A systematic review of the relationship factor between women and health professionals within the multivariant analysis of maternal satisfaction.

PubMed

Macpherson, Ignacio; Roqué-Sánchez, María V; Legget Bn, Finola O; Fuertes, Ferran; Segarra, Ignacio

2016-10-01

personalised support provided to women by health professionals is one of the prime factors attaining women's satisfaction during pregnancy and childbirth. However the multifactorial nature of 'satisfaction' makes difficult to assess it. Statistical multivariate analysis may be an effective technique to obtain in depth quantitative evidence of the importance of this factor and its interaction with the other factors involved. This technique allows us to estimate the importance of overall satisfaction in its context and suggest actions for healthcare services. systematic review of studies that quantitatively measure the personal relationship between women and healthcare professionals (gynecologists, obstetricians, nurse, midwifes, etc.) regarding maternity care satisfaction. The literature search focused on studies carried out between 1970 and 2014 that used multivariate analyses and included the woman-caregiver relationship as a factor of their analysis. twenty-four studies which applied various multivariate analysis tools to different periods of maternity care (antenatal, perinatal, post partum) were selected. The studies included discrete scale scores and questionnaires from women with low-risk pregnancies. The "personal relationship" factor appeared under various names: care received, personalised treatment, professional support, amongst others. The most common multivariate techniques used to assess the percentage of variance explained and the odds ratio of each factor were principal component analysis and logistic regression. the data, variables and factor analysis suggest that continuous, personalised care provided by the usual midwife and delivered within a family or a specialised setting, generates the highest level of satisfaction. In addition, these factors foster the woman's psychological and physiological recovery, often surpassing clinical action (e.g. medicalization and hospital organization) and/or physiological determinants (e.g. pain, pathologies, etc.). Copyright © 2016 Elsevier Ltd. All rights reserved.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Multivariate Data Analysis

DTIC Science & Technology

1975-02-03

the anthropometrists, biologists, and psychologists of that era. Such initial contributors to modern statistics as Francis Galton and Karl Pearson...1159-78. [5] Galton , Francis (1888), "Co-relations and Their Measurements, Chiefly from Anthropometric Data," Proceedings of the...stem from that period. Galton seemed to be perpetually engaged in data analysis. He and his cousin, Darwin, and others revolved in an age of

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

PubMed

Wang, Longfei; Lee, Sungyoung; Gim, Jungsoo; Qiao, Dandi; Cho, Michael; Elston, Robert C; Silverman, Edwin K; Won, Sungho

2016-09-01

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows. © 2016 WILEY PERIODICALS, INC.

Evidence-based provisional clinical classification criteria for autoinflammatory periodic fevers.

PubMed

Federici, Silvia; Sormani, Maria Pia; Ozen, Seza; Lachmann, Helen J; Amaryan, Gayane; Woo, Patricia; Koné-Paut, Isabelle; Dewarrat, Natacha; Cantarini, Luca; Insalaco, Antonella; Uziel, Yosef; Rigante, Donato; Quartier, Pierre; Demirkaya, Erkan; Herlin, Troels; Meini, Antonella; Fabio, Giovanna; Kallinich, Tilmann; Martino, Silvana; Butbul, Aviel Yonatan; Olivieri, Alma; Kuemmerle-Deschner, Jasmin; Neven, Benedicte; Simon, Anna; Ozdogan, Huri; Touitou, Isabelle; Frenkel, Joost; Hofer, Michael; Martini, Alberto; Ruperto, Nicolino; Gattorno, Marco

2015-05-01

The objective of this work was to develop and validate a set of clinical criteria for the classification of patients affected by periodic fevers. Patients with inherited periodic fevers (familial Mediterranean fever (FMF); mevalonate kinase deficiency (MKD); tumour necrosis factor receptor-associated periodic fever syndrome (TRAPS); cryopyrin-associated periodic syndromes (CAPS)) enrolled in the Eurofever Registry up until March 2013 were evaluated. Patients with periodic fever, aphthosis, pharyngitis and adenitis (PFAPA) syndrome were used as negative controls. For each genetic disease, patients were considered to be 'gold standard' on the basis of the presence of a confirmatory genetic analysis. Clinical criteria were formulated on the basis of univariate and multivariate analysis in an initial group of patients (training set) and validated in an independent set of patients (validation set). A total of 1215 consecutive patients with periodic fevers were identified, and 518 gold standard patients (291 FMF, 74 MKD, 86 TRAPS, 67 CAPS) and 199 patients with PFAPA as disease controls were evaluated. The univariate and multivariate analyses identified a number of clinical variables that correlated independently with each disease, and four provisional classification scores were created. Cut-off values of the classification scores were chosen using receiver operating characteristic curve analysis as those giving the highest sensitivity and specificity. The classification scores were then tested in an independent set of patients (validation set) with an area under the curve of 0.98 for FMF, 0.95 for TRAPS, 0.96 for MKD, and 0.99 for CAPS. In conclusion, evidence-based provisional clinical criteria with high sensitivity and specificity for the clinical classification of patients with inherited periodic fevers have been developed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

NASA Astrophysics Data System (ADS)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

PERIODIC AUTOREGRESSIVE-MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES.

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

Results involving correlation properties and parameter estimation for autogressive-moving average models with periodic parameters are presented. A multivariate representation of the PARMA model is used to derive parameter space restrictions and difference equations for the periodic autocorrelations. Close approximation to the likelihood function for Gaussian PARMA processes results in efficient maximum-likelihood estimation procedures. Terms in the Fourier expansion of the parameters are sequentially included, and a selection criterion is given for determining the optimal number of harmonics to be included. Application of the techniques is demonstrated through analysis of a monthly streamflow time series.

Multivariate synaptic and behavioral profiling reveals new developmental endophenotypes in the prefrontal cortex

PubMed Central

Iafrati, Jillian; Malvache, Arnaud; Gonzalez Campo, Cecilia; Orejarena, M. Juliana; Lassalle, Olivier; Bouamrane, Lamine; Chavis, Pascale

2016-01-01

The postnatal maturation of the prefrontal cortex (PFC) represents a period of increased vulnerability to risk factors and emergence of neuropsychiatric disorders. To disambiguate the pathophysiological mechanisms contributing to these disorders, we revisited the endophenotype approach from a developmental viewpoint. The extracellular matrix protein reelin which contributes to cellular and network plasticity, is a risk factor for several psychiatric diseases. We mapped the aggregate effect of the RELN risk allele on postnatal development of PFC functions by cross-sectional synaptic and behavioral analysis of reelin-haploinsufficient mice. Multivariate analysis of bootstrapped datasets revealed subgroups of phenotypic traits specific to each maturational epoch. The preeminence of synaptic AMPA/NMDA receptor content to pre-weaning and juvenile endophenotypes shifts to long-term potentiation and memory renewal during adolescence followed by NMDA-GluN2B synaptic content in adulthood. Strikingly, multivariate analysis shows that pharmacological rehabilitation of reelin haploinsufficient dysfunctions is mediated through induction of new endophenotypes rather than reversion to wild-type traits. By delineating previously unknown developmental endophenotypic sequences, we conceived a promising general strategy to disambiguate the molecular underpinnings of complex psychiatric disorders and for the rational design of pharmacotherapies in these disorders. PMID:27765946

Relating N2O emissions during biological nitrogen removal with operating conditions using multivariate statistical techniques.

PubMed

Vasilaki, V; Volcke, E I P; Nandi, A K; van Loosdrecht, M C M; Katsou, E

2018-04-26

Multivariate statistical analysis was applied to investigate the dependencies and underlying patterns between N 2 O emissions and online operational variables (dissolved oxygen and nitrogen component concentrations, temperature and influent flow-rate) during biological nitrogen removal from wastewater. The system under study was a full-scale reactor, for which hourly sensor data were available. The 15-month long monitoring campaign was divided into 10 sub-periods based on the profile of N 2 O emissions, using Binary Segmentation. The dependencies between operating variables and N 2 O emissions fluctuated according to Spearman's rank correlation. The correlation between N 2 O emissions and nitrite concentrations ranged between 0.51 and 0.78. Correlation >0.7 between N 2 O emissions and nitrate concentrations was observed at sub-periods with average temperature lower than 12 °C. Hierarchical k-means clustering and principal component analysis linked N 2 O emission peaks with precipitation events and ammonium concentrations higher than 2 mg/L, especially in sub-periods characterized by low N 2 O fluxes. Additionally, the highest ranges of measured N 2 O fluxes belonged to clusters corresponding with NO 3 -N concentration less than 1 mg/L in the upstream plug-flow reactor (middle of oxic zone), indicating slow nitrification rates. The results showed that the range of N 2 O emissions partially depends on the prior behavior of the system. The principal component analysis validated the findings from the clustering analysis and showed that ammonium, nitrate, nitrite and temperature explained a considerable percentage of the variance in the system for the majority of the sub-periods. The applied statistical methods, linked the different ranges of emissions with the system variables, provided insights on the effect of operating conditions on N 2 O emissions in each sub-period and can be integrated into N 2 O emissions data processing at wastewater treatment plants. Copyright © 2018. Published by Elsevier Ltd.

Predictive monitoring and diagnosis of periodic air pollution in a subway station.

PubMed

Kim, YongSu; Kim, MinJung; Lim, JungJin; Kim, Jeong Tai; Yoo, ChangKyoo

2010-11-15

The purpose of this study was to develop a predictive monitoring and diagnosis system for the air pollutants in a subway system using a lifting technique with a multiway principal component analysis (MPCA) which monitors the periodic patterns of the air pollutants and diagnoses the sources of the contamination. The basic purpose of this lifting technique was to capture the multivariate and periodic characteristics of all of the indoor air samples collected during each day. These characteristics could then be used to improve the handling of strong periodic fluctuations in the air quality environment in subway systems and will allow important changes in the indoor air quality to be quickly detected. The predictive monitoring approach was applied to a real indoor air quality dataset collected by telemonitoring systems (TMS) that indicated some periodic variations in the air pollutants and multivariate relationships between the measured variables. Two monitoring models--global and seasonal--were developed to study climate change in Korea. The proposed predictive monitoring method using the lifted model resulted in fewer false alarms and missed faults due to non-stationary behavior than that were experienced with the conventional methods. This method could be used to identify the contributions of various pollution sources. Copyright © 2010 Elsevier B.V. All rights reserved.

Culture and alcohol use: historical and sociocultural themes from 75 years of alcohol research.

PubMed

Castro, Felipe Gonzalez; Barrera, Manuel; Mena, Laura A; Aguirre, Katherine M

2014-01-01

For the period of almost 75 years, we examined the literature for studies regarding the influences of culture on alcohol use and misuse. This review is a chronology of research articles published from 1940 to 2013. From a structured literature search with select criteria, 38 articles were identified and 34 reviewed. This analysis revealed a progression across this period of research from studies that began as descriptive ethnographic evaluations of one or more indigenous societies or cultural groups, evolving to studies using complex multivariate models to test cross-cultural effects in two or more cultural groups. Major findings across this period include the assertions that (a) a function of alcohol use may be to reduce anxiety, (b) certain cultural groups possess features of alcohol use that are not associated with negative consequences, (c) the disruptive effects of acculturative change and the stressors of new demands are associated with an increase in alcohol consumption, (d) cultural groups shape expectations about the effects of alcohol use and their definition of drunkenness, and (e) the hypothesized relationships of culture with alcohol use and misuse have been demonstrated in multivariate model analyses. Across this 75-year period, the early proposition that culture is an important and prominent correlate of alcohol use and misuse has persisted. Within the current era of alcohol studies, this proposition has been supported by multivariate model analyses. Thus, the proposition that culture might affect alcohol use remains prominent and is as relevant today as it was when it was first proposed nearly 75 years ago.

A Multivariate Analysis of Termination Status in a Rural Community Mental Health Center.

ERIC Educational Resources Information Center

Tutin, Judith; Kessler, Marc

It has been estimated that the most pressing problem in community mental health care clinics is dropout, defined as unilateral termination by the client without therapist approval. To clarify the nature of dropout patients, 133 outpatient records at a rural community mental health center were examined over a one year period. Variables expected to…

Determinants of Budget Allocations to Academic Departments: A Case Study. ASHE 1987 Annual Meeting Paper.

ERIC Educational Resources Information Center

Winans, Glen T.

General fund budgetary determinants in 27 academic departments at the University of California Santa Barbara were studied for the period from 1977/78 through 1983/84. The focus was resource allocation and utilization within departments of the College of Letters and Science. The research design included a pooled multivariate regression analysis of…

Factors Impacting Growth in Infants with Single Ventricle Physiology: A Report from Pediatric Heart Network Infant Single Ventricle Trial

PubMed Central

Williams, Richard V.; Zak, Victor; Ravishankar, Chitra; Altmann, Karen; Anderson, Jeffrey; Atz, Andrew M.; Dunbar-Masterson, Carolyn; Ghanayem, Nancy; Lambert, Linda; Lurito, Karen; Medoff-Cooper, Barbara; Margossian, Renee; Pemberton, Victoria L.; Russell, Jennifer; Stylianou, Mario; Hsu, Daphne

2011-01-01

Objectives To describe growth patterns in infants with single ventricle physiology and determine factors influencing growth. Study design Data from 230 subjects enrolled in the Pediatric Heart Network Infant Single Ventricle Enalapril Trial were used to assess factors influencing change in weight-for-age z-score (Δz) from study enrollment (0.7 ± 0.4 months) to pre-superior cavopulmonary connection (SCPC) (5.1 ± 1.8 months, period 1), and pre-SCPC to final study visit (14.1 ± 0.9 months, period 2). Predictor variables included patient characteristics, feeding regimen, clinical center, and medical factors during neonatal (period 1) and SCPC hospitalizations (period 2). Univariate regression analysis was performed, followed by backward stepwise regression and bootstrapping reliability to inform a final multivariable model. Results Weights were available for 197/230 subjects for period 1 and 173/197 for period 2. For period 1, greater gestational age, younger age at study enrollment, tube feeding at neonatal discharge, and clinical center were associated with a greater negative Δz (poorer growth) in multivariable modeling (adjusted R2 = 0.39, p < 0.001). For period 2, younger age at SCPC and greater daily caloric intake were associated with greater positive Δz (better growth) (R2 = 0.10, p = 0.002). Conclusions Aggressive nutritional support and earlier SCPC are modifiable factors associated with a favorable change in weight-for-age z-score. PMID:21784436

Effects of Flavor and Texture on the Sensory Perception of Gouda-Type Cheese Varieties during Ripening Using Multivariate Analysis.

PubMed

Shiota, Makoto; Iwasawa, Ai; Suzuki-Iwashima, Ai; Iida, Fumiko

2015-12-01

The impact of flavor composition, texture, and other factors on desirability of different commercial sources of Gouda-type cheese using multivariate analyses on the basis of sensory and instrumental analyses were investigated. Volatile aroma compounds were measured using headspace solid-phase microextraction gas chromatography/mass spectrometry (GC/MS) and steam distillation extraction (SDE)-GC/MS, and fatty acid composition, low-molecular-weight compounds, including amino acids, and organic acids, as well pH, texture, and color were measured to determine their relationship with sensory perception. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to discriminate between 2 different ripening periods in 7 sample sets, revealing that ethanol, ethyl acetate, hexanoic acid, and octanoic acid increased with increasing sensory attribute scores for sweetness, fruity, and sulfurous. A partial least squares (PLS) regression model was constructed to predict the desirability of cheese using these parameters. We showed that texture and buttery flavors are important factors affecting the desirability of Gouda-type cheeses for Japanese consumers using these multivariate analyses. © 2015 Institute of Food Technologists®

The potential use of cuticular hydrocarbons and multivariate analysis to age empty puparial cases of Calliphora vicina and Lucilia sericata.

PubMed

Moore, Hannah E; Pechal, Jennifer L; Benbow, M Eric; Drijfhout, Falko P

2017-05-16

Cuticular hydrocarbons (CHC) have been successfully used in the field of forensic entomology for identifying and ageing forensically important blowfly species, primarily in the larval stages. However in older scenes where all other entomological evidence is no longer present, Calliphoridae puparial cases can often be all that remains and therefore being able to establish the age could give an indication of the PMI. This paper examined the CHCs present in the lipid wax layer of insects, to determine the age of the cases over a period of nine months. The two forensically important species examined were Calliphora vicina and Lucilia sericata. The hydrocarbons were chemically extracted and analysed using Gas Chromatography - Mass Spectrometry. Statistical analysis was then applied in the form of non-metric multidimensional scaling analysis (NMDS), permutational multivariate analysis of variance (PERMANOVA) and random forest models. This study was successful in determining age differences within the empty cases, which to date, has not been establish by any other technique.

Cytologic separation of branchial cleft cyst from metastatic cystic squamous cell carcinoma: A multivariate analysis of nineteen cytomorphologic features.

PubMed

Layfield, Lester J; Esebua, Magda; Schmidt, Robert L

2016-07-01

The separation of branchial cleft cysts from metastatic cystic squamous cell carcinomas in adults can be clinically and cytologically challenging. Diagnostic accuracy for separation is reported to be as low as 75% prompting some authors to recommend frozen section evaluation of suspected branchial cleft cysts before resection. We evaluated 19 cytologic features to determine which were useful in this distinction. Thirty-three cases (21 squamous carcinoma and 12 branchial cysts) of histologically confirmed cystic lesions of the lateral neck were graded for the presence or absence of 19 cytologic features by two cytopathologists. The cytologic features were analyzed for agreement between observers and underwent multivariate analysis for correlation with the diagnosis of carcinoma. Interobserver agreement was greatest for increased nuclear/cytoplasmic (N/C) ratio, pyknotic nuclei, and irregular nuclear membranes. Recursive partitioning analysis showed increased N/C ratio, small clusters of cells, and irregular nuclear membranes were the best discriminators. The distinction of branchial cleft cysts from cystic squamous cell carcinoma is cytologically difficult. Both digital image analysis and p16 testing have been suggested as aids in this separation, but analysis of cytologic features remains the main method for diagnosis. In an analysis of 19 cytologic features, we found that high nuclear cytoplasmic ratio, irregular nuclear membranes, and small cell clusters were most helpful in their distinction. Diagn. Cytopathol. 2016;44:561-567. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Serum dehydroepiandrosterone sulphate, psychosocial factors and musculoskeletal pain in workers.

PubMed

Marinelli, A; Prodi, A; Pesel, G; Ronchese, F; Bovenzi, M; Negro, C; Larese Filon, F

2017-12-30

The serum level of dehydroepiandrosterone sulphate (DHEA-S) has been suggested as a biological marker of stress. To assess the association between serum DHEA-S, psychosocial factors and musculoskeletal (MS) pain in university workers. The study population included voluntary workers at the scientific departments of the University of Trieste (Italy) who underwent periodical health surveillance from January 2011 to June 2012. DHEA-S level was analysed in serum. The assessment tools included the General Health Questionnaire (GHQ) and a modified Nordic musculoskeletal symptoms questionnaire. The relation between DHEA-S, individual characteristics, pain perception and psychological factors was assessed by means of multivariable linear regression analysis. There were 189 study participants. The study population was characterized by high reward and low effort. Pain perception in the neck, shoulder, upper limbs, upper back and lower back was reported by 42, 32, 19, 29 and 43% of people, respectively. In multivariable regression analysis, gender, age and pain perception in the shoulder and upper limbs were significantly related to serum DHEA-S. Effort and overcommitment were related to shoulder and neck pain but not to DHEA-S. The GHQ score was associated with pain perception in different body sites and inversely to DHEA-S but significance was lost in multivariable regression analysis. DHEA-S was associated with age, gender and perception of MS pain, while effort-reward imbalance dimensions and GHQ score failed to reach the statistical significance in multivariable regression analysis. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

¹H NMR and multivariate data analysis of the relationship between the age and quality of duck meat.

PubMed

Liu, Chunli; Pan, Daodong; Ye, Yangfang; Cao, Jinxuan

2013-11-15

To contribute to a better understanding of the factors affecting meat quality, we investigated the influence of age on the chemical composition of duck meat. Aging probably affects the quality of meat through changes in metabolism. Therefore, we studied the metabolic composition of duck meat using (1)H nuclear magnetic resonance (NMR) spectroscopy. Comprehensive multivariate data analysis showed significant differences between extracts from ducks that had been aged for four different time periods. Although lactate and anserine increased with age, fumarate, betaine, taurine, inosine and alkyl-substituted free amino acids decreased. These results contribute to a better understanding of changes in duck meat metabolism as meat ages, which could be used to help assess the quality of duck meat as a food. Copyright © 2013 Elsevier Ltd. All rights reserved.

Relations among soil radon, environmental parameters, volcanic and seismic events at Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Giammanco, S.; Ferrera, E.; Cannata, A.; Montalto, P.; Neri, M.

2013-12-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol probe located on the upper NE flank of Mt. Etna volcano (Italy), close both to the Piano Provenzana fault and to the NE-Rift. Seismic, volcanological and radon data were analysed together with data on environmental parameters, such as air and soil temperature, barometric pressure, snow and rain fall. In order to find possible correlations among the above parameters, and hence to reveal possible anomalous trends in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-day time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-day moving averages showed that, similar to multivariate linear regression analysis, the summer period was characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allowed to study the relations among different signals either in the time or in the frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Using the above analysis, two periods were recognized when radon variations were significantly correlated with marked soil temperature changes and also with local seismic or volcanic activity. This allowed to produce two different physical models of soil gas transport that explain the observed anomalies. Our work suggests that in order to make an accurate analysis of the relations among different signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be the most effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

The Multidisciplinary Swallowing Team Approach Decreases Pneumonia Onset in Acute Stroke Patients.

PubMed

Aoki, Shiro; Hosomi, Naohisa; Hirayama, Junko; Nakamori, Masahiro; Yoshikawa, Mineka; Nezu, Tomohisa; Kubo, Satoshi; Nagano, Yuka; Nagao, Akiko; Yamane, Naoya; Nishikawa, Yuichi; Takamoto, Megumi; Ueno, Hiroki; Ochi, Kazuhide; Maruyama, Hirofumi; Yamamoto, Hiromi; Matsumoto, Masayasu

2016-01-01

Dysphagia occurs in acute stroke patients at high rates, and many of them develop aspiration pneumonia. Team approaches with the cooperation of various professionals have the power to improve the quality of medical care, utilizing the specialized knowledge and skills of each professional. In our hospital, a multidisciplinary participatory swallowing team was organized. The aim of this study was to clarify the influence of a team approach on dysphagia by comparing the rates of pneumonia in acute stroke patients prior to and post team organization. All consecutive acute stroke patients who were admitted to our hospital between April 2009 and March 2014 were registered. We analyzed the difference in the rate of pneumonia onset between the periods before team organization (prior period) and after team organization (post period). Univariate and multivariate analyses were performed using a Cox proportional hazards model to determine the predictors of pneumonia. We recruited 132 acute stroke patients from the prior period and 173 patients from the post period. Pneumonia onset was less frequent in the post period compared with the prior period (6.9% vs. 15.9%, respectively; p = 0.01). Based on a multivariate analysis using a Cox proportional hazards model, it was determined that a swallowing team approach was related to pneumonia onset independent from the National Institutes of Health Stroke Scale score on admission (adjusted hazard ratio 0.41, 95% confidence interval 0.19-0.84, p = 0.02). The multidisciplinary participatory swallowing team effectively decreased the pneumonia onset in acute stroke patients.

Alternative statistical methods for interpreting airborne Alder (Alnus glutimosa (L.) Gaertner) pollen concentrations.

PubMed

González Parrado, Zulima; Valencia Barrera, Rosa M; Fuertes Rodríguez, Carmen R; Vega Maray, Ana M; Pérez Romero, Rafael; Fraile, Roberto; Fernández González, Delia

2009-01-01

This paper reports on the behaviour of Alnus glutinosa (alder) pollen grains in the atmosphere of Ponferrada (León, NW Spain) from 1995 to 2006. The study, which sought to determine the effects of various weather-related parameters on Alnus pollen counts, was performed using a volumetric method. The main pollination period for this taxon is January-February. Alder pollen is one of the eight major airborne pollen allergens found in the study area. An analysis was made of the correlation between pollen counts and major weather-related parameters over each period. In general, the strongest positive correlation was with temperature, particularly maximum temperature. During each period, peak pollen counts occurred when the maximum temperature fell within the range 9 degrees C-14 degrees C. Finally, multivariate analysis showed that the parameter exerting the greatest influence was temperature, a finding confirmed by Spearman correlation tests. Principal components analysis suggested that periods with high pollen counts were characterised by high maximum temperature, low rainfall and an absolute humidity of around 6 g m(-3). Use of this type of analysis in conjunction with other methods is essential for obtaining an accurate record of pollen-count variations over a given period.

Tailored multivariate analysis for modulated enhanced diffraction

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

Caliandro, Rocco; Guccione, Pietro; Nico, Giovanni

2015-10-21

Modulated enhanced diffraction (MED) is a technique allowing the dynamic structural characterization of crystalline materials subjected to an external stimulus, which is particularly suited forin situandoperandostructural investigations at synchrotron sources. Contributions from the (active) part of the crystal system that varies synchronously with the stimulus can be extracted by an offline analysis, which can only be applied in the case of periodic stimuli and linear system responses. In this paper a new decomposition approach based on multivariate analysis is proposed. The standard principal component analysis (PCA) is adapted to treat MED data: specific figures of merit based on their scoresmore » and loadings are found, and the directions of the principal components obtained by PCA are modified to maximize such figures of merit. As a result, a general method to decompose MED data, called optimum constrained components rotation (OCCR), is developed, which produces very precise results on simulated data, even in the case of nonperiodic stimuli and/or nonlinear responses. The multivariate analysis approach is able to supply in one shot both the diffraction pattern related to the active atoms (through the OCCR loadings) and the time dependence of the system response (through the OCCR scores). When applied to real data, OCCR was able to supply only the latter information, as the former was hindered by changes in abundances of different crystal phases, which occurred besides structural variations in the specific case considered. To develop a decomposition procedure able to cope with this combined effect represents the next challenge in MED analysis.« less

Outbreak of resistant Acinetobacter baumannii- measures and proposal for prevention and control.

PubMed

Romanelli, Roberta Maia de Castro; Jesus, Lenize Adriana de; Clemente, Wanessa Trindade; Lima, Stella Sala Soares; Rezende, Edna Maria; Coutinho, Rosane Luiza; Moreira, Ricardo Luiz Fontes; Neves, Francelli Aparecida Cordeiro; Brás, Nelma de Jesus

2009-10-01

Acinetobacter baumannii colonization and infection, frequent in Intensive Care Unit (ICU) patients, is commonly associated with high morbimortality. Several outbreaks due to multidrug-resistant (MDR) A. baumanii have been reported but few of them in Brazil. This study aimed to identify risk factors associated with colonization and infection by MDR and carbapenem-resistant A. baumannii strains isolated from patients admitted to the adult ICU at HC/UFMG. A case-control study was performed from January 2007 to June 2008. Cases were defined as patients colonized or infected by MDR/carbapenem-resistant A. baumannii, and controls were patients without MDR/carbapenem-resistant A. baumannii isolation, in a 1:2 proportion. For statistical analysis, due to changes in infection control guidelines, infection criteria and the notification process, this study was divided into two periods. During the first period analyzed, from January to December 2007, colonization or infection by MDR/carbapenem-resistant A. baumannii was associated with prior infection, invasive device utilization, prior carbapenem use and clinical severity. In the multivariate analysis, prior infection and mechanical ventilation proved to be statistically significant risk factors. Carbapenem use showed a tendency towards a statistical association. During the second study period, from January to June 2008, variables with a significant association with MDR/carbapenem-resistant A. baumannii colonization/infection were catheter utilization, carbapenem and third-generation cephalosporin use, hepatic transplantation, and clinical severity. In the multivariate analysis, only CVC use showed a statistical difference. Carbapenem and third-generation cephalosporin use displayed a tendency to be risk factors. Risk factors must be focused on infection control and prevention measures considering A. baumanni dissemination.

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

[Temporary employment and health: a multivariate analysis of occupational injury risk by job tenure].

PubMed

Bena, Antonella; Giraudo, Massimiliano

2013-01-01

To study the relationship between job tenure and injury risk, controlling for individual factors and company characteristics. Analysis of incidence and injury risk by job tenure, controlling for gender, age, nationality, economic activity, firm size. Sample of 7% of Italian workers registered in the INPS (National Institute of Social Insurance) database. Private sector employees who worked as blue collars or apprentices. First-time occupational injuries, all occupational injuries, serious occupational injuries. Our findings show an increase in injury risk among those who start a new job and an inverse relationship between job tenure and injury risk. Multivariate analysis confirm these results. Recommendations for improving this situation include the adoption of organizational models that provide periods of mentoring from colleagues already in the company and the assignment to simple and not much hazardous tasks. The economic crisis may exacerbate this problem: it is important for Italy to improve the systems of monitoring relations between temporary employment and health.

Comparison of Outcomes of Acute Coronary Syndrome in Patients ≥80 Years Versus Those <80 Years in Israel from 2000 to 2013.

