'Ikanatha, Nkuchia M

2018-05-14

Sometimes compliance with medical recommendations is problematic. We investigated pediatric caregivers' (N = 606) patterns of noncompliance with antibiotic stewardship based on the obstacle hypothesis. We tested predictors of noncompliance framed by the obstacle hypothesis, dissonance theory, and psychological reactance. The results revealed four profiles of caregivers' stewardship: one marked by compliance (Stewards) and three marked by types of noncompliance (Stockers, Persuaders, and Dissenters). The covariate analysis showed that, although psychological reactance predicted being noncompliant, it was types of obstacles and discrepant experiences that predicted caregivers' patterns of noncompliance with antibiotic stewardship. Campaign planning often focuses on identifying the belief most associated with the targeted outcome, such as compliance. Noncompliance research, however, points out that persuaders may be successful to the extent to which they anticipate obstacles to compliance and address them in their influence attempts. A shift from medical noncompliance to patient engagement also affords an opportunity to consider how some recommendations create obstacles for others and to find positive ways to embrace conflicting needs, tensions, and reasons for refusal in order to promote collective goals.

Identifying Key Hospital Service Quality Factors in Online Health Communities

PubMed Central

Jung, Yuchul; Hur, Cinyoung; Jung, Dain

2015-01-01

Background The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. Objective As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. Methods We defined social media–based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea’s two biggest online portals were used to test the effectiveness of detection of social media–based key quality factors for hospitals. Results To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is

Identifying key hospital service quality factors in online health communities.

PubMed

Jung, Yuchul; Hur, Cinyoung; Jung, Dain; Kim, Minki

2015-04-07

The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. We defined social media-based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea's two biggest online portals were used to test the effectiveness of detection of social media-based key quality factors for hospitals. To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and

Prediction of beef carcass and meat traits from rearing factors in young bulls and cull cows.

PubMed

Soulat, J; Picard, B; Léger, S; Monteils, V

2016-04-01

The aim of this study was to predict the beef carcass and LM (thoracis part) characteristics and the sensory properties of the LM from rearing factors applied during the fattening period. Individual data from 995 animals (688 young bulls and 307 cull cows) in 15 experiments were used to establish prediction models. The data concerned rearing factors (13 variables), carcass characteristics (5 variables), LM characteristics (2 variables), and LM sensory properties (3 variables). In this study, 8 prediction models were established: dressing percentage and the proportions of fat tissue and muscle in the carcass to characterize the beef carcass; cross-sectional area of fibers (mean fiber area) and isocitrate dehydrogenase activity to characterize the LM; and, finally, overall tenderness, juiciness, and flavor intensity scores to characterize the LM sensory properties. A random effect was considered in each model: the breed for the prediction models for the carcass and LM characteristics and the trained taste panel for the prediction of the meat sensory properties. To evaluate the quality of prediction models, 3 criteria were measured: robustness, accuracy, and precision. The model was robust when the root mean square errors of prediction of calibration and validation sub-data sets were near to one another. Except for the mean fiber area model, the obtained predicted models were robust. The prediction models were considered to have a high accuracy when the mean prediction error (MPE) was ≤0.10 and to have a high precision when the was the closest to 1. The prediction of the characteristics of the carcass from the rearing factors had a high precision ( > 0.70) and a high prediction accuracy (MPE < 0.10), except for the fat percentage model ( = 0.67, MPE = 0.16). However, the predictions of the LM characteristics and LM sensory properties from the rearing factors were not sufficiently precise ( < 0.50) and accurate (MPE > 0.10). Only the flavor intensity of the beef

Systematic review of prognostic factors predicting outcome in non-surgically treated patients with sciatica.

PubMed

Verwoerd, A J H; Luijsterburg, P A J; Lin, C W C; Jacobs, W C H; Koes, B W; Verhagen, A P

2013-09-01

Identification of prognostic factors for surgery in patients with sciatica is important to be able to predict surgery in an early stage. Identification of prognostic factors predicting persistent pain, disability and recovery are important for better understanding of the clinical course, to inform patient and physician and support decision making. Consequently, we aimed to systematically review prognostic factors predicting outcome in non-surgically treated patients with sciatica. A search of Medline, Embase, Web of Science and Cinahl, up to March 2012 was performed for prospective cohort studies on prognostic factors for non-surgically treated sciatica. Two reviewers independently selected studies for inclusion and assessed the risk of bias. Outcomes were pain, disability, recovery and surgery. A best evidence synthesis was carried out in order to assess and summarize the data. The initial search yielded 4392 articles of which 23 articles reporting on 14 original cohorts met the inclusion criteria. High clinical, methodological and statistical heterogeneity among studies was found. Reported evidence regarding prognostic factors predicting the outcome in sciatica is limited. The majority of factors that have been evaluated, e.g., age, body mass index, smoking and sensory disturbance, showed no association with outcome. The only positive association with strong evidence was found for leg pain intensity at baseline as prognostic factor for subsequent surgery. © 2013 European Federation of International Association for the Study of Pain Chapters.

Prediction of beef carcass and meat quality traits from factors characterising the rearing management system applied during the whole life of heifers.

PubMed

Soulat, J; Picard, B; Léger, S; Monteils, V

2018-06-01

In this study, four prediction models were developed by logistic regression using individual data from 96 heifers. Carcass and sensory rectus abdominis quality clusters were identified then predicted using the rearing factors data. The obtained models from rearing factors applied during the fattening period were compared to those characterising the heifers' whole life. The highest prediction power of carcass and meat quality clusters were obtained from the models considering the whole life, with success rates of 62.8% and 54.9%, respectively. Rearing factors applied during both pre-weaning and fattening periods influenced carcass and meat quality. According to models, carcass traits were improved when heifer's mother was older for first calving, calves ingested concentrates during pasture preceding weaning and heifers were slaughtered older. Meat traits were improved by the genetic of heifers' parents (i.e., calving ease and early muscularity) and when heifers were slaughtered older. A management of carcass and meat quality traits is possible at different periods of the heifers' life. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identifying Human Factors Issues in Aircraft Maintenance Operations

NASA Technical Reports Server (NTRS)

Veinott, Elizabeth S.; Kanki, Barbara G.; Shafto, Michael G. (Technical Monitor)

1995-01-01

Maintenance operations incidents submitted to the Aviation Safety Reporting System (ASRS) between 1986-1992 were systematically analyzed in order to identify issues relevant to human factors and crew coordination. This exploratory analysis involved 95 ASRS reports which represented a wide range of maintenance incidents. The reports were coded and analyzed according to the type of error (e.g, wrong part, procedural error, non-procedural error), contributing factors (e.g., individual, within-team, cross-team, procedure, tools), result of the error (e.g., aircraft damage or not) as well as the operational impact (e.g., aircraft flown to destination, air return, delay at gate). The main findings indicate that procedural errors were most common (48.4%) and that individual and team actions contributed to the errors in more than 50% of the cases. As for operational results, most errors were either corrected after landing at the destination (51.6%) or required the flight crew to stop enroute (29.5%). Interactions among these variables are also discussed. This analysis is a first step toward developing a taxonomy of crew coordination problems in maintenance. By understanding what variables are important and how they are interrelated, we may develop intervention strategies that are better tailored to the human factor issues involved.

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients.

PubMed

Cattaneo, Annamaria; Ferrari, Clarissa; Uher, Rudolf; Bocchio-Chiavetto, Luisella; Riva, Marco Andrea; Pariante, Carmine M

2016-10-01

Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more assertive antidepressant strategies

Factors affecting species distribution predictions: A simulation modeling experiment

Treesearch

Gordon C. Reese; Kenneth R. Wilson; Jennifer A. Hoeting; Curtis H. Flather

2005-01-01

Geospatial species sample data (e.g., records with location information from natural history museums or annual surveys) are rarely collected optimally, yet are increasingly used for decisions concerning our biological heritage. Using computer simulations, we examined factors that could affect the performance of autologistic regression (ALR) models that predict species...

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.

1989-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Stress factors predicting injuries of hospital personnel.

PubMed

Salminen, Simo; Kivimäki, Mika; Elovainio, Marko; Vahtera, Jussi

2003-07-01

Stress at work has long been recognized as a factor in increasing risk for mental and physical health problems. The extent to which work stressors and stress predicted injuries occur in a large population of Finnish hospital workers was studied. A total of 5,111 employees (624 men, 4,487 women) from 10 hospitals participated in this study. Their psychological distress was measured by the General Health Questionnaire, and overload and job control by the Harris scale and the Job Content Questionnaire, respectively. Injuries certified by a physician were followed up for 3 years: injuries in 1997 (n = 213) were used as a measure of baseline and injuries in 1998-1999 (n = 443) were the dependent variables. Psychological distress was not significantly related to injuries. However, low decision latitude (risk ratio = 1.27 (1.04 to 1.54)), low skill discretion only for men (risk ratio = 2.76 (1.78 to 4.30)), and highly monotonous work (risk ratio = 1.26 (1.02 to 1.55)) were stressors predicting injuries. In addition, workers with numerous problems in interpersonal relationships (risk ratio = 1.43 (1.18 to 1.73)) or many conflicts in collaboration at work (risk ratio = 1.40 (1.15 to 1.71)) were more often involved in injuries. This study showed that stressors related to autonomy of work and interpersonal relationship at workplace are predictors of injuries in hospital settings. These factors are potentially amenable to organizational interventions. Copyright 2003 Wiley-Liss, Inc.

What Makes Sports Fans Interactive? Identifying Factors Affecting Chat Interactions in Online Sports Viewing

PubMed Central

Yeo, Jaeryong; Lee, Juyeong

2016-01-01

Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers’ online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans’ interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users. PMID:26849568

An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

PubMed

Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

2014-01-01

Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances Ch

ACUTE PANCREATITIS GRAVITY PREDICTIVE FACTORS: WHICH AND WHEN TO USE THEM?

PubMed Central

FERREIRA, Alexandre de Figueiredo; BARTELEGA, Janaina Alves; URBANO, Hugo Corrêa de Andrade; de SOUZA, Iure Kalinine Ferraz

2015-01-01

Introduction: Acute pancreatitis has as its main causes lithiasic biliary disease and alcohol abuse. Most of the time, the disease shows a self-limiting course, with a rapid recovery, only with supportive treatment. However, in a significant percentage of cases, it runs with important local and systemic complications associated with high mortality rates. Aim: To present the current state of the use of these prognostic factors (predictive scores) of gravity, as the time of application, complexity and specificity. Method: A non-systematic literature review through 28 papers, with emphasis on 13 articles published in indexed journals between 2008 and 2013 using Lilacs, Medline, Pubmed. Results: Several clinical, laboratory analysis, molecular and image variables can predict the development of severe acute pancreatitis. Some of them by themselves can be determinant to the progression of the disease to a more severe form, such as obesity, hematocrit, age and smoking. Hematocrit with a value lower than 44% and serum urea lower than 20 mg/dl, both at admission, appear as risk factors for pancreatic necrosis. But the PCR differentiates mild cases of serious ones in the first 24 h. Multifactorial scores measured on admission and during the first 48 h of hospitalization have been used in intensive care units, being the most ones used: Ranson, Apache II, Glasgow, Iget and Saps II. Conclusion: Acute pancreatitis is a disease in which several prognostic factors are employed being useful in predicting mortality and on the development of the severe form. It is suggested that the association of a multifactorial score, especially the Saps II associated with Iget, may increase the prognosis accuracy. However, the professional's preferences, the experience on the service as well as the available tools, are factors that have determined the choice of the most suitable predictive score. PMID:26537149

Cowpeas in Northern Ghana and the Factors that Predict Caregivers’ Intention to Give Them to Schoolchildren

PubMed Central

Abizari, Abdul-Razak; Pilime, Nerisa; Armar-Klemesu, Margaret; Brouwer, Inge D.

2013-01-01

Background Cowpeas are important staple legumes among the rural poor in northern Ghana. Our objectives were to assess the iron and zinc content of cowpea landraces and identify factors that predict the intention of mothers/caregivers to give cowpeas to their schoolchildren. Methods and Findings We performed biochemical analysis on 14 landraces of cowpeas and assessed the opinion of 120 caregiver-child pairs on constructs based on the combined model of the Theory of Planned Behaviour and Health Belief Model. We used correlations and multiple regressions to measure simple associations between constructs and identify predictive constructs. Cowpea landraces contained iron and zinc in the range of 4.9–8.2 mg/100 g d.w and 2.7–4.1 mg/100 g d.w respectively. The landraces also contained high amounts of phytate (477–1110 mg/100 g d.w) and polyphenol (327–1055 mg/100 g d.w). Intention of mothers was strongly associated (rs = 0.72, P<0.001) with and predicted (β = 0.63, P<0.001) behaviour. The constructs, barriers (β = –0.42, P = 0.001) and attitudes towards behaviour (β = 0.25, P<0.028), significantly predicted intention albeit the predictive ability of the model was weak. Conclusions We conclude that some cowpea landraces from northern Ghana have appreciable amounts of iron and zinc but probably with poor bioavailability. Attitudes towards giving cowpeas and perception of barriers are important predictors of caregivers’ intention to give cowpeas to their schoolchildren. Finally our results suggest that increasing knowledge on nutritional benefits of cowpeas may increase health values caregivers hold for their children in support of giving cowpeas to schoolchildren. PMID:23951289

Predicting the cosmological constant with the scale-factor cutoff measure

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

De Simone, Andrea; Guth, Alan H.; Salem, Michael P.

2008-09-15

It is well known that anthropic selection from a landscape with a flat prior distribution of cosmological constant {lambda} gives a reasonable fit to observation. However, a realistic model of the multiverse has a physical volume that diverges with time, and the predicted distribution of {lambda} depends on how the spacetime volume is regulated. A very promising method of regulation uses a scale-factor cutoff, which avoids a number of serious problems that arise in other approaches. In particular, the scale-factor cutoff avoids the 'youngness problem' (high probability of living in a much younger universe) and the 'Q and G catastrophes'more » (high probability for the primordial density contrast Q and gravitational constant G to have extremely large or small values). We apply the scale-factor cutoff measure to the probability distribution of {lambda}, considering both positive and negative values. The results are in good agreement with observation. In particular, the scale-factor cutoff strongly suppresses the probability for values of {lambda} that are more than about 10 times the observed value. We also discuss qualitatively the prediction for the density parameter {omega}, indicating that with this measure there is a possibility of detectable negative curvature.« less

Absence of back disorders in adults and work-related predictive factors in a 5-year perspective.