PubMed

Shechter, Michael; Rubinstein, Roy; Goldenberg, Ilan; Matetzki, Shlomi

2017-10-15

Although patients ≥80 years old constitute the fastest-growing segment of the population and have a high prevalence of coronary artery disease, few data exist regarding the outcome of octogenarians with acute coronary syndrome (ACS). In a retrospective study based on data of 13,432 ACS patients who were enrolled in the ACS Israel Survey, we first evaluated the clinical outcome of 1,731 ACS patients ≥80 years (13%) compared with 11,701 ACS patients <80 years (87%) hospitalized during 2000 to 2013. Second, we evaluated the clinical outcome of patients ≥80 years hospitalized during the 2000 to 2006 ("early") period (n = 1,037) compared with those of the same age group of patients hospitalized during the 2008 to 2013 ("late") period (n = 694). Implementation of the ACS AHA/ACC/ESC therapeutic guidelines was lower in ACS patients ≥80 years compared with patients <80 years. Multivariate Cox regression analysis demonstrated a worse 1-year survival rate in the ACS patients ≥80 years compared with those <80 years. During the late period, patients ≥80 years were more frequently treated with guideline-recommended therapies compared with patients from the same age group who were hospitalized in the early period. Multivariate Cox regression analysis demonstrated a better 1-year survival rate of patients ≥80 years during the late period compared with the early period (hazard ratio 1.17, 95% confidence interval 1.15 to 1.61; p = 0.01). In addition, adverse outcome rates of ACS patients ≥80 years were significantly higher compared with those of patients <80 years. However, survival rates of ACS patients ≥80 years were improved over the 200 to 2013 period. Copyright © 2017 Elsevier Inc. All rights reserved.

TU-FG-201-05: Varian MPC as a Statistical Process Control Tool

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

Carver, A; Rowbottom, C

Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whethermore » or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity and beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.« less

Guideline-Driven Care Improves Outcomes in Patients with Traumatic Rib Fractures.

PubMed

Flarity, Kathleen; Rhodes, Whitney C; Berson, Andrew J; Leininger, Brian E; Reckard, Paul E; Riley, Keyan D; Shahan, Charles P; Schroeppel, Thomas J

2017-09-01

There is no established national standard for rib fracture management. A clinical practice guideline (CPG) for rib fractures, including monitoring of pulmonary function, early initiation of aggressive loco-regional analgesia, and early identification of deteriorating respiratory function, was implemented in 2013. The objective of the study was to evaluate the effect of the CPG on hospital length of stay. Hospital length of stay (LOS) was compared for adult patients admitted to the hospital with rib fracture(s) two years before and two years after CPG implementation. A separate analysis was done for the patients admitted to the intensive care unit (ICU). Over the 48-month study period, 571 patients met inclusion criteria for the study. Pre-CPG and CPG study groups were well matched with few differences. Multivariable regression did not demonstrate a difference in LOS (B = -0.838; P = 0.095) in the total study cohort. In the ICU cohort (n = 274), patients in the CPG group were older (57 vs 52 years; P = 0.023) and had more rib fractures (4 vs 3; P = 0.003). Multivariable regression identified a significant decrease in LOS for those patients admitted in the CPG period (B = -2.29; P = 0.019). Despite being significantly older with more rib fractures in the ICU cohort, patients admitted after implementation of the CPG had a significantly reduced LOS on multivariable analysis, reducing LOS by over two days. This structured intervention can limit narcotic usage, improve pulmonary function, and decrease LOS in the most injured patients with chest trauma.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Multivariate Bioclimatic Ecosystem Change Approaches

DTIC Science & Technology

2015-02-06

course the sandy soils of the Sandhills will not migrate. This observation suggests that a new nomenclature for ecosystems must be developed if...Coast Sandhills. At that time period, not only will the climate be similar, but the soil character will also be similar. Therefore about the year 2115...Disaggregation of global circulation model outputs decision and policy analysis. Working Paper No. 2. Cali, Colombia : International Centre for Tropical

Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG-fMRI recordings.

PubMed

Ji, Hong; Petro, Nathan M; Chen, Badong; Yuan, Zejian; Wang, Jianji; Zheng, Nanning; Keil, Andreas

2018-02-06

Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework. This approach accomplishes three tasks: (1) It provides a measure for testing multivariate correlation and multivariate uncorrelation of the two modalities; (2) it provides criterion for the selection of EEG features; (3) it performs a screening of relevant EEG information by grouping the EEG channels into clusters to improve efficiency and to reduce computational load when searching for the best predictors of the BOLD signal. The present report applies this approach to a data set with concurrent recordings of steady-state-visual evoked potentials (ssVEPs) and fMRI, recorded while observers viewed phase-reversing Gabor patches. We test the hypothesis that fluctuations in visuo-cortical mass potentials systematically covary with BOLD fluctuations not only in visual cortical, but also in anterior temporal and prefrontal areas. Results supported the hypothesis and showed that the xMCC-based analysis provides straightforward identification of neurophysiological plausible brain regions with EEG-fMRI covariance. Furthermore xMCC converged with other extant methods for EEG-fMRI analysis. © 2018 The Authors Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Multivariate data analysis on historical IPV production data for better process understanding and future improvements.

PubMed

Thomassen, Yvonne E; van Sprang, Eric N M; van der Pol, Leo A; Bakker, Wilfried A M

2010-09-01

Historical manufacturing data can potentially harbor a wealth of information for process optimization and enhancement of efficiency and robustness. To extract useful data multivariate data analysis (MVDA) using projection methods is often applied. In this contribution, the results obtained from applying MVDA on data from inactivated polio vaccine (IPV) production runs are described. Data from over 50 batches at two different production scales (700-L and 1,500-L) were available. The explorative analysis performed on single unit operations indicated consistent manufacturing. Known outliers (e.g., rejected batches) were identified using principal component analysis (PCA). The source of operational variation was pinpointed to variation of input such as media. Other relevant process parameters were in control and, using this manufacturing data, could not be correlated to product quality attributes. The gained knowledge of the IPV production process, not only from the MVDA, but also from digitalizing the available historical data, has proven to be useful for troubleshooting, understanding limitations of available data and seeing the opportunity for improvements. 2010 Wiley Periodicals, Inc.

Prognostic factors in patients with malignant pleural effusion: Is it possible to predict mortality in patients with good performance status?

PubMed

Abrao, Fernando Conrado; Peixoto, Renata D'Alpino; de Abreu, Igor Renato Louro Bruno; Janini, Maria Cláudia; Viana, Geisa Garcia; de Oliveira, Mariana Campello; Younes, Riad Naim

2016-04-01

The aim of this study was to identify predictors of mortality only in patients with malignant pleural effusion (MPE) showing good performance status which required pleural palliative procedures. All patients with MPE submitted to pleural palliative procedure were enrolled in a prospective study between 2013 and 2014. Patients with Eastern cooperative oncology group (ECOG) score zero, one, and two were considered with good performance status. The possible prognostic factors were tested for significance using the log-rank test (Kaplan-Meier method) and those with significance on univariate analysis were entered into a multivariable Cox model. A total of 64 patients were included in the analysis. Median follow-up time for surviving patients was 263 days. Median survival for the entire cohort was not reached yet. In the multivariate analysis, gastrointestinal primary site (P = 0.006), low albumin concentration in the pleural fluid (P = 0.017), and high serum NLR (P = 0.007) were associated with mortality. In our cohort of ECOG 0-2 patients with MPE submitted to pleural palliative procedures, gastrointestinal malignancy compared to other sites, low pleural fluid albumin and high NLR were significantly associated with mortality. The identification of these prognostic factors may assist the choice of the optimal palliative technique. J. Surg. Oncol. 2016;113:570-574. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Parallel experimental design and multivariate analysis provides efficient screening of cell culture media supplements to improve biosimilar product quality.

PubMed

Brühlmann, David; Sokolov, Michael; Butté, Alessandro; Sauer, Markus; Hemberger, Jürgen; Souquet, Jonathan; Broly, Hervé; Jordan, Martin

2017-07-01

Rational and high-throughput optimization of mammalian cell culture media has a great potential to modulate recombinant protein product quality. We present a process design method based on parallel design-of-experiment (DoE) of CHO fed-batch cultures in 96-deepwell plates to modulate monoclonal antibody (mAb) glycosylation using medium supplements. To reduce the risk of losing valuable information in an intricate joint screening, 17 compounds were separated into five different groups, considering their mode of biological action. The concentration ranges of the medium supplements were defined according to information encountered in the literature and in-house experience. The screening experiments produced wide glycosylation pattern ranges. Multivariate analysis including principal component analysis and decision trees was used to select the best performing glycosylation modulators. Subsequent D-optimal quadratic design with four factors (three promising compounds and temperature shift) in shake tubes confirmed the outcome of the selection process and provided a solid basis for sequential process development at a larger scale. The glycosylation profile with respect to the specifications for biosimilarity was greatly improved in shake tube experiments: 75% of the conditions were equally close or closer to the specifications for biosimilarity than the best 25% in 96-deepwell plates. Biotechnol. Bioeng. 2017;114: 1448-1458. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Compound effects of temperature and precipitation in making droughts more frequent in Marathwada, India

NASA Astrophysics Data System (ADS)

Mondal, A.; Zachariah, M.; Achutarao, K. M.; Otto, F. E. L.

2017-12-01

The Marathwada region in Maharashtra, India is known to suffer significantly from agrarian crisis including farmer suicides resulting from persistent droughts. Drought monitoring in India is commonly based on univariate indicators that consider the deficiency in precipitation alone. However, droughts may involve complex interplay of multiple physical variables, necessitating an integrated, multivariate approach to analyse their behaviour. In this study, we compare the behaviour of drought characteristics in Marathwada in the recent years as compared to the first half of the twentieth century, using a joint precipitation and temperature-based Multivariate Standardized Drought Index (MSDI). Drought events in the recent times are found to exhibit exceptional simultaneous anomalies of high temperature and precipitation deficits in this region, though studies on precipitation alone show that these events are within the range of historically observed variability. Additionally, we also develop multivariate copula-based Severity-Duration-Frequency (SDF) relationships for droughts in this region and compare their natures pre- and post- 1950. Based on multivariate return periods considering both temperature and precipitation anomalies, as well as the severity and duration of droughts, it is found that droughts have become more frequent in the post-1950 period. Based on precipitation alone, such an observation cannot be made. This emphasizes the sensitivity of droughts to temperature and underlines the importance of considering compound effects of temperature and precipitation in order to avoid an underestimation of drought risk. This observation-based analysis is the first step towards investigating the causal mechanisms of droughts, their evolutions and impacts in this region, particularly those influenced by anthropogenic climate change.

ENSO related variability in the Southern Hemisphere, 1948-2000

NASA Astrophysics Data System (ADS)

Ribera, Pedro; Mann, Michael E.

2003-01-01

The spatiotemporal evolution of Southern Hemisphere climate variability is diagnosed based on the use of the NCEP reanalysis (1948-2000) dataset. Using the MTM-SVD analysis method, significant narrowband variability is isolated from the multi-variate dataset. It is found that the ENSO signal exhibits statistically significant behavior at quasiquadrennial (3-6 yr) timescales for the full time-period. A significant quasibiennial (2-3 yr) timescales emerges only for the latter half of period. Analyses of the spatial evolution of the two reconstructed signals shed additional light on linkages between low and high-latitude Southern Hemisphere climate anomalies.

Tailored multivariate analysis for modulated enhanced diffraction

DOE PAGES

Caliandro, Rocco; Guccione, Pietro; Nico, Giovanni; ...

2015-10-21

Modulated enhanced diffraction (MED) is a technique allowing the dynamic structural characterization of crystalline materials subjected to an external stimulus, which is particularly suited forin situandoperandostructural investigations at synchrotron sources. Contributions from the (active) part of the crystal system that varies synchronously with the stimulus can be extracted by an offline analysis, which can only be applied in the case of periodic stimuli and linear system responses. In this paper a new decomposition approach based on multivariate analysis is proposed. The standard principal component analysis (PCA) is adapted to treat MED data: specific figures of merit based on their scoresmore » and loadings are found, and the directions of the principal components obtained by PCA are modified to maximize such figures of merit. As a result, a general method to decompose MED data, called optimum constrained components rotation (OCCR), is developed, which produces very precise results on simulated data, even in the case of nonperiodic stimuli and/or nonlinear responses. Furthermore, the multivariate analysis approach is able to supply in one shot both the diffraction pattern related to the active atoms (through the OCCR loadings) and the time dependence of the system response (through the OCCR scores). Furthermore, when applied to real data, OCCR was able to supply only the latter information, as the former was hindered by changes in abundances of different crystal phases, which occurred besides structural variations in the specific case considered. In order to develop a decomposition procedure able to cope with this combined effect represents the next challenge in MED analysis.« less

Occurrence and transport of pesticides and alkylphenols in water samples along the Ebro River Basin

NASA Astrophysics Data System (ADS)

Navarro, Alícia; Tauler, Romà; Lacorte, Sílvia; Barceló, Damià

2010-03-01

SummaryWe report the temporal and geographical variations of a set of 30 pesticides (including triazines, organophosphorus and acetanilides) and industrial compounds in surface waters along the Ebro River during the period 2004-2006. Using descriptive statistics we found that the compounds with industrial origin (tributylphosphate, octylphenol and nonylphenol) appeared in over 60% of the samples analyzed and at very high concentrations, while pesticides had a point source origin in the Ebro delta area and overall low-levels, between 0.005 and 2.575 μg L -1. Correlations among pollutants and their distributions were studied using Principal Component Analysis (PCA), a multivariate exploratory data analysis technique which permitted us to discern between agricultural and industrial source contamination. Over a 3 years period a seasonal trend revealed highest concentrations of pesticides over the spring-summer period following pesticide application.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Role of pelvic radiotherapy for locally advanced rectal cancer and synchronous unresectable distant metastases.

PubMed

Liu, K T; Wan, J F; Zhu, J; Li, G C; Sun, W J; Shen, L J; Cai, S J; Gu, W L; Lian, P; Zhang, Z

2016-12-01

To evaluate the efficacy and safety of pelvic irradiation combined systematic chemotherapy in patients with locally advanced (cT3-T4 and/or cN+) rectal cancer and synchronous unresectable distant metastases. A total of 76 eligible patients who received pelvic radiotherapy and concurrent capecitabine-based chemotherapy were retrospectively reviewed. Patients survival curves were constructed using the Kaplan-Meier method, and a multivariate analysis was performed to identify independent prognostic factors. Most of the adverse events were mild during the period of combined chemoradiotherapy. Twenty-two patients experienced resection of primary tumour and 16 patients underwent radical surgery of all lesions. Only five patients had pelvic progression during the follow-up period. The median progression-free survival and median overall survival were 13 and 30 months, respectively. Radical surgery of all lesions following chemoradiotherapy was found to be an independent prognostic factor according to multivariate analysis. Pelvic irradiation combined with systematic chemotherapy in patients with locally advanced rectal cancer and synchronous unresectable distant metastases is effective and tolerable, both for pelvic and distant control. A curative resection following chemoradiotherapy was associated with prolonged survival. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Integration of multivariate empirical mode decomposition and independent component analysis for fetal ECG separation from abdominal signals.

PubMed

Thanaraj, Palani; Roshini, Mable; Balasubramanian, Parvathavarthini

2016-11-14

The fetal electrocardiogram (FECG) signals are essential to monitor the health condition of the baby. Fetal heart rate (FHR) is commonly used for diagnosing certain abnormalities in the formation of the heart. Usually, non-invasive abdominal electrocardiogram (AbECG) signals are obtained by placing surface electrodes in the abdomen region of the pregnant woman. AbECG signals are often not suitable for the direct analysis of fetal heart activity. Moreover, the strength and magnitude of the FECG signals are low compared to the maternal electrocardiogram (MECG) signals. The MECG signals are often superimposed with the FECG signals that make the monitoring of FECG signals a difficult task. Primary goal of the paper is to separate the fetal electrocardiogram (FECG) signals from the unwanted maternal electrocardiogram (MECG) signals. A multivariate signal processing procedure is proposed here that combines the Multivariate Empirical Mode Decomposition (MEMD) and Independent Component Analysis (ICA). The proposed method is evaluated with clinical abdominal signals taken from three pregnant women (N= 3) recorded during the 38-41 weeks of the gestation period. The number of fetal R-wave detected (NEFQRS), the number of unwanted maternal peaks (NMQRS), the number of undetected fetal R-wave (NUFQRS) and the FHR detection accuracy quantifies the performance of our method. Clinical investigation with three test subjects shows an overall detection accuracy of 92.8%. Comparative analysis with benchmark signal processing method such as ICA suggests the noteworthy performance of our method.

Occurrence of mastitis and associated risk factors in lactating goats under pastoral management in Borana, Southern Ethiopia.

PubMed

Megersa, Bekele; Tadesse, Chala; Abunna, Fufa; Regassa, Alemayehu; Mekibib, Berhanu; Debela, Etana

2010-08-01

Mastitis prevalence and related risk factors were studied in 1,072 udder halves of 536 lactating goats from October, 2008 to February, 2009. Clinical and subclinical mastitis were prevalent in 4.3% (95% CI = 2.8, 6.5) and 11.2% (95% CI = 8.7, 14.3) of the studied animals, respectively, resulting in an overall prevalence of 15.5% (95% CI = 12.6, 18.9). Univariate analysis of the potential risk factors has depicted that mastitis was more prevalent in does with previous mastitis history, increased parity, poor body conditions, increased milk production, late lactation stage, long teat, and housed goats. Furthermore, prevalence was significantly higher (p < 0.05) during the wet period of October to November than the dry periods of January to February. No significant variations (p > 0.05) were observed in mastitis prevalence with udder tick infestation, mixing goat with sheep and flock size. With multivariable analysis, lactation stage, teat length, body condition, and season (wet months) have showed significant association with mastitis prevalence, and these factors maintained significant in the stepwise elimination of multivariable logistic regression model. As a result, does in late stage of lactation (OR = 4.3, 1.8, 10.4), poor body condition (OR = 5.0, 1.7, 10.0), long teats (OR = 2.2, 95% CI = 1.1, 4.2) and does examined in wet period were at higher risk of udder infections than early lactation, good body condition, short teat, and examined in dry period, respectively. The study showed occurrence of mastitis and associated risk factors in studied goats, which suggests the need for control intervention. Further investigations into pathogens involved in goat mastitis will optimize our knowledge of causative agents and control interventions.

OGLE II Eclipsing Binaries In The LMC: Analysis With Class

NASA Astrophysics Data System (ADS)

Devinney, Edward J.; Prsa, A.; Guinan, E. F.; DeGeorge, M.

2011-01-01

The Eclipsing Binaries (EBs) via Artificial Intelligence (EBAI) Project is applying machine learning techniques to elucidate the nature of EBs. Previously, Prsa, et al. applied artificial neural networks (ANNs) trained on physically-realistic Wilson-Devinney models to solve the light curves of the 1882 detached EBs in the LMC discovered by the OGLE II Project (Wyrzykowski, et al.) fully automatically, bypassing the need for manually-derived starting solutions. A curious result is the non-monotonic distribution of the temperature ratio parameter T2/T1, featuring a subsidiary peak noted previously by Mazeh, et al. in an independent analysis using the EBOP EB solution code (Tamuz, et al.). To explore this and to gain a fuller understanding of the multivariate EBAI LMC observational plus solutions data, we have employed automatic clustering and advanced visualization (CAV) techniques. Clustering the OGLE II data aggregates objects that are similar with respect to many parameter dimensions. Measures of similarity for example, could include the multidimensional Euclidean Distance between data objects, although other measures may be appropriate. Applying clustering, we find good evidence that the T2/T1 subsidiary peak is due to evolved binaries, in support of Mazeh et al.'s speculation. Further, clustering suggests that the LMC detached EBs occupying the main sequence region belong to two distinct classes. Also identified as a separate cluster in the multivariate data are stars having a Period-I band relation. Derekas et al. had previously found a Period-K band relation for LMC EBs discovered by the MACHO Project (Alcock, et al.). We suggest such CAV techniques will prove increasingly useful for understanding the large, multivariate datasets increasingly being produced in astronomy. We are grateful for the support of this research from NSF/RUI Grant AST-05-75042 f.

Medicaid Participation among Liver Transplant Candidates after the Affordable Care Act Medicaid Expansion.

PubMed

Tumin, Dmitry; Beal, Eliza W; Mumtaz, Khalid; Hayes, Don; Tobias, Joseph D; Pawlik, Timothy M; Washburn, W Kenneth; Black, Sylvester M

2017-08-01

The 2014 Medicaid expansion in participating states increased insurance coverage among people with chronic health conditions, but its implications for access to surgical care remain unclear. We investigated how Medicaid expansion influenced the insurance status of candidates for liver transplantation (LT) and transplant center payor mix. Data on LT candidates aged 18 to 64 years, in 2012 to 2013 (pre-expansion) and 2014 to 2015 (post-expansion), were obtained from the United Network for Organ Sharing registry. Change between the 2 periods in the percent of LT candidates using Medicaid was compared between expansion and nonexpansion states. Multivariable logistic regression was used to determine how Medicaid expansion influenced individual LT candidates' likelihood of using Medicaid insurance. The study included 33,017 LT candidates, of whom 29,666 had complete data for multivariable analysis. Medicaid enrollment increased by 4% after Medicaid expansion in participating states. One-quarter of the transplant centers in these states experienced ≥10% increase in the proportion of LT candidates using Medicaid insurance. Multivariable analysis confirmed that Medicaid expansion was associated with increased odds of LT candidates using Medicaid insurance (odds ratio 1.49; 95% CI 1.34, 1.66; p < 0.001). However, the absolute number and demographic characteristics of patients listed for LT did not change in Medicaid expansion states during the post-expansion period. Candidates for LT became more likely to use Medicaid after the 2014 Medicaid expansion policy came into effect. Enactment of this policy did not appear to increase access to LT or address socioeconomic and demographic disparities in access to the LT wait list. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Estimating the net effect of progesterone elevation on the day of hCG on live birth rates after IVF: a cohort analysis of 3296 IVF cycles.

PubMed

Venetis, Christos A; Kolibianakis, Efstratios M; Bosdou, Julia K; Lainas, George T; Sfontouris, Ioannis A; Tarlatzis, Basil C; Lainas, Tryfon G

2015-03-01

What is the proper way of assessing the effect of progesterone elevation (PE) on the day of hCG on live birth in women undergoing fresh embryo transfer after in vitro fertilization (IVF) using GnRH analogues and gonadotrophins? This study indicates that a multivariable approach, where the effect of the most important confounders is controlled for, can lead to markedly different results regarding the association between PE on the day of hCG and live birth rates after IVF when compared with the bivariate analysis that has been typically used in the relevant literature up to date. PE on the day of hCG is associated with decreased pregnancy rates in fresh IVF cycles. Evidence for this comes from observational studies that mostly failed to control for potential confounders. This is a retrospective analysis of a cohort of fresh IVF/intracytoplasmic sperm injection cycles (n = 3296) performed in a single IVF centre during the period 2001-2013. Patients in whom ovarian stimulation was performed with gonadotrophins and GnRH analogues. Natural cycles and cycles where stimulation involved the administration of clomiphene were excluded. In order to reflect routine clinical practice, no other exclusion criteria were imposed on this dataset. The primary outcome measure for this study was live birth defined as the delivery of a live infant after 24 weeks of gestation. We compared the association between PE on the day of hCG (defined as P > 1.5 ng/ml) and live birth rates calculated by simple bivariate analyses with that derived from multivariable logistic regression. The multivariable analysis controlled for female age, number of oocytes retrieved, number of embryos transferred, developmental stage of embryos at transfer (cleavage versus blastocyst), whether at least one good-quality embryo was transferred, the woman's body mass index, the total dose of FSH administered during ovarian stimulation and the type of GnRH analogues used (agonists versus antagonists) during ovarian stimulation. In addition, an interaction analysis was performed in order to assess whether the ovarian response (<6, 6-18, >18 oocytes) has a moderating effect on the association of PE on the day of hCG with live birth rates after IVF. Live birth rates were not significantly different between cycles with and those without PE when a bivariate analysis was performed [odds ratio (OR): 0.78, 95% confidence interval (CI): 0.56-1.09]. However, when a multivariable analysis was performed, controlling for the effect of the aforementioned confounders, live birth rates (OR: 0.68, 95% CI: 0.48-0.97) were significantly decreased in the group with PE on the day of hCG. The number of oocytes retrieved was the most potent confounder, causing a 29.4% reduction in the OR for live birth between the two groups compared. Furthermore, a moderating effect of ovarian response on the association between PE and live birth rates was not supported in the present analysis since no interaction was detected between PE and the type of ovarian response (<6, 6-18, >18 oocytes). This is a retrospective analysis of data collected during a 12-year period, and although the effect of the most important confounders was controlled for in the multivariable analysis, the presence of residual bias cannot be excluded. This analysis highlights the need for a multivariable approach when researchers or clinicians aim to evaluate the impact of PE on pregnancy rates in their own clinical setting. Failure to do so might explain why many past studies have failed to identify the detrimental effect of PE in fresh IVF cycles. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Effect of age on rates of palliative surgery and chemotherapy use in patients with locally advanced or metastatic gastric cancer.

PubMed

Nelen, S D; van Putten, M; Lemmens, V E P P; Bosscha, K; de Wilt, J H W; Verhoeven, R H A

2017-12-01

This study assessed trends in the treatment and survival of palliatively treated patients with gastric cancer, with a focus on age-related differences. For this retrospective, population-based, nationwide cohort study, all patients diagnosed between 1989 and 2013 with non-cardia gastric cancer with metastasized disease or invasion into adjacent structures were selected from the Netherlands Cancer Registry. Trends in treatment and 2-year overall survival were analysed and compared between younger (age less than 70 years) and older (aged 70 years or more) patients. Analyses were done for five consecutive periods of 5 years, from 1989-1993 to 2009-2013. Multivariable logistic regression analysis was used to examine the probability of undergoing surgery. Multivariable Cox regression analysis was used to identify independent risk factors for death. Palliative resection rates decreased significantly in both younger and older patients, from 24·5 and 26·2 per cent to 3·0 and 5·0 per cent respectively. Compared with patients who received chemotherapy alone, both younger (21·6 versus 6·3 per cent respectively; P < 0·001) and older (14·7 versus 4·6 per cent; P < 0·001) patients who underwent surgery had better 2-year overall survival rates. Multivariable analysis demonstrated that younger and older patients who received chemotherapy alone had worse overall survival than patients who had surgery only (younger: hazard ratio (HR) 1·22, 95 per cent c.i. 1·12 to 1·33; older: HR 1·12, 1·01 to 1·24). After 2003 there was no association between period of diagnosis and overall survival in younger or older patients. Despite changes in the use of resection and chemotherapy as palliative treatment, overall survival rates of patients with advanced and metastatic gastric cancer did not improve. © 2017 BJS Society Ltd Published by John Wiley & Sons Ltd.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City.

PubMed

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place.

Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City

PubMed Central

Chau, Tang-Tat; Wang, Kuo-Ying

2016-01-01

An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. PMID:26815039

Seasonal assessment and apportionment of surface water pollution using multivariate statistical methods: Sinos River, southern Brazil.

PubMed

Alves, Darlan Daniel; Riegel, Roberta Plangg; de Quevedo, Daniela Müller; Osório, Daniela Montanari Migliavacca; da Costa, Gustavo Marques; do Nascimento, Carlos Augusto; Telöken, Franko

2018-06-08

Assessment of surface water quality is an issue of currently high importance, especially in polluted rivers which provide water for treatment and distribution as drinking water, as is the case of the Sinos River, southern Brazil. Multivariate statistical techniques allow a better understanding of the seasonal variations in water quality, as well as the source identification and source apportionment of water pollution. In this study, the multivariate statistical techniques of cluster analysis (CA), principal component analysis (PCA), and positive matrix factorization (PMF) were used, along with the Kruskal-Wallis test and Spearman's correlation analysis in order to interpret a water quality data set resulting from a monitoring program conducted over a period of almost two years (May 2013 to April 2015). The water samples were collected from the raw water inlet of the municipal water treatment plant (WTP) operated by the Water and Sewage Services of Novo Hamburgo (COMUSA). CA allowed the data to be grouped into three periods (autumn and summer (AUT-SUM); winter (WIN); spring (SPR)). Through the PCA, it was possible to identify that the most important parameters in contribution to water quality variations are total coliforms (TCOLI) in SUM-AUT, water level (WL), water temperature (WT), and electrical conductivity (EC) in WIN and color (COLOR) and turbidity (TURB) in SPR. PMF was applied to the complete data set and enabled the source apportionment water pollution through three factors, which are related to anthropogenic sources, such as the discharge of domestic sewage (mostly represented by Escherichia coli (ECOLI)), industrial wastewaters, and agriculture runoff. The results provided by this study demonstrate the contribution provided by the use of integrated statistical techniques in the interpretation and understanding of large data sets of water quality, showing also that this approach can be used as an efficient methodology to optimize indicators for water quality assessment.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Summer microhabitat use by adult and young-of-year snail darters (Percina tanasi) in two rivers

USGS Publications Warehouse

Ashton, M.J.; Layzer, James B.

2010-01-01

We characterised microhabitat availability and use by adult and young-of-year (YOY) snail darters (Percina tanasi Etnier 1976) while snorkelling in the French Broad and Hiwassee rivers, TN, USA. Both age groups of snail darters disproportionately used most microhabitat variables compared to their availability. Snail darters primarily occupied moderately deep, swift water over gravel substrates with little macrophyte coverage and no silt. Univariate comparisons indicated that adult and YOY darters occupied different habitat, but there was no marked differences between principal components analysis plots of multivariate microhabitat use within a river. Although the availability of microhabitat variables differed between the French Broad and Hiwassee rivers, univariate means and multivariate plots illustrated that the habitats used were generally similar by age groups of snail darters between rivers. Because our observations of habitat availability and use were constrained to low flow periods and depths <1 m, the transferability of our results to higher flow periods may be limited. However, the similarity in habitat use between rivers suggests that our results can be applied to low-normal flow conditions in other streams.

Multivariate stochastic analysis for Monthly hydrological time series at Cuyahoga River Basin

NASA Astrophysics Data System (ADS)

zhang, L.

2011-12-01

Copula has become a very powerful statistic and stochastic methodology in case of the multivariate analysis in Environmental and Water resources Engineering. In recent years, the popular one-parameter Archimedean copulas, e.g. Gumbel-Houggard copula, Cook-Johnson copula, Frank copula, the meta-elliptical copula, e.g. Gaussian Copula, Student-T copula, etc. have been applied in multivariate hydrological analyses, e.g. multivariate rainfall (rainfall intensity, duration and depth), flood (peak discharge, duration and volume), and drought analyses (drought length, mean and minimum SPI values, and drought mean areal extent). Copula has also been applied in the flood frequency analysis at the confluences of river systems by taking into account the dependence among upstream gauge stations rather than by using the hydrological routing technique. In most of the studies above, the annual time series have been considered as stationary signal which the time series have been assumed as independent identically distributed (i.i.d.) random variables. But in reality, hydrological time series, especially the daily and monthly hydrological time series, cannot be considered as i.i.d. random variables due to the periodicity existed in the data structure. Also, the stationary assumption is also under question due to the Climate Change and Land Use and Land Cover (LULC) change in the fast years. To this end, it is necessary to revaluate the classic approach for the study of hydrological time series by relaxing the stationary assumption by the use of nonstationary approach. Also as to the study of the dependence structure for the hydrological time series, the assumption of same type of univariate distribution also needs to be relaxed by adopting the copula theory. In this paper, the univariate monthly hydrological time series will be studied through the nonstationary time series analysis approach. The dependence structure of the multivariate monthly hydrological time series will be studied through the copula theory. As to the parameter estimation, the maximum likelihood estimation (MLE) will be applied. To illustrate the method, the univariate time series model and the dependence structure will be determined and tested using the monthly discharge time series of Cuyahoga River Basin.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Capital market based warning indicators of bank runs

NASA Astrophysics Data System (ADS)

Vakhtina, Elena; Wosnitza, Jan Henrik

2015-01-01

In this investigation, we examine the univariate as well as the multivariate capabilities of the log-periodic [super-exponential] power law (LPPL) for the prediction of bank runs. The research is built upon daily CDS spreads of 40 international banks for the period from June 2007 to March 2010, i.e. at the heart of the global financial crisis. For this time period, 20 of the financial institutions received federal bailouts and are labeled as defaults while the remaining institutions are categorized as non-defaults. The employed multivariate pattern recognition approach represents a modification of the CORA3 algorithm. The approach is found to be robust regardless of reasonable changes of its inputs. Despite the fact that distinct alarm indices for banks do not clearly demonstrate predictive capabilities of the LPPL, the synchronized alarm indices confirm the multivariate discriminative power of LPPL patterns in CDS spread developments acknowledged by bootstrap intervals with 70% confidence level.

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Multivariate statistical analysis of hemlock (Tsuga) volatiles by SPME/GC/MS: insights into the phytochemistry of the hemlock woolly adelgid (Adelges tsugae Annand)

Treesearch

Anthony Lagalante; Frank Calvosa; Michael Mirzabeigi; Vikram Iyengar; Michael Montgomery; Kathleen Shields

2007-01-01

A previously developed single-needle, SPME/GC/MS technique was used to measure the terpenoid content of T. canadensis growing in a hemlock forest at Lake Scranton, PA (Lagalante and Montgomery 2003). The volatile terpenoid composition was measured over a 1-year period from June 2003 to May 2004 to follow the annual cycle of foliage development from...

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Prognostic predictors of patients with carcinoma of the gastric cardia.

PubMed

Zhang, Ming; Li, Zhigao; Ma, Yan; Zhu, Guanyu; Zhang, Hongfeng; Xue, Yingwei

2012-05-01

This study gives insight into survival predictors and clinicopathological features of carcinoma of the gastric cardia. The study included 233 patients who underwent operation for carcinoma of the gastric cardia. Clinicopathological prognostic variables were evaluated as predictors of long-term survival by univariate and multivariate analysis. Cox regression was used for multivariate analysis and survival curves were drawn by the Kaplan- Meier method. Carcinoma of the gastric cardia was characterized by positive lymph node metastasis (77.3%), serosal invasion (83.3%) and more stage III or IV tumors (72.5%). Overall 5-year survival rate was 21.9% and median survival period was 24 months. The 5-year survival rate was influenced by tumor size, depth on invasion, lymph node metastasis, extent of lymph node dissection, disease stage, operation methods and resection margin. The absent of serosal invasion and lymph node metastasis, curative resection should be considered to be the favourable predictors of long-term survival of patients with carcinoma of the gastric cardia.

Carbon financial markets: A time-frequency analysis of CO2 prices

NASA Astrophysics Data System (ADS)

Sousa, Rita; Aguiar-Conraria, Luís; Soares, Maria Joana

2014-11-01

We characterize the interrelation of CO2 prices with energy prices (electricity, gas and coal), and with economic activity. Previous studies have relied on time-domain techniques, such as Vector Auto-Regressions. In this study, we use multivariate wavelet analysis, which operates in the time-frequency domain. Wavelet analysis provides convenient tools to distinguish relations at particular frequencies and at particular time horizons. Our empirical approach has the potential to identify relations getting stronger and then disappearing over specific time intervals and frequencies. We are able to examine the coherency of these variables and lead-lag relations at different frequencies for the time periods in focus.

A novel multi-variant epitope ensemble vaccine against avian leukosis virus subgroup J.

PubMed

Wang, Xiaoyu; Zhou, Defang; Wang, Guihua; Huang, Libo; Zheng, Qiankun; Li, Chengui; Cheng, Ziqiang

2017-12-04

The hypervariable antigenicity and immunosuppressive features of avian leukosis virus subgroup J (ALV-J) has led to great challenges to develop effective vaccines. Epitope vaccine will be a perspective trend. Previously, we identified a variant antigenic neutralizing epitope in hypervariable region 1 (hr1) of ALV-J, N-LRDFIA/E/TKWKS/GDDL/HLIRPYVNQS-C. BLAST analysis showed that the mutation of A, E, T and H in this epitope cover 79% of all ALV-J strains. Base on this data, we designed a multi-variant epitope ensemble vaccine comprising the four mutation variants linked with glycine and serine. The recombinant multi-variant epitope gene was expressed in Escherichia coli BL21. The expressed protein of the variant multi-variant epitope gene can react with positive sera and monoclonal antibodies of ALV-J, while cannot react with ALV-J negative sera. The multi-variant epitope vaccine that conjugated Freund's adjuvant complete/incomplete showed high immunogenicity that reached the titer of 1:64,000 at 42 days post immunization and maintained the immune period for at least 126 days in SPF chickens. Further, we demonstrated that the antibody induced by the variant multi-variant ensemble epitope vaccine recognized and neutralized different ALV-J strains (NX0101, TA1, WS1, BZ1224 and BZ4). Protection experiment that was evaluated by clinical symptom, viral shedding, weight gain, gross and histopathology showed 100% chickens that inoculated the multi-epitope vaccine were well protected against ALV-J challenge. The result shows a promising multi-variant epitope ensemble vaccine against hypervariable viruses in animals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Changes in Case-Mix and Health Outcomes of Medicare Fee-for-Service Beneficiaries and Managed Care Enrollees During the Years 1992-2011.

PubMed

Koroukian, Siran M; Basu, Jayasree; Schiltz, Nicholas K; Navale, Suparna; Bakaki, Paul M; Warner, David F; Dor, Avi; Given, Charles W; Stange, Kurt C

2018-01-01

Recent studies suggest that managed care enrollees (MCEs) and fee-for-service beneficiaries (FFSBs) have become similar in case-mix over time; but comparisons of health outcomes have yielded mixed results. To examine changes in differentials between MCEs and FFSBs both in case-mix and health outcomes over time. Temporal study of the linked Health and Retirement Study (HRS) and Medicare data, comparing case-mix and health outcomes between MCEs and FFSBs across 3 time periods: 1992-1998, 1999-2004, and 2005-2011. We used multivariable analysis, stratified by, and pooled across the study periods. The unit of analysis was the person-wave (n=167,204). HRS participants who were also enrolled in Medicare. Outcome measures included self-reported fair/poor health, 2-year self-rated worse health, and 2-year mortality. Our main covariate was a composite measure of multimorbidity (MM), MM0-MM3, defined as the co-occurrence of chronic conditions, functional limitations, and/or geriatric syndromes. The case-mix differential between MCEs and FFSBs persisted over time. Results from multivariable models on the pooled data and incorporating interaction terms between managed care status and study period indicated that MCEs and FFSBs were as likely to die within 2 years from the HRS interview (P=0.073). This likelihood remained unchanged across the study periods. However, MCEs were more likely than FFSBs to report fair/poor health in the third study period (change in probability for the interaction term: 0.024, P=0.008), but less likely to rate their health worse in the last 2 years, albeit at borderline significance (change in probability: -0.021, P=0.059). Despite the persistence of selection bias, the differential in self-reported fair/poor status between MCEs and FFSBs seems to be closing over time.

A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

PubMed

Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

2016-09-01

In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic traits characteristic of high-performance clones and enables informed decisions on which clones provide a good match for a particular process platform. The proposed approach also provides a mechanistic link between observed clone phenotype, process setup, and feeding regimes, and thereby offers concrete starting points for subsequent process optimization. Biotechnol. Bioeng. 2016;113: 2005-2019. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multi objective climate change impact assessment using multi downscaled climate scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-04-01

Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional and global scale. In the present study, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from a set of statistically downscaled GCM projections for Columbia River Basin (CRB). Analysis is performed using 2 different statistically downscaled climate projections namely the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. Analysis is performed on spatial, temporal and frequency based parameters in the future period at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice-versa for temperature. Frequency analysis provided insights into possible explanation to changes in precipitation.

Historic changes in fish assemblage structure in midwestern nonwadeable rivers

USGS Publications Warehouse

Parks, Timothy P.; Quist, Michael C.; Pierce, Clay L.

2014-01-01

Historical change in fish assemblage structure was evaluated in the mainstems of the Des Moines, Iowa, Cedar, Wapsipinicon, and Maquoketa rivers, in Iowa. Fish occurrence data were compared in each river between historical and recent time periods to characterize temporal changes among 126 species distributions and assess spatiotemporal patterns in faunal similarity. A resampling procedure was used to estimate species occurrences in rivers during each assessment period and changes in species occurrence were summarized. Spatiotemporal shifts in species composition were analyzed at the river and river section scale using cluster analysis, pairwise Jaccard's dissimilarities, and analysis of multivariate beta dispersion. The majority of species exhibited either increases or declines in distribution in all rivers with the exception of several “unknown” or inconclusive trends exhibited by species in the Maquoketa River. Cluster analysis identified temporal patterns of similarity among fish assemblages in the Des Moines, Cedar, and Iowa rivers within the historical and recent assessment period indicating a significant change in species composition. Prominent declines of backwater species with phytophilic spawning strategies contributed to assemblage changes occurring across river systems.

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Analysis of antique bronze coins by Laser Induced Breakdown Spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Bachler, M. Orlić; Bišćan, M.; Kregar, Z.; Jelovica Badovinac, I.; Dobrinić, J.; Milošević, S.

2016-09-01

This work presents a feasibility study of applying the Principal Component Analysis (PCA) to data obtained by Laser-Induced Breakdown Spectroscopy (LIBS) with the aim of determining correlation between different samples. The samples were antique bronze coins coated in silver (follis) dated in the Roman Empire period and were made during different rulers in different mints. While raw LIBS data revealed that in the period from the year 286 to 383 CE content of silver was constantly decreasing, the PCA showed that the samples can be somewhat grouped together based on their place of origin, which could be a useful hint when analysing unknown samples. It was also found that PCA can help in discriminating spectra corresponding to ablation from the surface and from the bulk. Furthermore, Partial Least Squares method (PLS) was used to obtain, based on a set of samples with known composition, an estimation of relative copper concentration in studied ancient coins. This analysis showed that copper concentration in surface layers ranged from 83% to 90%.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms.

PubMed

Matero, Sanni; van Den Berg, Frans; Poutiainen, Sami; Rantanen, Jukka; Pajander, Jari

2013-05-01

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed. Copyright © 2013 Wiley Periodicals, Inc.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

On certain families of rational functions arising in dynamics

NASA Technical Reports Server (NTRS)

Byrnes, C. I.

1979-01-01

It is noted that linear systems, depending on parameters, can occur in diverse situations including families of rational solutions to the Korteweg-de Vries equation or to the finite Toda lattice. The inverse scattering method used by Moser (1975) to obtain canonical coordinates for the finite homogeneous Toda lattice can be used for the synthesis of RC networks. It is concluded that the multivariable RC setting is ideal for the analysis of the periodic Toda lattice.

Mathematics and statistics research department. Progress report, period ending June 30, 1981

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

Lever, W.E.; Kane, V.E.; Scott, D.S.

1981-09-01

This report is the twenty-fourth in the series of progress reports of the Mathematics and Statistics Research Department of the Computer Sciences Division, Union Carbide Corporation - Nuclear Division (UCC-ND). Part A records research progress in biometrics research, materials science applications, model evaluation, moving boundary problems, multivariate analysis, numerical linear algebra, risk analysis, and complementary areas. Collaboration and consulting with others throughout the UCC-ND complex are recorded in Part B. Included are sections on biology and health sciences, chemistry, energy, engineering, environmental sciences, health and safety research, materials sciences, safeguards, surveys, and uranium resource evaluation. Part C summarizes the variousmore » educational activities in which the staff was engaged. Part D lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

Risk of Postoperative Complications Among Inflammatory Bowel Disease Patients Treated Preoperatively With Vedolizumab.

PubMed

Yamada, Akihiro; Komaki, Yuga; Patel, Nayan; Komaki, Fukiko; Aelvoet, Arthur S; Tran, Anthony L; Pekow, Joel; Dalal, Sushila; Cohen, Russell D; Cannon, Lisa; Umanskiy, Konstantin; Smith, Radhika; Hurst, Roger; Hyman, Neil; Rubin, David T; Sakuraba, Atsushi

2017-09-01

Vedolizumab is increasingly used to treat patients with ulcerative colitis (UC) and Crohn's disease (CD), however, its safety during the perioperative period remains unclear. We compared the 30-day postoperative complications among patients treated preoperatively with vedolizumab, anti-tumor necrosis factor (TNF)-α agents or non-biological therapy. The retrospective study cohort was comprised of patients receiving vedolizumab, anti-TNF-α agents or non-biological therapy within 4 weeks of surgery. The rates of 30-day postoperative complications were compared between groups using univariate and multivariate analysis. Propensity score-matched analysis was performed to compare the outcome between groups. Among 443 patients (64 vedolizumab, 129 anti-TNF-α agents, and 250 non-biological therapy), a total of 144 patients experienced postoperative complications (32%). In multivariate analysis, age >65 (odds ratio (OR) 3.56, 95% confidence interval (CI) 1.30-9.76) and low-albumin (OR 2.26, 95% CI 1.28-4.00) were associated with increased risk of 30-day postoperative complications. For infectious complications, steroid use (OR 3.67, 95% CI 1.57-8.57, P=0.003) and low hemoglobin (OR 3.03, 95% CI 1.32-6.96, P=0.009) were associated with increased risk in multivariate analysis. Propensity score matched analysis demonstrated that the risks of postoperative complications were not different among patients preoperatively receiving vedolizumab, anti-TNF-α agents or non-biological therapy (UC, P=0.40; CD, P=0.35). In the present study, preoperative vedolizumab exposure did not affect the risk of 30-day postoperative complications in UC and CD. Further, larger studies are required to confirm our findings.

Multi-hazard Assessment and Scenario Toolbox (MhAST): A Framework for Analyzing Compounding Effects of Multiple Hazards

NASA Astrophysics Data System (ADS)

Sadegh, M.; Moftakhari, H.; AghaKouchak, A.

2017-12-01

Many natural hazards are driven by multiple forcing variables, and concurrence/consecutive extreme events significantly increases risk of infrastructure/system failure. It is a common practice to use univariate analysis based upon a perceived ruling driver to estimate design quantiles and/or return periods of extreme events. A multivariate analysis, however, permits modeling simultaneous occurrence of multiple forcing variables. In this presentation, we introduce the Multi-hazard Assessment and Scenario Toolbox (MhAST) that comprehensively analyzes marginal and joint probability distributions of natural hazards. MhAST also offers a wide range of scenarios of return period and design levels and their likelihoods. Contribution of this study is four-fold: 1. comprehensive analysis of marginal and joint probability of multiple drivers through 17 continuous distributions and 26 copulas, 2. multiple scenario analysis of concurrent extremes based upon the most likely joint occurrence, one ruling variable, and weighted random sampling of joint occurrences with similar exceedance probabilities, 3. weighted average scenario analysis based on a expected event, and 4. uncertainty analysis of the most likely joint occurrence scenario using a Bayesian framework.

Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series.

PubMed

Faes, Luca; Nollo, Giandomenico; Porta, Alberto

2012-03-01

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respiration variability series measured from healthy humans in the resting supine position and in the upright position after head-up tilt. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Wavelet analysis for the study of the relations among soil radon anomalies, volcanic and seismic events: the case of Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Ferrera, Elisabetta; Giammanco, Salvatore; Cannata, Andrea; Montalto, Placido

2013-04-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol® probe located on the upper NE flank of Mt. Etna volcano, close either to the Piano Provenzana fault or to the NE-Rift. Seismic and volcanological data have been analyzed together with radon data. We also analyzed air and soil temperature, barometric pressure, snow and rain fall data. In order to find possible correlations among the above parameters, and hence to reveal possible anomalies in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-days time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-days moving averages showed that, similar to multivariate linear regression analysis, the summer period is characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allows to study the relations among different signals either in time or frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Our work suggests that in order to make an accurate analysis of the relations among distinct signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be very effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review

PubMed Central

Xiao, Li; Wei, Hui; Himmel, Michael E.; Jameel, Hasan; Kelley, Stephen S.

2014-01-01

Optimizing the use of lignocellulosic biomass as the feedstock for renewable energy production is currently being developed globally. Biomass is a complex mixture of cellulose, hemicelluloses, lignins, extractives, and proteins; as well as inorganic salts. Cell wall compositional analysis for biomass characterization is laborious and time consuming. In order to characterize biomass fast and efficiently, several high through-put technologies have been successfully developed. Among them, near infrared spectroscopy (NIR) and pyrolysis-molecular beam mass spectrometry (Py-mbms) are complementary tools and capable of evaluating a large number of raw or modified biomass in a short period of time. NIR shows vibrations associated with specific chemical structures whereas Py-mbms depicts the full range of fragments from the decomposition of biomass. Both NIR vibrations and Py-mbms peaks are assigned to possible chemical functional groups and molecular structures. They provide complementary information of chemical insight of biomaterials. However, it is challenging to interpret the informative results because of the large amount of overlapping bands or decomposition fragments contained in the spectra. In order to improve the efficiency of data analysis, multivariate analysis tools have been adapted to define the significant correlations among data variables, so that the large number of bands/peaks could be replaced by a small number of reconstructed variables representing original variation. Reconstructed data variables are used for sample comparison (principal component analysis) and for building regression models (partial least square regression) between biomass chemical structures and properties of interests. In this review, the important biomass chemical structures measured by NIR and Py-mbms are summarized. The advantages and disadvantages of conventional data analysis methods and multivariate data analysis methods are introduced, compared and evaluated. This review aims to serve as a guide for choosing the most effective data analysis methods for NIR and Py-mbms characterization of biomass. PMID:25147552

Socio-demographic and clinical profiles of paranoid and nonparanoid schizophrenia: a prospective, multicenter study in China.

PubMed

Xiang, Yu-Tao; Wang, Chuan-Yue; Chiu, Helen F K; Weng, Yong-Zhen; Bo, Qi-Jing; Chan, Sandra S M; Lee, Edwin H M; Ungvari, Gabor S

2011-07-01

This study aimed to explore the socio-demographic and clinical characteristics of paranoid and nonparanoid subtypes of schizophrenia. In a multicenter, randomized, controlled, longitudinal study, 374 clinically stable schizophrenia patients were interviewed at entry with standardized assessment instruments and followed for 12-26 months. In the multivariate analysis, male sex, married marital status, urban abode, and more frequent relapse over the study period were independently associated with paranoid schizophrenia. The socio-demographic and clinical characteristics of Chinese patients with the paranoid subtype of schizophrenia are different from those of their Caucasian counterparts who are more likely to be women and have a better outcome. © 2010 Wiley Periodicals, Inc.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Current trends and outcomes of breast reconstruction following nipple-sparing mastectomy: results from a national multicentric registry with 1006 cases over a 6-year period.

PubMed

Casella, Donato; Calabrese, Claudio; Orzalesi, Lorenzo; Gaggelli, Ilaria; Cecconi, Lorenzo; Santi, Caterina; Murgo, Roberto; Rinaldi, Stefano; Regolo, Lea; Amanti, Claudio; Roncella, Manuela; Serra, Margherita; Meneghini, Graziano; Bortolini, Massimiliano; Altomare, Vittorio; Cabula, Carlo; Catalano, Francesca; Cirilli, Alfredo; Caruso, Francesco; Lazzaretti, Maria Grazia; Meattini, Icro; Livi, Lorenzo; Cataliotti, Luigi; Bernini, Marco

2017-05-01

Reconstruction options following nipple-sparing mastectomy (NSM) are diverse and not yet investigated with level IA evidence. The analysis of surgical and oncological outcomes of NSM from the Italian National Registry shows its safety and wide acceptance both for prophylactic and therapeutic cases. A further in-depth analysis of the reconstructive approaches with their trend over time and their failures is the aim of this study. Data extraction from the National Database was performed restricting cases to the 2009-2014 period. Different reconstruction procedures were analyzed in terms of their distribution over time and with respect to specific indications. A 1-year minimum follow-up was conducted to assess reconstructive unsuccessful events. Univariate and multivariate analyses were performed to investigate the causes of both prosthetic and autologous failures. 913 patients, for a total of 1006 procedures, are included in the analysis. A prosthetic only reconstruction is accomplished in 92.2 % of cases, while pure autologous tissues are employed in 4.2 % and a hybrid (prosthetic plus autologous) in 3.6 %. Direct-to-implant (DTI) reaches 48.7 % of all reconstructions in the year 2014. Prophylactic NSMs have a DTI reconstruction in 35.6 % of cases and an autologous tissue flap in 12.9 % of cases. Failures are 2.7 % overall: 0 % in pure autologous flaps and 9.1 % in hybrid cases. Significant risk factors for failures are diabetes and the previous radiation therapy on the operated breast. Reconstruction following NSM is mostly prosthetic in Italy, with DTI gaining large acceptance over time. Failures are low and occurring in diabetic and irradiated patients at the multivariate analysis.

A matched-pair study comparing whole-brain irradiation alone to radiosurgery or fractionated stereotactic radiotherapy alone in patients irradiated for up to three brain metastases.

PubMed

Rades, Dirk; Janssen, Stefan; Dziggel, Liesa; Blanck, Oliver; Bajrovic, Amira; Veninga, Theo; Schild, Steven E

2017-01-06

This matched-pair study was initiated to validate the results of a retrospective study of 186 patients published in 2007 that compared whole-brain irradiation (WBI) alone and radiosurgery (RS) alone for up to three brain metastases. One-hundred-fifty-two patients receiving WBI alone for up to three brain metastases were matched with 152 patients treated with RS of fractionated stereotactic radiotherapy (FSRT) alone 1:1 for each of eight factors (age, gender, Eastern Oncology Cooperative Group (ECOG)-performance score, nature of tumor, brain metastases number, extra-cerebral spread, period from cancer detection to irradiation of brain metastases, and recursive partitioning analysis (RPA)-class. Groups were analyzed regarding intracerebral control (IC) and overall survival (OS). On univariate analysis of IC, type of irradiation did not significantly affect outcomes (p = 0.84). On Cox regression, brain metastases number (p < 0.001), nature of tumor (p < 0.001) and period from cancer detection to irradiation of brain metastases (p = 0.013) were significantly associated with IC. On univariate analysis of OS, type of irradiation showed no significant association with outcomes (p = 0.63). On multivariate analyses, OS was significantly associated with ECOG performance score (p = 0.011), nature of tumor (p = 0.035), brain metastases number (p = 0.048), extra-cerebral spread (p = 0.002) and RPA-class (p < 0.001). In this matched-pair study, RS/FSRT alone was not superior to WBI alone regarding IC and OS. These results can be considered a revision of the findings from our retrospective previous study without matched-pair design, where RS alone resulted in significantly better IC than WBI alone on multivariate analysis.

Lifetime use of illicit drugs and associated factors among Brazilian schoolchildren, National Adolescent School-based Health Survey (PeNSE 2012).

PubMed

Horta, Rogério Lessa; Horta, Bernardo Lessa; da Costa, Andre Wallace Nery; do Prado, Rogério Ruscitto; Oliveira-Campos, Maryane; Malta, Deborah Carvalho

2014-01-01

This study aimed at describing the prevalence of illicit drug use among 9th grade students in the morning period of public and private schools in Brazil, and assessing associated factors. The Brazilian survey PeNSE (National Adolescent School-based Health Survey) 2012 evaluated a representative sample of 9th grade students in the morning period, in Brazil and its five regions. The use of illicit drugs at least once in life was assessed for the most commonly used drugs, such as marijuana, cocaine, crack, solvent-based glue, general ether-based inhalants, ecstasy and oxy. Data were subjected to descriptive analysis, and Pearson's χ² test and logistic regression was used in the multivariate analysis. The use of illicit drugs at least once in life was reported by 7.3% (95%CI 5.3 - 9.4) of the respondents. Logistic regression was used for multivariate analysis and the evidences suggest that illicit drug use is associated to social conditions of greater consumption power, the use of alcohol and tobacco, behaviors related to socialization, such as having friends or sexual activity, and also the perception of loneliness, loose contact between school and parents and experiences of abuse in the family environment. The outcome was inversely associated with close contact with parents and parental supervision. In addition to the association with the processes of socialization and consumption, the influence of family and school is expressed in a particularly protective manner in different records of direct supervision and care.

Evaluation of functional outcome of the floating knee injury using multivariate analysis.

PubMed

Yokoyama, Kazuhiko; Tsukamoto, Tatsuro; Aoki, Shinichi; Wakita, Ryuji; Uchino, Masataka; Noumi, Takashi; Fukushima, Nobuaki; Itoman, Moritoshi

2002-11-01

The objective of this study is to evaluate significant contributing factors affecting the functional prognosis of floating knee injuries using multivariate analysis. A total of 68 floating knee injuries (67 patients) were treated at Kitasato University Hospital from 1986 to 1999. Both the femoral fractures and the tibial fractures were managed surgically by various methods. The functional results of these injuries were evaluated using the grading system of Karlström and Olerud. Follow-up periods ranged from 2 to 19 years (mean 50.2 months) after the original injury. We defined satisfactory (S) outcomes as those cases with excellent or good results and unsatisfactory (US) outcomes as those cases with acceptable or poor results. Logistic regression analysis was used as a multivariate analysis, and the dependent variables were defined as a satisfactory outcome or as an unsatisfactory outcome. The explanatory variables were predicting factors influencing the functional outcome such as age at trauma, gender, severity of soft-tissue injury in the femur and the tibia, AO fracture grade in the femur and the tibia, Fraser type (type I or type II), Injury Severity Score (ISS), and fixation time after injury (less than 1 week or more than 1 week) in the femur and the tibia. The final functional results were as follows: 25 cases had excellent results, 15 cases good results, 16 cases acceptable results, and 12 cases poor results. The predictive logistic regression equation was as follows: Log 1-p/p = 3.12-1.52 x Fraser type - 1.65 x severity of soft-tissue injury in the tibia - 1.31 x fixation time after injury in the tibia - 0.821 x AO fracture grade in the tibia + 1.025 x fixation time after injury in the femur - 0.687 x AO fracture grade in the femur ( p=0.01). Among the variables, Fraser type and the severity of soft-tissue injury in the tibia were significantly related to the final result. The multivariate analysis showed that both the involvement of the knee joint and the severity grade of soft-tissue injury in the tibia represented significant risk factors of poor outcome in floating knee injuries in this study.