PubMed

Reigo, T; Tropp, H; Timpka, T

2001-06-01

Factors important for avoiding back disorders in different age-groups have seldom been compared and studied over time. We therefore set out to study age-related differences in socio-economic and work-related factors associated with the absence of back disorders in a 5-year comparative cohort study using a mailed questionnaire. Two subgroups (aged 25-34 and 54-59 years) derived from a representative sample of the Swedish population were followed at baseline, 1 year and 5 years. Questions were asked about the duration of back pain episodes, relapses, work changes and work satisfaction. A work adaptability, partnership, growth, affection, resolve (APGAR) score was included in the final questionnaire. Multivariate logistic regression was used to identify factors predicting the absence of back disorders. Absence of physically heavy work predicted an absence of back disorders [odds ratio (OR), 2.86; 95% confidence interval (CI), 1.3-6.3] in the older group. In the younger age-group, the absence of stressful work predicted absence of back disorders (OR, 2.0; 95% CI, 1.1-3.6). Thirty-seven per cent of the younger age-group and 43% of the older age-group did not experience any back pain episodes during the study period. The exploratory work APGAR scores indicated that back disorders were only associated with lower work satisfaction in the older group. The analyses point out the importance of avoiding perceived psychological stress in the young and avoiding perceived physically heavy work in the older age-group for avoiding back disorders. The results suggest a need for different programmes at workplaces to avoid back disorders depending on the age of the employees concerned.

Sexual harassment: identifying risk factors.

PubMed

O'Hare, E A; O'Donohue, W

1998-12-01

A new model of the etiology of sexual harassment, the four-factor model, is presented and compared with several models of sexual harassment including the biological model, the organizational model, the sociocultural model, and the sex role spillover model. A number of risk factors associated with sexually harassing behavior are examined within the framework of the four-factor model of sexual harassment. These include characteristics of the work environment (e.g., sexist attitudes among co-workers, unprofessional work environment, skewed sex ratios in the workplace, knowledge of grievance procedures for sexual harassment incidents) as well as personal characteristics of the subject (e.g., physical attractiveness, job status, sex-role). Subjects were 266 university female faculty, staff, and students who completed the Sexual Experience Questionnaire to assess the experience of sexual harassment and a questionnaire designed to assess the risk factors stated above. Results indicated that the four-factor model is a better predictor of sexual harassment than the alternative models. The risk factors most strongly associated with sexual harassment were an unprofessional environment in the workplace, sexist atmosphere, and lack of knowledge about the organization's formal grievance procedures.

Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

PubMed

Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

2018-04-11

Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree

RM-DEMATEL: a new methodology to identify the key factors in PM2.5.

PubMed

Chen, Yafeng; Liu, Jie; Li, Yunpeng; Sadiq, Rehan; Deng, Yong

2015-04-01

Weather system is a relative complex dynamic system, the factors of the system are mutually influenced PM2.5 concentration. In this paper, a new method is proposed to quantify the influence on PM2.5 by other factors in the weather system and identify the most important factors for PM2.5 with limited resources. The relation map (RM) is used to figure out the direct relation matrix of 14 factors in PM2.5. The decision making trial and evaluation laboratory(DEMATEL) is applied to calculate the causal relationship and extent to a mutual influence of 14 factors in PM2.5. According to the ranking results of our proposed method, the most important key factors is sulfur dioxide (SO2) and nitrogen oxides (NO(X)). In addition, the other factors, the ambient maximum temperature (T(max)), concentration of PM10, and wind direction (W(dir)), are important factors for PM2.5. The proposed method can also be applied to other environment management systems to identify key factors.

Hazardous drinking and military community functioning: identifying mediating risk factors.

PubMed

Foran, Heather M; Heyman, Richard E; Slep, Amy M Smith

2011-08-01

Hazardous drinking is a serious societal concern in military populations. Efforts to reduce hazardous drinking among military personnel have been limited in effectiveness. There is a need for a deeper understanding of how community-based prevention models apply to hazardous drinking in the military. Community-wide prevention efforts may be most effective in targeting community functioning (e.g., support from formal agencies, community cohesion) that impacts hazardous drinking via other proximal risk factors. The goal of the current study is to inform community-wide prevention efforts by testing a model of community functioning and mediating risk factors of hazardous drinking among active duty U.S. Air Force personnel. A large, representative survey sample of U.S. Air Force active duty members (N = 52,780) was collected at 82 bases worldwide. Hazardous drinking was assessed with the widely used Alcohol Use Disorders Identification Test (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). A variety of individual, family, and community measures were also assessed. Structural equation modeling was used to test a hypothesized model of community functioning, mediating risk factors and hazardous drinking. Depressive symptoms, perceived financial stress, and satisfaction with the U.S. Air Force were identified as significant mediators of the link between community functioning and hazardous drinking for men and women. Relationship satisfaction was also identified as a mediator for men. These results provide a framework for further community prevention research and suggest that prevention efforts geared at increasing aspects of community functioning (e.g., the U.S. Air Force Community Capacity model) may indirectly lead to reductions in hazardous drinking through other proximal risk factors.

Factors predictive of risk for complications in patients with oesophageal foreign bodies.

PubMed

Sung, Sang Hun; Jeon, Seong Woo; Son, Hyuk Su; Kim, Sung Kook; Jung, Min Kyu; Cho, Chang Min; Tak, Won Young; Kweon, Young Oh

2011-08-01

Reports on predictive risk factors associated with complications of ingested oesophageal foreign bodies are rare. The aim of this study was to determine the predictive risk factors associated with the complications of oesophageal foreign bodies. Three hundred sixteen cases with foreign bodies in the oesophagus were retrospectively investigated. The predictive risk factors for complications after foreign body ingestion were analysed by multivariate logistic regression, and included age, size and type of foreign body ingested, duration of impaction, and the level of foreign body impaction. The types of oesophageal foreign bodies included fish bones (37.0%), food (19.0%), and metals (18.4%). The complications associated with foreign bodies were ulcers (21.2%), lacerations (14.9%), erosions (12.0%), and perforation (1.9%). Multivariate analysis showed that the duration of impaction (p<0.001), and the type (p<0.001) and size of the foreign bodies (p<0.001) were significant independent risk factors associated with the development of complications in patients with oesophageal foreign bodies. In patients with oesophageal foreign bodies, the risk of complications was increased with a longer duration of impaction, bone type, and larger size. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

What Factors are Predictive of Patient-reported Outcomes? A Prospective Study of 337 Shoulder Arthroplasties.

PubMed

Matsen, Frederick A; Russ, Stacy M; Vu, Phuong T; Hsu, Jason E; Lucas, Robert M; Comstock, Bryan A

2016-11-01

were associated with the outcomes. The model predictive of a better result was driven mainly by the six factors listed above. The area under the receiver operating characteristic curve generated from the cross-validated enhanced predictive model was 0.79 (generally values of 0.7 to 0.8 are considered fair and values of 0.8 to 0.9 are considered good). The false-positive fraction and the true-positive fraction depended on the cutoff probability selected (ie, the selected probability above which the prediction would be classified as a better outcome). A cutoff probability of 0.68 yielded the best performance of the model with cross-validation predictions of better outcomes for 236 patients (80%) and worse outcomes for 58 patients (20%); sensitivity of 91% (95% CI, 88%-95%); specificity of 65% (95% CI, 53%-77%); positive predictive value of 92% (95% CI, 88%-95%); and negative predictive value of 64% (95% CI, 51%-76%). We found six easy-to-determine preoperative patient and shoulder factors that were significantly associated with better outcomes of shoulder arthroplasty. A model based on these characteristics had good predictive properties for identifying patients likely to have a better outcome from shoulder arthroplasty. Future research could refine this model with larger patient populations from multiple practices. Level II, therapeutic study.

Using an interdisciplinary approach to identify factors that affect clinicians' compliance with evidence-based guidelines.

PubMed

Gurses, Ayse P; Marsteller, Jill A; Ozok, A Ant; Xiao, Yan; Owens, Sharon; Pronovost, Peter J

2010-08-01

Our objective was to identify factors that affect clinicians' compliance with the evidence-based guidelines using an interdisciplinary approach and develop a conceptual framework that can provide a comprehensive and practical guide for designing effective interventions. A literature review and a brainstorming session with 11 researchers from a variety of scientific disciplines were used to identify theoretical and conceptual models describing clinicians' guideline compliance. MEDLINE, EMBASE, CINAHL, and the bibliographies of the papers identified were used as data sources for identifying the relevant theoretical and conceptual models. Thirteen different models that originated from various disciplines including medicine, rural sociology, psychology, human factors and systems engineering, organizational management, marketing, and health education were identified. Four main categories of factors that affect compliance emerged from our analysis: clinician characteristics, guideline characteristics, system characteristics, and implementation characteristics. Based on these findings, we developed an interdisciplinary conceptual framework that specifies the expected interrelationships among these four categories of factors and their impact on clinicians' compliance. An interdisciplinary approach is needed to improve clinicians' compliance with evidence-based guidelines. The conceptual framework from this research can provide a comprehensive and systematic guide to identify barriers to guideline compliance and design effective interventions to improve patient safety.

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

Predictive factors for the occurrence of idiopathic menorrhagia: evidence for a hereditary trait.

PubMed

Kuzmina, Natalia; Palmblad, Jan; Mints, Miriam

2011-01-01

The aim of the present study was to assess predictive factors for occurrence of idiopathic menorrhagia (IM), a disease characterized by abnormal endometrial blood vessel morphology. It was hypothesized that IM exhibits familial clustering (suggesting inheritance) and is associated with other vascular abnormalities, primarily cutaneous hemangiomas. Women with IM (n=152) and healthy, regularly menstruating (n=56) women answered a questionnaire concerning menstrual pattern, susceptibility to bleeding and family history of abnormal gynecological bleeding. Factor analysis with principal component extraction was used to separate predictive factors that may be associated with IM. A total of 35 different items were analyzed. A strong association was found between IM and a family history of heavy menstrual bleeding (r=0.68), but not with cutaneous vascular abnormalities. Our results revealed that a family history of heavy menstrual bleeding may have the highest predictive value for the diagnosis of IM, indicating a hereditary trait.

Predictive factors associated with neck pain in patients with cervical disc degeneration

PubMed Central

Kong, Lingde; Tian, Weifeng; Cao, Peng; Wang, Haonan; Zhang, Bing; Shen, Yong

2017-01-01

Abstract The predictive factors associated with neck pain remain unclear. We conducted a cross-sectional study to assess predictive factors, especially Modic changes (MCs), associated with the intensity and duration of neck pain in patients with cervical disc degenerative disease. We retrospectively reviewed patients in our hospital from January 2013 to December 2016. Severe neck pain (SNP) and persistent neck pain (PNP) were the 2 main outcomes, and were assessed based on the numerical rating scale (NRS). Basic data, and also imaging data, were collected and analyzed as potential predictive factors. Univariate analysis and multiple logistic regression analysis were performed to assess the predictive factors for neck pain. In all, 381 patients (193 males and 188 females) with cervical degenerative disease were included in our study. The number of patients with SNP and PNP were 94 (24.67%) and 109 (28.61%), respectively. The NRS of neck pain in patients with type 1 MCs was significantly higher than type 2 MCs (4.8 ± 0.9 vs 3.9 ± 1.1; P = .004). The multivariate logistic analysis showed that kyphosis curvature (odds ratio [OR] 1.082, 95% confidence interval [CI] 1.044–1.112), spondylolisthesis (OR 1.339, 95% CI 1.226–1.462), and annular tear (OR 1.188, 95% CI 1.021–1.382) were factors associated with SNP, whereas kyphosis curvature (OR 1.568, 95% CI 1.022–2.394), spondylolisthesis (OR 1.486, 95% CI 1.082–2.041), and MCs (OR 1.152, 95% CI 1.074–1.234) were associated with PNP. We concluded that kyphosis curvature, spondylolisthesis, and annular tear are associated with SNP, whereas kyphosis curvature, spondylolisthesis, and MCs are associated with PNP. This study supports the view that MCs can lead to a long duration of neck pain. PMID:29069048

Identifying and describing feelings and psychological flexibility predict mental health in men with HIV.

PubMed

Landstra, Jodie M B; Ciarrochi, Joseph; Deane, Frank P; Hillman, Richard J

2013-11-01

Difficulty identifying and describing feelings (DIDF) and psychological flexibility (PF) predict poor emotional adjustment. To examine the relationship between DIDF and PF and whether DIDF and low PF would put men undergoing cancer screening at risk for poor adjustment. Longitudinal self-report survey. Two hundred and one HIV-infected men who have sex with men participated in anal cancer screening at two time points over 14 weeks. Psychological flexibility was assessed by the Acceptance and Action Questionnaire II and DIDF by the Toronto Alexithymia Scale-20. We also measured depression, anxiety, stress (DASS) and health-related quality of life (QOL; SF-12). Both DIDF and PF were reliable predictors of mental health. When levels of baseline mental health were controlled, greater DIDF predicted increases in Time 2 depression, anxiety and stress and decreases in mental and physical QOL. The link between PF and mental health was entirely mediated by DIDF. Being chronically low in PF could lead to greater DIDF and thereby worse mental health. Having more PF promotes the ability to identify and differentiate the nuances of pleasant and unpleasant emotions, which enhances an individual's mental health. Intentionally enhancing men's ability to identify and describe feelings or PF may assist them to better manage a range of difficult life experiences such as health screenings and other potentially threatening information. © 2013 The British Psychological Society.

Quantifying prognosis with risk predictions.

PubMed

Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

2012-01-01

Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

PubMed

Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

2015-07-01

Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period.

Identifying Dust Sources by Positive Matrix Factorization (PMF)

NASA Astrophysics Data System (ADS)

Engelbrecht, Johann P.