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

Evaluation and simplification of the occupational slip, trip and fall risk-assessment test

PubMed Central

NAKAMURA, Takehiro; OYAMA, Ichiro; FUJINO, Yoshihisa; KUBO, Tatsuhiko; KADOWAKI, Koji; KUNIMOTO, Masamizu; ODOI, Haruka; TABATA, Hidetoshi; MATSUDA, Shinya

2016-01-01

Objective: The purpose of this investigation is to evaluate the efficacy of the occupational slip, trip and fall (STF) risk assessment test developed by the Japan Industrial Safety and Health Association (JISHA). We further intended to simplify the test to improve efficiency. Methods: A previous cohort study was performed using 540 employees aged ≥50 years who took the JISHA’s STF risk assessment test. We conducted multivariate analysis using these previous results as baseline values and answers to questionnaire items or score on physical fitness tests as variables. The screening efficiency of each model was evaluated based on the obtained receiver operating characteristic (ROC) curve. Results: The area under the ROC obtained in multivariate analysis was 0.79 when using all items. Six of the 25 questionnaire items were selected for stepwise analysis, giving an area under the ROC curve of 0.77. Conclusion: Based on the results of follow-up performed one year after the initial examination, we successfully determined the usefulness of the STF risk assessment test. Administering a questionnaire alone is sufficient for screening subjects at risk of STF during the subsequent one-year period. PMID:27021057

[Risk indicators associated with the consumption of illicit drugs by schoolchildren in a community in the south of Brazil].

PubMed

Backes, Dirce Stein; Zanatta, Fabrício Batistin; Costenaro, Regina Santini; Rangel, Rosiane Filipin; Vidal, Janice; Kruel, Cristina Saling; de Mattos, Karen Mallo

2014-03-01

This study sought to identify the risk indicators associated with the consumption of illicit drugs by schoolchildren in public schools in a community in the south of Brazil. This is a non-experimental cross-sectional study conducted with 535 students of primary schoolchildren from six public schools. Data were collected using a questionnaire between October 2011 and March 2012. The results were presented by simple and relative distribution of frequency and odds ratio (OR) and the 95% reliability intervals were calculated to verify the association between the dependent and independent variables. Multivariate analysis was also performed using the question "have you ever used illicit drugs?" Univariate analysis revealed an association between family income, color, period in which the child studied, failure to pass annual tests, use of methods of prevention, smoking habit and knowing someone who uses drugs with the fact of having experimented with the use of illicit drugs. After multivariate analysis, the smoking habit was the only indicator significantly associated with the question of having made use of illicit drugs. The results indicate that the smoking habit is an important indicator of the predictive risk for the use of illicit drugs.

Summer microhabitat use by adult and young-of-year snail darters (Percina tanasi) in two rivers

USGS Publications Warehouse

Ashton, M.J.; Layzer, J.B.

2010-01-01

We characterised microhabitat availability and use by adult and young-of-year (YOY) snail darters (Percina tanasiEtnier 1976) while snorkelling in the French Broad and Hiwassee rivers, TN, USA. Both age groups of snail darters disproportionately used most microhabitat variables compared to their availability. Snail darters primarily occupied moderately deep, swift water over gravel substrates with little macrophyte coverage and no silt. Univariate comparisons indicated that adult and YOY darters occupied different habitat, but there was no marked differences between principal components analysis plots of multivariate microhabitat use within a river. Although the availability of microhabitat variables differed between the French Broad and Hiwassee rivers, univariate means and multivariate plots illustrated that the habitats used were generally similar by age groups of snail darters between rivers. Because our observations of habitat availability and use were constrained to low flow periods and depths <1 m, the transferability of our results to higher flow periods may be limited. However, the similarity in habitat use between rivers suggests that our results can be applied to low-normal flow conditions in other streams. ?? Published 2010. This article is a US Government work and is in the public domain in the USA.

Timing of deep vein thrombosis formation after aneurysmal subarachnoid hemorrhage

PubMed Central

Liang, Conrad W.; Su, Kimmy; Liu, Jesse J.; Dogan, Aclan; Hinson, Holly E.

2015-01-01

OBJECT Deep vein thrombosis (DVT) is a common complication of aneurysmal subarachnoid hemorrhage (aSAH). The time period of greatest risk for developing DVT after aSAH is not currently known. aSAH induces a prothrombotic state, which may contribute to DVT formation. Using repeated ultrasound screening, the hypothesis that patients would be at greatest risk for developing DVT in the subacute post-rupture period was tested. METHODS One hundred ninety-eight patients with aSAH admitted to the Oregon Health & Science University Neurosciences Intensive Care Unit between April 2008 and March 2012 were included in a retrospective analysis. Ultrasound screening was performed every 5.2 ± 3.3 days between admission and discharge. The chi-square test was used to compare DVT incidence during different time periods of interest. Patient baseline characteristics as well as stroke severity and hospital complications were evaluated in univariate and multivariate analyses. RESULTS Forty-two (21%) of 198 patients were diagnosed with DVT, and 3 (2%) of 198 patients were symptomatic. Twenty-nine (69%) of the 42 cases of DVT were first detected between Days 3 and 14, compared with 3 cases (7%) detected between Days 0 and 3 and 10 cases (24%) detected after Day 14 (p < 0.05). The postrupture 5-day window of highest risk for DVT development was between Days 5 and 9 (40%, p < 0.05). In the multivariate analysis, length of hospital stay and use of mechanical prophylaxis alone were significantly associated with DVT formation. CONCLUSIONS DVT formation most commonly occurs in the first 2 weeks following aSAH, with detection in this cohort peaking between Days 5 and 9. Chemoprophylaxis is associated with a significantly lower incidence of DVT. PMID:26162047

Trends in Pulmonary Hypertension Over a Period of 30 Years: Experience From a Single Referral Centre.

PubMed

Quezada Loaiza, Carlos Andrés; Velázquez Martín, María Teresa; Jiménez López-Guarch, Carmen; Ruiz Cano, María José; Navas Tejedor, Paula; Carreira, Patricia Esmeralda; Flox Camacho, Ángela; de Pablo Gafas, Alicia; Delgado Jiménez, Juan Francisco; Gómez Sánchez, Miguel Ángel; Escribano Subías, Pilar

2017-11-01

Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary vascular resistance, right ventricular dysfunction and death. Despite scientific advances, is still associated with high morbidity and mortality. The aim is to describe the clinical approach and determine the prognostic factors of patients with PAH treated in a national reference center over 30 years. Three hundred and seventy nine consecutive patients with PAH (January 1984 to December 2014) were studied. Were divided into 3 periods of time: before 2004, 2004-2009 and 2010-2014. Prognostic factors (multivariate analysis) were analyzed for clinical deterioration. Median age was 44 years (68.6% women), functional class III-IV: 72%. An increase was observed in more complex etiologies in the last period of time: Pulmonary venooclusive disease and portopulmonary hypertension. Upfront combination therapy significantly increased (5% before 2004 vs 27% after 2010; P < .05). Multivariate analysis showed prognostic significance in age, sex, etiology and combined clinical variables as they are independent predictors of clinical deterioration (P < .05). Survival free from death or transplantation for the 1st, 3rd and 5th year was 92.2%, 80.6% and 68.5% respectively. The median survival was 9 years (95% confidence interval, 7.532-11.959) CONCLUSIONS: The PAH is a heterogeneous and complex disease, the median survival free from death or transplantation in our series is 9 years after diagnosis. The structure of a multidisciplinary unit PAH must adapt quickly to changes that occur over time incorporating new diagnostic and therapeutic techniques. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Improvement of the Management of Infants, Children and Adults with a Molecular Diagnosis of Enterovirus Meningitis during Two Observational Study Periods

PubMed Central

Archimbaud, Christine; Ouchchane, Lemlih; Mirand, Audrey; Chambon, Martine; Demeocq, François; Labbé, André; Laurichesse, Henri; Schmidt, Jeannot; Clavelou, Pierre; Aumaître, Olivier; Regagnon, Christel; Bailly, Jean-Luc; Henquell, Cécile; Peigue-Lafeuille, Hélène

2013-01-01

Enteroviruses (EVs) are a major cause of aseptic meningitis, and RNA detection using molecular assay is the gold standard diagnostic test. The aim of this study was to assess the impact of an EV positive diagnosis on the clinical management of patients admitted for meningitis over the course of two observational study periods (2005 and 2008–09) in the same clinical departments. We further investigated in multivariate analysis various factors possibly associated with hospital length of stay (LOS) in all age groups (infants, children, and adults). The results showed an overall improvement in the management of patients (n = 142) between the study periods, resulting in a significantly shorter hospital LOS for adults and children, and a shorter duration of antibiotic use for adults and infants. In multivariate analysis, we observed that the time from molecular test results to discharge of patients and the median duration of antibiotic treatment were associated with an increase in LOS in all age groups. In addition, among adults, the turnaround time of the molecular assay was significantly correlated with LOS. The use of CT scan in children and hospital admission outside the peak of EV prevalence in infants tended to increase LOS. In conclusion, the shorter length of stay of patients with meningitis in this study was due to various factors including the rapidity of the EV molecular test (particularly in adults), greater physician responsiveness after a positive result (in adults and children), and greater experience on the part of physicians in handling EV meningitis, as evidenced by the shorter duration of antibiotic use in adults and infants. PMID:23874676

Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques.

PubMed

Li, Siyue; Zhang, Quanfa

2010-04-15

A data matrix (4032 observations), obtained during a 2-year monitoring period (2005-2006) from 42 sites in the upper Han River is subjected to various multivariate statistical techniques including cluster analysis, principal component analysis (PCA), factor analysis (FA), correlation analysis and analysis of variance to determine the spatial characterization of dissolved trace elements and heavy metals. Our results indicate that waters in the upper Han River are primarily polluted by Al, As, Cd, Pb, Sb and Se, and the potential pollutants include Ba, Cr, Hg, Mn and Ni. Spatial distribution of trace metals indicates the polluted sections mainly concentrate in the Danjiang, Danjiangkou Reservoir catchment and Hanzhong Plain, and the most contaminated river is in the Hanzhong Plain. Q-model clustering depends on geographical location of sampling sites and groups the 42 sampling sites into four clusters, i.e., Danjiang, Danjiangkou Reservoir region (lower catchment), upper catchment and one river in headwaters pertaining to water quality. The headwaters, Danjiang and lower catchment, and upper catchment correspond to very high polluted, moderate polluted and relatively low polluted regions, respectively. Additionally, PCA/FA and correlation analysis demonstrates that Al, Cd, Mn, Ni, Fe, Si and Sr are controlled by natural sources, whereas the other metals appear to be primarily controlled by anthropogenic origins though geogenic source contributing to them. 2009 Elsevier B.V. All rights reserved.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Job insecurity and risk of diabetes: a meta-analysis of individual participant data.

PubMed

Ferrie, Jane E; Virtanen, Marianna; Jokela, Markus; Madsen, Ida E H; Heikkilä, Katriina; Alfredsson, Lars; Batty, G David; Bjorner, Jakob B; Borritz, Marianne; Burr, Hermann; Dragano, Nico; Elovainio, Marko; Fransson, Eleonor I; Knutsson, Anders; Koskenvuo, Markku; Koskinen, Aki; Kouvonen, Anne; Kumari, Meena; Nielsen, Martin L; Nordin, Maria; Oksanen, Tuula; Pahkin, Krista; Pejtersen, Jan H; Pentti, Jaana; Salo, Paula; Shipley, Martin J; Suominen, Sakari B; Tabák, Adam; Theorell, Töres; Väänänen, Ari; Vahtera, Jussi; Westerholm, Peter J M; Westerlund, Hugo; Rugulies, Reiner; Nyberg, Solja T; Kivimäki, Mika

2016-12-06

Job insecurity has been associated with certain health outcomes. We examined the role of job insecurity as a risk factor for incident diabetes. We used individual participant data from 8 cohort studies identified in 2 open-access data archives and 11 cohort studies participating in the Individual-Participant-Data Meta-analysis in Working Populations Consortium. We calculated study-specific estimates of the association between job insecurity reported at baseline and incident diabetes over the follow-up period. We pooled the estimates in a meta-analysis to produce a summary risk estimate. The 19 studies involved 140 825 participants from Australia, Europe and the United States, with a mean follow-up of 9.4 years and 3954 incident cases of diabetes. In the preliminary analysis adjusted for age and sex, high job insecurity was associated with an increased risk of incident diabetes compared with low job insecurity (adjusted odds ratio [OR] 1.19, 95% confidence interval [CI] 1.09-1.30). In the multivariable-adjusted analysis restricted to 15 studies with baseline data for all covariates (age, sex, socioeconomic status, obesity, physical activity, alcohol and smoking), the association was slightly attenuated (adjusted OR 1.12, 95% CI 1.01-1.24). Heterogeneity between the studies was low to moderate (age- and sex-adjusted model: I 2 = 24%, p = 0.2; multivariable-adjusted model: I 2 = 27%, p = 0.2). In the multivariable-adjusted analysis restricted to high-quality studies, in which the diabetes diagnosis was ascertained from electronic medical records or clinical examination, the association was similar to that in the main analysis (adjusted OR 1.19, 95% CI 1.04-1.35). Our findings suggest that self-reported job insecurity is associated with a modest increased risk of incident diabetes. Health care personnel should be aware of this association among workers reporting job insecurity. © 2016 Canadian Medical Association or its licensors.

[Factors affecting how long exclusive breastfeeding lasts].

PubMed

Rodríguez-García, Jesús; Acosta-Ramírez, Naydú

2008-01-01

Identifying factors associated with exclusive breastfeeding by poor urban women in Colombia . A random sample of women living in poor neighborhoods from four Colombian cities ( Cali , Cartagena , Medellín and Ibague ) was made (survey method), using a cross-sectional design; survival analysis techniques were applied. Bivariate analysis identified hospital bottle use, the women's marital status, and relationship with the head of household as having had a significant effect on the duration of exclusive breastfeeding. Multivariate analysis identified the non-use of bottles in hospital as favoring a longer breast feeding period. Reducing hospital bottle use is readily achievable by health system action; increasing the time mothers spend with their infants is more difficult. A relevant finding was that more mothers were unaware of breastfeeding's maternal benefits than those who were unaware of its benefits for the baby. If mothers were made more aware of the maternal benefits, an increasing number might insist on being the main caregiver and take care of their children for longer periods of time.

Prognostic molecular markers with no impact on decision-making: the paradox of gliomas based on a prospective study.

PubMed

Wager, M; Menei, P; Guilhot, J; Levillain, P; Michalak, S; Bataille, B; Blanc, J-L; Lapierre, F; Rigoard, P; Milin, S; Duthe, F; Bonneau, D; Larsen, C-J; Karayan-Tapon, L

2008-06-03

This study assessed the prognostic value of several markers involved in gliomagenesis, and compared it with that of other clinical and imaging markers already used. Four-hundred and sixteen adult patients with newly diagnosed glioma were included over a 3-year period and tumour suppressor genes, oncogenes, MGMT and hTERT expressions, losses of heterozygosity, as well as relevant clinical and imaging information were recorded. This prospective study was based on all adult gliomas. Analyses were performed on patient groups selected according to World Health Organization histoprognostic criteria and on the entire cohort. The endpoint was overall survival, estimated by the Kaplan-Meier method. Univariate analysis was followed by multivariate analysis according to a Cox model. p14(ARF), p16(INK4A) and PTEN expressions, and 10p 10q23, 10q26 and 13q LOH for the entire cohort, hTERT expression for high-grade tumours, EGFR for glioblastomas, 10q26 LOH for grade III tumours and anaplastic oligodendrogliomas were found to be correlated with overall survival on univariate analysis and age and grade on multivariate analysis only. This study confirms the prognostic value of several markers. However, the scattering of the values explained by tumour heterogeneity prevents their use in individual decision-making.

Factors affecting survival outcomes of patients with non-metastatic Ewing's sarcoma family tumors in the spine: a retrospective analysis of 63 patients in a single center.

PubMed

Wan, Wei; Lou, Yan; Hu, Zhiqi; Wang, Ting; Li, Jinsong; Tang, Yu; Wu, Zhipeng; Xu, Leqin; Yang, Xinghai; Song, Dianwen; Xiao, Jianru

2017-01-01

Little information has been published in the literature regarding survival outcomes of patients with Ewing's sarcoma family tumors (ESFTs) of the spine. The purpose of this study is to explore factors that may affect the prognosis of patients with non-metastatic spinal ESFTs. A retrospective analysis of survival outcomes was performed in patients with non-metastatic spinal ESFTs. Univariate and multivariate analyses were employed to identify prognostic factors for recurrence and survival. Recurrence-free survival (RFS) and overall survival (OS) were defined as the date of surgery to the date of local relapse and death. Kaplan-Meier methods were applied to estimate RFS and OS. Log-rank test was used to analyze single factors for RFS and OS. Factors with p values ≤0.1 were subjected to multivariate analysis. A total of 63 patients with non-metastatic spinal ESFTs were included in this study. The mean follow-up period was 35.1 months (range 1-155). Postoperative recurrence was detected in 25 patients, and distant metastasis and death occurred in 22 and 36 patients respectively. The result of multivariate analysis suggested that age older than 25 years and neoadjuvant chemotherapy were favorable independent prognostic factors for RFS and OS. In addition, total en-bloc resection, postoperative chemotherapy, radiotherapy and non-distant metastasis were favorable independent prognostic factors for OS. Age older than 25 years and neoadjuvant chemotherapy are favorable prognostic factors for both RFS and OS. In addition, total en-bloc resection, postoperative chemotherapy, radiotherapy and non-distant metastasis are closely associated with favorable survival.

Influence of microclimatic ammonia levels on productive performance of different broilers' breeds estimated with univariate and multivariate approaches.

PubMed

Soliman, Essam S; Moawed, Sherif A; Hassan, Rania A

2017-08-01

Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=-0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.

Influence of microclimatic ammonia levels on productive performance of different broilers’ breeds estimated with univariate and multivariate approaches

PubMed Central

Soliman, Essam S.; Moawed, Sherif A.; Hassan, Rania A.

2017-01-01

Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people’s health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Results: Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=−0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. Conclusion: The study revealed that broiler’s growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers’ growth performance parameters data using multivariate discriminant function analysis. PMID:28919677

Progress in multirate digital control system design

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1991-01-01

A new methodology for multirate sampled-data control design based on a new generalized control law structure, two new parameter-optimization-based control law synthesis methods, and a new singular-value-based robustness analysis method are described. The control law structure can represent multirate sampled-data control laws of arbitrary structure and dynamic order, with arbitrarily prescribed sampling rates for all sensors and update rates for all processor states and actuators. The two control law synthesis methods employ numerical optimization to determine values for the control law parameters. The robustness analysis method is based on the multivariable Nyquist criterion applied to the loop transfer function for the sampling period equal to the period of repetition of the system's complete sampling/update schedule. The complete methodology is demonstrated by application to the design of a combination yaw damper and modal suppression system for a commercial aircraft.

Summer weather characteristics and periodicity observed over the period 1888-2013 in the region of Belgrade, Serbia

NASA Astrophysics Data System (ADS)

Vujović, Dragana; Todorović, Nedeljko; Paskota, Mira

2018-04-01

With the goal of finding summer climate patterns in the region of Belgrade (Serbia) over the period 1888-2013, different techniques of multivariate statistical analysis were used in order to analyze the simultaneous changes of a number of climatologic parameters. An increasing trend of the mean daily minimum temperature was detected. In the recent decades (1960-2013), this increase was much more pronounced. The number of days with the daily minimum temperature greater or equal to 20 °C also increased significantly. Precipitation had no statistically significant trend. Spectral analysis showed a repetitive nature of the climatologic parameters which had periods that roughly can be classified into three groups, with the durations of the following: (1) 6 to 7 years, (2) 10 to 18 years, and (3) 21, 31, and 41 years. The temperature variables mainly had one period of repetitiveness of 5 to 7 years. Among other variables, the correlations of regional fluctuations of the temperature and precipitation and atmospheric circulation indices were analyzed. The North Atlantic oscillation index had the same periodicity as that of the precipitation, and it was not correlated to the temperature variables. Atlantic multidecadal oscillation index correlated well to the summer mean daily minimum and summer mean temperatures. The underlying structure of the data was analyzed by principal component analysis, which detected the following four easily interpreted dimensions: More sunshine-Higher temperature, Precipitation, Extreme heats, and Changeable summer.

Multivariate analysis of infant death in England and Wales in 2005-06, with focus on socio-economic status and deprivation.

PubMed

Oakley, Laura; Maconochie, Noreen; Doyle, Pat; Dattani, Nirupa; Moser, Kath

2009-01-01

Current health inequality targets include the goal of reducing the differential in infant mortality between social groups. This article reports on a multivariate analysis of risk factors for infant mortality, with specific focus on deprivation and socio-economic status. Data on all singleton live births in England and Wales in 2005-06 were used, and deprivation quintile (Carstairs index) was assigned to each birth using postcode at birth registration. Deprivation had a strong independent effect on infant mortality, risk of death tending to increase with increasing levels of deprivation. The strength of this relationship depended, however, on whether the babies were low birthweight, preterm or small-for-gestational-age. Trends of increasing mortality risk with increasing deprivation were strongest in the postneonatal period. Uniquely, this article reports the number and proportion of all infant deaths which would potentially be avoided if all levels of deprivation were reduced to that of the least deprived group. It estimates that one quarter of all infant deaths would potentially be avoided if deprivation levels were reduced in this way.

Fractionation of Palliative Radiation Therapy for Bone Metastases in Ontario: Do Practice Guidelines Guide Practice?

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

Ashworth, Allison; Cancer Center of Southeastern Ontario, Kingston, Ontario; Kong, Weidong

Purpose: To evaluate the effect of a provincial practice guideline on the fractionation of palliative radiation therapy for bone metastases (PRT.B) in Ontario. Methods and Materials: The present retrospective study used electronic treatment records linked to Ontario's population-based cancer registry. Hierarchical multivariable regression analysis was used to evaluate temporal trends in the use of single fractions (SFs), controlling for patient-related factors associated with the use of SFs. Results: From 1984 to 2012, 43.9% of 161,835 courses of PRT.B were administered as SFs. The percentage of SF courses was greater for older patients (age <50 years, 39.8% vs age >80 years, 52.5%), thosemore » with a shorter life expectancy (survival >12 months, 36.9% vs < 1 month, 53.6%), and those who lived farther from a radiation therapy center (<10 km, 42.1% vs > 50 km, 47.3%). The percentage of SFs to spinal fields was lower than that to other skeletal sites (31.5% vs 57.1%). The percentage of SFs varied among the cancer centers (range, 26.0%-67.8%). These differences were all highly significant in the multivariable analysis (P<.0001). In 2004, Cancer Care Ontario released a practice guideline endorsing the use of SFs for uncomplicated bone metastases. The rate of use of SFs increased from 42.3% in the pre-guideline period (1999-2003) to 52.6% in the immediate post-guideline period (2004-2007). However, it subsequently decreased again to 44.0% (2009-2012). These temporal trends were significant after controlling for patient-related factors in the multivariable analysis (P<.0001). Large intercenter variations in the use of SFs persisted after publication of the guideline. Conclusions: The publication of an Ontario practice guideline endorsing the use of SF PRT.B was associated with only a transient increase in the use of SFs in Ontario and did little to reduce intercenter variations in fractionation.« less

Determining the response of sea level to atmospheric pressure forcing using TOPEX/POSEIDON data

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng; Pihos, Greg

1994-01-01

The static response of sea level to the forcing of atmospheric pressure, the so-called inverted barometer (IB) effect, is investigated using TOPEX/POSEIDON data. This response, characterized by the rise and fall of sea level to compensate for the change of atmospheric pressure at a rate of -1 cm/mbar, is not associated with any ocean currents and hence is normally treated as an error to be removed from sea level observation. Linear regression and spectral transfer function analyses are applied to sea level and pressure to examine the validity of the IB effect. In regions outside the tropics, the regression coefficient is found to be consistently close to the theoretical value except for the regions of western boundary currents, where the mesoscale variability interferes with the IB effect. The spectral transfer function shows near IB response at periods of 30 degrees is -0.84 +/- 0.29 cm/mbar (1 standard deviation). The deviation from = 1 cm /mbar is shown to be caused primarily by the effect of wind forcing on sea level, based on multivariate linear regression model involving both pressure and wind forcing. The regression coefficient for pressure resulting from the multivariate analysis is -0.96 +/- 0.32 cm/mbar. In the tropics the multivariate analysis fails because sea level in the tropics is primarily responding to remote wind forcing. However, after removing from the data the wind-forced sea level estimated by a dynamic model of the tropical Pacific, the pressure regression coefficient improves from -1.22 +/- 0.69 cm/mbar to -0.99 +/- 0.46 cm/mbar, clearly revealing an IB response. The result of the study suggests that with a proper removal of the effect of wind forcing the IB effect is valid in most of the open ocean at periods longer than 20 days and spatial scales larger than 500 km.

Preeclampsia and Long-term Renal Function in Women Who Underwent Kidney Transplantation.

PubMed

Vannevel, Valerie; Claes, Kathleen; Baud, David; Vial, Yvan; Golshayan, Delaviz; Yoon, Eugene W; Hodges, Ryan; Le Nepveu, Anne; Kerr, Peter G; Kennedy, Claire; Higgins, Mary; Resch, Elisabeth; Klaritsch, Philipp; Van Mieghem, Tim

2018-01-01

Preeclampsia often complicates pregnancies after maternal kidney transplantation. We aimed to assess whether preeclampsia is associated with kidney function decline either during the pregnancy or in the long term. We performed an international multicenter retrospective cohort study. Renal function at conception, pregnancy outcomes, and short- and long-term graft outcomes were collected for women who were pregnant after renal transplantation and had transplant and obstetric care at the participating centers. In women who had multiple pregnancies during the study period, only the last pregnancy was included. Univariate and multivariable analyses were performed. We retrieved pregnancy outcomes and long-term renal outcomes for 52 women. Chronic hypertension was present at baseline in 27%. Mean estimated glomerular filtration rate (GFR) at start of pregnancy was 52.4±17.5 mL/min/1.73 m. Mean estimated GFR at delivery was 47.6±21.6 mL/min/1.73 m, which was significantly lower than at conception (P=.03). Twenty women (38%) developed preeclampsia. In multivariable analysis, women who developed preeclampsia had a 10.7-mL/min/1.73 m higher drop in estimated GFR between conception and delivery than women who did not develop preeclampsia (P=.02). Long-term estimated GFR follow-up was obtained at a median of 5.8 years (range 1.3-27.5 years). Mean estimated GFR at last follow-up was 38±23 mL/kg/1.73 m. Seventeen women (33%) experienced graft loss over the follow-up period. Incidence of graft loss was similar in women with and without preeclampsia in their last pregnancy (30% and 34%, respectively; P=.99). In multivariable analysis, the decrease in estimated GFR between conception and last follow-up was similar in women who experienced preeclampsia during pregnancy and those who did not (difference -2.69 mL/min/1.73 m, P=.65). Preeclampsia commonly complicates pregnancies after renal transplantation but is not associated with long-term renal dysfunction or graft loss.

Association Between Treatment at High-Volume Facilities and Improved Overall Survival in Soft Tissue Sarcomas.

PubMed

Venigalla, Sriram; Nead, Kevin T; Sebro, Ronnie; Guttmann, David M; Sharma, Sonam; Simone, Charles B; Levin, William P; Wilson, Robert J; Weber, Kristy L; Shabason, Jacob E

2018-03-15

Soft tissue sarcomas (STS) are rare malignancies that require complex multidisciplinary management. Therefore, facilities with high sarcoma case volume may demonstrate superior outcomes. We hypothesized that STS treatment at high-volume (HV) facilities would be associated with improved overall survival (OS). Patients aged ≥18 years with nonmetastatic STS treated with surgery and radiation therapy at a single facility from 2004 through 2013 were identified from the National Cancer Database. Facilities were dichotomized into HV and low-volume (LV) cohorts based on total case volume over the study period. OS was assessed using multivariable Cox regression with propensity score-matching. Patterns of care were assessed using multivariable logistic regression analysis. Of 9025 total patients, 1578 (17%) and 7447 (83%) were treated at HV and LV facilities, respectively. On multivariable analysis, high educational attainment, larger tumor size, higher grade, and negative surgical margins were statistically significantly associated with treatment at HV facilities; conversely, black race and non-metropolitan residence were negative predictors of treatment at HV facilities. On propensity score-matched multivariable analysis, treatment at HV facilities versus LV facilities was associated with improved OS (hazard ratio, 0.87, 95% confidence interval, 0.80-0.95; P = .001). Older age, lack of insurance, greater comorbidity, larger tumor size, higher tumor grade, and positive surgical margins were associated with statistically significantly worse OS. In this observational cohort study using the National Cancer Database, receipt of surgery and radiation therapy at HV facilities was associated with improved OS in patients with STS. Potential sociodemographic disparities limit access to care at HV facilities for certain populations. Our findings highlight the importance of receipt of care at HV facilities for patients with STS and warrant further study into improving access to care at HV facilities. Copyright © 2017 Elsevier Inc. All rights reserved.

Two time-series analyses of the impact of antibiotic consumption and alcohol-based hand disinfection on the incidences of nosocomial methicillin-resistant Staphylococcus aureus infection and Clostridium difficile infection.

PubMed

Kaier, Klaus; Hagist, Christian; Frank, Uwe; Conrad, Andreas; Meyer, Elisabeth

2009-04-01

To determine the impact of antibiotic consumption and alcohol-based hand disinfection on the incidences of nosocomial methicillin-resistant Staphylococcus aureus (MRSA) infection and Clostridium difficile infection (CDI). Two multivariate time-series analyses were performed that used as dependent variables the monthly incidences of nosocomial MRSA infection and CDI at the Freiburg University Medical Center during the period January 2003 through October 2007. The volume of alcohol-based hand rub solution used per month was quantified in liters per 1,000 patient-days. Antibiotic consumption was calculated in terms of the number of defined daily doses per 1,000 patient-days per month. The use of alcohol-based hand rub was found to have a significant impact on the incidence of nosocomial MRSA infection (P< .001). The multivariate analysis (R2=0.66) showed that a higher volume of use of alcohol-based hand rub was associated with a lower incidence of nosocomial MRSA infection. Conversely, a higher level of consumption of selected antimicrobial agents was associated with a higher incidence of nosocomial MRSA infection. This analysis showed this relationship was the same for the use of second-generation cephalosporins (P= .023), third-generation cephalosporins (P= .05), fluoroquinolones (P= .01), and lincosamides (P= .05). The multivariate analysis (R2=0.55) showed that a higher level of consumption of third-generation cephalosporins (P= .008), fluoroquinolones (P= .084), and/or macrolides (P= .007) was associated with a higher incidence of CDI. A correlation with use of alcohol-based hand rub was not detected. In 2 multivariate time-series analyses, we were able to show the impact of hand hygiene and antibiotic use on the incidence of nosocomial MRSA infection, but we found no association between hand hygiene and incidence of CDI.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Determinants of quality of life of patients with heart failure and iron deficiency treated with ferric carboxymaltose: FAIR-HF sub-analysis.

PubMed

Gutzwiller, Florian S; Pfeil, Alena M; Comin-Colet, Josep; Ponikowski, Piotr; Filippatos, Gerasimos; Mori, Claudio; Braunhofer, Peter G; Szucs, Thomas D; Schwenkglenks, Matthias; Anker, Stefan D

2013-10-09

Heart failure (HF) is a burden to patients and health care systems. The objectives of HF treatment are to improve health related quality of life (HRQoL) and reduce mortality and morbidity. We aimed to evaluate determinants of health-related quality of life (HRQoL) in patients with iron deficiency and HF treated with intravenous (i.v.) iron substitution or placebo. A randomised, double-blind, placebo-controlled trial (n = 459) in iron-deficient chronic heart failure (CHF) patients with or without anaemia studied clinical and HRQoL benefits of i.v. iron substitution using ferric carboxymaltose (FCM) over a 24-week trial period. Multivariate analysis was carried out with various clinical variables as independent variables and HRQoL measures as dependent variables. Mean change from baseline of European Quality of Life - 5 Dimensions (EQ-5D) (value set-based) utilities (on a 0 to 100 scale) at week 24 was 8.91 (i.v. iron) and 0.68 (placebo; p < 0.01). In a multivariate analysis excluding baseline HRQoL, a higher exercise tolerance and i.v. iron substitution positively influenced HRQoL, whereas impaired renal function and a history of stroke had a negative effect. The level of HRQoL was also influenced by country of residence. When baseline HRQoL was factored in, the multivariate model remained stable. In this study, i.v. iron substitution, exercise tolerance, stroke, country of residence and renal function influenced measures of HRQoL in patients with heart failure and iron deficiency. © 2013.

Compulsive buying: Earlier illicit drug use, impulse buying, depression, and adult ADHD symptoms.

PubMed

Brook, Judith S; Zhang, Chenshu; Brook, David W; Leukefeld, Carl G

2015-08-30

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant's earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Compulsive Buying: Earlier Illicit Drug Use, Impulse Buying, Depression, and Adult ADHD Symptoms

PubMed Central

Brook, Judith S.; Zhang, Chenshu; Brook, David W.; Leukefeld, Carl G.

2015-01-01

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant’s earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. PMID:26165963

[Multivariate Adaptive Regression Splines (MARS), an alternative for the analysis of time series].

PubMed

Vanegas, Jairo; Vásquez, Fabián

Multivariate Adaptive Regression Splines (MARS) is a non-parametric modelling method that extends the linear model, incorporating nonlinearities and interactions between variables. It is a flexible tool that automates the construction of predictive models: selecting relevant variables, transforming the predictor variables, processing missing values and preventing overshooting using a self-test. It is also able to predict, taking into account structural factors that might influence the outcome variable, thereby generating hypothetical models. The end result could identify relevant cut-off points in data series. It is rarely used in health, so it is proposed as a tool for the evaluation of relevant public health indicators. For demonstrative purposes, data series regarding the mortality of children under 5 years of age in Costa Rica were used, comprising the period 1978-2008. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

Impact of Resident Rotations on Critically Ill Patient Outcomes: Results of a French Multicenter Observational Study.

PubMed

Chousterman, Benjamin G; Pirracchio, Romain; Guidet, Bertrand; Aegerter, Philippe; Mentec, Hervé

2016-01-01

The impact of resident rotation on patient outcomes in the intensive care unit (ICU) has been poorly studied. The aim of this study was to address this question using a large ICU database. We retrospectively analyzed the French CUB-REA database. French residents rotate every six months. Two periods were compared: the first (POST) and fifth (PRE) months of the rotation. The primary endpoint was ICU mortality. The secondary endpoints were the length of ICU stay (LOS), the number of organ supports, and the duration of mechanical ventilation (DMV). The impact of resident rotation was explored using multivariate regression, classification tree and random forest models. 262,772 patients were included between 1996 and 2010 in the database. The patient characteristics were similar between the PRE (n = 44,431) and POST (n = 49,979) periods. Multivariate analysis did not reveal any impact of resident rotation on ICU mortality (OR = 1.01, 95% CI = 0.94; 1.07, p = 0.91). Based on the classification trees, the SAPS II and the number of organ failures were the strongest predictors of ICU mortality. In the less severe patients (SAPS II<24), the POST period was associated with increased mortality (OR = 1.65, 95%CI = 1.17-2.33, p = 0.004). After adjustment, no significant association was observed between the rotation period and the LOS, the number of organ supports, or the DMV. Resident rotation exerts no impact on overall ICU mortality at French teaching hospitals but might affect the prognosis of less severe ICU patients. Surveillance should be reinforced when treating those patients.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

Outcome of non-variceal acute upper gastrointestinal bleeding in relation to the time of endoscopy and the experience of the endoscopist: A two-year survey

PubMed Central

Parente, Fabrizio; Anderloni, Andrea; Bargiggia, Stefano; Imbesi, Venerina; Trabucchi, Emilio; Baratti, Cinzia; Gallus, Silvano; Porro, Gabriele Bianchi

2005-01-01

AIM: To prospectively assess the impact of time of endoscopy and endoscopist’s experience on the outcome of non-variceal acute upper gastrointestinal (GI) bleeding patients in a large teaching hospital. METHODS: All patients admitted for non-variceal acute upper GI bleeding for over a 2-year period were potentially eligible for this study. They were managed by a team of seven endoscopists on 24-h call whose experience was categorized into two levels (high and low) according to the number of endoscopic hemostatic procedures undertaken before the study. Endoscopic treatment was standardized according to Forrest classification of lesions as well as the subsequent medical therapy. Time of endoscopy was subdivided into two time periods: routine (8 a.m.-5 p.m.) and on-call (5 p.m.-8 a.m.). For each category of experience and time periods rebleeding rate, transfusion requirement, need for surgery, length of hospital stay and mortality we compared. Multivariate analysis was used to discriminate the impact of different variables on the outcomes that were considered. RESULTS: Study population consisted of 272 patients (mean age 67.3 years) with endoscopic stigmata of hemorrhage. The patients were equally distributed among the endoscopists, whereas only 19% of procedures were done out of working hours. Rockall score and Forrest classification at admission did not differ between time periods and degree of experience. Univariate analysis showed that higher endoscopist’s experience was associated with significant reduction in rebleeding rate (14% vs 37%), transfusion requirements (1.8±0.6 vs 3.0±1.7 units) as well as surgery (4% vs 10%), but not associated with the length of hospital stay nor mortality. By contrast, outcomes did not significantly differ between the two time periods of endoscopy. On multivariate analysis, endoscopist’s experience was independently associated with rebleeding rate and transfusion requirements. Odds ratios for low experienced endoscopist were 4.47 for rebleeding and 6.90 for need of transfusion after the endoscopy. CONCLUSION: Endoscopist’s experience is an important independent prognostic factor for non-variceal acute upper GI bleeding. Urgent endoscopy should be undertaken preferentially by a skilled endoscopist as less expert staff tends to underestimate some risk lesions with a negative influence on hemostasis. PMID:16437658

Individual and hospital-specific factors influencing medical graduates' time to medical specialization.

PubMed

Johannessen, Karl-Arne; Hagen, Terje P

2013-11-01

Previous studies of gender differences in relation to medical specialization have focused more on social variables than hospital-specific factors. In a multivariate analysis with extended Cox regression, we used register data for socio-demographic variables (gender, family and having a child born during the study period) together with hospital-specific variables (the amount of supervision available, efficiency pressure and the type of teaching hospital) to study the concurrent effect of these variables on specialty qualification among all 2474 Norwegian residents who began specialization in 1999-2001. We followed the residents until 2010. A lower proportion of women qualified for a specialty in the study period (67.9% compared with 78.7% of men, p < 0.001), and they took on average six months longer than men did to complete the specialization qualification (p < 0.01). Fewer women than men entered specialties providing emergency services and those with longer working hours, and women worked shorter hours than men in all specialties. Hospital factors were significant predictors for the timely attainment of specialization: working at university hospitals (regional) or central hospitals was associated with a reduction in the time taken to complete the specialization, whereas an increased patient load and less supervision had the opposite effect. Multivariate analysis showed that the smaller proportion of women who qualified for a specialty was explained principally by childbirth and by the number of children aged under 18 years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Amino acid substitutions in the hepatitis C virus core region predict hepatocarcinogenesis following eradication of HCV RNA by all-oral direct-acting antiviral regimens.

PubMed

Ogata, Fumihiro; Akuta, Norio; Kobayashi, Masahiro; Fujiyama, Shunichiro; Kawamura, Yusuke; Sezaki, Hitomi; Hosaka, Tetsuya; Kobayashi, Mariko; Saitoh, Satoshi; Suzuki, Yoshiyuki; Suzuki, Fumitaka; Arase, Yasuji; Ikeda, Kenji; Kumada, Hiromitsu

2018-06-01

Impact of substitution of aa70 in the core region (Core aa70) in HCV genotype 1b (HCV-1b) on hepatocarcinogenesis following eradication of HCV RNA by direct-acting antiviral therapy is not clear. In a retrospective study, 533 patients with HCV-related chronic liver disease, with sustained virological response defined as negative HCV RNA at 12 weeks after cessation of direct-acting antiviral therapy, were examined to evaluate the relationship between Core aa70 substitution and hepatocarcinogenesis. Twelve patients developed hepatocellular carcinoma during the follow-up period. The cumulative hepatocarcinogenesis rates were 1.7% and 2.4% at the end of 1 and 2 years, respectively. Overall, multivariate analysis identified HCV subgroup (HCV-1b with Gln70(His70); P = 0.003) and age (>65 years; P = 0.049), as pretreatment predictors of hepatocarcinogenesis. In HCV-1b patients, multivariate analysis identified post-treatment Wisteria floribunda agglutinin positive Mac-2 binding protein (>1.8 COI; P = 0.042) and HCV subgroup (HCV-1b with Gln70(His70); P = 0.071), as predictors of hepatocarcinogenesis, including post-treatment parameter. In conclusion, Core aa70 substitution in HCV-1b at the start of direct-acting antiviral therapy is an important predictor of hepatocarcinogenesis following eradication of HCV RNA. This study emphasizes the importance of detection of Core aa70 substitution before initiating antiviral therapy. © 2018 Wiley Periodicals, Inc.

Diagnosis of abnormal patterns in multivariate microclimate monitoring: a case study of an open-air archaeological site in Pompeii (Italy).

PubMed

Merello, Paloma; García-Diego, Fernando-Juan; Zarzo, Manuel

2014-08-01

Chemometrics has been applied successfully since the 1990s for the multivariate statistical control of industrial processes. A new area of interest for these tools is the microclimatic monitoring of cultural heritage. Sensors record climatic parameters over time and statistical data analysis is performed to obtain valuable information for preventive conservation. A case study of an open-air archaeological site is presented here. A set of 26 temperature and relative humidity data-loggers was installed in four rooms of Ariadne's house (Pompeii). If climatic values are recorded versus time at different positions, the resulting data structure is equivalent to records of physical parameters registered at several points of a continuous chemical process. However, there is an important difference in this case: continuous processes are controlled to reach a steady state, whilst open-air sites undergo tremendous fluctuations. Although data from continuous processes are usually column-centred prior to applying principal components analysis, it turned out that another pre-treatment (row-centred data) was more convenient for the interpretation of components and to identify abnormal patterns. The detection of typical trajectories was more straightforward by dividing the whole monitored period into several sub-periods, because the marked climatic fluctuations throughout the year affect the correlation structures. The proposed statistical methodology is of interest for the microclimatic monitoring of cultural heritage, particularly in the case of open-air or semi-confined archaeological sites. Copyright © 2014 Elsevier B.V. All rights reserved.

Risk factor analysis of bloodstream infection in pediatric patients after hematopoietic stem cell transplantation.

PubMed

Sarashina, Takeo; Yoshida, Makoto; Iguchi, Akihiro; Okubo, Hitoshi; Toriumi, Naohisa; Suzuki, Daisuke; Sano, Hirozumi; Kobayashi, Ryoji

2013-01-01

Bloodstream infection (BSI) is a recognized cause of morbidity and mortality in children after hematopoietic stem cell transplantation (HSCT). However, there are limited reports on BSI after HSCT in pediatric patients in multiple centers. This study was a retrospective cohort analysis of consecutive patients who underwent allogeneic and autologous HSCT at the Department of Paediatrics, Hokkaido University Hospital, between 1988 and 2009; the Department of Paediatrics, Sapporo Hokuyu Hospital, between 2007 and 2009; and the Department of Paediatrics, Asahikawa Medical University, between 1989 and 2009. A total of 277 patients underwent HSCT during the study period. In this multicenter analysis, cases of BSI after HSCT were recorded in the early posttransplant period (within the first 100 d), and BSI was observed in 24 of 277 HSCT patients. Multivariate analysis showed that nonmalignant disease was an independent factor associated with BSI after HSCT (hazard ratio 6.3 for aplastic anemia or Wiskott-Aldrich syndrome patients; confidence interval, 1.4-12.8; P = 0.012). We conclude that aplastic anemia and Wiskott-Aldrich syndrome were the novel risk factors for BSI in pediatric patients after HSCT.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

The dynamic correlation between policy uncertainty and stock market returns in China

NASA Astrophysics Data System (ADS)

Yang, Miao; Jiang, Zhi-Qiang

2016-11-01

The dynamic correlation is examined between government's policy uncertainty and Chinese stock market returns in the period from January 1995 to December 2014. We find that the stock market is significantly correlated to policy uncertainty based on the results of the Vector Auto Regression (VAR) and Structural Vector Auto Regression (SVAR) models. In contrast, the results of the Dynamic Conditional Correlation Generalized Multivariate Autoregressive Conditional Heteroscedasticity (DCC-MGARCH) model surprisingly show a low dynamic correlation coefficient between policy uncertainty and market returns, suggesting that the fluctuations of each variable are greatly influenced by their values in the preceding period. Our analysis highlights the understanding of the dynamical relationship between stock market and fiscal and monetary policy.

Epidemiology of uveitis among the Chinese population in Taiwan: a population-based study.

PubMed

Hwang, De-Kuang; Chou, Yiing-Jeng; Pu, Cheng-Yun; Chou, Pesus

2012-11-01

This study aimed to investigate the incidence and prevalence of uveitis in Taiwan, and then analyzed the risk factors related to uveitis using multivariate regression. Population-based cohort study using medical claims data. We randomly selected 1 000 000 residents from the Taiwan National Health Insurance Research Database. All participants with correct registry data (96%) were included in the study. The study period was from 2000 to 2008. All types of uveitis were identified using the International Classification of Diseases, 9th revision, Clinical Modification diagnostic codes. The annual incidence and cumulative prevalence of uveitis were calculated. A univariate and a multivariate Poisson regression were used to determine the risk factors associated with uveitis. The first diagnosis of uveitis noted during the study period. The annual cumulative incidence rate of uveitis ranged from 102.2 to 122.0 cases per 100 000 persons over the study period, and the average incidence density was 111.3 cases per 100 000 person-years (95% confidence interval, 108.4-114.1). The cumulative prevalence was found to have increased from 318.8 cases per 100 000 persons in 2003 to 622.7 cases per 100 000 persons in 2008. Anterior uveitis was the most common location and accounted for 77.7% of all incident cases, which was followed by panuveitis, posterior uveitis, and intermediate uveitis. Multivariate regression analysis showed that males, the elderly, and individuals who lived in an urban area had higher incidence rates for uveitis. The epidemiology of uveitis in Taiwan differs from most previous studies in other countries. The incidence of uveitis in Taiwan has increased significantly recently. The elderly and individuals living in urban areas are the populations that are most commonly affected by uveitis. These findings are consistent with suggestions found in several recent studies. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Dietary patterns and changes in body weight in women.

PubMed

Schulze, Matthias B; Fung, Teresa T; Manson, Joann E; Willett, Walter C; Hu, Frank B

2006-08-01

Our objective was to examine the association between adherence to dietary patterns and weight change in women. Women (51,670, 26 to 46 years old) in the Nurses' Health Study II were followed from 1991 to 1999. Dietary intake and body weight were ascertained in 1991, 1995, and 1999. A Western pattern, characterized by high intakes of red and processed meats, refined grains, sweets and desserts, and potatoes, and a prudent pattern, characterized by high intakes of fruits, vegetables, whole grains, fish, poultry, and salad dressing, were identified with principal component analysis, and associations between patterns and change in body weight were estimated. Women who increased their Western pattern score had greater weight gain (multivariate adjusted means, 4.55 kg for 1991 to 1995 and 2.86 kg for 1995 to 1999) than women who decreased their Western pattern score (2.70 and 1.37 kg for the two time periods), adjusting for baseline lifestyle and dietary confounders and changes in confounders over time (p < 0.001 for both time periods). Furthermore, among women who increased their prudent pattern score, weight gain was smaller (multivariate-adjusted means, 1.93 kg for 1991 to 1995 and 0.66 kg for 1995 to 1999) than among women who decreased their prudent pattern score (4.83 and 3.35 kg for the two time periods) (p < 0.001). The largest weight gain between 1991 and 1995 and between 1995 and 1999 was observed among women who decreased their prudent pattern score while increasing their Western pattern score (multivariate adjusted means, 6.80 and 4.99 kg), whereas it was smallest for the opposite change in patterns (0.87 and -0.64 kg) (p < 0.001). Adoption of a Western dietary pattern is associated with larger weight gain in women, whereas a prudent dietary pattern may facilitate weight maintenance.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Risk stratification of periprocedural myocardial infarction after percutaneous coronary intervention: Analysis based on the SCAI definition.

PubMed

Zhang, Dong; Li, Yiping; Yin, Dong; He, Yuan; Chen, Changzhe; Song, Chenxi; Yan, Ruohua; Zhu, Chen'gang; Xu, Bo; Dou, Kefei

2017-03-01

To investigate the predictors of and generate a risk prediction method for periprocedural myocardial infarction (PMI) after percutaneous coronary intervention (PCI) using the new PMI definition proposed by the Society for Cardiovascular Angiography and Interventions (SCAI). The SCAI-defined PMI was found to be associated with worse prognosis than the PMI diagnosed by other definitions. However, few large-sample studies have attempted to predict the risk of SCAI-defined PMI. A total of 3,371 patients (3,516 selective PCIs) were included in this single-center retrospective analysis. The diagnostic criteria for PMI were set according to the SCAI definition. All clinical characteristics, coronary angiography findings and PCI procedural factors were collected. Multivariate logistic regression analysis was performed to identify independent predictors of PMI. To evaluate the risk of PMI, a multivariable risk score (PMI score) was constructed with incremental weights attributed to each component variable according to their estimated coefficients. PMI occurred in 108 (3.1%) of all patients. Age, multivessel treatment, at least one bifurcation treatment and total treated lesion length were independent predictors of SCAI-defined PMI. PMI scores ranged from 0 to 20. The C-statistic of PMI score was 0.71 (95% confidence interval: 0.66-0.76). PMI rates increased significantly from 1.96% in the non-high-risk group (PMI score < 10) to 6.26% in the high-risk group (PMI score ≥ 10) (P < 0.001). Age, multivessel treatment, at least one bifurcation treatment, and total treated lesion length are predictive of PMI. The PMI score could help identify patients at high risk of PMI after PCI. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

DIVERGT screening procedure predicts general cognitive functioning in adult long-term survivors of pediatric acute lymphoblastic leukemia: A PETALE study.

PubMed

Boulet-Craig, Aubree; Robaey, Philippe; Laniel, Julie; Bertout, Laurence; Drouin, Simon; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Sultan, Serge; Lippé, Sarah

2018-05-24

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Because of major improvements in treatment protocols, the survival rate now exceeds 80%. However, ALL treatments can cause long-term neurocognitive sequelae, which negatively impact academic achievement and quality of life. Therefore, cognitive sequelae need to be carefully evaluated. The DIVERGT is a battery of tests proposed as a screening tool, sensitive to executive function impairments in children and adolescent cancer survivors. Our study aimed at verifying the predictive value of the DIVERGT on general cognitive functioning in adult long-term survivors of ALL. ALL survivors completed the DIVERGT 13.4 years, on average, after remission (N = 247). In addition, 49 of these survivors (equally selected amongst those with low, average, and high DIVERGT scores) as well as 29 controls completed a more comprehensive neuropsychological evaluation within a 3-year period from DIVERGT administration. Multivariate regression analysis was used to assess the predictive value of the DIVERGT on general intelligence, mathematics, verbal memory, and working memory. As a follow-up analysis, three performance groups were created based on the DIVERGT results. Multivariate analysis of variance (MANOVA) assessed neuropsychological differences between groups. The DIVERGT accurately predicted General Ability Index (GAI) (P < 0.0001), mathematics (P < 0.0001) and verbal memory (P = 0.045). Moreover, the low-performance group consistently had poorer performance than the high-performance and control groups on the neuropsychological tests. The DIVERGT is a useful, time-effective screening battery for broader neurocognitive impairments identification in long-term adult ALL survivors. It could be implemented as routine examination in cancer follow-up clinics. © 2018 Wiley Periodicals, Inc.

[Study on the status of institutional delivery and its determinants in rural Guangxi autonomous region].

PubMed

Li, Jian; Chen, Li-Li; Chen, Shu-Zhen; Cen, Ming-Yang; Zhao, Nai-Qing; Qian, Xu

2008-03-01

To understand the situation of institutional delivery of rural pregnant women in Guangxi Autonomous Region in the period of 1998 - 2003 and to identify the determinants on institutional delivery utilization. Using Andersen's behavioral model as analytical framework and Guangxi databank of the 3rd National Health Service Survey as data source, we described the status of institutional delivery with the rural women having had live birth history in the period of 1998 - 2003 as subjects, while and the univariate analysis and multivariate logistic analysis were done to identify determinants of institutional delivery utilization. Among a total number of 407 women with live birth history, 39.80 percent of them delivered at the health-care facilities. The rate of institutional delivery increased annually in 1998 - 2003 (P< 0.0001). The proportion of delivery in township health centers increased and the proportion of home delivery decreased by year (P< 0.0001). Results from both univariate and multivariate analysis showed that parity, education background of women, type of drinking water, time needed to get to the nearest healthcare facilities by the most convenient traffic,frequency of prenatal checkup, together with whether or not being advocated on institutional delivery etc. were determinants of delivery utilization. The OR value were 1.749 for multipara, 1.995 for those going to the nearest healthcare facilities by the most convenient traffic in less than 10 minutes, 3.011 for those drinking tap water, 5.435 for those with the education of high school, 29.149 for those with over 5 times in terms of frequency of prenatal checkup and 37.822 for those being advocated on institutional delivery. Socio-economic situation, status of maternal health care and parity made main contribution to institutional delivery and skilled birth attendance for women in rural Guangxi.

Interglacial vegetation succession: A view from southern Europe

NASA Astrophysics Data System (ADS)

Tzedakis, P. C.; Bennett, K. D.

Factors influencing interglacial vegetation development in southern Europe are considered in a series of comparisons of the vegetation and climatic signatures of selected periods. Multivariate analysis provides a method for standardizing comparison of interglacial vegetation successions, and insolation values and geological evidence supply information on the climatic character of individual periods. Application of this comparative approach to a long pollen record from northwest Greece presents an opportunity to examine a series of interglacial successions under constant background site characteristics, secure chronostratigraphical positions and minimal differences in species' immigration rates. The record of four interglacial period equivalent to marine oxygen isotopic substages 5e, 7c, 9c and 11c is examined. The comparison shows that the two earliest periods are characterized by similar vegetation development despite differences in climatic regimes. Dependence on initial conditions is one of the emergent aspects of the comparisons, suggesting that the nature of surviving populations during a cold stage may be critical in determining the course of interglacial succession.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

PubMed Central

Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.

2016-01-01

Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095

Distant stereoacuity in children with anisometropic amblyopia.

PubMed

Chung, Yeon Woong; Park, Shin Hae; Shin, Sun Young

2017-09-01

To characterize changes in distant stereoacuity using Frisby-Davis Distance test (FD2) and Distant Randot test (DR) during treatment for anisometropic amblyopia, to determine factors that influence posttreatment stereoacuity and to compare the two distant stereotests. Fifty-eight anisometropic amblyopic patients with an interocular difference of ≥1.00 diopter who achieved the visual acuity 20/20 following amblyopia treatment were retrospectively included. Stereoacuity using FD2 and DR for distant and Titmus test for near measurement were assessed and compared at the initial, intermediate, and final visit. Multivariate regression models were used to identify factors associated with initial and final stereoacuity. The two distant stereotests revealed a significant improvement in distant stereoacuity after successful amblyopia treatment. Distant stereoacuity using FD2 showed the greatest improvement during the follow up period. The number of nil scores was higher in DR than FD2 at each period. In multivariate analysis, better final stereoacuity was associated with better initial amblyopic eye acuity in both distant stereotests, but not in the Titmus test. Comparing the two distant stereotests, final stereoacuity using FD2 was associated with initial stereoacuity and was moderately related with the Titmus test at each period, but final stereoacuity using DR was not. Distant stereoacuity measured with both FD2 and DR showed significant improvement when the visual acuity of the amblyopic eye achieved 20/20. Changes in distant stereoacuity by FD2 and DR during the amblyopia treatment were somewhat different.

Stroke Severity Affects Timing: Time From Stroke Code Activation to Initial Imaging is Longer in Patients With Milder Strokes.

PubMed

Kwei, Kimberly T; Liang, John; Wilson, Natalie; Tuhrim, Stanley; Dhamoon, Mandip

2018-05-01

Optimizing the time it takes to get a potential stroke patient to imaging is essential in a rapid stroke response. At our hospital, door-to-imaging time is comprised of 2 time periods: the time before a stroke is recognized, followed by the period after the stroke code is called during which the stroke team assesses and brings the patient to the computed tomography scanner. To control for delays due to triage, we isolated the time period after a potential stroke has been recognized, as few studies have examined the biases of stroke code responders. This "code-to-imaging time" (CIT) encompassed the time from stroke code activation to initial imaging, and we hypothesized that perception of stroke severity would affect how quickly stroke code responders act. In consecutively admitted ischemic stroke patients at The Mount Sinai Hospital emergency department, we tested associations between National Institutes of Health Stroke Scale scores (NIHSS), continuously and at different cutoffs, and CIT using spline regression, t tests for univariate analysis, and multivariable linear regression adjusting for age, sex, and race/ethnicity. In our study population, mean CIT was 26 minutes, and mean presentation NIHSS was 8. In univariate and multivariate analyses comparing CIT between mild and severe strokes, stroke scale scores <4 were associated with longer response times. Milder strokes are associated with a longer CIT with a threshold effect at a NIHSS of 4.

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

Psycho-physiological analysis of an aerobic dance programme for women

PubMed Central

Rockefeller, Kathleen A.; Burke, E. J.

1979-01-01

The purpose of this study was to determine: (1) the energy cost and (2) the psycho-physiological effects of an aerobic dance programme in young women. Twenty-one college-age women participated 40 minutes a day, three days a week, for a 10-week training period. Each work session included a five-minute warm-up period, a 30-minute stimulus period (including walk-runs) and a five-minute cool-down period. During the last four weeks of the training period, the following parameters were monitored in six of the subjects during two consecutive sessions: perceived exertion (RPE) utilising the Borg 6-20 scale, Mean = 13.19; heart rate (HR) monitored at regular intervals during the training session, Mean = 166.37; and estimated caloric expenditure based on measured oxygen consumption (V̇O2) utilising a Kofranyi-Michaelis respirometer, Mean = 289.32. Multivariate analysis of variance (MANOVA) computed between pre and post tests for the six dependent variables revealed a significant approximate F-ratio of 5.72 (p <.05). Univariate t-test analysis of mean changes revealed significant pre-post test differences for V̇O2 max expressed in ml/kg min-1, maximal pulmonary ventilation, maximal working capacity on the bicycle ergometer, submaximal HR and submaximal RPE. Body weight was not significantly altered. It was concluded that the aerobic dance training programme employed was of sufficient intensity to elicit significant physiological and psycho-physiological alterations in college-age women. PMID:465914

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP. PMID:29312134

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Quality by design case study: an integrated multivariate approach to drug product and process development.