2010-05-01

elemental species was modeled by PMF. A five factor solution identified three soil factors, a silicate soil, limestone soil, and a gypsum soil, as well as a salt factor and an anthropogenic metal factor. Similarly, a set of 362 quartz filter samples analyzed for 10 selected chemical species was modeled by PMF. A five factor solution provided a limestone-gypsum soil, diesel combustion, secondary ammonium sulfate, salt and agricultural-burnpit combustion source type. Examples of time series plots of PMF factor contributions for each of six sampling sites (Balad, Baghdad, Tallil, Tikrit, Taji, and Al Asad) will be discussed. Engelbrecht , J. P., McDonald, E. V., Gillies, J. A., Jayanty, R. K. M., Casuccio, G., and Gertler, A. W., 2009, Characterizing mineral dusts and other aerosols from the Middle East - Part 1: Ambient sampling: Inhalation Toxicology, v. 21, p. 297-326.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

PubMed Central

Wenger, Aaron M.; Clarke, Shoa L.; Guturu, Harendra; Chen, Jenny; Schaar, Bruce T.; McLean, Cory Y.; Bejerano, Gill

2013-01-01

The human genome encodes 1500–2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells. PMID:23382538

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

PubMed

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

2017-01-09

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Baseline Risk Factors that Predict the Development of Open-angle Glaucoma in a Population: The Los Angeles Latino Eye Study

PubMed Central

Jiang, Xuejuan; Varma, Rohit; Wu, Shuang; Torres, Mina; Azen, Stanley P; Francis, Brian A.; Chopra, Vikas; Nguyen, Betsy Bao-Thu

2012-01-01

Objective To determine which baseline socio-demographic, lifestyle, anthropometric, clinical, and ocular risk factors predict the development of open-angle glaucoma (OAG) in an adult population. Design A population-based, prospective cohort study. Participants A total of 3,772 self-identified Latinos aged 40 years and older from Los Angeles, California who were free of OAG at baseline. Methods Participants from the Los Angeles Latino Eye Study had standardized study visits at baseline and 4-year follow-up with structured interviews and a comprehensive ophthalmologic examination. OAG was defined as the presence of an open angle and a glaucomatous visual field abnormality and/or evidence of glaucomatous optic nerve damage in at least one eye. Multivariate logistic regression with stepwise selection was performed to determine which potential baseline risk factors independently predict the development of OAG. Main Outcome Measure Odds ratios for various risk factors. Results Over the 4-year follow-up, 87 participants developed OAG. The baseline risk factors that predict the development of OAG include: older age (odds ratio [OR] per decade, 2.19; 95% confidence intervals [CI], 1.74-2.75; P<0.001), higher intraocular pressure (OR per mmHg, 1.18; 95% CI, 1.10-1.26; P<0.001), longer axial length (OR per mm, 1.48; 95% CI, 1.22-1.80; P<0.001), thinner central cornea (OR per 40 μm thinner, 1.30; 95% CI, 1.00-1.70; P=0.050) higher waist to hip ratio (OR per 0.05 higher, 1.21; 95% CI, 1.05-1.39; P=0.007) and lack of vision insurance (OR, 2.08; 95% CI, 1.26-3.41; P=0.004). Conclusions Despite a mean baseline IOP of 14 mmHg in Latinos, higher intraocular pressure is an important risk factor for developing OAG. Biometric measures suggestive of less structural support such as longer axial length and thin CCT were identified as important risk factors. Lack of health insurance reduces access to eye care and increases the burden of OAG by reducing the likelihood of early detection

Identifying important motivational factors for professionals in Greek hospitals

PubMed Central

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P < 0.001). Within subgroups, motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P < 0.05). Remuneration (and salary in particular) was reported as a significant incentive only for professionals in managerial positions. Health professionals in private hospitals were motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

Global analysis of bacterial transcription factors to predict cellular target processes.

PubMed

Doerks, Tobias; Andrade, Miguel A; Lathe, Warren; von Mering, Christian; Bork, Peer

2004-03-01

Whole-genome sequences are now available for >100 bacterial species, giving unprecedented power to comparative genomics approaches. We have applied genome-context methods to predict target processes that are regulated by transcription factors (TFs). Of 128 orthologous groups of proteins annotated as TFs, to date, 36 are functionally uncharacterized; in our analysis we predict a probable cellular target process or biochemical pathway for half of these functionally uncharacterized TFs.

Predictive factors for the methotrexate treatment outcome in ectopic pregnancy: A comparative study of 400 cases.

PubMed

Bonin, Lucie; Pedreiro, Cécile; Moret, Stéphanie; Chene, Gautier; Gaucherand, Pascal; Lamblin, Géry

2017-01-01

We sought to evaluate the global success rate of intramuscular methotrexate for the treatment of ectopic pregnancy, identify factors predictive of treatment success or failure, and study methotrexate tolerability in a large patient cohort. For this single-center retrospective observational study, we retrieved the records of all women who had a clinically or echographically confirmed ectopic pregnancy with a Fernandez score <13 and who were treated according to a 1mg/kg intramuscular single-dose methotrexate protocol. Medical treatment failure was defined by an obligation to proceed to laparoscopy. Needing a second injection was not considered to be medical treatment failure. Between February 2008 and November 2013 (69 months), 400 women received methotrexate for ectopic pregnancy. The medical treatment protocol was effective for 314 patients, i.e., an overall success rate of 78.5%. A single methotrexate dose was sufficient for 63.5% of the women and a second dose was successful for 73.2% of the remaining women. The medical treatment success rate fell as initial hCG levels climbed. The main factors associated with methotrexate failure included day (D) 0, D4 and D7 hCG levels, pretherapeutic blood progesterone, hematosalpinx at D0 and pain at D7. Early favorable kinetics of hCG levels was predictive of success. Methotrexate treatment was successful in 90% of women who had D0 hCG <1000IU/l. Methotrexate tolerability was good, with only 9% of the women reporting non-severe adverse effects. The fertility rate with delivery after medical treatment for ectopic pregnancy was 80.7%. In this study, we showed that an initial hCG value <1000IU/l and favorable early HCG kinetics were predictive factors for the successful medical treatment of ectopic pregnancy by methotrexate, and hematosalpinx and pretherapeutic blood progesterone >5ng/ml at diagnosis were predictive of its failure. We also confirmed good tolerability for single-dose methotrexate protocols. Copyright �

Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks.

PubMed

Ranjbar, Mansour; Shoghli, Alireza; Kolifarhood, Goodarz; Tabatabaei, Seyed Mehdi; Amlashi, Morteza; Mohammadi, Mahdi

2016-03-02

Malaria re-introduction is a challenge in elimination settings. To prevent re-introduction, receptivity, vulnerability, and health system capacity of foci should be monitored using appropriate tools. This study aimed to design an applicable model to monitor predicting factors of re-introduction of malaria in highly prone areas. This exploratory, descriptive study was conducted in a pre-elimination setting with a high-risk of malaria transmission re-introduction. By using nominal group technique and literature review, a list of predicting indicators for malaria re-introduction and outbreak was defined. Accordingly, a checklist was developed and completed in the field for foci affected by re-introduction and for cleared-up foci as a control group, for a period of 12 weeks before re-introduction and for the same period in the previous year. Using field data and analytic hierarchical process (AHP), each variable and its sub-categories were weighted, and by calculating geometric means for each sub-category, score of corresponding cells of interaction matrices, lower and upper threshold of different risks strata, including low and mild risk of re-introduction and moderate and high risk of malaria outbreaks, were determined. The developed predictive model was calibrated through resampling with different sets of explanatory variables using R software. Sensitivity and specificity of the model were calculated based on new samples. Twenty explanatory predictive variables of malaria re-introduction were identified and a predictive model was developed. Unpermitted immigrants from endemic neighbouring countries were determined as a pivotal factor (AHP score: 0.181). Moreover, quality of population movement (0.114), following malaria transmission season (0.088), average daily minimum temperature in the previous 8 weeks (0.062), an outdoor resting shelter for vectors (0.045), and rainfall (0.042) were determined. Positive and negative predictive values of the model were 81.8 and

Which factors predict the time spent answering queries to a drug information centre?

PubMed Central

Reppe, Linda A.; Spigset, Olav

2010-01-01

Objective To develop a model based upon factors able to predict the time spent answering drug-related queries to Norwegian drug information centres (DICs). Setting and method Drug-related queries received at 5 DICs in Norway from March to May 2007 were randomly assigned to 20 employees until each of them had answered a minimum of five queries. The employees reported the number of drugs involved, the type of literature search performed, and whether the queries were considered judgmental or not, using a specifically developed scoring system. Main outcome measures The scores of these three factors were added together to define a workload score for each query. Workload and its individual factors were subsequently related to the measured time spent answering the queries by simple or multiple linear regression analyses. Results Ninety-six query/answer pairs were analyzed. Workload significantly predicted the time spent answering the queries (adjusted R2 = 0.22, P < 0.001). Literature search was the individual factor best predicting the time spent answering the queries (adjusted R2 = 0.17, P < 0.001), and this variable also contributed the most in the multiple regression analyses. Conclusion The most important workload factor predicting the time spent handling the queries in this study was the type of literature search that had to be performed. The categorisation of queries as judgmental or not, also affected the time spent answering the queries. The number of drugs involved did not significantly influence the time spent answering drug information queries. PMID:20922480

Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia

PubMed Central

Oswald, William E.; Stewart, Aisha E. P.; Flanders, W. Dana; Kramer, Michael R.; Endeshaw, Tekola; Zerihun, Mulat; Melaku, Birhanu; Sata, Eshetu; Gessesse, Demelash; Teferi, Tesfaye; Tadesse, Zerihun; Guadie, Birhan; King, Jonathan D.; Emerson, Paul M.; Callahan, Elizabeth K.; Moe, Christine L.; Clasen, Thomas F.

2016-01-01

This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies. PMID:27430547

A characterization of factors determining postoperative ileus after laparoscopic colectomy enables the generation of a novel predictive score.

PubMed

Kronberg, Udo; Kiran, Ravi P; Soliman, Mohamed S M; Hammel, Jeff P; Galway, Ursula; Coffey, John Calvin; Fazio, Victor W

2011-01-01

Postoperative ileus (POI) after colorectal surgery is associated with prolonged hospital stay and increased costs. The aim of this study is to investigate pre-, intra-, and postoperative risk factors associated with the development of POI in patients undergoing laparoscopic partial colectomy. Patients operated between 2004 and 2008 were retrospectively identified from a prospectively maintained database, and clinical, metabolic, and pharmacologic data were obtained. Postoperative ileus was defined as the absence of bowel function for 5 or more days or the need for reinsertion of a nasogastric tube after starting oral diet in the absence of mechanical obstruction. Associations between likelihood of POI and study variables were assessed univariably by using χ tests, Fisher exact tests, and logistic regression models. A scoring system for prediction of POI was constructed by using a multivariable logistic regression model based on forward stepwise selection of preoperative factors. A total of 413 patients (mean age, 58 years; 53.5% women) were included, and 42 (10.2%) of them developed POI. Preoperative albumin, postoperative deep-vein thrombosis, and electrolyte levels were associated with POI. Age, previous abdominal surgery, and chronic preoperative use of narcotics were independently correlated with POI on multivariate analysis, which allowed the creation of a predictive score. Patients with a score of 2 or higher had an 18.3% risk of POI (P < 0.001). Postoperative ileus after laparoscopic partial colectomy is associated with specific preoperative and postoperative factors. The likelihood of POI can be predicted by using a preoperative scoring system. Addressing the postoperative factors may be expected to reduce the incidence of this common complication in high-risk patients.

Predictive Factors of Mortality in Burn Patients

PubMed Central

Fazeli, Shahram; Karami-Matin, Reza; Kakaei, Neda; Pourghorban, Samira; Safari-Faramani, Roya; Safari-Faramani, Bahare

2014-01-01

Background: Burn injuries impose a considerable burden on healthcare systems in Iran. It is among the top ten causes of mortality and a main cause of disability. Objectives: This study aimed to examine factors influencing mortality in burn patients admitted to the main educational tertiary referral hospital in Kermanshah. Patients and Methods: All patients admitted to the Imam Khomeini Hospital (from March 2011 to March 2012), due to thermal burn injuries were included in the study. We applied multiple logistic regressions to identify risk and protective factors of mortality. Also we calculated lethal area fifty percent (LA50), as an aggregate index for hospital quality. Results: During the study period, 540 burn patients were admitted. Male to female ratio was 1.12:1. Twenty three percent of the patients were less than 15 years-old. Median of age was 25 years (Inter Quartile Range, 16 - 37). Overall, probability of death was 25.8%. Lethal area fifty percent (LA50) was 50.82 (CI 95%: 47.76 - 54.48). In the final model, after adjustment of sex, age, total body surface area (TBSA), cause of burn and it’s severity, female gender (P < 0.05), age ≥ 60 years (in comparison with age less than 15 years, P < 0.05) and larger burn size (P < 0.0001) were identified as the main risk factors of death in these patients. Conclusions: Findings showed that the main risk factors of death were female gender, burn size and old age. Directing more attention to these vulnerable patients is required to reduce mortality and improve patient survival. PMID:24719826

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds

Risk factors predict post-traumatic stress disorder differently in men and women

PubMed Central

Christiansen, Dorte M; Elklit, Ask

2008-01-01

Background About twice as many women as men develop post-traumatic stress disorder (PTSD), even though men as a group are exposed to more traumatic events. Exposure to different trauma types does not sufficiently explain why women are more vulnerable. Methods The present work examines the effect of age, previous trauma, negative affectivity (NA), anxiety, depression, persistent dissociation, and social support on PTSD separately in men and women. Subjects were exposed to either a series of explosions in a firework factory near a residential area or to a high school stabbing incident. Results Some gender differences were found in the predictive power of well known risk factors for PTSD. Anxiety predicted PTSD in men, but not in women, whereas the opposite was found for depression. Dissociation was a better predictor for PTSD in women than in men in the explosion sample but not in the stabbing sample. Initially, NA predicted PTSD better in women than men in the explosion sample, but when compared only to other significant risk factors, it significantly predicted PTSD for both men and women in both studies. Previous traumatic events and age did not significantly predict PTSD in either gender. Conclusion Gender differences in the predictive value of social support on PTSD appear to be very complex, and no clear conclusions can be made based on the two studies included in this article. PMID:19017412

A Western diet ecological module identified from the 'humanized' mouse microbiota predicts diet in adults and formula feeding in children.

PubMed

Siddharth, Jay; Holway, Nicholas; Parkinson, Scott J

2013-01-01

The interplay between diet and the microbiota has been implicated in the growing frequency of chronic diseases associated with the Western lifestyle. However, the complexity and variability of microbial ecology in humans and preclinical models has hampered identification of the molecular mechanisms underlying the association of the microbiota in this context. We sought to address two key questions. Can the microbial ecology of preclinical models predict human populations? And can we identify underlying principles that surpass the plasticity of microbial ecology in humans? To do this, we focused our study on diet; perhaps the most influential factor determining the composition of the gut microbiota. Beginning with a study in 'humanized' mice we identified an interactive module of 9 genera allied with Western diet intake. This module was applied to a controlled dietary study in humans. The abundance of the Western ecological module correctly predicted the dietary intake of 19/21 top and 21/21 of the bottom quartile samples inclusive of all 5 Western and 'low-fat' diet subjects, respectively. In 98 volunteers the abundance of the Western module correlated appropriately with dietary intake of saturated fatty acids, fat-soluble vitamins and fiber. Furthermore, it correlated with the geographical location and dietary habits of healthy adults from the Western, developing and third world. The module was also coupled to dietary intake in children (and piglets) correlating with formula (vs breast) feeding and associated with a precipitous development of the ecological module in young children. Our study provides a conceptual platform to translate microbial ecology from preclinical models to humans and identifies an ecological network module underlying the association of the gut microbiota with Western dietary habits.

Macrophage Migration Inhibitory Factor Induces Inflammation and Predicts Spinal Progression in Ankylosing Spondylitis.