PubMed

Huang, Jun; Kaul, Goldi; Cai, Chunsheng; Chatlapalli, Ramarao; Hernandez-Abad, Pedro; Ghosh, Krishnendu; Nagi, Arwinder

2009-12-01

To facilitate an in-depth process understanding, and offer opportunities for developing control strategies to ensure product quality, a combination of experimental design, optimization and multivariate techniques was integrated into the process development of a drug product. A process DOE was used to evaluate effects of the design factors on manufacturability and final product CQAs, and establish design space to ensure desired CQAs. Two types of analyses were performed to extract maximal information, DOE effect & response surface analysis and multivariate analysis (PCA and PLS). The DOE effect analysis was used to evaluate the interactions and effects of three design factors (water amount, wet massing time and lubrication time), on response variables (blend flow, compressibility and tablet dissolution). The design space was established by the combined use of DOE, optimization and multivariate analysis to ensure desired CQAs. Multivariate analysis of all variables from the DOE batches was conducted to study relationships between the variables and to evaluate the impact of material attributes/process parameters on manufacturability and final product CQAs. The integrated multivariate approach exemplifies application of QbD principles and tools to drug product and process development.

Improved long-term outcomes after resection of pancreatic adenocarcinoma: a comparison between two time periods.

PubMed

Serrano, Pablo E; Cleary, Sean P; Dhani, Neesha; Kim, Peter T W; Greig, Paul D; Leung, Kenneth; Moulton, Carol-Anne; Gallinger, Steven; Wei, Alice C

2015-04-01

Despite reduced perioperative mortality and routine use of adjuvant therapy following pancreatectomy for pancreatic ductal adenocarcinoma (PDAC), improvement in long-term outcome has been difficult to ascertain. This study compares outcomes in patients undergoing resection for PDAC within a single, high-volume academic institution over two sequential time periods. Retrospective review of patients with resected PDAC, in two cohorts: period 1 (P1), 1991-2000; and period 2 (P2), 2001-2010. Univariate and multivariate analyses using the Cox proportional hazards model were performed to determine prognostic factors associated with long-term survival. Survival was evaluated using Kaplan-Meier analyses. A total of 179 pancreatectomies were performed during P1 and 310 during P2. Perioperative mortality was 6.7 % (12/179) in P1 and 1.6 % (5/310) in P2 (p = 0.003). P2 had a greater number of lymph nodes resected (17 [0-50] vs. 7 [0-31]; p < 0.001), and a higher lymph node positivity rate (69 % [215/310] vs. 58 % [104/179]; p = 0.021) compared with P1. The adjuvant therapy rate was 30 % (53/179) in P1 and 63 % (195/310) in P2 (p < 0.001). By multivariate analysis, node and margin status, tumor grade, adjuvant therapy, and time period of resection were independently associated with overall survival (OS) for both time periods. Median OS was 16 months (95 % confidence interval [CI] 14-20) in P1 and 27 months (95 % CI 24-30) in P2 (p < 0.001). Factors associated with improved long-term survival remain comparable over time. Short- and long-term survival for patients with resected PDAC has improved over time due to decreased perioperative mortality and increased use of adjuvant therapy, although the proportion of 5-year survivors remains small.

Risk factors associated with gastric cancer in Mexico: education, breakfast and chili.

PubMed

Trujillo Rivera, Alejandro; Sampieri, Clara Luz; Morales Romero, Jaime; Montero, Hilda; Acosta Mesa, Héctor Gabriel; Cruz Ramírez, Nicandro; Novoa Del Toro, Elva María; León Córdoba, Kenneth

2018-06-01

the aim of the study was to use a validated questionnaire to identify factors associated with the development of gastric cancer (GC) in the Mexican population. the study included cases and controls that were paired by sex and ± 10 years of age at diagnosis. In relation to cases, 46 patients with a confirmed histopathological diagnosis of adenocarcinoma-type GC, as reported in the hospital records, were selected, and 46 blood bank donors from the same hospital were included as controls. The previously validated Questionnaire to Find Factors Associated with Gastric Cancer (QUFA-GC©) was used to collect data. Odds ratio (OR) and 95% confidence interval (IC) were estimated via univariate analysis (paired OR). Multivariate analysis was performed by logistic regression. A decision tree was constructed using the J48 algorithm. an association was found by univariate analysis between GC risk and a lack of formal education, having smoked for ≥ 10 years, eating rapidly, consuming very hot food and drinks, a non-suitable breakfast within two hours of waking, pickled food and capsaicin. In contrast, a protective association against GC was found with taking recreational exercise and consuming fresh fruit and vegetables. No association was found between the development of GC and having an income that reflected poverty, using a refrigerator, perception of the omission of breakfast and time period of alcoholism. In the final multivariate analysis model, having no formal education (OR = 17.47, 95% CI = 5.17-76.69), consuming a non-suitable breakfast within two hours of waking (OR = 8.99, 95% CI = 2.85-35.50) and the consumption of capsaicin ˃ 29.9 mg capsaicin per day (OR = 3.77, 95% CI = 1.21-13.11) were factors associated with GC. an association was found by multivariate analysis between the presence of GC and education, type of breakfast and the consumption of capsaicin. These variables are susceptible to intervention and can be identified via the QUFA-GC ©.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

PubMed

Zhou, Hua; Blangero, John; Dyer, Thomas D; Chan, Kei-Hang K; Lange, Kenneth; Sobel, Eric M

2017-04-01

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel. © 2016 WILEY PERIODICALS, INC.

Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida

NASA Astrophysics Data System (ADS)

Sayemuzzaman, M.; Ye, M.

2015-12-01

The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface waters can be undertaken.

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

ERIC Educational Resources Information Center

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

FTIR microspectroscopy for rapid screening and monitoring of polyunsaturated fatty acid production in commercially valuable marine yeasts and protists.

PubMed

Vongsvivut, Jitraporn; Heraud, Philip; Gupta, Adarsha; Puri, Munish; McNaughton, Don; Barrow, Colin J

2013-10-21

The increase in polyunsaturated fatty acid (PUFA) consumption has prompted research into alternative resources other than fish oil. In this study, a new approach based on focal-plane-array Fourier transform infrared (FPA-FTIR) microspectroscopy and multivariate data analysis was developed for the characterisation of some marine microorganisms. Cell and lipid compositions in lipid-rich marine yeasts collected from the Australian coast were characterised in comparison to a commercially available PUFA-producing marine fungoid protist, thraustochytrid. Multivariate classification methods provided good discriminative accuracy evidenced from (i) separation of the yeasts from thraustochytrids and distinct spectral clusters among the yeasts that conformed well to their biological identities, and (ii) correct classification of yeasts from a totally independent set using cross-validation testing. The findings further indicated additional capability of the developed FPA-FTIR methodology, when combined with partial least squares regression (PLSR) analysis, for rapid monitoring of lipid production in one of the yeasts during the growth period, which was achieved at a high accuracy compared to the results obtained from the traditional lipid analysis based on gas chromatography. The developed FTIR-based approach when coupled to programmable withdrawal devices and a cytocentrifugation module would have strong potential as a novel online monitoring technology suited for bioprocessing applications and large-scale production.

Application of quality by design concepts in the development of fluidized bed granulation and tableting processes.

PubMed

Djuris, Jelena; Medarevic, Djordje; Krstic, Marko; Djuric, Zorica; Ibric, Svetlana

2013-06-01

This study illustrates the application of experimental design and multivariate data analysis in defining design space for granulation and tableting processes. According to the quality by design concepts, critical quality attributes (CQAs) of granules and tablets, as well as critical parameters of granulation and tableting processes, were identified and evaluated. Acetaminophen was used as the model drug, and one of the study aims was to investigate the possibility of the development of immediate- or extended-release acetaminophen tablets. Granulation experiments were performed in the fluid bed processor using polyethylene oxide polymer as a binder in the direct granulation method. Tablets were compressed in the laboratory excenter tablet press. The first set of experiments was organized according to Plackett-Burman design, followed by the full factorial experimental design. Principal component analysis and partial least squares regression were applied as the multivariate analysis techniques. By using these different methods, CQAs and process parameters were identified and quantified. Furthermore, an in-line method was developed to monitor the temperature during the fluidized bed granulation process, to foresee possible defects in granules CQAs. Various control strategies that are based on the process understanding and assure desired quality attributes of the product are proposed. Copyright © 2013 Wiley Periodicals, Inc.

Why you cannot transform your way out of trouble for small counts.

PubMed

Warton, David I

2018-03-01

While data transformation is a common strategy to satisfy linear modeling assumptions, a theoretical result is used to show that transformation cannot reasonably be expected to stabilize variances for small counts. Under broad assumptions, as counts get smaller, it is shown that the variance becomes proportional to the mean under monotonic transformations g(·) that satisfy g(0)=0, excepting a few pathological cases. A suggested rule-of-thumb is that if many predicted counts are less than one then data transformation cannot reasonably be expected to stabilize variances, even for a well-chosen transformation. This result has clear implications for the analysis of counts as often implemented in the applied sciences, but particularly for multivariate analysis in ecology. Multivariate discrete data are often collected in ecology, typically with a large proportion of zeros, and it is currently widespread to use methods of analysis that do not account for differences in variance across observations nor across responses. Simulations demonstrate that failure to account for the mean-variance relationship can have particularly severe consequences in this context, and also in the univariate context if the sampling design is unbalanced. © 2017 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Multivariable harmonic balance analysis of the neuronal oscillator for leech swimming.

PubMed

Chen, Zhiyong; Zheng, Min; Friesen, W Otto; Iwasaki, Tetsuya

2008-12-01

Biological systems, and particularly neuronal circuits, embody a very high level of complexity. Mathematical modeling is therefore essential for understanding how large sets of neurons with complex multiple interconnections work as a functional system. With the increase in computing power, it is now possible to numerically integrate a model with many variables to simulate behavior. However, such analysis can be time-consuming and may not reveal the mechanisms underlying the observed phenomena. An alternative, complementary approach is mathematical analysis, which can demonstrate direct and explicit relationships between a property of interest and system parameters. This paper introduces a mathematical tool for analyzing neuronal oscillator circuits based on multivariable harmonic balance (MHB). The tool is applied to a model of the central pattern generator (CPG) for leech swimming, which comprises a chain of weakly coupled segmental oscillators. The results demonstrate the effectiveness of the MHB method and provide analytical explanations for some CPG properties. In particular, the intersegmental phase lag is estimated to be the sum of a nominal value and a perturbation, where the former depends on the structure and span of the neuronal connections and the latter is roughly proportional to the period gradient, communication delay, and the reciprocal of the intersegmental coupling strength.

Dangers in Using Analysis of Covariance Procedures.

ERIC Educational Resources Information Center

Campbell, Kathleen T.

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

Monitoring of pistachio (Pistacia Vera) ripening by high field nuclear magnetic resonance spectroscopy.

PubMed

Sciubba, Fabio; Avanzato, Damiano; Vaccaro, Angela; Capuani, Giorgio; Spagnoli, Mariangela; Di Cocco, Maria Enrica; Tzareva, Irina Nikolova; Delfini, Maurizio

2017-04-01

The metabolic profiling of pistachio (Pistacia vera) aqueous extracts from two different cultivars, namely 'Bianca' and 'Gloria', was monitored over the months from May to September employing high field NMR spectroscopy. A large number of water-soluble metabolites were assigned by means of 1D and 2D NMR experiments. The change in the metabolic profiles monitored over time allowed the pistachio development to be investigated. Specific temporal trends of amino acids, sugars, organic acids and other metabolites were observed and analysed by multivariate Partial Least Squares (PLS) analysis. Statistical analysis showed that while in the period from May to September there were few differences between the two cultivars, the ripening rate was different.

Defining the surgical margins of adenoid cystic carcinoma and their impact on outcome: An international collaborative study.

PubMed

Amit, Moran; Na'ara, Shorook; Trejo-Leider, Leonor; Ramer, Naomi; Burstein, David; Yue, Ma; Miles, Brett; Yang, Xinjie; Lei, Delin; Bjoerndal, Kristine; Godballe, Christian; Mücke, Thomas; Wolff, Klaus-Dietrich; Eckardt, André M; Copelli, Chiara; Sesenna, Enrico; Patel, Snehal; Ganly, Ian; Gil, Ziv

2017-05-01

The mainstay of treatment in adenoid cystic carcinoma (ACC) of the head and neck is surgical resection with negative margins. The purpose of this study was to define the margin status that associates with survival outcomes of ACC of the head and neck. We conducted univariate and multivariate analyses of international data. Data of 507 patients with ACC of the head and neck were analyzed; negative margins defined as ≥5 mm were detected in 253 patients (50%). On multivariate analysis, the hazard ratios (HRs) of positive margin status were 2.68 (95% confidence interval [CI], 1.2-6.2; p = .04) and 2.63 (95% CI, 1.1-6.3; p = .03) for overall survival (OS) and disease-specific survival (DSS), respectively. Close margins had no significant impact on outcome, with HRs of 1.1 (95% CI, 0.4-3.0; p = .12) and 1.07 (95% CI, 0.3-3.4; p = .23) for OS and DSS, respectively, relative with negative margins. In head and neck ACC, positive margins are associated with the worst outcome. Negative or close margins are associated with improved outcome, regardless of the distance from the tumor. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1008-1014, 2017. © 2017 Wiley Periodicals, Inc.

[Association between risk factors during maternal pregnancy and the neonatal period and childhood bronchial asthma].

PubMed

Zhang, Hui-Qin; Fan, Rui; Zhang, Jing-Jing; Tao, Xiao-Juan; Sun, Xin

2017-01-01

To study the association of the risk factors during maternal pregnancy and the neonatal period with childhood bronchial asthma. A total of 306 children with asthma (asthma group) and 250 healthy children (control group) were enrolled. Their clinical data during the neonatal period and the maternal data during pregnancy were retrospectively studied. The univariate analysis showed that there were significant differences in the rates of maternal use of antibiotics during pregnancy, use of antibiotics and probiotics during the neonatal period, preterm birth, cesarean section, low birth weight, and breast feeding (>6 months) between the asthma and control groups (P<0.05). The multivariate logistic regression analysis showed that use of antibiotics during pregnancy (OR=3.908, 95%CI: 1.277-11.962), use of antibiotics during neonatal period (OR=24.154, 95%CI: 7.864-74.183), preterm birth (OR=8.535, 95%CI: 2.733-26.652), and cesarean section (OR=4.588, 95%CI: 2.887-7.291) were independent risk factors for childhood asthma. The use of probiotics during the neonatal period (OR=0.014, 95%CI: 0.004-0.046) and breast feeding (>6 months) (OR=0.161, 95%CI: 0.103-0.253) were protective factors for childhood asthma. The early prevention of childhood asthma can be improved by reducing the use of antibiotics during pregnancy, reducing cesarean section, avoiding abuse of antibiotics during the neonatal period, trying breast feeding and taking probiotics in early stage.

Racial and ethnic disparities in maternal morbidity and obstetric care.

PubMed

Grobman, William A; Bailit, Jennifer L; Rice, Madeline Murguia; Wapner, Ronald J; Reddy, Uma M; Varner, Michael W; Thorp, John M; Leveno, Kenneth J; Caritis, Steve N; Iams, Jay D; Tita, Alan T N; Saade, George; Rouse, Dwight J; Blackwell, Sean C; Tolosa, Jorge E; VanDorsten, J Peter

2015-06-01

To evaluate whether racial and ethnic disparities exist in obstetric care and adverse outcomes. We analyzed data from a cohort of women who delivered at 25 hospitals across the United States over a 3-year period. Race and ethnicity was categorized as non-Hispanic white, non-Hispanic black, Hispanic, or Asian. Associations between race and ethnicity and severe postpartum hemorrhage, peripartum infection, and severe perineal laceration at spontaneous vaginal delivery as well as between race and ethnicity and obstetric care (eg, episiotomy) relevant to the adverse outcomes were estimated by univariable analysis and multivariable logistic regression. Of 115,502 studied women, 95% were classified by one of the race and ethnicity categories. Non-Hispanic white women were significantly less likely to experience severe postpartum hemorrhage (1.6% non-Hispanic white compared with 3.0% non-Hispanic black compared with 3.1% Hispanic compared with 2.2% Asian) and peripartum infection (4.1% non-Hispanic white compared with 4.9% non-Hispanic black compared with 6.4% Hispanic compared with 6.2% Asian) than others (P<.001 for both). Severe perineal laceration at spontaneous vaginal delivery was significantly more likely in Asian women (2.5% non-Hispanic white compared with 1.2% non-Hispanic black compared with 1.5% Hispanic compared with 5.5% Asian; P<.001). These disparities persisted in multivariable analysis. Many types of obstetric care examined also were significantly different according to race and ethnicity in both univariable and multivariable analysis. There were no significant interactions between race and ethnicity and hospital of delivery. Racial and ethnic disparities exist for multiple adverse obstetric outcomes and types of obstetric care and do not appear to be explained by differences in patient characteristics or by delivery hospital. II.

Racial and Ethnic Disparities in Maternal Morbidity and Obstetric Care

PubMed Central

Grobman, William A.; Bailit, Jennifer L.; Rice, Madeline Murguia; Wapner, Ronald J.; Reddy, Uma M.; Varner, Michael W.; Thorp, John M.; Leveno, Kenneth J.; Caritis, Steve N.; Iams, Jay D.; Tita, Alan T. N.; Saade, George; Rouse, Dwight J.; Blackwell, Sean C.; Tolosa, Jorge E.; VanDorsten, J. Peter

2015-01-01

Objective To evaluate whether racial and ethnic disparities exist in obstetric care and adverse outcomes. Methods We analyzed data from a cohort of women who delivered at 25 hospitals across the United States over a 3-year period. Race and ethnicity was categorized as Non-Hispanic white, Non-Hispanic black, Hispanic, or Asian. Associations between race and ethnicity and severe postpartum hemorrhage (PPH), peripartum infection, and severe perineal laceration at spontaneous vaginal delivery, as well as between race and ethnicity and obstetric care (eg, episiotomy) relevant to the adverse outcomes, were estimated by univariable analysis and multivariable logistic regression. Results Of 115,502 studied women, 95% were classified by one of the race and ethnicity categories. Non-Hispanic white women were significantly less likely to experience severe PPH (1.6% non-Hispanic white vs. 3.0% Non-Hispanic black vs. 3.1% Hispanic vs. 2.2%Asian) and peripartum infection (4.1% non-Hispanic white vs. 4.9% Non-Hispanic black vs. 6.4% Hispanic vs. 6.2% Asian) than others (P < 0.001 for both). Severe perineal laceration at spontaneous vaginal delivery was significantly more likely in Asian women (2.5% non-Hispanic white vs. 1.2% Non-Hispanic black vs. 1.5% Hispanic vs. 5.5% Asian) P< 0.001). These disparities persisted in multivariable analysis. Many types of obstetric care examined also were significantly different according to race and ethnicity in both univariable and multivariable analysis. There were no significant interactions between race and ethnicity and hospital of delivery. Conclusion Racial and ethnic disparities exist for multiple adverse obstetric outcomes and types of obstetric care, and do not appear to be explained by differences in patient characteristics or by delivery hospital. PMID:26000518

Community-acquired pneumonia in the elderly: A multivariate analysis of risk and prognostic factors.

PubMed

Riquelme, R; Torres, A; El-Ebiary, M; de la Bellacasa, J P; Estruch, R; Mensa, J; Fernández-Solá, J; Hernández, C; Rodriguez-Roisin, R

1996-11-01

To assess the risk and prognostic factors of community-acquired pneumonia occurring in the elderly (over age 65 yr) requiring hospitalization, two studies, case-control and cohort, were performed over an 8-mo period in a 1,000-bed university teaching hospital. We studied 101 patients with pneumonia (cases), age 78.5 +/- 7.9 yr (mean +/- SD). Each case was matched for sex, age (+/- 5 yr), and date of admission (+/- 2 d) with a control subject, without pneumonia during the preceding 3 yr, arriving at the emergency room. Etiologic diagnosis was obtained in 43 of 101 (42%) cases. The main microbial agents causing pneumonia were: Streptococcus pneumoniae (19 of 43, 44%), and Chlamydia pneumoniae (9 of 43, 21%). Gram-negative bacilli were uncommon (2 of 43, 5%). The multivariate analysis demonstrated that large-volume aspiration, and low serum albumin (< 30 mg/dl) were independent risk factors associated with the development of pneumonia. Crude mortality rate was 26% (26 of 101), while pneumonia-related mortality was 20% (20 of 101). The attributable mortality was 23% (odds ratio [OR]: 11.3; 95% confidence interval [CI]: 3.25 to 60.23; p < 0.0001). The multivariate analysis showed that patients had a worse prognosis if they were previously bedridden, had prior swallowing disorders, body temperature on admission was less than 37 degrees C, respiratory frequency was greater than 30/min or had three or more affected lobes on chest radiograph. Age by itself was not a significant factor related to prognosis. Among the significant risk factors, only nutritional status is probably amenable to medical intervention. The prognostic factors found in this study may help to identify, upon admission, those subjects at higher risk and who may require special observation.

Periprosthetic Joint Infection in Hip Arthroplasty: Is There an Association Between Infection and Bearing Surface Type?

PubMed

Pitto, Rocco P; Sedel, Laurent

2016-10-01

Preliminary studies have raised the question of whether certain prosthetic biomaterials used in total hip arthroplasty (THA) bearings are associated with increased risk of periprosthetic joint infection (PJI). For example, some observational data suggest the risk of PJI is higher with metal-on-metal bearings. However, it is not known whether other bearings-including ceramic bearings or metal-on-polyethylene bearings-may be associated with a higher or lower risk of PJI. The objective of this study was to use a national arthroplasty registry to assess whether the choice of bearings-metal-on-polyethylene (MoP), ceramic-on-polyethylene (CoP), ceramic-on-ceramic (CoC), or metal-on-metal (MoM)-is associated with differences in the risk of revision for deep infection, either (1) within 6 months or (2) over the entire period of observation, which spanned 15 years. Data from primary THAs were extracted from the New Zealand Joint Registry over a 15-year period. A total of 97,889 hips were available for analysis. Inclusion criterion was degenerative joint disease; exclusion criteria were previous surgery, trauma, and any other diagnosis (12,566 hips). We also excluded a small group of ceramic-on-metal THAs (429) with short followup. The median observation period of the selected group of hips (84,894) was 9 years (range, 1-15 years). The mean age of patients was 68 years (SD ± 11 years), and 52% were women. There were 54,409 (64%) MoP, 16,503 (19%) CoP, 9051 (11%) CoC, and 4931 (6%) MoM hip arthroplasties. Four hundred one hips were revised for deep infection. A multivariate assessment was carried out including the following risks factors available for analysis: age, sex, operating room type, use of body exhaust suits, THA fixation mode, and surgeon volume. Because of late introduction of data collection in the Registry, we were unable to include body mass index (BMI, recording started 2010) and medical comorbidities according to the American Society of Anesthesiologists class (ASA, recording started 2005) in the multivariate analysis. The rate of early PJI (< 6 months) did not differ by bearing surface. In contrast, we observed a difference over the total observation period. Within the first 6 months after the index surgery, CoC THAs were not associated with a lower risk of revision for PJI (p = 0.118) when compared with CoP (hazard ratio [HR], 1.31; 95% confidence interval [CI], 0.50-3.41), MoP (HR, 2.10; CI, 0.91-4.82), and MoM (HR, 2.04; CI, 0.69-6.09). When the whole observation period was considered, CoC hips were associated with a lower risk of revision for deep infection when compared with CoP (HR, 1.30; CI, 0.78-2.18; p = 0.01), MoP (HR, 1.75; CI, 1.07-2.86; p = 0.02), and MoM (HR, 2.12; CI, 1.23-3.65; p = 0.008). Our finding associating CoC THA bearings with a lower risk of infection after THA must be considered very preliminary, and we caution readers against attributing all of the observed difference to the bearing surface. It is possible that some or all of the observed difference associated with bearing type may have been driven by other factors such as ASA and BMI, which could not be included in our multivariate analysis, and so future registry studies on this topic must assess those variables carefully. Level III, therapeutic study.

Factors associated with intern noncompliance with the 2003 Accreditation Council for Graduate Medical Education’s 30-hour duty period requirement

PubMed Central

2012-01-01

Background In 2003 the Accreditation Council for Graduate Medical Education mandated work hour restrictions. Violations can results in a residency program being cited or placed on probation. Recurrent violations could results in loss of accreditation. We wanted to determine specific intern and workload factors associated with violation of a specific mandate, the 30-hour duty period requirement. Methods Retrospective review of interns’ performance against the 30-hour duty period requirement during inpatient ward rotations at a pediatric residency program between June 24, 2008 and June 23, 2009. The analytical plan included both univariate and multivariable logistic regression analyses. Results Twenty of the 26 (77%) interns had 80 self-reported episodes of continuous work hours greater than 30 hours. In multivariable analysis, noncompliance was inversely associated with the number of prior inpatient rotations (odds ratio: 0.49, 95% confidence interval (0.38, 0.64) per rotation) but directly associated with the total number of patients (odds ratio: 1.30 (1.10, 1.53) per additional patient). The number of admissions on-call, number of admissions after midnight and number of discharges post-call were not significantly associated with noncompliance. The level of noncompliance also varied significantly between interns after accounting for intern experience and workload factors. Subject to limitations in statistical power, we were unable to identify specific intern characteristics, such as demographic variables or examination scores, which account for the variation in noncompliance between interns. Conclusions Both intern and workload factors were associated with pediatric intern noncompliance with the 30-hour duty period requirement during inpatient ward rotations. Residency programs must develop information systems to understand the individual and experience factors associated with noncompliance and implement appropriate interventions to ensure compliance with the duty hour regulations. PMID:22621439

Impact of Reproductive History and Exogenous Hormone Use on Cognitive Function in Midlife and Late Life

PubMed Central

Karim, Roksana; Dang, Ha; Henderson, Victor W.; Hodis, Howard N.; St John, Jan; Brinton, Roberta D.; Mack, Wendy J.

2016-01-01

Background/objectives Given the potent role of sex hormones on brain chemistry and function, we investigated the association of reproductive history indicators of hormonal exposures, including reproductive period, pregnancy, and use of hormonal contraceptives, on mid- and late-life cognition in postmenopausal women. Design Analysis of baseline data from two randomized clinical trials, the Women’s Isoflavone Soy Health (WISH) and the Early vs Late Intervention Trial of Estradiol (ELITE). Setting University academic research center Participants 830 naturally menopausal women Measurements Participants were uniformly evaluated with a cognitive battery and a structured reproductive history. Outcomes were composite scores for verbal episodic memory, executive functions, and global cognition. Reproductive variables included ages at pregnancies, menarche, and menopause, reproductive period, number of pregnancies, and use of hormones for contraception and menopausal symptoms. Multivariable linear regression evaluated associations between cognitive scores (dependent variable) and reproductive factors (independent variables), adjusting for age, race/ethnicity, income and education. Results On multivariable modeling, age at menarche ≥ 13 years of age was inversely associated with global cognition (p= 0.05). Last pregnancy after age 35 was positively associated with verbal memory (p=0.03). Use of hormonal contraceptives was positively associated with global cognition (p trend=0.04), and verbal memory (p trend=0.007). The association between hormonal contraceptive use and verbal memory and executive functions was strongest for more than 10 years of use. Reproductive period was positively associated with global cognition (p=0.04) and executive functions (p=0.04). Conclusion In this sample of healthy postmenopausal women, reproductive life events related to sex hormones, including earlier age at menarche, later age at last pregnancy, length of reproductive period, and use of oral contraceptives are positively related to aspects of cognition in later life. PMID:27996108

Factors associated with intern noncompliance with the 2003 Accreditation Council for Graduate Medical Education's 30-hour duty period requirement.

PubMed

Maloney, Christopher G; Antommaria, Armand H Matheny; Bale, James F; Ying, Jian; Greene, Tom; Srivastava, Rajendu

2012-07-13

In 2003 the Accreditation Council for Graduate Medical Education mandated work hour restrictions. Violations can results in a residency program being cited or placed on probation. Recurrent violations could results in loss of accreditation. We wanted to determine specific intern and workload factors associated with violation of a specific mandate, the 30-hour duty period requirement. Retrospective review of interns' performance against the 30-hour duty period requirement during inpatient ward rotations at a pediatric residency program between June 24, 2008 and June 23, 2009. The analytical plan included both univariate and multivariable logistic regression analyses. Twenty of the 26 (77%) interns had 80 self-reported episodes of continuous work hours greater than 30 hours. In multivariable analysis, noncompliance was inversely associated with the number of prior inpatient rotations (odds ratio: 0.49, 95% confidence interval (0.38, 0.64) per rotation) but directly associated with the total number of patients (odds ratio: 1.30 (1.10, 1.53) per additional patient). The number of admissions on-call, number of admissions after midnight and number of discharges post-call were not significantly associated with noncompliance. The level of noncompliance also varied significantly between interns after accounting for intern experience and workload factors. Subject to limitations in statistical power, we were unable to identify specific intern characteristics, such as demographic variables or examination scores, which account for the variation in noncompliance between interns. Both intern and workload factors were associated with pediatric intern noncompliance with the 30-hour duty period requirement during inpatient ward rotations. Residency programs must develop information systems to understand the individual and experience factors associated with noncompliance and implement appropriate interventions to ensure compliance with the duty hour regulations.