PubMed

Ranganathan, Vidya; Ciccia, Francesco; Zeng, Fanxing; Sari, Ismail; Guggino, Guiliana; Muralitharan, Janogini; Gracey, Eric; Haroon, Nigil

2017-09-01

To investigate the role of macrophage migration inhibitory factor (MIF) in the pathogenesis of ankylosing spondylitis (AS). Patients who met the modified New York criteria for AS were recruited for the study. Healthy volunteers, rheumatoid arthritis patients, and osteoarthritis patients were included as controls. Based on the annual rate of increase in modified Stoke AS Spine Score (mSASSS), AS patients were classified as progressors or nonprogressors. MIF levels in serum and synovial fluid were quantitated by enzyme-linked immunosorbent assay. Predictors of AS progression were evaluated using logistic regression analysis. Immunohistochemical analysis of ileal tissue was performed to identify MIF-producing cells. Flow cytometry was used to identify MIF-producing subsets, expression patterns of the MIF receptor (CD74), and MIF-induced tumor necrosis factor (TNF) production in the peripheral blood. MIF-induced mineralization of osteoblast cells (SaOS-2) was analyzed by alizarin red S staining, and Western blotting was used to quantify active β-catenin levels. Baseline serum MIF levels were significantly elevated in AS patients compared to healthy controls and were found to independently predict AS progression. MIF levels were higher in the synovial fluid of AS patients, and MIF-producing macrophages and Paneth cells were enriched in their gut. MIF induced TNF production in monocytes, activated β-catenin in osteoblasts, and promoted the mineralization of osteoblasts. Our findings indicate an unexplored pathogenic role of MIF in AS and a link between inflammation and new bone formation. © 2017, American College of Rheumatology.

[Two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education].

PubMed

Lee, Soon Ok; Lee, Sang Yeoup; Baek, Sunyong; Woo, Jae Seok; Im, Sun Ju; Yune, So Jung; Lee, Sun Hee; Kam, Beesung

2015-06-01

We performed a two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education. Strategy factors in successful learning were identified using a content analysis of open-ended responses from 30 medical students who were ranked in the top 10 of their class. Core words were selected among their responses in each category and the frequency of the words were counted. Then, a factors survey was conducted among year 2 students, before the second semester. Finally, we performed an analysis to assess the association between the factors score and academic achievement for the same students 2.5 years later. The core words were "planning and execution," "daily reviews" in the study schedule category; "focusing in class" and "taking notes" among class-related category; and "lecture notes," "previous exams or papers," and "textbooks" in the primary self-learning resources category. There were associations between the factors scores for study planning and execution, focusing in class, and taking notes and academic achievement, representing the second year second semester credit score, third year written exam scores and fourth year written and skill exam scores. Study planning was only one independent variable to predict fourth year summative written exam scores. In a two-and-a-half year follow-up study, associations were founded between academic achievement and the factors scores for study planning and execution, focusing in class, and taking notes. Study planning as only one independent variable is useful for predicting fourth year summative written exam score.

Prevalence and predictive factors of post-traumatic hypopituitarism.

PubMed

Klose, M; Juul, A; Poulsgaard, L; Kosteljanetz, M; Brennum, J; Feldt-Rasmussen, U

2007-08-01

To estimate the prevalence and predictive factors of hypopituitarism following traumatic brain injury (TBI). A cross-sectional cohort study. One hundred and four hospitalized TBI patients (26F/78M), median age 41 (range 18-64) years, body mass index (BMI) 25 (17-39) kg/m(2); severity: mild [Glasgow Coma Scale (GCS) score 13-15) n = 44, moderate (GCS 9-12) n = 20, severe (GCS < 9) n = 40]. Patients were evaluated 13 (10-27) months post-injury, with measurement of baseline (0800-1000 h) and post-stimulatory hormonal levels during an insulin tolerance test (ITT) (86%) or, if contraindicated, an arginine(arg)-GHRH test + Synacthen test (14%). Insufficiencies were confirmed by retesting. Hypopituitarism was found in 16 (15%) patients, affecting one axis in 10, two axes in four and more than two axes in two patients. The GH axis was most frequently affected (15%), followed by secondary hypoadrenalism (5%), hypogonadism (2%), hypothyroidism (2%) and diabetes insipidus (2%). The risk of pituitary insufficiency was increased in patients with severe TBI as opposed to mild TBI [odds ratio (OR) 10.1, 95% confidence interval (CI) 2.1-48.4, P = 0.004], and in those patients with increased intracerebral pressure [OR 6.5, 95% CI 1.0-42.2, P = 0.03]. Patients with only one affected axis were all GH deficient; 60% (n = 6) of these were overweight or obese. The prevalence of hypopituitarism was estimated at 16%. Although high, this value was lower than previously reported, and may still be overestimated because of well-known confounding factors, such as obesity. Indicators of increased TBI severity were predictive of hypopituitarism, with a high negative predictive value. Neuroendocrine evaluation should therefore be considered in patients with severe TBI, and in particular in those with increased intracerebral pressure (ICP).

Specific headache factors predict sleep disturbances among youth with migraine.

PubMed

Heyer, Geoffrey L; Rose, Sean C; Merison, Kelsey; Perkins, Sara Q; Lee, Jo Ellen M

2014-10-01

There is a paucity of pediatric data addressing the complex relationship between primary headaches and sleep disturbances. Our study objective was to explore headache-related factors that predict sleep disturbance and to compare sleep complaints with other forms of headache-related disability among youth with migraines. A prospective cohort study was conducted in patients 10-18 years old with migraine or probable migraine and without daily sleep complaints. The patients completed a 90-day internet-based headache diary. On headache days, patients rated headache intensity, answered Pediatric Migraine Disability Assessment-based questions modified for daily scoring, and reported sleep disturbances that resulted as a direct effect of proximate headaches. Fifty-two patients generated 4680 diary entries, 984 patients (21%) involved headaches. Headache intensity (P = 0.009) and timing of headache onset (P < 0.001) were predictive of sleep disturbances. Three Pediatric Migraine Disability Assessment-based items were also associated with sleep disturbances: partial school-day absence (P = 0.04), recreational activities prevented (P < 0.001), and decreased functioning during recreational activities (P < 0.001). Sleep disturbances correlated positively and significantly with daily headache disability scores (rpb = 0.35; P < 0.01). We conclude that specific headache factors predict sleep disturbances among youth with primary headaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Can shoulder dystocia be reliably predicted?

PubMed

Dodd, Jodie M; Catcheside, Britt; Scheil, Wendy

2012-06-01

To evaluate factors reported to increase the risk of shoulder dystocia, and to evaluate their predictive value at a population level. The South Australian Pregnancy Outcome Unit's population database from 2005 to 2010 was accessed to determine the occurrence of shoulder dystocia in addition to reported risk factors, including age, parity, self-reported ethnicity, presence of diabetes and infant birth weight. Odds ratios (and 95% confidence interval) of shoulder dystocia was calculated for each risk factor, which were then incorporated into a logistic regression model. Test characteristics for each variable in predicting shoulder dystocia were calculated. As a proportion of all births, the reported rate of shoulder dystocia increased significantly from 0.95% in 2005 to 1.38% in 2010 (P = 0.0002). Using a logistic regression model, induction of labour and infant birth weight greater than both 4000 and 4500 g were identified as significant independent predictors of shoulder dystocia. The value of risk factors alone and when incorporated into the logistic regression model was poorly predictive of the occurrence of shoulder dystocia. While there are a number of factors associated with an increased risk of shoulder dystocia, none are of sufficient sensitivity or positive predictive value to allow their use clinically to reliably and accurately identify the occurrence of shoulder dystocia. © 2012 The Authors ANZJOG © 2012 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Hemorrhage control for laparoscopic hepatectomy: technical details and predictive factors for intraoperative blood loss.

PubMed

Kawaguchi, Yoshikuni; Nomi, Takeo; Fuks, David; Mal, Frederic; Kokudo, Norihiro; Gayet, Brice

2016-06-01

Controlling bleeding during laparoscopic hepatectomy (LH) is technically demanding, but reportedly associated with less estimated blood loss (EBL) than open surgery. The present study aimed to describe and evaluate hemorrhage control techniques during LH and identify predictors of high intraoperative EBL. The data of 438 consecutive patients undergoing LH between 1995 and 2012 were reviewed. Bleeding control was facilitated by the proper use of hemostatic devices and surgical maneuvers unique to LH and by preserving intra-abdominal pressure. EBL was evaluated among three groups of 146 patients in each group: 1995-2006 (group A), 2006-2009 (group B), and 2009-2012 (group C). We also sought factors that predicted EBL ≥800 mL. Mean EBL decreased overtime from groups A to C: group A, 378 ± 619 mL; group B, 293 ± 391 mL; groups C, 257 ± 366 mL; P = 0.127. Transfusion rate was 6.7 % in group A, 5.5 % in group B, and 4.8 % in group C (P = 0.743). Hypertension (odds ratio (OR) 2.82, 95 % confidence interval CI 1.37-5.78; P = 0.006), preoperative chemotherapy (OR 2.55, 95 % CI 1.26-5.31; P = 0.009), resection of posterosuperior segments (OR 3.73, 95 % CI 1.33-12.17; P = 0.012), and major hepatectomy (OR 4.21, 95 % CI 1.64-13.02; P < 0.001) independently predicted high EBL. Improvements in bleeding control techniques over time have reduced EBL during LH. The use of these techniques and an understanding of the predictive factors for high EBL will help surgeons improve outcomes after LH.

[Lightning-caused fire, its affecting factors and prediction: a review].

PubMed

Zhang, Ji-Li; Bi, Wu; Wang, Xiao-Hong; Wang, Zi-Bo; Li, Di-Fei

2013-09-01

Lightning-caused fire is the most important natural fire source. Its induced forest fire brings enormous losses to human beings and ecological environment. Many countries have paid great attention to the prediction of lightning-caused fire. From the viewpoint of the main factors affecting the formation of lightning-caused fire, this paper emphatically analyzed the effects and action mechanisms of cloud-to-ground lightning, fuel, meteorology, and terrain on the formation and development process of lightning-caused fire, and, on the basis of this, summarized and reviewed the logistic model, K-function, and other mathematical methods widely used in prediction research of lightning-caused fire. The prediction methods and processes of lightning-caused fire in America and Canada were also introduced. The insufficiencies and their possible solutions for the present researches as well as the directions of further studies were proposed, aimed to provide necessary theoretical basis and literature reference for the prediction of lightning-caused fire in China.

Identifying mediating factors of moral reasoning in science education

NASA Astrophysics Data System (ADS)

Zeidler, Dana L.; Schafer, Larry E.

The purpose of this research was to examine how science content knowledge, moral reasoning ability, attitudes, and past experiences mediate the formation of moral judgments on environmental dilemmas. The study was conducted in two phases using environmental science majors and nonscience majors of college age. Phase One determined if environmental science majors exhibited higher levels of moral reasoning on nontechnical environmental social issues than on general social issues and examined the extent to which possible mediating factors accounted for differences in moral reasoning. Phase Two was qualitative in nature, the purpose of which was to observe and identify trends in conversations between subjects as to how certain mediating factors are revealed as people form moral judgments. The framework on which this study was constructed incorporates a progressive educational position; a position that views science education as being interdisciplinary, and a social means to a social end.

Development and Validation of a Clinic-Based Prediction Tool to Identify Female Athletes at High Risk for Anterior Cruciate Ligament Injury

PubMed Central

Myer, Gregory D.; Ford, Kevin R.; Khoury, Jane; Succop, Paul; Hewett, Timothy E.

2012-01-01

Background Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at high risk for anterior cruciate ligament injury. Laboratory-based measurements demonstrate 90% accuracy in prediction of high KAM. Clinic-based prediction algorithms that employ correlates derived from laboratory-based measurements also demonstrate high accuracy for prediction of high KAM mechanics during landing. Hypotheses Clinic-based measures derived from highly predictive laboratory-based models are valid for the accurate prediction of high KAM status, and simultaneous measurements using laboratory-based and clinic-based techniques highly correlate. Study Design Cohort study (diagnosis); Level of evidence, 2. Methods One hundred female athletes (basketball, soccer, volleyball players) were tested using laboratory-based measures to confirm the validity of identified laboratory-based correlate variables to clinic-based measures included in a prediction algorithm to determine high KAM status. To analyze selected clinic-based surrogate predictors, another cohort of 20 female athletes was simultaneously tested with both clinic-based and laboratory-based measures. Results The prediction model (odds ratio: 95% confidence interval), derived from laboratory-based surrogates including (1) knee valgus motion (1.59: 1.17-2.16 cm), (2) knee flexion range of motion (0.94: 0.89°-1.00°), (3) body mass (0.98: 0.94-1.03 kg), (4) tibia length (1.55: 1.20-2.07 cm), and (5) quadriceps-to-hamstrings ratio (1.70: 0.48%-6.0%), predicted high KAM status with 84% sensitivity and 67% specificity (P < .001). Clinic-based techniques that used a calibrated physician’s scale, a standard measuring tape, standard camcorder, ImageJ software, and an isokinetic dynamometer showed high correlation (knee valgus motion, r = .87; knee flexion range of motion, r = .95; and tibia length, r = .98) to simultaneous laboratory-based measurements. Body mass and quadriceps-to-hamstrings ratio

Use of NMR and NMR Prediction Software to Identify Components in Red Bull Energy Drinks

ERIC Educational Resources Information Center

Simpson, Andre J.; Shirzadi, Azadeh; Burrow, Timothy E.; Dicks, Andrew P.; Lefebvre, Brent; Corrin, Tricia

2009-01-01

A laboratory experiment designed as part of an upper-level undergraduate analytical chemistry course is described. Students investigate two popular soft drinks (Red Bull Energy Drink and sugar-free Red Bull Energy Drink) by NMR spectroscopy. With assistance of modern NMR prediction software they identify and quantify major components in each…

Predictive factors for overall quality of life in patients with advanced cancer.

PubMed

Cramarossa, Gemma; Chow, Edward; Zhang, Liying; Bedard, Gillian; Zeng, Liang; Sahgal, Arjun; Vassiliou, Vassilios; Satoh, Takefumi; Foro, Palmira; Ma, Brigette B Y; Chie, Wei-Chu; Chen, Emily; Lam, Henry; Bottomley, Andrew

2013-06-01

This study examined which domains/symptoms from the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 15 Palliative (QLQ-C15-PAL), an abbreviated version of the health-related EORTC QLQ-C30 questionnaire designed for palliative cancer patients, were predictive of overall quality of life (QOL) in advanced cancer patients. Patients with advanced cancer from six countries completed the QLQ-C15-PAL at consultation and at one follow-up point. Univariate and multivariate regression analyses were conducted to determine the predictive value of the EORTC QLQ-C15-PAL functional/symptom scores for global QOL (question 15). Three hundred forty-nine patients completed the EORTC QLQ-C15-PAL at baseline. In the total patient sample, worse emotional functioning, pain, and appetite loss were the most significant predictive factors for worse QOL. In the subgroup of patients with bone metastases (n = 240), the domains mentioned above were also the most significant predictors, whereas in patients with brain metastases (n = 109), worse physical and emotional functioning most significantly predicted worse QOL. One-month follow-up in 267 patients revealed that the significant predictors changed somewhat over time. For example, in the total patient sample, physical functioning, fatigue, and appetite loss were significant predictors at the follow-up point. A sub-analysis of predictive factors affecting QOL by primary cancer (lung, breast, and prostate) was also conducted for the total patient sample. Deterioration of certain EORTC QLQ-C15-PAL functional/symptom scores significantly contributes to worse overall QOL. Special attention should be directed to managing factors most influential on overall QOL to ensure optimal management of advanced cancer patients.