A population-based analysis of temporal perioperative complication rates after minimally invasive radical prostatectomy.

PubMed

Schmitges, Jan; Trinh, Quoc-Dien; Abdollah, Firas; Sun, Maxine; Bianchi, Marco; Budäus, Lars; Zorn, Kevin; Perotte, Paul; Schlomm, Thorsten; Haese, Alexander; Montorsi, Francesco; Menon, Mani; Graefen, Markus; Karakiewicz, Pierre I

2011-09-01

Existing population-based reports on complication rates after minimally invasive radical prostatectomy (MIRP) did not address temporal trends. To examine contemporary temporal trends in perioperative MIRP outcomes. Between 2001 and 2007, 4387 patients undergoing MIRP were identified using the Nationwide Inpatient Sample. To examine the rates and trends of intraoperative and postoperative complications, transfusion rates, length of stay in excess of the median, and in-hospital mortality. We tested the effect of the late (2006-2007) versus the early (2001-2005) study period on all outcomes using multivariable logistic regression models controlled for clustering among hospitals. Intraoperative and postoperative complications decreased from 7.0% to 0.8% (p < 0.001) and from 28.5% to 8.7% (p < 0.001), respectively. Transfusion rates decreased from 3.5% to 2.1% (p = 0.3). Hospital length of stay >2 d decreased from 56% to 15% (p < 0.001). In multivariable analyses, intraoperative (odds ratio [OR]: 0.41; p = 0.002) and postoperative (OR: 0.65; p = 0.007) complications were less frequent in the late versus the early study period. Late study period patients were less likely to stay >2 d than early study period patients (OR: 0.34; p > 0.001). Limitations of these findings include the lack of adjustment for several patient variables including disease characteristics, surgeon variables including surgeon caseload, and the restriction to in-hospital events. Our analyses demonstrate that in-hospital complication rates and length of stay after MIRP decreased over time. This implies that temporal differences specific to complication rates after MIRP must be considered when comparisons are made with other radical prostatectomy techniques. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

What matters? Assessing and developing inquiry and multivariable reasoning skills in high school chemistry

NASA Astrophysics Data System (ADS)

Daftedar Abdelhadi, Raghda Mohamed

Although the Next Generation Science Standards (NGSS) present a detailed set of Science and Engineering Practices, a finer grained representation of the underlying skills is lacking in the standards document. Therefore, it has been reported that teachers are facing challenges deciphering and effectively implementing the standards, especially with regards to the Practices. This analytical study assessed the development of high school chemistry students' (N = 41) inquiry, multivariable causal reasoning skills, and metacognition as a mediator for their development. Inquiry tasks based on concepts of element properties of the periodic table as well as reaction kinetics required students to conduct controlled thought experiments, make inferences, and declare predictions of the level of the outcome variable by coordinating the effects of multiple variables. An embedded mixed methods design was utilized for depth and breadth of understanding. Various sources of data were collected including students' written artifacts, audio recordings of in-depth observational groups and interviews. Data analysis was informed by a conceptual framework formulated around the concepts of coordinating theory and evidence, metacognition, and mental models of multivariable causal reasoning. Results of the study indicated positive change towards conducting controlled experimentation, making valid inferences and justifications. Additionally, significant positive correlation between metastrategic and metacognitive competencies, and sophistication of experimental strategies, signified the central role metacognition played. Finally, lack of consistency in indicating effective variables during the multivariable prediction task pointed towards the fragile mental models of multivariable causal reasoning the students had. Implications for teacher education, science education policy as well as classroom research methods are discussed. Finally, recommendations for developing reform-based chemistry curricula based on the Practices are presented.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

Impact of specialized inpatient IBD care on outcomes of IBD hospitalizations: A cohort study

PubMed Central

Law, Cindy CY; Sasidharan, Saranya; Rodrigues, Rodrigo; Nguyen, Deanna D; Sauk, Jenny; Garber, John; Giallourakis, Cosmas; Xavier, Ramnik; Khalili, Hamed; Yajnik, Vijay; Ananthakrishnan, Ashwin N

2016-01-01

Background The management of inflammatory bowel diseases (IBD; Crohn’s disease (CD), ulcerative colitis (UC)) is increasingly complex. Specialized care has been associated with improved ambulatory IBD outcomes. Aims To examine if the implementation of specialized inpatient IBD care modified short and long-term clinical outcomes in IBD-related hospitalizations. Methods This retrospective cohort study included IBD patients hospitalized between July 2013 and April 2015 at a single tertiary referral center where a specialized inpatient IBD care model was implemented in July 2014. In-hospital medical and surgical outcomes as well as post-discharge outcomes at 30 and 90 days were analyzed along with measures of quality of in-hospital care. Effect of specialist IBD care was examined on multivariate analysis. Results A total of 408 IBD-related admissions were included. With implementation of specialized IBD inpatient care, we observed increased frequency of use of high-dose biologic therapy for induction (26% vs. 9%, odds ratio (OR) 5.50, 95% CI 1.30 – 23.17) and higher proportion of patients in remission at 90 days after discharge (multivariate OR 1.60, 95% CI 0.99 – 2.69). While there was no difference in surgery by 90 days, among those who underwent surgery, early surgery defined as in-hospital or within 30 days of discharge, was more common in the study period (71%) compared to the control period (46%, multivariate OR 2.73, 95% CI 1.22 – 6.12). There was no difference in length of stay between the two years. Conclusions Implementation of specialized inpatient IBD care beneficially impacted remission and facilitated early surgical treatment. PMID:27482978

Exploring effects of therapeutic massage and patient teaching in the practice of diaphragmatic breathing on blood pressure, stress, and anxiety in hypertensive African-American women: an intervention study.

PubMed

Jefferson, Lenetra L

2010-07-01

The problem of hypertension among African-Americans is one of the major areas of health disparities. The American Heart Association (2009) noted that the prevalence of hypertension among African-Americans is perhaps among the highest in the world and this is particularly so among African-American women (44.0%). The purpose of this study was to determine how therapeutic chair massage and patient teaching in diaphragmatic breathing affected African-American women's blood pressure, stress, and anxiety levels over one week or six weeks time periods. A Modified Stress, Coping, and Adaptation Model (Roy, 1976; Lazarus, 1966), Descriptives, T-tests, Pearson Product Moment Correlations, Multivariate analysis of variance (MANOVA), and Multivariate analysis of variance with covariate (MANCOVA) were used. Descriptive statistics indicated a significance for decreased systolic blood pressure levels for the one week post massage intervention measurement with p = .01, diastolic blood pressure level significance for the same group p = .02, significance for this group's State Trait Anxiety Inventory (STAI) Y2 Scale score p = .01, and Roy's Largest Root p = .03.

Clinical factors affecting pathological fracture and healing of unicameral bone cysts

PubMed Central

2014-01-01

Background Unicameral bone cyst (UBC) is the most common benign lytic bone lesion seen in children. The aim of this study is to investigate clinical factors affecting pathological fracture and healing of UBC. Methods We retrospectively reviewed 155 UBC patients who consulted Nagoya musculoskeletal oncology group hospitals in Japan. Sixty of the 155 patients had pathological fracture at presentation. Of 141 patients with follow-up periods exceeding 6 months, 77 were followed conservatively and 64 treated by surgery. Results The fracture risk was significantly higher in the humerus than other bones. In multivariate analysis, ballooning of bone, cyst in long bone, male sex, thin cortical thickness and multilocular cyst were significant adverse prognostic factors for pathological fractures at presentation. The healing rates were 30% and 83% with observation and surgery, respectively. Multivariate analysis revealed that fracture at presentation and history of biopsy were good prognostic factors for healing of UBC in patients under observation. Conclusion The present results suggest that mechanical disruption of UBC such as fracture and biopsy promotes healing, and thus watchful waiting is indicated in these patients, whereas patients with poor prognostic factors for fractures should be considered for surgery. PMID:24884661

Clinical factors affecting pathological fracture and healing of unicameral bone cysts.

PubMed

Urakawa, Hiroshi; Tsukushi, Satoshi; Hosono, Kozo; Sugiura, Hideshi; Yamada, Kenji; Yamada, Yoshihisa; Kozawa, Eiji; Arai, Eisuke; Futamura, Naohisa; Ishiguro, Naoki; Nishida, Yoshihiro

2014-05-17

Unicameral bone cyst (UBC) is the most common benign lytic bone lesion seen in children. The aim of this study is to investigate clinical factors affecting pathological fracture and healing of UBC. We retrospectively reviewed 155 UBC patients who consulted Nagoya musculoskeletal oncology group hospitals in Japan. Sixty of the 155 patients had pathological fracture at presentation. Of 141 patients with follow-up periods exceeding 6 months, 77 were followed conservatively and 64 treated by surgery. The fracture risk was significantly higher in the humerus than other bones. In multivariate analysis, ballooning of bone, cyst in long bone, male sex, thin cortical thickness and multilocular cyst were significant adverse prognostic factors for pathological fractures at presentation. The healing rates were 30% and 83% with observation and surgery, respectively. Multivariate analysis revealed that fracture at presentation and history of biopsy were good prognostic factors for healing of UBC in patients under observation. The present results suggest that mechanical disruption of UBC such as fracture and biopsy promotes healing, and thus watchful waiting is indicated in these patients, whereas patients with poor prognostic factors for fractures should be considered for surgery.

CRISP: Catheterization RISk score for Pediatrics: A Report from the Congenital Cardiac Interventional Study Consortium (CCISC).

PubMed

Nykanen, David G; Forbes, Thomas J; Du, Wei; Divekar, Abhay A; Reeves, Jaxk H; Hagler, Donald J; Fagan, Thomas E; Pedra, Carlos A C; Fleming, Gregory A; Khan, Danyal M; Javois, Alexander J; Gruenstein, Daniel H; Qureshi, Shakeel A; Moore, Phillip M; Wax, David H

2016-02-01

We sought to develop a scoring system that predicts the risk of serious adverse events (SAE's) for individual pediatric patients undergoing cardiac catheterization procedures. Systematic assessment of risk of SAE in pediatric catheterization can be challenging in view of a wide variation in procedure and patient complexity as well as rapidly evolving technology. A 10 component scoring system was originally developed based on expert consensus and review of the existing literature. Data from an international multi-institutional catheterization registry (CCISC) between 2008 and 2013 were used to validate this scoring system. In addition we used multivariate methods to further refine the original risk score to improve its predictive power of SAE's. Univariate analysis confirmed the strong correlation of each of the 10 components of the original risk score with SAE attributed to a pediatric cardiac catheterization (P < 0.001 for all variables). Multivariate analysis resulted in a modified risk score (CRISP) that corresponds to an increase in value of area under a receiver operating characteristic curve (AUC) from 0.715 to 0.741. The CRISP score predicts risk of occurrence of an SAE for individual patients undergoing pediatric cardiac catheterization procedures. © 2015 Wiley Periodicals, Inc.

Silicosis prevalence and risk factors in semi-precious stone mining in Brazil.

PubMed

Souza, Tamires P; Watte, Guilherme; Gusso, Alaíde M; Souza, Rafaela; Moreira, José da S; Knorst, Marli M

2017-06-01

Underground mining generates large amounts of dust and exposes workers to silica. This study aims to determine the prevalence and predictor factors for the development of silicosis among semi-precious-stone mineworkers in southern Brazil working in a self-administered cooperative. In a cross-sectional study of 348 current workers and retirees, demographic data, medical, and occupational history were collected through an interview performed by a nurse and medical record review. Risk factor associations were studied by Poisson multivariate regression. The overall prevalence of silicosis was 37%, while in current miners it was 28%. Several risk factors for silicosis were identified in the univariate analysis. Inadequate ventilation in the underground galleries combined with dry drilling, duration of silica exposure, and (inversely) education remained significant in the multivariate analysis (P < 0.05). This study is unusual in studying semi-precious stone mineworkers in a self-administered worker cooperative with limited resources. The prevalence of silicosis was very high. A number of recommendations are made-including technical support for worker cooperatives, surveillance of silica exposure and silicosis, exposure reduction measures, and benefits allowing impaired miners to leave the industry. © 2017 Wiley Periodicals, Inc.

Gap Shape Classification using Landscape Indices and Multivariate Statistics

PubMed Central

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-01-01

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

Chronic osteomyelitis correlates with increased risk of acute pancreatitis in a case-control study in Taiwan.

PubMed

Lai, Shih-Wei; Lai, Hsueh-Chou; Lin, Cheng-Li; Liao, Kuan-Fu; Tseng, Chun-Hung

2015-07-01

The objective of this study was to examine the relationship between chronic osteomyelitis and acute pancreatitis in Taiwan. This was a population-based case-control study utilizing the database of the Taiwan National Health Insurance Program. We identified 7678 cases aged 20-84 with newly diagnosed acute pancreatitis during the period of 1998 to 2011. From the same database, 30,712 subjects without diagnosis of acute pancreatitis were selected as controls. The cases and controls were matched with sex, age and index year of diagnosing acute pancreatitis. The odds ratio with 95% confidence interval of acute pancreatitis associated with chronic osteomyelitis was examined by the multivariable unconditional logistic regression analysis. After adjustment for multiple confounders, the multivariable analysis showed that the adjusted odds ratio of acute pancreatitis was 1.93 for subjects with chronic osteomyelitis (95% confidence interval 1.01, 3.69), when compared with subjects without chronic osteomyelitis. Chronic osteomyelitis correlates with increased risk of acute pancreatitis. Patients with chronic osteomyelitis should be carefully monitored about the risk of acute pancreatitis. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Quality of Acute Care for Patients With Urinary Stones in the United States.

PubMed

Scales, Charles D; Bergman, Jonathan; Carter, Stacey; Jack, Gregory; Saigal, Christopher S; Litwin, Mark S

2015-11-01

To describe guideline adherence for patients with suspected upper tract stones. We performed a cross-sectional analysis of visits recorded by the National Hospital Ambulatory Medical Care Survey (emergency department [ED] component) in 2007-2010 (most recent data). We assessed adherence to clinical guidelines for diagnostic laboratory testing, imaging, and pharmacologic therapy. Multivariable regression models controlled for important covariates. An estimated 4,956,444 ED visits for patients with suspected kidney stones occurred during the study period. Guideline adherence was highest for diagnostic imaging, with 3,122,229 (63%) visits providing optimal imaging. Complete guideline-based laboratory testing occurred in only 2 of every 5 visits. Pharmacologic therapy to facilitate stone passage was prescribed during only 17% of eligible visits. In multivariable analysis of guideline adherence, we found little variation by patient, provider, or facility characteristics. Guideline-recommended care was absent from a substantial proportion of acute care visits for patients with suspected kidney stones. These failures of care delivery likely increase costs and temporary disability. Targeted interventions to improve guideline adherence should be designed and evaluated to improve care for patients with symptomatic kidney stones. Published by Elsevier Inc.

Quality of Acute Care for Patients with Urinary Stones in the United States

PubMed Central

Scales, Charles D.; Bergman, Jonathan; Carter, Stacey; Jack, Gregory; Saigal, Christopher S.; Litwin, Mark S.

2015-01-01

Objective To describe guideline adherence for patients with suspected upper tract stones. Methods We performed a cross-sectional analysis of visits recorded by the National Hospital Ambulatory Medical Care Survey (ED component) in 2007–2010 (most recent data). We assessed adherence to clinical guidelines for diagnostic laboratory testing, imaging, and pharmacologic therapy. Multivariable regression models controlled for important covariates. Results An estimated 4,956,444 ED visits for patients with suspected kidney stones occurred during the study period. Guideline adherence was highest for diagnostic imaging, with 3,122,229 (63%) visits providing optimal imaging. Complete guideline-based laboratory testing occurred in only 2 of every 5 visits. Pharmacologic therapy to facilitate stone passage was prescribed during only 17% of eligible visits. In multivariable analysis of guideline adherence, we found little variation by patient, provider or facility characteristics. Conclusions Guideline-recommended care was absent from a substantial proportion of acute care visits for patients with suspected kidney stones. These failures of care delivery likely increase costs and temporary disability. Targeted interventions to improve guideline adherence should be designed and evaluated to improve care for patients with symptomatic kidney stones. PMID:26335495

Gap Shape Classification using Landscape Indices and Multivariate Statistics.

PubMed

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-11-30

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

Changing epidemiology of pediatric Staphylococcus aureus bacteremia in Denmark from 1971 through 2000.

PubMed

Frederiksen, Marianne Sjølin; Espersen, Frank; Frimodt-Møller, Niels; Jensen, Allan Garlik; Larsen, Anders Rhod; Pallesen, Lars Villiam; Skov, Robert; Westh, Henrik; Skinhøj, Peter; Benfield, Thomas

2007-05-01

Staphylococcus aureus is known to be a leading cause of bacteremia in childhood, and is associated with severe morbidity and increased mortality. To determine developments in incidence and mortality rates, as well as risk factors associated with outcome, we analyzed data from 1971 through 2000. Nationwide registration of S. aureus bacteremia (SAB) among children and adolescents from birth to 20 years of age was performed. Data on age, sex, source of bacteremia, comorbidity and outcome were extracted from discharge records. Rates were population adjusted and risk factors for death were assessed by multivariate logistic regression analysis. During the 30-year study period, 2648 cases of SAB were reported. Incidence increased from 4.6 to 8.4 cases per 100,000 population and case-mortality rates decreased from 19.6% to 2.5% (P = 0.0001). Incidence in the infant age group (<1 year) were 10- to 17-fold greater compared with that in the other age strata and mortality rate was twice as high. Hospital-acquired infections dominated the infant group, accounting for 73.9%-91.0% versus 39.2%-50.5% in the other age groups. By multivariate analysis, pulmonary infection and endocarditis for all age groups, comorbidity for the older than 1 year, and hospital-acquired infections for the oldest group were independently associated with an increased risk of death. Mortality rates associated with SAB decreased significantly in the past 3 decades, possibly because of new and improved treatment modalities. However, incidence rates have increased significantly in the same period, underscoring that S. aureus remains an important invasive pathogen.

First line treatment of aplastic anemia with thymoglobuline in Europe and Asia: Outcome of 955 patients treated 2001-2012.

PubMed

Bacigalupo, Andrea; Oneto, Rosi; Schrezenmeier, Hubert; Hochsmann, Britta; Dufour, Carlo; Kojima, Seiji; Zhu, Xiaofan; Chen, Xiaojuan; Issaragrisil, Surapol; Chuncharunee, Suporn; Jeong, Dae Chul; Giammarco, Sabrina; Van Lint, Maria Teresa; Zheng, Yizhou; Vallejo, Carlos

2018-05-01

The aim of this study was to assess the outcome of patients with aplastic anemia (AA), receiving rabbit anti-thymocyte globulin (Thymoglobulin, SANOFI) and cyclosporin, as first line treatment. Eligible were 955 patients with AA, treated first line with Thymoglobulin, between 2001 and 2008 (n = 492), or between 2009 and 2012 (n = 463). The median age of the patients was 21 years (range 1-84). Mortality within 90 days was 5.7% and 2.4%, respectively in the two time periods (P = .007).The actuarial 10-year survival for the entire population was 70%; transplant free survival was 64%. Predictors of survival in multivariate analysis, were severity of the disease, patients age and the interval between diagnosis and treatment. Survival was 87% vs 61% for responders at 6 months versus nonresponders (P < .0001). The 10-year survival of nonresponders at 6 months, undergoing a subsequent transplant (n = 110), was 64%, vs 60% for patient not transplantated (n = 266) (P = .1). The cumulative incidence of response was 37%, 52%, 65% respectively, at 90, 180, and 365 days. In multivariate analysis, negative predictors of response at 6 months, were older age, longer interval diagnosis treatment, and greater severity of the disease. In conclusion, early mortality is low after first line treatment of AA with Thymoglobulin, and has been further reduced after year 2008. Patients age, together with interval diagnosis-treament and severity of the disease, remain strong predictors of response and survival. © 2018 Wiley Periodicals, Inc.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.

PubMed

Goldrick, Stephen; Holmes, William; Bond, Nicholas J; Lewis, Gareth; Kuiper, Marcel; Turner, Richard; Farid, Suzanne S

2017-10-01

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (Ambr TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population

PubMed Central

Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2015-01-01

Background Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. Methods and Results We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Conclusions Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. PMID:26224048

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Antrochoanal polyposis: a review of 33 cases.

PubMed

Cook, P R; Davis, W E; McDonald, R; McKinsey, J P

1993-06-01

We report on a series of 33 consecutive cases of antrochoanal polyp (ACP) treated by endoscopic sinus surgery over a five-year period. All but one patient was treated by endoscopic sinus surgery alone. This method of treatment was quite effective for ACPs. These 33 patients represent 22.3% of all nasal polyp patients on whom we operated during the same period. This incidence of ACP is greater than that generally reported in the literature. Some authors have attempted to distinguish ACPs from common nasal polyps primarily on the basis of morphology, histology, and the clinical behavior of the ACPs. In our series, a multivariate analysis, including histopathologic correlation, did not support the notion that ACPs are clearly distinct from common nasal polyps. Some interesting differences between the polyp groups did, however, become evident in our data analysis. Generally, ACPs are not thought to be associated with allergic disease; however, in our series we found the association of allergic disease with ACPs to be statistically significant (Chi-square = 4.575, p < .05).

Prognostic value of lymphovascular invasion of the primary tumor in hypopharyngeal carcinoma after total laryngopharyngectomy.

PubMed

Saito, Yuki; Omura, Go; Yasuhara, Kazuo; Rikitake, Ryoko; Akashi, Ken; Fukuoka, Osamu; Yoshida, Masafumi; Ando, Mizuo; Asakage, Takahiro; Yamasoba, Tatsuya

2017-08-01

We aimed to determinate the prognostic value of lymphovascular invasion in the specimens resected during total laryngopharyngectomy for hypopharyngeal carcinoma. Patients who underwent total laryngopharyngectomy at our institution between 2004 and 2014 were included in this study and retrospectively analyzed. We then discriminated for vascular invasion and lymphatic invasion of the primary tumor in all cases. We reviewed 135 records (120 men and 15 women; age range, 36-84 years). Tumors with lymphatic invasion tended to be associated with more metastatic lymph nodes and extracapsular spread (ECS) of metastatic lymph nodes. Tumors with vascular invasion tended to be associated with nonpyriform sinus locations. In a multivariate analysis, nonpyriform sinus locations, >3 metastatic lymph nodes, and vascular invasion remained significant prognostic factors for overall survival (OS); in recursive partitioning analysis, ECS and vascular invasion remained important categorical variables for OS. Vascular invasion is a strong prognostic biomarker for advanced hypopharyngeal carcinoma. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1535-1543, 2017. © 2017 Wiley Periodicals, Inc.

A modal analysis of flexible aircraft dynamics with handling qualities implications

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

A multivariable modal analysis technique is presented for evaluating flexible aircraft dynamics, focusing on meaningful vehicle responses to pilot inputs and atmospheric turbulence. Although modal analysis is the tool, vehicle time response is emphasized, and the analysis is performed on the linear, time-domain vehicle model. In evaluating previously obtained experimental pitch tracking data for a family of vehicle dynamic models, it is shown that flexible aeroelastic effects can significantly affect pitch attitude handling qualities. Consideration of the eigenvalues alone, of both rigid-body and aeroelastic modes, does not explain the simulation results. Modal analysis revealed, however, that although the lowest aeroelastic mode frequency was still three times greater than the short-period frequency, the rigid-body attitude response was dominated by this aeroelastic mode. This dominance was defined in terms of the relative magnitudes of the modal residues in selected vehicle responses.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

A power analysis for multivariate tests of temporal trend in species composition.

PubMed

Irvine, Kathryn M; Dinger, Eric C; Sarr, Daniel

2011-10-01

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that monitor entire multispecies assemblages require a method for determining the power of multivariate statistical models to detect trend. We provide a method to simulate presence-absence species assemblage data that are consistent with increasing or decreasing directional change in species composition within multiple sites. This step is the foundation for using Monte Carlo methods to approximate the power of any multivariate method for detecting temporal trends. We focus on comparing the power of the Mantel test, permutational multivariate analysis of variance, and constrained analysis of principal coordinates. We find that the power of the various methods we investigate is sensitive to the number of species in the community, univariate species patterns, and the number of sites sampled over time. For increasing directional change scenarios, constrained analysis of principal coordinates was as or more powerful than permutational multivariate analysis of variance, the Mantel test was the least powerful. However, in our investigation of decreasing directional change, the Mantel test was typically as or more powerful than the other models.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

A climatology of total ozone mapping spectrometer data using rotated principal component analysis

NASA Astrophysics Data System (ADS)

Eder, Brian K.; Leduc, Sharon K.; Sickles, Joseph E.

1999-02-01

The spatial and temporal variability of total column ozone (Ω) obtained from the total ozone mapping spectrometer (TOMS version 7.0) during the period 1980-1992 was examined through the use of a multivariate statistical technique called rotated principal component analysis. Utilization of Kaiser's varimax orthogonal rotation led to the identification of 14, mostly contiguous subregions that together accounted for more than 70% of the total Ω variance. Each subregion displayed statistically unique Ω characteristics that were further examined through time series and spectral density analyses, revealing significant periodicities on semiannual, annual, quasi-biennial, and longer term time frames. This analysis facilitated identification of the probable mechanisms responsible for the variability of Ω within the 14 homogeneous subregions. The mechanisms were either dynamical in nature (i.e., advection associated with baroclinic waves, the quasi-biennial oscillation, or El Niño-Southern Oscillation) or photochemical in nature (i.e., production of odd oxygen (O or O3) associated with the annual progression of the Sun). The analysis has also revealed that the influence of a data retrieval artifact, found in equatorial latitudes of version 6.0 of the TOMS data, has been reduced in version 7.0.

Statistical polarization in greenhouse gas emissions: Theory and evidence.

PubMed

Remuzgo, Lorena; Trueba, Carmen

2017-11-01

The current debate on climate change is over whether global warming can be limited in order to lessen its impacts. In this sense, evidence of a decrease in the statistical polarization in greenhouse gas (GHG) emissions could encourage countries to establish a stronger multilateral climate change agreement. Based on the interregional and intraregional components of the multivariate generalised entropy measures (Maasoumi, 1986), Gigliarano and Mosler (2009) proposed to study the statistical polarization concept from a multivariate view. In this paper, we apply this approach to study the evolution of such phenomenon in the global distribution of the main GHGs. The empirical analysis has been carried out for the time period 1990-2011, considering an endogenous grouping of countries (Aghevli and Mehran, 1981; Davies and Shorrocks, 1989). Most of the statistical polarization indices showed a slightly increasing pattern that was similar regardless of the number of groups considered. Finally, some policy implications are commented. Copyright © 2017 Elsevier Ltd. All rights reserved.

B-mode sonographic criteria for differential diagnosis of cervicofacial lymphadenopathy in cat-scratch disease and toxoplasmosis.

PubMed

Ridder, Gerd Jürgen; Boedeker, Carsten Christof; Lee, Tao-Kwang Kevin; Sander, Anna

2003-04-01

Our purpose was to evaluate different sonographic parameters of cervicofacial lymphadenopathy caused by cat-scratch disease (CSD) and toxoplasmosis. By use of high-resolution B-mode sonography a total of 552 lymph nodes in the head and neck were detected between January 1997 and December 2001. There were 71 patients (422 lymph nodes) with CSD and 19 patients (130 lymph nodes) with toxoplasmosis. Sonographic variables, including 20 sonomorphologic features along with age and gender, were analyzed with multivariate logistic regression. Heterogenous lymph nodes were more often found in CSD (p =.003), and nonsharp nodal borders showed a significant association with CSD (p =.0005). Multivariate analysis identified sharpness of borders (p =.0001), S/L ratio (p =.0006), and type of lymphadenopathy (acute, abscessed, chronic) (p =.0006) as most significant for differentiating between CSD and toxoplasmosis. These results provide significant and useful criteria for ultrasonographic differentiation between CSD and toxoplasmosis. Copyright 2003 Wiley Periodicals, Inc.

Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks.

PubMed

Faes, Luca; Nollo, Giandomenico; Krohova, Jana; Czippelova, Barbora; Turianikova, Zuzana; Javorka, Michal

2017-07-01

To fully elucidate the complex physiological mechanisms underlying the short-term autonomic regulation of heart period (H), systolic and diastolic arterial pressure (S, D) and respiratory (R) variability, the joint dynamics of these variables need to be explored using multivariate time series analysis. This study proposes the utilization of information-theoretic measures to measure causal interactions between nodes of the cardiovascular/cardiorespiratory network and to assess the nature (synergistic or redundant) of these directed interactions. Indexes of information transfer and information modification are extracted from the H, S, D and R series measured from healthy subjects in a resting state and during postural stress. Computations are performed in the framework of multivariate linear regression, using bootstrap techniques to assess on a single-subject basis the statistical significance of each measure and of its transitions across conditions. We find patterns of information transfer and modification which are related to specific cardiovascular and cardiorespiratory mechanisms in resting conditions and to their modification induced by the orthostatic stress.