Prediction of Pathway Activation by Xenobiotic-Responsive Transcription Factors in the Mouse Liver

EPA Science Inventory

Many drugs and environmentally-relevant chemicals activate xenobioticresponsive transcription factors (TF). Identification of target genes of these factors would be useful in predicting pathway activation in in vitro chemical screening. Starting with a large compendium of Affymet...

Using an autologistic regression model to identify spatial risk factors and spatial risk patterns of hand, foot and mouth disease (HFMD) in Mainland China

PubMed Central

2014-01-01

Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD

CT and 3-T MRI accurately identify T3c disease in colon cancer, which strongly predicts disease-free survival.

PubMed

Hunter, C; Siddiqui, M; Georgiou Delisle, T; Blake, H; Jeyadevan, N; Abulafi, M; Swift, I; Toomey, P; Brown, G

2017-04-01

To compare the preoperative staging accuracy of computed tomography (CT) and 3-T magnetic resonance imaging (MRI) in colon cancer, and to investigate the prognostic significance of identified risk factors. Fifty-eight patients undergoing primary resection of their colon cancer were prospectively recruited, with 53 patients included for final analysis. Accuracy of CT and MRI were compared for two readers, using postoperative histology as the reference standard. Patients were followed-up for a median of 39 months. Risk factors were compared by modality and reader in terms of metachronous metastases and disease-free survival (DFS), stratified for adjuvant chemotherapy. Accuracy for the identification of T3c+ disease was non-significantly greater on MRI (75% and 79%) than CT (70% and 77%). Differences in the accuracy of MRI and CT for identification of T3+ disease (MRI 75% and 57%, CT 72% and 66%) and N+ disease (MRI 62% and 63%, CT 62% and 56%) were also non-significant. Identification of extramural venous invasion (EMVI+) disease was significantly greater on MRI (75% and 75%) than CT (79% and 54%) for one reader (p=0.029). T3c+ disease at histopathology was the only risk factor that demonstrated a significant difference in rate of metachronous metastases (odds ratio [OR] 8.6, p=0.0044) and DFS stratified for adjuvant therapy (OR=4, p=0.048). T3c or greater disease is the strongest risk factor for predicting DFS in colon cancer, and is accurately identified on imaging. T3c+ disease may therefore be the best imaging entry criteria for trials of neoadjuvant treatment. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

PubMed Central

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Mª; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle. PMID:22163639

Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

PubMed

Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

2010-01-01

The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy.

PubMed

Thiels, Cornelius A; Yu, Denny; Abdelrahman, Amro M; Habermann, Elizabeth B; Hallbeck, Susan; Pasupathy, Kalyan S; Bingener, Juliane

2017-01-01

Reliable prediction of operative duration is essential for improving patient and care team satisfaction, optimizing resource utilization and reducing cost. Current operative scheduling systems are unreliable and contribute to costly over- and underestimation of operative time. We hypothesized that the inclusion of patient-specific factors would improve the accuracy in predicting operative duration. We reviewed all elective laparoscopic cholecystectomies performed at a single institution between 01/2007 and 06/2013. Concurrent procedures were excluded. Univariate analysis evaluated the effect of age, gender, BMI, ASA, laboratory values, smoking, and comorbidities on operative duration. Multivariable linear regression models were constructed using the significant factors (p < 0.05). The patient factors model was compared to the traditional surgical scheduling system estimates, which uses historical surgeon-specific and procedure-specific operative duration. External validation was done using the ACS-NSQIP database (n = 11,842). A total of 1801 laparoscopic cholecystectomy patients met inclusion criteria. Female sex was associated with reduced operative duration (-7.5 min, p < 0.001 vs. male sex) while increasing BMI (+5.1 min BMI 25-29.9, +6.9 min BMI 30-34.9, +10.4 min BMI 35-39.9, +17.0 min BMI 40 + , all p < 0.05 vs. normal BMI), increasing ASA (+7.4 min ASA III, +38.3 min ASA IV, all p < 0.01 vs. ASA I), and elevated liver function tests (+7.9 min, p < 0.01 vs. normal) were predictive of increased operative duration on univariate analysis. A model was then constructed using these predictive factors. The traditional surgical scheduling system was poorly predictive of actual operative duration (R 2  = 0.001) compared to the patient factors model (R 2  = 0.08). The model remained predictive on external validation (R 2  = 0.14).The addition of surgeon as a variable in the institutional model further improved predictive ability of the model

Predictive factors for postoperative visual function of primary chronic rhegmatogenous retinal detachment after scleral buckling.

PubMed

Fang, Wei; Li, Jiu-Ke; Jin, Xiao-Hong; Dai, Yuan-Min; Li, Yu-Min

2016-01-01

To evaluate predictive factors for postoperative visual function of primary chronic rhegmatgenous retinal detachment (RRD) after sclera buckling (SB). Totally 48 patients (51 eyes) with primary chronic RRD were included in this prospective interventional clinical cases study, which underwent SB alone from June 2008 to December 2014. Age, sex, symptoms duration, detached extension, retinal hole position, size, type, fovea on/off, proliferative vitreoretinopathy (PVR), posterior vitreous detachment (PVD), baseline best corrected visual acuity (BCVA), operative duration, follow up duration, final BCVA were measured. Pearson correlation analysis, Spearman correlation analysis and multivariate linear stepwise regression were used to confirm predictive factors for better final visual acuity. Student's t-test, Wilcoxon two-sample test, Chi-square test and logistic stepwise regression were used to confirm predictive factors for better vision improvement. Baseline BCVA was 0.8313±0.6911 logMAR and final BCVA was 0.4761±0.4956 logMAR. Primary surgical success rate was 92.16% (47/51). Correlation analyses revealed shorter symptoms duration (r=0.3850, P=0.0053), less detached area (r=0.5489, P<0.0001), fovea (r=0.4605, P=0.0007), no PVR (r=0.3138, P=0.0250), better baseline BCVA (r=0.7291, P<0.0001), shorter operative duration (r=0.3233, P=0.0207) and longer follow up (r=-0.3358, P=0.0160) were related with better final BCVA, while independent predictive factors were better baseline BCVA [partial R-square (PR(2))=0.5316, P<0.0001], shorter symptoms duration (PR(2)=0.0609, P=0.0101), longer follow up duration (PR(2)=0.0278, P=0.0477) and shorter operative duration (PR(2)=0.0338, P=0.0350). Patients with vision improvement took up 49.02% (25/51). Univariate and multivariate analyses both revealed predictive factors for better vision improvement were better baseline vision [odds ratio (OR) =50.369, P=0.0041] and longer follow up duration (OR=1.144, P=0.0067). Independent

Risk factors and prediction analysis of cutaneous leishmaniasis due to Leishmania tropica in Southwestern Morocco.

PubMed

El Alem, Mohamed Mahmoud Mohamed; Hakkour, Maryam; Hmamouch, Asmae; Halhali, Meryem; Delouane, Bouchra; Habbari, Khalid; Fellah, Hajiba; Sadak, Abderrahim; Sebti, Faiza

2018-07-01

Cutaneous leishmaniasis is currently a serious public health problem in northern Africa, especially in Morocco. The causative parasite is transmitted to a human host through the bite of infected female sandflies of the genus Phlebotomus. The objective of the present study is to characterize the causative organisms and to predict the risk of cutaneous leishmaniasis (CL) cases in six provinces in southwestern Morocco, based on the spatial distribution of cases in relation to environmental factors and other risk factors such as socio-economic status and demographics. A molecular study was carried out using ITS1 PCR-RFLP method of the ribosomal DNA of Leishmania. An epidemiological study on CL cases was reported between 2000 and 2016 in this current investigation in six provinces in southwestern Morocco. Statistical analysis was performed using a linear regression model to identify the impact as well as the interaction between all predictor variables on the distribution of CL in the studied provinces. The forecast Holt-Winters (HW) method was used to describe the trend and seasonality of CL cases. The ITS1-PCR- RFLP analysis revealed the presence of Leishmania tropica in all studied provinces. The spatial distribution of CL cases documented in all studied provinces during the sixteen years showed a heterogeneous pattern and fluctuation trend with an average prevalence of 9.92 per 100,000 inhabitants. In addition, the forecast HW model predicts continued variability of trend and seasonality of CL cases in the upcoming years. This study confirmed the importance of socioeconomic factors, in particular poverty and the vulnerability rate, on distribution and emergence of CL. This study revealed a relationship between increasing risk of CL occurrence due to Leishmania tropica, as well as the distribution and emergence thereof, and socioeconomic factors in the investigated area. Copyright © 2018 Elsevier B.V. All rights reserved.

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate

PubMed Central

2013-01-01

Background The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). Methods and findings Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China. The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. Conclusions Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships. PMID:23497145

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate.

PubMed

Yang, Qingsheng; Mwenda, Kevin M; Ge, Miao

2013-03-12

The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China.The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships.

A Predictive Model Has Identified Tick-Borne Encephalitis High-Risk Areas in Regions Where No Cases Were Reported Previously, Poland, 1999–2012

PubMed Central

Rubikowska, Barbara; Bratkowski, Jakub; Ustrnul, Zbigniew; Vanwambeke, Sophie O.

2018-01-01

During 1999–2012, 77% of the cases of tick-borne encephalitis (TBE) were recorded in two out of 16 Polish provinces. However, historical data, mostly from national serosurveys, suggest that the disease could be undetected in many areas. The aim of this study was to identify which routinely-measured meteorological, environmental, and socio-economic factors are associated to TBE human risk across Poland, with a particular focus on areas reporting few cases, but where serosurveys suggest higher incidence. We fitted a zero-inflated Poisson model using data on TBE incidence recorded in 108 NUTS-5 administrative units in high-risk areas over the period 1999–2012. Subsequently we applied the best fitting model to all Polish municipalities. Keeping the remaining variables constant, the predicted rate increased with the increase of air temperature over the previous 10–20 days, precipitation over the previous 20–30 days, in forestation, forest edge density, forest road density, and unemployment. The predicted rate decreased with increasing distance from forests. The map of predicted rates was consistent with the established risk areas. It predicted, however, high rates in provinces considered TBE-free. We recommend raising awareness among physicians working in the predicted high-risk areas and considering routine use of household animal surveys for risk mapping. PMID:29617333

Automatically Identifying and Predicting Unplanned Wind Turbine Stoppages Using SCADA and Alarms System Data: Case Study and Results

NASA Astrophysics Data System (ADS)

Leahy, Kevin; Gallagher, Colm; Bruton, Ken; O'Donovan, Peter; O'Sullivan, Dominic T. J.

2017-11-01

Using 10-minute wind turbine SCADA data for fault prediction offers an attractive way of gaining additional prognostic capabilities without needing to invest in extra hardware. To use these data-driven methods effectively, the historical SCADA data must be labelled with the periods when the turbine was in faulty operation as well the sub-system the fault was attributed to. Manually identifying faults using maintenance logs can be effective, but is also highly time consuming and tedious due to the disparate nature of these logs across manufacturers, operators and even individual maintenance events. Turbine alarm systems can help to identify these periods, but the sheer volume of alarms and false positives generated makes analysing them on an individual basis ineffective. In this work, we present a new method for automatically identifying historical stoppages on the turbine using SCADA and alarms data. Each stoppage is associated with either a fault in one of the turbine’s sub-systems, a routine maintenance activity, a grid-related event or a number of other categories. This is then checked against maintenance logs for accuracy and the labelled data fed into a classifier for predicting when these stoppages will occur. Results show that the automated labelling process correctly identifies each type of stoppage, and can be effectively used for SCADA-based prediction of turbine faults.

Mass gathering medicine: event factors predicting patient presentation rates.

PubMed

Locoh-Donou, Samuel; Yan, Guofen; Berry, Thomas; O'Connor, Robert; Sochor, Mark; Charlton, Nathan; Brady, William

2016-08-01

This study was conducted to identify the event characteristics of mass gatherings that predict patient presentation rates held in a southeastern US university community. We conducted a retrospective review of all event-based emergency medical services (EMS) records from mass gathering patient presentations over an approximate 23 month period, from October 24, 2009 to August 27, 2011. All patrons seen by EMS were included. Event characteristics included: crowd size, venue percentage filled seating, venue location (inside/outside), venue boundaries (bounded/unbounded), presence of free water (i.e., without cost), presence of alcohol, average heat index, presence of climate control (i.e., air conditioning), and event category (football, concerts, public exhibitions, non-football athletic events). We identified 79 mass gathering events, for a total of 670 patient presentations. The cumulative patron attendance was 917,307 persons. The patient presentation rate (PPR) for each event was calculated as the number of patient presentations per 10,000 patrons in attendance. Overdispersed Poisson regression was used to relate this rate to the event characteristics while controlling for crowd size. In univariate analyses, increased rates of patient presentations were strongly associated with outside venues [rate ratio (RR) = 3.002, p < 0.001], unbounded venues (RR = 2.839, p = 0.001), absence of free water (RR = 1.708, p = 0.036), absence of climate control (RR = 3.028, p < 0.001), and a higher heat index (RR = 1.211 per 10-unit heat index increase, p = 0.003). The presence of alcohol was not significantly associated with the PPR. Football events had the highest PPR, followed sequentially by public exhibitions, concerts, and non-football athletic events. In multivariate models, the strong predictors from the univariate analyses retained their predictive significance for the PPR, together with heat index and percent seating. In the setting of mass event

[Cesarean after labor induction: Risk factors and prediction score].

PubMed

Branger, B; Dochez, V; Gervier, S; Winer, N

2018-05-01

The objective of the study is to determine the risk factors for caesarean section at the time of labor induction, to establish a prediction algorithm, to evaluate its relevance and to compare the results with observation. A retrospective study was carried out over a year at Nantes University Hospital with 941 cervical ripening and labor inductions (24.1%) terminated by 167 caesarean sections (17.8%). Within the cohort, a case-control study was conducted with 147 caesarean sections and 148 vaginal deliveries. A multivariate analysis was carried out with a logistic regression allowing the elaboration of an equation of prediction and an ROC curve and the confrontation between the prediction and the reality. In univariate analysis, six variables were significant: nulliparity, small size of the mother, history of scarried uterus, use of prostaglandins as a mode of induction, unfavorable Bishop score<6, variety of posterior release. In multivariate analysis, five variables were significant: nulliparity, maternal size, maternal BMI, scar uterus and Bishop score. The most predictive model corresponded to an area under the curve of 0.86 (0.82-0.90) with a correct prediction percentage ("well classified") of 67.6% for a caesarean section risk of 80%. The prediction criteria would make it possible to inform the woman and the couple about the potential risk of Caesarean section in urgency or to favor a planned Caesarean section or a low-lying attempt on more objective, repeatable and transposable arguments in a medical team. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Potential Psychosocial Risk Factors for Chronic TMD: Descriptive Data and Empirically Identified Domains from the OPPERA Case-Control Study

PubMed Central

Fillingim, Roger B.; Ohrbach, Richard; Greenspan, Joel D.; Knott, Charles; Dubner, Ronald; Bair, Eric; Baraian, Cristina; Slade, Gary D.; Maixner, William

2011-01-01

Case-control studies have consistently associated psychosocial factors with chronic pain in general, and with temporomandibular disorders (TMD) specifically. Moreover, a handful of prospective studies suggest that pre-existing psychosocial characteristics represent risk factors for new onset TMD. The current study presents psychosocial findings from the baseline case-control study of the Orofacial Pain Prospective Evaluation and Risk Assessment (OPPERA) cooperative agreement. For this study, 1,633 TMD-free controls and 185 TMD cases completed a battery of psychosocial instruments assessing general psychosocial adjustment and personality, affective distress, psychosocial stress, somatic awareness, and pain coping and catastrophizing. In bivariate and demographically-adjusted analyses, odds of TMD were associated with higher levels of psychosocial symptoms, affective distress, somatic awareness, and pain catastrophizing. Among controls, significant gender and ethnic group differences in psychosocial measures were observed, consistent with previous findings. Principal component analysis was undertaken to identify latent constructs revealing four components: stress and negative affectivity, global psychosocial symptoms, passive pain coping, and active pain coping. These findings provide further evidence of associations between psychosocial factors and TMD. Future prospective analyses in the OPPERA cohort will determine if the premorbid presence of these psychosocial factors predicts increased risk for developing new-onset TMD. PMID:22074752

Predicting dropout using student- and school-level factors: An ecological perspective.

PubMed

Wood, Laura; Kiperman, Sarah; Esch, Rachel C; Leroux, Audrey J; Truscott, Stephen D

2017-03-01

High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors associated with dropout for the purpose of better understanding how to prevent it. We used the Education Longitudinal Study of 2002 dataset. Participants included 14,106 sophomores across 684 public and private schools. We identified variables of interest based on previous research on dropout and implemented hierarchical generalized linear modeling. In the final model, significant student-level predictors included academic achievement, retention, sex, family socioeconomic status (SES), and extracurricular involvement. Significant school-level predictors included school SES and school size. Race/ethnicity, special education status, born in the United States, English as first language, school urbanicity, and school region did not significantly predict dropout after controlling for the aforementioned predictors. Implications for prevention and intervention efforts within a multitiered intervention model are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Can we predict the outcome for people with patellofemoral pain? A systematic review on prognostic factors and treatment effect modifiers.

PubMed

Matthews, M; Rathleff, M S; Claus, A; McPoil, T; Nee, R; Crossley, K; Vicenzino, B

2017-12-01

Patellofemoral pain (PFP) is a multifactorial and often persistent knee condition. One strategy to enhance patient outcomes is using clinically assessable patient characteristics to predict the outcome and match a specific treatment to an individual. A systematic review was conducted to determine which baseline patient characteristics were (1) associated with patient outcome (prognosis); or (2) modified patient outcome from a specific treatment (treatment effect modifiers). 6 electronic databases were searched (July 2016) for studies evaluating the association between those with PFP, their characteristics and outcome. All studies were appraised using the Epidemiological Appraisal Instrument. Studies that aimed to identify treatment effect modifiers underwent a checklist for methodological quality. The 24 included studies evaluated 180 participant characteristics. 12 studies investigated prognosis, and 12 studies investigated potential treatment effect modifiers. Important methodological limitations were identified. Some prognostic studies used a retrospective design. Studies aiming to identify treatment effect modifiers often analysed too many variables for the limiting sample size and typically failed to use a control or comparator treatment group. 16 factors were reported to be associated with a poor outcome, with longer duration of symptoms the most reported (>4 months). Preliminary evidence suggests increased midfoot mobility may predict those who have a successful outcome to foot orthoses. Current evidence can identify those with increased risk of a poor outcome, but methodological limitations make it difficult to predict the outcome after one specific treatment compared with another. Adequately designed randomised trials are needed to identify treatment effect modifiers. 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/.

Predicting conformational ensembles and genome-wide transcription factor binding sites from DNA sequences.

PubMed

Andrabi, Munazah; Hutchins, Andrew Paul; Miranda-Saavedra, Diego; Kono, Hidetoshi; Nussinov, Ruth; Mizuguchi, Kenji; Ahmad, Shandar

2017-06-22

DNA shape is emerging as an important determinant of transcription factor binding beyond just the DNA sequence. The only tool for large scale DNA shape estimates, DNAshape was derived from Monte-Carlo simulations and predicts four broad and static DNA shape features, Propeller twist, Helical twist, Minor groove width and Roll. The contributions of other shape features e.g. Shift, Slide and Opening cannot be evaluated using DNAshape. Here, we report a novel method DynaSeq, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features. We compared the DNAshape and DynaSeq predictions for the common features and applied both to predict the genome-wide binding sites of 1312 TFs available from protein interaction quantification (PIQ) data. The results indicate a good agreement between the two methods for the common shape features and point to advantages in using DynaSeq. Predictive models employing ensembles from individual conformational parameters revealed that base-pair opening - known to be important in strand separation - was the best predictor of transcription factor-binding sites (TFBS) followed by features employed by DNAshape. Of note, TFBS could be predicted not only from the features at the target motif sites, but also from those as far as 200 nucleotides away from the motif.

Factor analysis and predictive validity of microcomputer-based tests

NASA Technical Reports Server (NTRS)

Kennedy, R. S.; Baltzley, D. R.; Turnage, J. J.; Jones, M. B.

1989-01-01

11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

Refractoriness to immunochemotherapy in follicular lymphoma: Predictive factors and outcome.

PubMed

Sorigue, Marc; Mercadal, Santiago; Alonso, Sara; Fernández-Álvarez, Ruben; García, Olga; Moreno, Miriam; Pomares, Helena; Alcoceba, Miguel; González-García, Esther; Motlló, Cristina; González-Barca, Eva; Martin, Alejandro; Sureda, Anna; Caballero, Dolores; Ribera, Josep-María; Sancho, Juan-Manuel

2017-12-01

Follicular lymphoma is characterized by a good response to immunochemotherapy (ICT). However, a small percentage of patients responds poorly to treatment and seems to have a worse outcome. This study attempted to identify the predictive factors and outcome of refractoriness to first-line ICT. All patients diagnosed with stage II to IV follicular lymphoma between 2002 and 2014 and treated with first-line ICT in 4 Spanish institutions were analyzed. Those with no response or progression or relapse within 6 months of first-line response assessment were considered ICT refractory. Three hundred forty-three patients were included (median age 58 years, 48% male), of whom 53 (15%) were ICT refractory. On multivariate analysis, high-risk follicular lymphoma international prognostic index (FLIPI) score, B symptoms, and elevated β2-microglobulin were correlated with refractoriness, and refractoriness, high-risk FLIPI score, and β2-microglobulin were correlated with overall survival (OS). Compared with ICT-sensitive, ICT-refractory patients had a higher incidence of histological transformation (5-year cumulative incidence 25% [14%-39%] vs. 6% [3%-10%], P < .001), a higher rate of refractoriness to second-line therapy (16/33 [48%] vs. 13/57 [23%], P = .01), and a lower OS (5-year OS probability 38% [95% CI 23%-53%] vs. 87% [82%-92%%], P < .001). In conclusion, refractoriness to ICT was seen in 15% of patients and was predicted by high-FLIPI scores, B symptoms, and elevated serum β2-micrglobulin. Immunochemotherapy-refractory patients had a worse prognosis than ICT-sensitive patients, and current treatment options for this subgroup are not satisfactory. Copyright © 2017 John Wiley & Sons, Ltd.

Factors Predicting Compliance to Ecological Momentary Assessment Among Adolescent Smokers

PubMed Central

2014-01-01

Introduction: Ecological momentary assessments (EMAs) are increasingly used in smoking research to understand contextual and individual differences related to smoking and changes in smoking. To date, there has been little detailed research into the predictors of EMA compliance. However, patterns or predictors of compliance may affect key relationships under investigation and introduce sources of bias in results. The purpose of this study was to investigate predictors of compliance to random prompts among a sample of adolescents who had ever smoked. Methods: Data for this study were drawn from a sample of 461 adolescents (9th and 10th graders at baseline) participating in a longitudinal study of smoking escalation. We examined 2 outcomes: subject-level EMA compliance (overall rate of compliance over a week-long EMA wave), and in-the-moment prompt-level compliance to the most proximal random prompt. We investigated several covariates including gender, race, smoking rate, alcohol use, psychological symptomatology, home composition, mood, social context, time in study, inter-prompt interval, and location. Results: At the overall subject level, higher mean negative affect, smoking rate, alcohol use, and male gender predicted lower compliance with random EMA prompts. At the prompt level, after controlling for significant subject-level predictors of compliance, increased positive affect, being outside of the home, and longer inter-prompt interval predicted lower momentary compliance. Conclusions: This study identifies several factors associated with overall and momentary EMA compliance among a sample of adolescents participating in a longitudinal study of smoking. We also propose a conceptual framework for investigating the contextual and momentary predictors of compliance within EMA studies. PMID:24097816

Risk factors for Apgar score using artificial neural networks.

PubMed

Ibrahim, Doaa; Frize, Monique; Walker, Robin C

2006-01-01

Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified.

A prospective study of primary care patients with musculoskeletal pain: the identification of predictive factors for chronicity.

PubMed Central

Potter, R G; Jones, J M; Boardman, A P

2000-01-01

Primary care faces the challenge of reducing the proportion of patients continuing with musculoskeletal pain beyond the acute phase. This study assessed patients presenting in general practice with a four- to 12-week history of pain and re-assessed them 12 weeks later. Patients whose pain was described as 'none' or 'slight' were allocated to the 'acute group', and those whose pain continued to be 'moderate' or 'severe' were allocated to the 'chronic group'. Comparative analysis of the two groups' responses at initial assessment identified pain intensity, active coping score, and previous pain episode to be factors independently predictive of chronicity. PMID:10750237

Predictive factors of occupational noise-induced hearing loss in Spanish workers: A prospective study.

PubMed

Pelegrin, Armando Carballo; Canuet, Leonides; Rodríguez, Ángeles Arias; Morales, Maria Pilar Arévalo

2015-01-01

The purpose of our study was to identify the main factors associated with objective noise-induced hearing loss (NIHL), as indicated by abnormal audiometric testing, in Spanish workers exposed to occupational noise in the construction industry. We carried out a prospective study in Tenerife, Spain, using 150 employees exposed to occupational noise and 150 age-matched controls who were not working in noisy environments. The variables analyzed included sociodemographic data, noise-related factors, types of hearing protection, self-report hearing loss, and auditory-related symptoms (e.g., tinnitus, vertigo). Workers with pathological audiograms had significantly longer noise-exposure duration (16.2 ± 11.4 years) relative to those with normal audiograms (10.2 ± 7.0 years; t = 3.99, P < 0.001). The vast majority of those who never used hearing protection measures had audiometric abnormalities (94.1%). Additionally, workers using at least one of the protection devices (earplugs or earmuffs) had significantly more audiometric abnormalities than those using both protection measures simultaneously (Chi square = 16.07; P < 0.001). The logistic regression analysis indicates that the use of hearing protection measures [odds ratio (OR) = 12.30, confidence interval (CI) = 4.36-13.81, P < 0.001], and noise-exposure duration (OR = 1.35, CI = 1.08-1.99, P = 0.040) are significant predictors of NIHL. This regression model correctly predicted 78.2% of individuals with pathological audiograms. The combined use of hearing protection measures, in particular earplugs and earmuffs, associates with a lower rate of audiometric abnormalities in subjects with high occupational noise exposure. The use of hearing protection measures at work and noise-exposure duration are best predictive factors of NIHL. Auditory-related symptoms and self-report hearing loss do not represent good indicators of objective NIHL. Routine monitoring of noise levels and hearing status are of great importance as part

Early dropout predictive factors in obesity treatment.

PubMed

Michelini, Ilaria; Falchi, Anna Giulia; Muggia, Chiara; Grecchi, Ilaria; Montagna, Elisabetta; De Silvestri, Annalisa; Tinelli, Carmine

2014-02-01

Diet attrition and failure of long term treatment are very frequent in obese patients. This study aimed to identify pre-treatment variables determining dropout and to customise the characteristics of those most likely to abandon the program before treatment, thus making it possible to modify the therapy to increase compliance. A total of 146 outpatients were consecutively enrolled; 73 patients followed a prescriptive diet while 73 followed a novel brief group Cognitive Behavioural Treatment (CBT) in addition to prescriptive diet. The two interventions lasted for six months. Anthropometric, demographic, psychological parameters and feeding behaviour were assessed, the last two with the Italian instrument VCAO Ansisa; than, a semi-structured interview was performed on motivation to lose weight. To identify the baseline dropout risk factors among these parameters, univariate and multivariate logistic models were used. Comparison of the results in the two different treatments showed a higher attrition rate in CBT group, despite no statistically significant difference between the two treatment arms (P = 0.127). Dropout patients did not differ significantly from those who did not dropout with regards to sex, age, Body Mass Index (BMI), history of cycling, education, work and marriage. Regardless of weight loss, the most important factor that determines the dropout appears to be a high level of stress revealed by General Health Questionnaire-28 items (GHQ-28) score within VCAO test. The identification of hindering factors during the assessment is fundamental to reduce the dropout risk. For subjects at risk, it would be useful to dedicate a stress management program before beginning a dietary restriction.

Do the same factors predict outcome in schizophrenia and non-schizophrenia syndromes after first-episode psychosis? A two-year follow-up study.

PubMed

Peña, Javier; Segarra, Rafael; Ojeda, Natalia; García, Jon; Eguiluz, José I; Gutiérrez, Miguel

2012-06-01

The aim of this two-year longitudinal study was to identify the best baseline predictors of functional outcome in first-episode psychosis (FEP). We tested whether the same factors predict functional outcomes in two different subsamples of FEP patients: schizophrenia and non-schizophrenia syndrome groups. Ninety-five patients with FEP underwent a full clinical evaluation (i.e., PANSS, Mania, Depression and Insight). Functional outcome measurements included the WHO Disability Assessment Schedule (DAS-WHO), Global Assessment of Functioning (GAF) and Clinical Global Impression (CGI). Estimation of cognition was obtained by a neuropsychological battery which included attention, processing speed, language, memory and executive functioning. Greater severity of visuospatial functioning at baseline predicted poorer functional outcome as measured by the three functional scales (GAF, CGI and DAS-WHO) in the pooled FEP sample (explaining ut to the 12%, 9% and 10% of the variance, respectively). Negative symptoms also effectively contributed to predict GAF scores (8%). However, we obtained different predictive values after differentiating sample diagnoses. Processing speed significantly predicted most functional outcome measures in patients with schizophrenia, whereas visuospatial functioning was the only significant predictor of functional outcomes in the non-schizophrenia subgroup. Our results suggest that processing speed, visuospatial functioning and negative symptoms significantly (but differentially) predict outcomes in patients with FEP, depending on their clinical progression. For patients without a schizophrenia diagnosis, visuospatial functioning was the best predictor of functional outcome. The performance on processing speed seemed to be a key factor in more severe syndromes. However, only a small proportion of the variance could be explained by the model, so there must be many other factors that have to be considered. Copyright © 2012 Elsevier Ltd. All rights

Identifying and reducing risk factors related to trainee-client sexual misconduct.

PubMed

Hamilton, J C; Spruill, J

1999-06-01

Sexual misconduct involving therapists-in-training and their clients is addressed. Personal and situational factors that may constitute risk factors for the development of inappropriate sexual activity between trainees and their clients are identified. Although there may be certain characteristics that put particular students at risk for such involvement, the authors believe this risk is more strongly related to systemic, programmatic, and pedagogic characteristics of the environments in which students train. Examples include, respectively, the decline of concern over transference and countertransference, failure to include education about client-therapist sexual attraction and the consequences of sexual misconduct in graduate psychology curricula, and the reluctance of supervisors to deal straightforwardly with trainees' sexual feelings. Suggestions for reducing risks for client-therapist sexual misconduct are directed toward these situational factors.

Factors influencing U.S. canine heartworm (Dirofilaria immitis) prevalence.

PubMed

Wang, Dongmei; Bowman, Dwight D; Brown, Heidi E; Harrington, Laura C; Kaufman, Phillip E; McKay, Tanja; Nelson, Charles Thomas; Sharp, Julia L; Lund, Robert

2014-06-06

This paper examines the individual factors that influence prevalence rates of canine heartworm in the contiguous United States. A data set provided by the Companion Animal Parasite Council, which contains county-by-county results of over nine million heartworm tests conducted during 2011 and 2012, is analyzed for predictive structure. The goal is to identify the factors that are important in predicting high canine heartworm prevalence rates. The factors considered in this study are those envisioned to impact whether a dog is likely to have heartworm. The factors include climate conditions (annual temperature, precipitation, and relative humidity), socio-economic conditions (population density, household income), local topography (surface water and forestation coverage, elevation), and vector presence (several mosquito species). A baseline heartworm prevalence map is constructed using estimated proportions of positive tests in each county of the United States. A smoothing algorithm is employed to remove localized small-scale variation and highlight large-scale structures of the prevalence rates. Logistic regression is used to identify significant factors for predicting heartworm prevalence. All of the examined factors have power in predicting heartworm prevalence, including median household income, annual temperature, county elevation, and presence of the mosquitoes Aedes trivittatus, Aedes sierrensis and Culex quinquefasciatus. Interactions among factors also exist. The factors identified are significant in predicting heartworm prevalence. The factor list is likely incomplete due to data deficiencies. For example, coyotes and feral dogs are known reservoirs of heartworm infection. Unfortunately, no complete data of their populations were available. The regression model considered is currently being explored to forecast future values of heartworm prevalence.

Stress and anger as contextual factors and preexisting cognitive schemas: predicting parental child maltreatment risk.

PubMed

Rodriguez, Christina M; Richardson, Michael J

2007-11-01

Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.

Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold.

PubMed

Zitnik, Marinka; Zupan, Blaž

2014-01-01

The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker's yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps.

Predicting preschool pain-related anticipatory distress: the relative contribution of longitudinal and concurrent factors.

PubMed

Racine, Nicole M; Pillai Riddell, Rebecca R; Flora, David B; Taddio, Anna; Garfield, Hartley; Greenberg, Saul

2016-09-01

Anticipatory distress prior to a painful medical procedure can lead to negative sequelae including heightened pain experiences, avoidance of future medical procedures, and potential noncompliance with preventative health care, such as vaccinations. Few studies have examined the longitudinal and concurrent predictors of pain-related anticipatory distress. This article consists of 2 companion studies to examine both the longitudinal factors from infancy as well as concurrent factors from preschool that predict pain-related anticipatory distress at the preschool age. Study 1 examined how well preschool pain-related anticipatory distress was predicted by infant pain response at 2, 4, 6, and 12 months of age. In study 2, using a developmental psychopathology framework, longitudinal analyses examined the predisposing, precipitating, perpetuating, and present factors that led to the development of anticipatory distress during routine preschool vaccinations. A sample of 202 caregiver-child dyads was observed during their infant and preschool vaccinations (the Opportunities to Understand Childhood Hurt cohort) and was used for both studies. In study 1, pain response during infancy was not found to significantly predict pain-related anticipatory distress at preschool. In study 2, a strong explanatory model was created whereby 40% of the variance in preschool anticipatory distress was explained. Parental behaviours from infancy and preschool were the strongest predictors of child anticipatory distress at preschool. Child age positively predicted child anticipatory distress. This strongly suggests that the involvement of parents in pain management interventions during immunization is one of the most critical factors in predicting anticipatory distress to the preschool vaccination.

Factors associated with therapeutic inertia in hypertension: validation of a predictive model.

PubMed

Redón, Josep; Coca, Antonio; Lázaro, Pablo; Aguilar, Ma Dolores; Cabañas, Mercedes; Gil, Natividad; Sánchez-Zamorano, Miguel Angel; Aranda, Pedro

2010-08-01

To study factors associated with therapeutic inertia in treating hypertension and to develop a predictive model to estimate the probability of therapeutic inertia in a given medical consultation, based on variables related to the consultation, patient, physician, clinical characteristics, and level of care. National, multicentre, observational, cross-sectional study in primary care and specialist (hospital) physicians who each completed a questionnaire on therapeutic inertia, provided professional data and collected clinical data on four patients. Therapeutic inertia was defined as a consultation in which treatment change was indicated (i.e., SBP >or= 140 or DBP >or= 90 mmHg in all patients; SBP >or= 130 or DBP >or= 80 in patients with diabetes or stroke), but did not occur. A predictive model was constructed and validated according to the factors associated with therapeutic inertia. Data were collected on 2595 patients and 13,792 visits. Therapeutic inertia occurred in 7546 (75%) of the 10,041 consultations in which treatment change was indicated. Factors associated with therapeutic inertia were primary care setting, male sex, older age, SPB and/or DBP values close to normal, treatment with more than one antihypertensive drug, treatment with an ARB II, and more than six visits/year. Physician characteristics did not weigh heavily in the association. The predictive model was valid internally and externally, with acceptable calibration, discrimination and reproducibility, and explained one-third of the variability in therapeutic inertia. Although therapeutic inertia is frequent in the management of hypertension, the factors explaining it are not completely clear. Whereas some aspects of the consultations were associated with therapeutic inertia, physician characteristics were not a decisive factor.

Review of Factors, Methods, and Outcome Definition in Designing Opioid Abuse Predictive Models.

PubMed

Alzeer, Abdullah H; Jones, Josette; Bair, Matthew J

2018-05-01

Several opioid risk assessment tools are available to prescribers to evaluate opioid analgesic abuse among chronic patients. The objectives of this study are to 1) identify variables available in the literature to predict opioid abuse; 2) explore and compare methods (population, database, and analysis) used to develop statistical models that predict opioid abuse; and 3) understand how outcomes were defined in each statistical model predicting opioid abuse. The OVID database was searched for this study. The search was limited to articles written in English and published from January 1990 to April 2016. This search generated 1,409 articles. Only seven studies and nine models met our inclusion-exclusion criteria. We found nine models and identified 75 distinct variables. Three studies used administrative claims data, and four studies used electronic health record data. The majority, four out of seven articles (six out of nine models), were primarily dependent on the presence or absence of opioid abuse or dependence (ICD-9 diagnosis code) to define opioid abuse. However, two articles used a predefined list of opioid-related aberrant behaviors. We identified variables used to predict opioid abuse from electronic health records and administrative data. Medication variables are the recurrent variables in the articles reviewed (33 variables). Age and gender are the most consistent demographic variables in predicting opioid abuse. Overall, there is similarity in the sampling method and inclusion/exclusion criteria (age, number of prescriptions, follow-up period, and data analysis methods). Intuitive research to utilize unstructured data may increase opioid abuse models' accuracy.

Prediction of chronic post-operative pain: pre-operative DNIC testing identifies patients at risk.

PubMed

Yarnitsky, David; Crispel, Yonathan; Eisenberg, Elon; Granovsky, Yelena; Ben-Nun, Alon; Sprecher, Elliot; Best, Lael-Anson; Granot, Michal

2008-08-15

Surgical and medical procedures, mainly those associated with nerve injuries, may lead to chronic persistent pain. Currently, one cannot predict which patients undergoing such procedures are 'at risk' to develop chronic pain. We hypothesized that the endogenous analgesia system is key to determining the pattern of handling noxious events, and therefore testing diffuse noxious inhibitory control (DNIC) will predict susceptibility to develop chronic post-thoracotomy pain (CPTP). Pre-operative psychophysical tests, including DNIC assessment (pain reduction during exposure to another noxious stimulus at remote body area), were conducted in 62 patients, who were followed 29.0+/-16.9 weeks after thoracotomy. Logistic regression revealed that pre-operatively assessed DNIC efficiency and acute post-operative pain intensity were two independent predictors for CPTP. Efficient DNIC predicted lower risk of CPTP, with OR 0.52 (0.33-0.77 95% CI, p=0.0024), i.e., a 10-point numerical pain scale (NPS) reduction halves the chance to develop chronic pain. Higher acute pain intensity indicated OR of 1.80 (1.28-2.77, p=0.0024) predicting nearly a double chance to develop chronic pain for each 10-point increase. The other psychophysical measures, pain thresholds and supra-threshold pain magnitudes, did not predict CPTP. For prediction of acute post-operative pain intensity, DNIC efficiency was not found significant. Effectiveness of the endogenous analgesia system obtained at a pain-free state, therefore, seems to reflect the individual's ability to tackle noxious events, identifying patients 'at risk' to develop post-intervention chronic pain. Applying this diagnostic approach before procedures that might generate pain may allow individually tailored pain prevention and management, which may substantially reduce suffering.

A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

PubMed Central

Musungu, Bryan; Bhatnagar, Deepak; Brown, Robert L.; Fakhoury, Ahmad M.; Geisler, Matt

2015-01-01

Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize. PMID:26089837

Clinical and Radiologic Predictive Factors of Rib Fractures in Outpatients With Chest Pain.

PubMed

Zhang, Liang; McMahon, Colm J; Shah, Samir; Wu, Jim S; Eisenberg, Ronald L; Kung, Justin W

To identify the clinical and radiologic predictive factors of rib fractures in stable adult outpatients presenting with chest pain and to determine the utility of dedicated rib radiographs in this population of patients. Following Institutional Review Board approval, we performed a retrospective review of 339 consecutive cases in which a frontal chest radiograph and dedicated rib series had been obtained for chest pain in the outpatient setting. The frontal chest radiograph and dedicated rib series were sequentially reviewed in consensus by two fellowship-trained musculoskeletal radiologists blinded to the initial report. The consensus interpretation of the dedicated rib series was used as the gold standard. Multiple variable logistic regression analysis assessed clinical and radiological factors associated with rib fractures. Fisher exact test was used to assess differences in medical treatment between the 2 groups. Of the 339 patients, 53 (15.6%) had at least 1 rib fracture. Only 20 of the 53 (37.7%) patients' fractures could be identified on the frontal chest radiograph. The frontal chest radiograph had a sensitivity of 38% and specificity of 100% when using the rib series as the reference standard. No pneumothorax, new mediastinal widening or pulmonary contusion was identified. Multiple variable logistic regression analysis of clinical factors associated with the presence of rib fractures revealed a significant association of trauma history (odds ratio 5.7 [p < 0.05]) and age ≥40 (odds radio 3.1 [p < 0.05]). Multiple variable logistic regression analysis of radiographic factors associated with rib fractures in this population demonstrated a significant association of pleural effusion with rib fractures (odds ratio 18.9 [p < 0.05]). Patients with rib fractures received narcotic analgesia in 47.2% of the cases, significantly more than those without rib fractures (21.3%, p < 0.05). None of the patients required hospitalization. In the stable outpatient setting

What Predicts Exercise Maintenance and Well-Being? Examining The Influence of Health-Related Psychographic Factors and Social Media Communication.

PubMed

Zhou, Xin; Krishnan, Archana

2018-01-26

Habitual exercising is an important precursor to both physical and psychological well-being. There is, thus, a strong interest in identifying key factors that can best motivate individuals to sustain regular exercise regimen. In addition to the importance of psychographic factors, social media use may act as external motivator by allowing users to interact and communicate about exercise. In this study, we examined the influence of health consciousness, health-oriented beliefs, intrinsic motivation, as willingness to communicate about health on social media, social media activity on exercise, and online social support on exercise maintenance and well-being on a sample of 532 American adults. Employing structural equation modeling, we found that health-oriented beliefs mediated the effect of health consciousness on intrinsic motivation which in turn was a significant predictor of exercise maintenance. Exercise maintenance significantly predicted both physical and psychological well-being. Extrinsic motivators, as measured by willingness to communicate about health on social media, social media activity on exercise, and online social support did not however significantly influence exercise maintenance. These findings have implications for the design and implementation of exercise-promoting interventions by identifying underlying factors that influence exercise maintenance.

Factors predictive of complicated appendicitis in children.

PubMed

Pham, Xuan-Binh D; Sullins, Veronica F; Kim, Dennis Y; Range, Blake; Kaji, Amy H; de Virgilio, Christian M; Lee, Steven L

2016-11-01

The ability to predict whether a child has complicated appendicitis at initial presentation may influence clinical management. However, whether complicated appendicitis is associated with prehospital or inhospital factors is not clear. We also investigate whether hyponatremia may be a novel prehospital factor associated with complicated appendicitis. A retrospective review of all pediatric patients (≤12 y) with appendicitis treated with appendectomy from 2000 to 2013 was performed. The main outcome measure was intraoperative confirmation of gangrenous or perforated appendicitis. A multivariable analysis was performed, and the main predictors of interest were age <5 y, symptom duration >24 h, leukocytosis (white blood cell count >12 × 10 3 /mL), hyponatremia (sodium ≤135 mEq/L), and time from admission to appendectomy. Of 392 patients, 179 (46%) had complicated appendicitis at the time of operation. Univariate analysis demonstrated that patients with complicated appendicitis were younger, had a longer duration of symptoms, higher white blood cell count, and lower sodium levels than patients with noncomplicated appendicitis. Multivariable analysis confirmed that symptom duration >24 h (odds ratio [OR] = 5.5, 95% confidence interval [CI] = 3.5-8.9, P < 0.01), hyponatremia (OR = 3.1, 95% CI = 2.0-4.9, P < 0.01), age <5 y (OR = 2.3, 95% CI = 1.3-4.0, P < 0.01), and leukocytosis (OR = 1.9, 95% CI = 1.0-3.5, P = 0.04) were independent predictors of complicated appendicitis. Increased time from admission to appendectomy was not a predictor of complicated appendicitis (OR = 0.8, 95% CI = 0.5-1.2, P = 0.2). Prehospital factors can predict complicated appendicitis in children with suspected appendicitis. Hyponatremia is a novel marker associated with complicated appendicitis. Delaying appendectomy does not increase the risk of complicated appendicitis once intravenous antibiotics are administered. This information may help guide

Predictive factors for lower extremity amputations in diabetic foot infections

PubMed Central

Aziz, Zameer; Lin, Wong Keng; Nather, Aziz; Huak, Chan Yiong

2011-01-01

The objective of this study was to evaluate the epidemiology of diabetic foot infections (DFIs) and its predictive factors for lower extremity amputations. A prospective study of 100 patients with DFIs treated at the National University Hospital of Singapore were recruited in the study during the period of January 2005–June 2005. A protocol was designed to document patient's demographics, type of DFI, presence of neuropathy and/or vasculopathy and its final outcome. Predictive factors for limb loss were determined using univariate and stepwise logistic regression analysis. The mean age of the study population was 59.8 years with a male to female ratio of about 1:1 and with a mean follow-up duration of about 24 months. All patients had type 2 diabetes mellitus. Common DFIs included abscess (32%), wet gangrene (29%), infected ulcers (19%), osteomyelitis (13%), necrotizing fasciitis (4%) and cellulitis (3%). Thirteen patients were treated conservatively, while surgical debridement or distal amputation was performed in 59 patients. Twenty-eight patients had major amputations (below or above knee) performed. Forty-eight percent had monomicrobial infections compared with 52% with polymicrobial infections. The most common pathogens found in all infections (both monomicrobial and polymicrobial) were Staphylococcus aureus (39.7%), Bacteroides fragilis (30.3%), Pseudomonas aeruginosa (26.0%) and Streptococcus agalactiae (21.0%). Significant univariate predictive factors for limb loss included age above 60 years, gangrene, ankle-brachial index (ABI) <0.8, monomicrobial infections, white blood cell (WBC) count ≥ 15.0×109/L, erythrocyte sedimentation rate ≥100 mm/hr, C-reactive protein ≥15.0 mg/dL, hemoglobin (Hb) ≤10.0g/dL and creatinine ≥150 µmol/L. Upon stepwise logistic regression, only gangrene, ABI <0.8, WBC ≥ 15.0×109/L and Hb ≤10.0g/dL were significant. PMID:22396824

Factors Predictive of Sentinel Lymph Node Involvement in Primary Breast Cancer.

PubMed

Malter, Wolfram; Hellmich, Martin; Badian, Mayhar; Kirn, Verena; Mallmann, Peter; Krämer, Stefan

2018-06-01

Sentinel lymph node biopsy (SLNB) has replaced axillary lymph node dissection (ALND) for axillary staging in patients with early-stage breast cancer. The need for therapeutic ALND is the subject of ongoing debate especially after the publication of the ACOSOG Z0011 trial. In a retrospective trial with univariate and multivariate analyses, factors predictive of sentinel lymph node involvement should be analyzed in order to define tumor characteristics of breast cancer patients, where SLNB should not be spared to receive important indicators for adjuvant treatment decisions (e.g. thoracic wall irradiation after mastectomy with or without reconstruction). Between 2006 and 2010, 1,360 patients with primary breast cancer underwent SLNB with/without ALND with evaluation of tumor localization, multicentricity and multifocality, histological subtype, tumor size, grading, lymphovascular invasion (LVI), and estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status. These characteristics were retrospectively analyzed in univariate and multivariate logistic regression models to define significant predictive factors for sentinel lymph node involvement. The multivariate analysis demonstrated that tumor size and LVI (p<0.001) were independent predictive factors for metastatic sentinel lymph node involvement in patients with early-stage breast cancer. Because of the increased risk for metastatic involvement of axillary sentinel nodes in cases with larger breast cancer or diagnosis of LVI, patients with these breast cancer characteristics should not be spared from SLNB in a clinically node-negative situation in order to avoid false-negative results with a high potential for wrong indication of primary breast reconstruction or wrong non-indication of necessary post-mastectomy radiation therapy. The prognostic impact of avoidance of axillary staging with SLNB is analyzed in the ongoing prospective INSEMA trial. Copyright© 2018, International

Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

PubMed

Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

2008-05-01

Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

Using a Delphi Method to Identify Human Factors Contributing to Nursing Errors.

PubMed

Roth, Cheryl; Brewer, Melanie; Wieck, K Lynn

2017-07-01

The purpose of this study was to identify human factors associated with nursing errors. Using a Delphi technique, this study used feedback from a panel of nurse experts (n = 25) on an initial qualitative survey questionnaire followed by summarizing the results with feedback and confirmation. Synthesized factors regarding causes of errors were incorporated into a quantitative Likert-type scale, and the original expert panel participants were queried a second time to validate responses. The list identified 24 items as most common causes of nursing errors, including swamping and errors made by others that nurses are expected to recognize and fix. The responses provided a consensus top 10 errors list based on means with heavy workload and fatigue at the top of the list. The use of the Delphi survey established consensus and developed a platform upon which future study of nursing errors can evolve as a link to future solutions. This list of human factors in nursing errors should serve to stimulate dialogue among nurses about how to prevent errors and improve outcomes. Human and system failures have been the subject of an abundance of research, yet nursing errors continue to occur. © 2016 Wiley Periodicals, Inc.

Factors predictive of alcohol abstention after resident detoxication among alcoholics followed in an hospital outpatient center.

PubMed

Gelsi, Eve; Vanbiervliet, Geoffroy; Chérikh, Faredj; Mariné-Barjoan, Eugénia; Truchi, Régine; Arab, Kamel; Delmont, Jean-Marie; Tran, Albert

2007-01-01

A cohort of patient hospitalized for alcohol detoxification between January 2004 and January 2005 were followed prospectively to search for factors predictive factors of sustained abstinence. One hundred and fifteen patients (79 males, 36 females, median age 45.9+/-10.7 years), were hospitalized for alcohol detoxification. Demographic, social, and medical data including daily alcohol intake and co-addictions were noted at inclusion and six months later. Patients who did not attend their six-month visit were contacted by phone. Among the 115 included patients, six month follow-up data could be collected for 73. Abstinence rate was 54.8%. Factors predictive of unsuccessful cessation were homelessness (P=0.004), duration of alcohol consumption (P=0.004), smoking (P=0.02), drug substitution (P=0.04) and multiple addictions (P=0.04). At multivariate analysis, multiple addictions was the only independent factor predictive of unsuccessful detoxification. Naltrexone or acamprosate treatments were not associated with a better rate of alcohol detoxification. Patient follow-up is problematic due to the large number of dropouts among alcoholics. Early screening in search for factors predictive of unsuccessful detoxification (long duration of alcohol consumption, multiple addiction) would be helpful in elaborating appropriate pluridisciplinary management.

Powder diffraction and crystal structure prediction identify four new coumarin polymorphs

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

Shtukenberg, Alexander G.; Zhu, Qiang; Carter, Damien J.

Coumarin, a simple, commodity chemical isolated from beans in 1820, has, to date, only yielded one solid state structure. Here, we report a rich polymorphism of coumarin grown from the melt. Four new metastable forms were identified and their crystal structures were solved using a combination of computational crystal structure prediction algorithms and X-ray powder diffraction. With five crystal structures, coumarin has become one of the few rigid molecules showing extensive polymorphism at ambient conditions. We demonstrate the crucial role of advanced electronic structure calculations including many-body dispersion effects for accurate ranking of the stability of coumarin polymorphs and themore » need to account for anharmonic vibrational contributions to their free energy. As such, coumarin is a model system for studying weak intermolecular interactions, crystallization mechanisms, and kinetic effects.« less

Powder diffraction and crystal structure prediction identify four new coumarin polymorphs

DOE PAGES

Shtukenberg, Alexander G.; Zhu, Qiang; Carter, Damien J.; ...

2017-05-15

Coumarin, a simple, commodity chemical isolated from beans in 1820, has, to date, only yielded one solid state structure. Here, we report a rich polymorphism of coumarin grown from the melt. Four new metastable forms were identified and their crystal structures were solved using a combination of computational crystal structure prediction algorithms and X-ray powder diffraction. With five crystal structures, coumarin has become one of the few rigid molecules showing extensive polymorphism at ambient conditions. We demonstrate the crucial role of advanced electronic structure calculations including many-body dispersion effects for accurate ranking of the stability of coumarin polymorphs and themore » need to account for anharmonic vibrational contributions to their free energy. As such, coumarin is a model system for studying weak intermolecular interactions, crystallization mechanisms, and kinetic effects.« less

Baseline placental growth factor levels for the prediction of benefit from early aspirin prophylaxis for preeclampsia prevention.

PubMed

Moore, Gaea S; Allshouse, Amanda A; Winn, Virginia D; Galan, Henry L; Heyborne, Kent D

2015-10-01

Placental growth factor (PlGF) levels early in pregnancy are lower in women who ultimately develop preeclampsia. Early initiation of low-dose aspirin reduces preeclampsia risk in some high risk women. We hypothesized that low PlGF levels may identify women at increased risk for preeclampsia who would benefit from aspirin. Secondary analysis of the MFMU High-Risk Aspirin study including singleton pregnancies randomized to aspirin 60mg/d (n=102) or placebo (n=72), with PlGF collected at 13w 0d-16w 6d. Within the placebo group, we estimated the probability of preeclampsia by PlGF level using logistic regression analysis, then determined a potential PlGF threshold for preeclampsia prediction using ROC analysis. We performed logistic regression modeling for potential confounders. ROC analysis indicated 87.71pg/ml as the threshold between high and low PlGF for preeclampsia-prediction. Within the placebo group high PlGF weakly predicted preeclampsia (AUC 0.653, sensitivity/specificity 63%/66%). We noted a 2.6-fold reduction in preeclampsia with aspirin in the high-PlGF group (12.15% aspirin vs 32.14% placebo, p=0.057), but no significant differences in preeclampsia in the low PlGF group (21.74% vs 15.91%, p=0.445). Unlike other studies, we found that high rather than low PlGF levels were associated with an increased preeclampsia risk. Low PlGF neither identified women at increased risk of preeclampsia nor women who benefitted from aspirin. Further research is needed to determine whether aspirin is beneficial in women with high PlGF, and whether the paradigm linking low PlGF and preeclampsia needs to be reevaluated. High-risk women with low baseline PlGF, a risk factor for preeclampsia, did not benefit from early initiation of low-dose aspirin. Copyright © 2015 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Prediction of response to PPI therapy and factors influencing treatment outcome in patients with GORD: a prospective pragmatic trial using pantoprazole

PubMed Central

2011-01-01

Background Management of patients with gastro-oesophageal reflux disease (GORD) can be assisted by information predicting the likely response to proton pump inhibitor (PPI) treatment. The aim was to undertake a study of GORD patients designed to approximate ordinary clinical practice that would identify patient characteristics predicting symptomatic response to pantoprazole treatment. Methods 1888 patients with symptoms of GORD were enrolled in a multicentre, multinational, prospective, open study of 8 weeks pantoprazole treatment, 40 mg daily. Response was assessed by using the ReQuest™ questionnaire, by the investigator making conventional clinical enquiry and by asking patients about their satisfaction with symptom control. Factors including pre-treatment oesophagitis, gender, age, body mass index (BMI), Helicobacter pylori status, anxiety and depression, and concurrent IBS symptoms were examined using logistic regression to determine if they were related to response, judged from the ReQuest™-GI score. Results Poorer treatment responses were associated with non-erosive reflux disease, female gender, lower BMI, anxiety and concurrent irritable bowel syndrome symptoms before treatment. No association was found with age, Helicobacter pylori status or oesophagitis grade. Some reflux-related symptoms were still present in 14% of patients who declared themselves 'well-satisfied' with their symptom control. Conclusions Some readily identifiable features help to predict symptomatic responses to a PPI and consequently may help in managing patient expectation. ClinicalTrial.gov identifier: NCT00312806. PMID:21569313

Risk terrain modeling predicts child maltreatment.

PubMed

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Biological and Sociocultural Factors During the School Years Predicting Women's Lifetime Educational Attainment.

PubMed

Hendrick, C Emily; Cohen, Alison K; Deardorff, Julianna; Cance, Jessica D

2016-03-01

Lifetime educational attainment is an important predictor of health and well-being for women in the United States. In this study, we examine the roles of sociocultural factors in youth and an understudied biological life event, pubertal timing, in predicting women's lifetime educational attainment. Using data from the National Longitudinal Survey of Youth 1997 cohort (N = 3889), we conducted sequential multivariate linear regression analyses to investigate the influences of macro-level and family-level sociocultural contextual factors in youth (region of country, urbanicity, race/ethnicity, year of birth, household composition, mother's education, and mother's age at first birth) and early menarche, a marker of early pubertal development, on women's educational attainment after age 24. Pubertal timing and all sociocultural factors in youth, other than year of birth, predicted women's lifetime educational attainment in bivariate models. Family factors had the strongest associations. When family factors were added to multivariate models, geographic region in youth, and pubertal timing were no longer significant. Our findings provide additional evidence that family factors should be considered when developing comprehensive and inclusive interventions in childhood and adolescence to promote lifetime educational attainment among girls. © 2016, American School Health Association.

Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.

PubMed

Fernández, Leónides; Mediano, Pilar; García, Ricardo; Rodríguez, Juan M; Marín, María

2016-09-01

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.

Higher neonatal growth rate and body condition score at 7 months are predictive factors of obesity in adult female Beagle dogs.

PubMed

Leclerc, Lucie; Thorin, Chantal; Flanagan, John; Biourge, Vincent; Serisier, Samuel; Nguyen, Patrick

2017-04-13

The risks during early growth on becoming overweight in adulthood are widely studied in humans. However, early-life predictive factors for canine adult overweight and obesity have not yet been studied. To identify factors that may help explain the development of overweight and obesity at adulthood in dogs, a longitudinal study of 2 years was conducted in 24 female Beagle dogs of the same age, sexual status, and raised under identical environmental conditions. By means of a hierarchical classification on principal components with the following quantitative values: fat-free mass (FFM), percentage fat mass and pelvic circumference at 2 years of age, three groups of dogs were established and were nominally named: ideal weight (IW, n = 9), slightly overweight (OW1, n = 6) and overweight (OW2, n = 9). With the aim of identifying predictive factors of development of obesity at adulthood parental characteristics, growth pattern, energy balance and plasma factors were analysed by logistic regression analysis. At 24 months, the group compositions were in line with the body condition scores (BCS 1-9) values of the IW (5 or 6/9), the OW1 (6/9) and the OW2 (7 or 8/9) groups. Logistic regression analysis permitted the identification of neonatal growth rate during the first 2 weeks of life (GR 2W ) and BCS at 7 months as predictors for the development of obesity at adulthood. Seventy percent of dogs with either GR 2W >125% or with BCS > 6/9 at 7 months belonged to the OW2 group. Results from energy intake and expenditure, corrected for FFM, showed that there was a greater positive energy imbalance between 7 and 10 months for the OW2, compared to the IW group. This study expands the understanding of previously reported risk factors for being overweight or obese in dogs, establishing that (i) 15 out of 24 of the studied dogs became overweight and (ii) GR 2W and BCS at 7 months of age could be used as predictive factors as overweight adult dogs in the OW2