The Potential of Multivariate Analysis in Assessing Students' Attitude to Curriculum Subjects

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…

Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects.

PubMed

Thulin, M

2016-09-10

Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

Spatio-temporal variational characteristics analysis of heavy metals pollution in water of the typical northern rivers, China

NASA Astrophysics Data System (ADS)

Lu, Hongwei; Yu, Sen

2018-04-01

The rapid urbanization and industrialization in developing countries have increased pollution by heavy metals, which is a concern for human health and the environment. In this study, according to the data obtained from the monitoring stations in the Songhua River basin, the multivariate statistical analysis methods are applied to the hydrological data of the Songhua River basin in order to examine the relation between human activities and the spatio-temporal change of heavy metals (Pb and Cu) in water. By comparing the concentrations at different flow periods, the minimum Pb concentrations are found to have occurred most frequently in low flow periods while the maximum values mostly appeared in average flow periods. Moreover, the minimum Cu concentration in the water frequently occurred in high flow periods. The results show there are low Pb and Cu concentrations in upstream and downstream sections and high concentrations in mid-stream sections, and high concentrations are most frequently measured in the sections of Ashihe' downstream and estuary. Moreover, we have predicted the future (during 2018-2025) trend of the change for the heavy metals pollution in the rivers. The results demonstrated intense human activities are the most important factor causing jump features of typical heavy metal pollution in the different periods for different sections of this study area. The research would provide decision-making and planning for the Songhua River basin during the period of China's 13th Five-Year Plan.

Climatic Drivers Of Seasonal Influenza Epidemics In French Guiana, 2006–2010

PubMed Central

Mahamat, A.; Dussart, P.; Bouix, A.; Carvalho, L.; Eltges, F.; Matheus, S.; Miller, MA.; Quenel, P.; Viboud, C.

2013-01-01

Objectives Influenza seasonality remains poorly studied in Equatorial regions. Here we assessed the seasonal characteristics and environmental drivers of influenza epidemics in French Guiana, where influenza surveillance was established in 2006. Methods Sentinel GPs monitored weekly incidence of Influenza-like illnesses (ILI) from January 2006 through December 2010 and collected nasopharyngeal specimens from patients for virological confirmation. Times series analysis was used to investigate relationship between ILI and climatic parameters (rainfall and specific humidity). Results Based on 1,533 viruses identified during the study period, we observed marked seasonality in the circulation of influenza virus in the pre-pandemic period, followed by year-round activity in the post-pandemic period, with a peak in the rainy season. ILI incidence showed seasonal autoregressive variation based on ARIMA analysis. Multivariate dynamic regression revealed that a 1mm increase of rainfall resulted in an increase of 0.33% in ILI incidence one week later, adjusting for specific humidity (SH). Conversely, an increase of 1g/kg of SH resulted in a decrease of 11% in ILI incidence 3 weeks later, adjusting for rainfall. Conclusions Increased rainfall and low levels of specific humidity favor influenza transmission in French Guiana. PMID:23597784

Investigating and Modelling Effects of Climatically and Hydrologically Indicators on the Urmia Lake Coastline Changes Using Time Series Analysis

NASA Astrophysics Data System (ADS)

Ahmadijamal, M.; Hasanlou, M.

2017-09-01

Study of hydrological parameters of lakes and examine the variation of water level to operate management on water resources are important. The purpose of this study is to investigate and model the Urmia Lake water level changes due to changes in climatically and hydrological indicators that affects in the process of level variation and area of this lake. For this purpose, Landsat satellite images, hydrological data, the daily precipitation, the daily surface evaporation and the daily discharge in total of the lake basin during the period of 2010-2016 have been used. Based on time-series analysis that is conducted on individual data independently with same procedure, to model variation of Urmia Lake level, we used polynomial regression technique and combined polynomial with periodic behavior. In the first scenario, we fit a multivariate linear polynomial to our datasets and determining RMSE, NRSME and R² value. We found that fourth degree polynomial can better fit to our datasets with lowest RMSE value about 9 cm. In the second scenario, we combine polynomial with periodic behavior for modeling. The second scenario has superiority comparing to the first one, by RMSE value about 3 cm.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

The significance of peripartum fever in women undergoing vaginal deliveries.

PubMed

Bensal, Adi; Weintraub, Adi Y; Levy, Amalia; Holcberg, Gershon; Sheiner, Eyal

2008-10-01

We investigated whether patients undergoing vaginal delivery who developed peripartum fever (PPF) had increased rates of other gestational complications. A retrospective study was undertaken comparing pregnancy complications of patients who developed PPF with those who did not. A multivariable logistic regression model was constructed to control for confounders. To avoid ascertainment bias, the year of birth was included in the model. Women who underwent cesarean delivery and those with multiple pregnancies were excluded from the study. During the study period, there were 169,738 singleton vaginal deliveries, and 0.4% of the women suffered from PPF. Hypertensive disorders, induction of labor, dystocia of labor in the second stage, suspected fetal distress, meconium-stained amniotic fluid, postpartum hemorrhage, manual lysis of a retained placenta, and revision of the uterine cavity and cervix were found to be independently associated with PPF by multivariable analysis. Year of birth was found to be a risk factor for fever. Apgar scores lower than 7 at 1 but not 5 minutes were significantly higher in the PPF group. Perinatal mortality rates were significantly higher among women with PPF (6.7% versus 1.3%, odds ratio [OR] = 5.4; 95% confidence interval [CI] 3.9 to 7.3; P < 0.001). Using another multivariable analysis, with perinatal mortality as the outcome variable, PPF was found as an independent risk factor for perinatal mortality (OR = 2.9; 95% CI 1.9 to 4.6; P < 0.001). PPF in women undergoing vaginal deliveries is associated with adverse perinatal outcomes and specifically is an independent risk factor for perinatal mortality.

High local unemployment rates limit work after lung transplantation.

PubMed

Nau, Michael; Shrider, Emily A; Tobias, Joseph D; Hayes, Don; Tumin, Dmitry

2016-10-01

Most lung transplant (LTx) recipients recover sufficient functional status to resume working, yet unemployment is common after LTx. Weak local labor markets may limit employment opportunities for LTx recipients. United Network for Organ Sharing data on first-time LTx recipients 18-60 years old who underwent transplant between 2010 and 2014 were linked to American Community Survey data on unemployment rates at the ZIP Code level. Multivariable competing-risks regression modeled the influence of dichotomous (≥8%) and continuous local unemployment rates on employment after LTx, accounting for the competing risk of mortality. For comparison, analyses were duplicated in a cohort of heart transplant (HTx) recipients who underwent transplant during the same period. The analysis included 3,897 LTx and 5,577 HTx recipients. Work after LTx was reported by 300 (16.3%) residents of low-unemployment areas and 244 (11.9%) residents of high-unemployment areas (p < 0.001). Multivariable analysis of 3,626 LTx recipients with complete covariate data found that high local unemployment rates limited employment after LTx (sub-hazard ratio = 0.605; 95% confidence interval = 0.477, 0.768; p < 0.001), conditional on not working before transplant. Employment after HTx was higher compared with employment after LTx, and not associated with local unemployment rates in multivariable analyses. LTx recipients of working age exhibit exceptionally low employment rates. High local unemployment rates exacerbate low work participation after LTx, and may discourage job search in this population. Copyright © 2016 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Medicare expenditures among nursing home residents with advanced dementia.

PubMed

Goldfeld, Keith S; Stevenson, David G; Hamel, Mary Beth; Mitchell, Susan L

2011-05-09

Nursing home residents with advanced dementia commonly experience burdensome and costly interventions (eg, tube feeding) that may be of limited clinical benefit. To our knowledge, Medicare expenditures have not been extensively described in this population. Nursing home residents with advanced dementia in 22 facilities (N = 323) were followed up for 18 months. Clinical and health services use data were collected every 90 days. Medicare expenditures were described. Multivariate analysis was used to identify factors associated with total 90-day expenditures for (1) all Medicare services and (2) all Medicare services excluding hospice. Over an 18-month period, total mean Medicare expenditures were $2303 per 90 days but were highly skewed; expenditures were less than $500 for 77.1% of the 90-day assessment periods and more than $12,000 for 5.5% of these periods. The largest proportion of Medicare expenditures were for hospitalizations (30.2%) and hospice (45.6%). Among decedents (n = 177), mean Medicare expenditures increased by 65% in each of the last 4 quarters before death owing to an increase in both acute care and hospice. After multivariable adjustment, not living in a special care dementia unit was a modifiable factor associated with higher total expenditures for all Medicare services. Lack of a do-not-hospitalize order, tube feeding, and not living in a special care unit were associated with higher nonhospice Medicare expenditures. Medicare expenditures among nursing home residents with advanced dementia vary substantially. Hospitalizations and hospice account for most spending. Strategies that promote high-quality palliative care may shift expenditures away from aggressive treatments for these patients at the end of life.

Trends in diabetes-related visits to US EDs from 1997 to 2007.

PubMed

Menchine, Michael D; Wiechmann, Warren; Peters, Anne L; Arora, Sanjay

2012-06-01

The aims of the study were to describe temporal trends in the number, proportion, and per capita use of diabetes-related emergency department (ED) visits and to examine any racial/ethnic disparity in ED use for diabetes-related reasons. We analyzed the ED portion of the National Hospital Ambulatory Medical Care Survey from 1997 through 2007. Diabetes-related ED visits were identified by International Classification of Diseases, Ninth Revision codes. Descriptive statistics were developed. Weighted linear and logistic regression models were used to determine significance of temporal trends, and multivariate logistic regression was used to examine racial/ethnic disparities. A total of 20.2 million (1.69%; 95% confidence interval [CI], 1.59%-1.78%) ED visits were diabetes-related during the study period. We observed significant increases in the number and proportion of diabetes-related ED visits. Overall, there was a 5.6% relative annual increase in the proportion of ED visits that were diabetes-related during the study period. However, the per capita ED use among the population with diabetes did not change over time (P>.05 for trend). On multivariate analysis, black race (odds ratio, 1.8; 95% CI, 1.7-2.0), Hispanic ethnicity (odds ratio, 1.6; 95% CI, 1.4-1.8), and advancing age were associated with significantly higher odds of having a diabetes-related visit. Despite a marked increase in number and proportion of diabetes-related ED visits during the study period, the per capita use of ED services for diabetes-related visits among the diabetic population remained stable. Copyright © 2012 Elsevier Inc. All rights reserved.

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Decomposition of algebraic sets and applications to weak centers of cubic systems

NASA Astrophysics Data System (ADS)

Chen, Xingwu; Zhang, Weinian

2009-10-01

There are many methods such as Gröbner basis, characteristic set and resultant, in computing an algebraic set of a system of multivariate polynomials. The common difficulties come from the complexity of computation, singularity of the corresponding matrices and some unnecessary factors in successive computation. In this paper, we decompose algebraic sets, stratum by stratum, into a union of constructible sets with Sylvester resultants, so as to simplify the procedure of elimination. Applying this decomposition to systems of multivariate polynomials resulted from period constants of reversible cubic differential systems which possess a quadratic isochronous center, we determine the order of weak centers and discuss the bifurcation of critical periods.

Heavy metals in edible seaweeds commercialised for human consumption

NASA Astrophysics Data System (ADS)

Besada, Victoria; Andrade, José Manuel; Schultze, Fernando; González, Juan José

2009-01-01

Though seaweed consumption is growing steadily across Europe, relatively few studies have reported on the quantities of heavy metals they contain and/or their potential effects on the population's health. This study focuses on the first topic and analyses the concentrations of six typical heavy metals (Cd, Pb, Hg, Cu, Zn, total As and inorganic As) in 52 samples from 11 algae-based products commercialised in Spain for direct human consumption ( Gelidium spp.; Eisenia bicyclis; Himanthalia elongata; Hizikia fusiforme; Laminaria spp.; Ulva rigida; Chondrus crispus; Porphyra umbilicales and Undaria pinnatifida). Samples were ground, homogenised and quantified by atomic absorption spectrometry (Cu and Zn by flame AAS; Cd, Pb and total As by electrothermal AAS; total mercury by the cold vapour technique; and inorganic As by flame-hydride generation). Accuracy was assessed by participation in periodic QUASIMEME (Quality Assurance of Information in Marine Environmental Monitoring in Europe) and IAEA (International Atomic Energy Agency) intercalibration exercises. To detect any objective differences existing between the seaweeds' metal concentrations, univariate and multivariate studies (principal component analysis, cluster analysis and linear discriminant analysis) were performed. It is concluded that the Hizikia fusiforme samples contained the highest values of total and inorganic As and that most Cd concentrations exceeded the French Legislation. The two harvesting areas (Atlantic and Pacific oceans) were differentiated using both univariate studies (for Cu, total As, Hg and Zn) and a multivariate discriminant function (which includes Zn, Cu and Pb).

Role of adjuvant chemoradiotherapy in T4N0 stage IV head and neck cancer: A National Cancer Database analysis.

PubMed

Kirke, Diana N; Qureshi, Muhammad M; Kamran, Sophia C; Ezzat, Waleed; Jalisi, Scharukh; Salama, Andrew; Everett, Peter C; Truong, Minh Tam

2018-06-01

The purpose of this study was to evaluate the role of postoperative adjuvant radiotherapy (surgery + adjuvant RT) versus adjuvant chemoradiotherapy (surgery + adjuvant CRT) in patients with T4N0M0, stage IV head and neck squamous cell carcinoma (HNSCC). Between 1998 and 2011, 3518 and 885 patients were treated with surgery + adjuvant RT and surgery + adjuvant CRT, respectively. Three-year overall survival (OS) rates were determined and crude and adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were computed. Median follow-up was 41.8 months with 2193 reported deaths. The 3-year OS was 67.5% for surgery + adjuvant RT and 70.5% for surgery + adjuvant CRT (P = .013). For negative margins, the corresponding 3-year OS was 70.1% and 74.9% (P = .005). For positive margins, the corresponding 3-year OS was 56.0% and 60.6% (P = .079). On multivariate analysis, the beneficial effect for adjuvant CRT over adjuvant RT was not significant (HR 0.90; CI 0.79-1.03; P = .124). In this cohort of patients with T4N0 HNSCC treated with surgery, there was no observed survival benefit of adjuvant CRT over adjuvant RT on multivariate analysis. © 2018 Wiley Periodicals, Inc.

Effects of shoulder dystocia training on the incidence of brachial plexus injury.

PubMed

Inglis, Steven R; Feier, Nikolaus; Chetiyaar, Jyothi B; Naylor, Margaret H; Sumersille, Melanie; Cervellione, Kelly L; Predanic, Mladen

2011-04-01

We sought to determine whether implementation of shoulder dystocia training reduces the incidence of obstetric brachial plexus injury (OBPI). After implementing training for maternity staff, the incidence of OBPI was compared between pretraining and posttraining periods using both univariate and multivariate analyses in deliveries complicated by shoulder dystocia. The overall incidence of OBPI in vaginal deliveries decreased from 0.40% pretraining to 0.14% posttraining (P < .01). OBPI after shoulder dystocia dropped from 30% to 10.67% posttraining (P < .01). Maternal body mass index (P < .01) and neonatal weight (P = .02) decreased and head-to-body delivery interval increased in the posttraining period (P = .03). Only shoulder dystocia training remained associated with reduced OBPI (P = .02) after logistic regression analysis. OBPI remained less in the posttraining period (P = .01), even after excluding all neonates with birthweights >2 SD above the mean. Shoulder dystocia training was associated with a lower incidence of OBPI and the incidence of OBPI in births complicated by shoulder dystocia. Copyright © 2011 Mosby, Inc. All rights reserved.

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Differences in Brain Glucose Metabolism During Preparation for 131I Ablation in Thyroid Cancer Patients: Thyroid Hormone Withdrawal Versus Recombinant Human Thyrotropin.

PubMed

Jeong, Hyeonseok S; Choi, Eun Kyoung; Song, In-Uk; Chung, Yong-An; Park, Jong-Sik; Oh, Jin Kyoung

2017-01-01

In preparation for 131 I ablation, temporary withdrawal of thyroid hormone is commonly used in patients with thyroid cancer after total thyroidectomy. The current study aimed to investigate brain glucose metabolism and its relationships with mood or cognitive function in these patients using 18 F-fluoro-2-deoxyglucose positron emission tomography ( 18 F-FDG-PET). A total of 40 consecutive adult patients with thyroid carcinoma who had undergone total thyroidectomy were recruited for this cross-sectional study. At the time of assessment, 20 patients were hypothyroid after two weeks of thyroid hormone withdrawal, while 20 received thyroid hormone replacement therapy and were euthyroid. All participants underwent brain 18 F-FDG-PET scans and completed mood questionnaires and cognitive tests. Multivariate spatial covariance analysis and univariate voxel-wise analysis were applied for the image data. The hypothyroid patients were more anxious and depressed than the euthyroid participants. The multivariate covariance analysis showed increases in glucose metabolism primarily in the bilateral insula and surrounding areas and concomitant decreases in the parieto-occipital regions in the hypothyroid group. The level of thyrotropin was positively associated with the individual expression of the covariance pattern. The decreased 18 F-FDG uptake in the right cuneus cluster from the univariate analysis was correlated with the increased thyrotropin level and greater depressive symptoms in the hypothyroid group. These results suggest that temporary hypothyroidism, even for a short period, may induce impairment in glucose metabolism and related affective symptoms.

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study.

PubMed

El-Sayed, Mohamed I; Ali, Amany M; Sayed, Heba A; Zaky, Eman M

2010-12-24

We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS) rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68%) presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered.

Vitrified-warmed embryo transfer is associated with mean higher singleton birth weight compared to fresh embryo transfer.

PubMed

Beyer, Daniel Alexander; Griesinger, Georg

2016-08-01

To test for differences in birth weight between singletons born after IVF with fresh embryo transfer vs. vitrified-warmed 2PN embryo transfer (vitrification protocol). Retrospective analysis of 464 singleton live births after IVF or ICSI during a 12 year period. University hospital. Fresh embryo transfer, vitrified-warmed 2PN embryo transfer (vitrification protocol). Birth weight standardized as a z-score, adjusting for gestational week at delivery and fetal sex. As a reference, birth weight means from regular deliveries from the same hospital were used. Multivariate regression analysis was used to investigate the relationship between the dependent variable z-score (fetal birth weight) and the independent predictor variables maternal age, weight, height, body mass index, RDS prophylaxis, transfer protocol, number of embryos transferred, indication for IVF treatment and sperm quality. The mean z-score was significantly lower after fresh transfer (-0.11±92) as compared to vitrification transfer (0.72±83) (p<0.001). Multivariate regression analysis indicated that only maternal height and maternal body mass index, but not type of cryopreservation protocol, was a significant predictor of birth weight. In this analysis focusing on 2PN oocytes, vitrified-warmed embryo transfer is associated with mean higher birth weight compared to fresh embryo transfer. Maternal height and body mass index are significant confounders of fetal birth weight and need to be taken into account when studying birth weight differences between ART protocols. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

Glascock, M. D.; Neff, H.; Vaughn, K. J.

2004-06-01

The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Localization of genes involved in the metabolic syndrome using multivariate linkage analysis.

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

There are no well accepted criteria for the diagnosis of the metabolic syndrome. However, the metabolic syndrome is identified clinically by the presence of three or more of these five variables: larger waist circumference, higher triglyceride levels, lower HDL-cholesterol concentrations, hypertension, and impaired fasting glucose. We use sets of two or three variables, which are available in the Framingham Heart Study data set, to localize genes responsible for this syndrome using multivariate quantitative linkage analysis. This analysis demonstrates the applicability of using multivariate linkage analysis and how its use increases the power to detect linkage when genes are involved in the same disease mechanism.

Intra-annual variability of cloud cover over the Mediterranean region based on NCEP/NCAR, MODIS and ECAD data sets

NASA Astrophysics Data System (ADS)

Ioannidis, Eleftherios; Lolis, Christos J.; Papadimas, Christos D.; Hatzianastassiou, Nikolaos; Bartzokas, Aristides

2017-04-01

The seasonal variability of total cloud cover in the Mediterranean region is examined for the period 1948-2014 using a multivariate statistical methodology. The data used consist of: i) daily gridded (1.875°x1.905°) values of total cloud cover over the broader Mediterranean region for the 66-year period 1948-2014, obtained from NCEP/NCAR Reanalysis data set, ii) daily gridded (1°x1°) values of total cloud cover for the period 2003-2014 obtained from the Moderate resolution Imaging Spectroradiometer (MODIS) satellite data set and iii) daily station cloud cover data for the period 2003-2014 obtained from the European Climate Assessment & Dataset (ECA&D). At first, the multivariate statistical method of Factor Analysis (S-mode) with varimax rotation is applied as a dimensionality reduction tool on the mean day to day intra-annual variation of NCEP/NCAR cloud cover for the period 1948-2014. According to the results, three main modes of intra-annual variation of cloud cover are found. The first mode is characterized by a winter maximum and a summer minimum and prevails mainly over the sea; a weak see-saw teleconnection over the Alps represents the opposite intra-annual marching. The second mode presents maxima in early autumn and late spring, and minima in late summer and winter, and prevails over the SW Europe and NW Africa inland regions. The third mode shows a maximum in June and a minimum in October and prevails over the eastern part of central Europe. Next, the mean day to day intra-annual variation of NCEP/NCAR cloud cover over the core regions of the above factors is calculated for the entire period 1948-2014 and the three 22-year sub-periods 1948-70, 1970-92 and 1992-2014. A comparison is carried out between each of the three sub-periods and the total period in order to reveal possible long-term changes in seasonal march of total cloud cover. The results show that cloud cover was reduced above all regions during the last 22-year sub-period 1992-2014 throughout the year, but especially in winter. Finally, given the different nature of the utilized NCEP/NCAR (Reanalysis), MODIS (satellite) and ECAD (stations) cloud cover data sets, an inter-comparison is made among them as it concerns the intra-annual variation of cloud cover for the common period 2003-2014. The results show a nice similarity among the three datasets, with some differences in magnitude during the cold period of the year.

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

Multivariate frequency domain analysis (MFDA) is proposed to characterize collective vibrational dynamics of protein obtained by a molecular dynamics (MD) simulation. MFDA performs principal component analysis (PCA) for a bandpass filtered multivariate time series using the multitaper method of spectral estimation. By applying MFDA to MD trajectories of bovine pancreatic trypsin inhibitor, we determined the collective vibrational modes in the frequency domain, which were identified by their vibrational frequencies and eigenvectors. At near zero temperature, the vibrational modes determined by MFDA agreed well with those calculated by normal mode analysis. At 300 K, the vibrational modes exhibited characteristic features that were considerably different from the principal modes of the static distribution given by the standard PCA. The influences of aqueous environments were discussed based on two different sets of vibrational modes, one derived from a MD simulation in water and the other from a simulation in vacuum. Using the varimax rotation, an algorithm of the multivariate statistical analysis, the representative orthogonal set of eigenmodes was determined at each vibrational frequency.

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

Background The primary cell wall of fruits and vegetables is a structure mainly composed of polysaccharides (pectins, hemicelluloses, cellulose). Polysaccharides are assembled into a network and linked together. It is thought that the percentage of components and of plant cell wall has an important influence on mechanical properties of fruits and vegetables. Results In this study the Raman microspectroscopy technique was introduced to the visualization of the distribution of polysaccharides in cell wall of fruit. The methodology of the sample preparation, the measurement using Raman microscope and multivariate image analysis are discussed. Single band imaging (for preliminary analysis) and multivariate image analysis methods (principal component analysis and multivariate curve resolution) were used for the identification and localization of the components in the primary cell wall. Conclusions Raman microspectroscopy supported by multivariate image analysis methods is useful in distinguishing cellulose and pectins in the cell wall in tomatoes. It presents how the localization of biopolymers was possible with minimally prepared samples. PMID:24917885

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Multivariate statistical analysis of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Caramelo, Liliana; Pereira, Mário

2013-04-01

Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

Determinants of Health Behaviors After Gestational Diabetes Mellitus: A Prospective Cohort Study in Geneva.

PubMed

Kaiser, Barbara; Jeannot, Emilien; Razurel, Chantal

2016-09-01

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy. The objective of this study was to specify the determinants of postpartum physical activity and dietary habits after a pregnancy complicated by GDM in a population of Swiss women. This information will be used to improve health promotion and diabetes prevention interventions for women with a history of GDM. A prospective cohort study of 173 pregnant women with a diagnosis of GDM was carried out. Quantitative data were collected at the end of pregnancy (T1) and at 6 months postpartum (T3). Bivariate and multivariate logistic regression analysis was conducted to assess associations between the level of healthy lifestyle at 6 months postpartum, clinical and sociodemographic characteristics, motivation to adopt a healthy lifestyle after birth at the end of pregnancy, and postulated psychosocial correlates of health behaviors. Multivariate regression analysis showed that only 2 variables were determinants in a low adherence to healthy lifestyle in the postpartum period after GDM: a lower level of social support (odds ratio [OR], 1.5; P < .001) and more perceived barriers to a healthy lifestyle (OR, 1.2; P = .002). This study shows that, for women who had GDM, the problem of low adherence to a healthy lifestyle to prevent the onset of type 2 diabetes may be secondary to the lack of resources available for the promotion and development of healthy eating habits and regular physical activity. The findings of this study suggest that some women with a history of GDM do not have the means and resources in the postpartum period to apply the advice given during antenatal monitoring. © 2016 by the American College of Nurse-Midwives.

Oedema is associated with clinical outcome following emergency abdominal surgery.

PubMed

Vaughan-Shaw, P G; Saunders, J; Smith, T; King, A T; Stroud, M A

2013-09-01

Oedema is observed frequently following surgery and may be associated with worse outcomes. To date, no study has investigated the role of oedema in the emergency surgical patient. This study assesses the incidence of oedema following emergency abdominal surgery and the value of early postoperative oedema measurement in predicting clinical outcome. A prospective cohort study of patients undergoing emergency abdominal surgery at a university unit over a two-month period was undertaken. Nutritional and clinical outcome data were collected and oedema was measured in the early postoperative period. Predictors of oedema and outcomes associated with postoperative oedema were identified through univariate and multivariate analysis. Overall, 55 patients (median age: 66 years) were included in the study. Postoperative morbidity included ileus (n=22) and sepsis (n=6) with 12 deaths at follow-up. Postoperative oedema was present in 19 patients and was associated with prolonged perioperative fasting (107 vs 30 hours, p=0.009) but not with body mass index (24 kg/m(2) vs 27 kg/m(2), p=0.169) or preadmission weight loss (5% vs 3%, p=0.923). On multivariate analysis, oedema was independently associated with gastrointestinal recovery (B=6.91, p=0.038), artificial nutritional support requirement (odds ratio: 6.91, p=0.037) and overall survival (χ(2) =13.1, df=1, p=0.001). Generalised oedema is common after emergency abdominal surgery and appears to independently predict gastrointestinal recovery, the need for artificial nutritional support and survival. Oedema is not associated with commonly applied markers of nutritional status such as body mass index or recent weight loss. Measurement of oedema offers utility in identifying those at risk of poor clinical outcome or those requiring artificial nutritional support following emergency abdominal surgery.

Oedema is associated with clinical outcome following emergency abdominal surgery

PubMed Central

Vaughan-Shaw, PG; Saunders, J; Smith, T; King, AT

2013-01-01

Introduction Oedema is observed frequently following surgery and may be associated with worse outcomes. To date, no study has investigated the role of oedema in the emergency surgical patient. This study assesses the incidence of oedema following emergency abdominal surgery and the value of early postoperative oedema measurement in predicting clinical outcome. Methods A prospective cohort study of patients undergoing emergency abdominal surgery at a university unit over a two-month period was undertaken. Nutritional and clinical outcome data were collected and oedema was measured in the early postoperative period. Predictors of oedema and outcomes associated with postoperative oedema were identified through univariate and multivariate analysis. Results Overall, 55 patients (median age: 66 years) were included in the study. Postoperative morbidity included ileus (n=22) and sepsis (n=6) with 12 deaths at follow-up. Postoperative oedema was present in 19 patients and was associated with prolonged perioperative fasting (107 vs 30 hours, p=0.009) but not with body mass index (24kg/m2 vs 27kg/m2, p=0.169) or preadmission weight loss (5% vs 3%, p=0.923). On multivariate analysis, oedema was independently associated with gastrointestinal recovery (B=6.91, p=0.038), artificial nutritional support requirement (odds ratio: 6.91, p=0.037) and overall survival (χ2=13.1, df=1, p=0.001). Conclusions Generalised oedema is common after emergency abdominal surgery and appears to independently predict gastrointestinal recovery, the need for artificial nutritional support and survival. Oedema is not associated with commonly applied markers of nutritional status such as body mass index or recent weight loss. Measurement of oedema offers utility in identifying those at risk of poor clinical outcome or those requiring artificial nutritional support following emergency abdominal surgery. PMID:24025285

Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population.

PubMed

Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2015-07-29

Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Psychological and relational correlates of intimate partner violence profiles among pregnant adolescent couples.

PubMed

Lewis, Jessica B; Sullivan, Tami P; Angley, Meghan; Callands, Tamora; Divney, Anna A; Magriples, Urania; Gordon, Derrick M; Kershaw, Trace S

2017-01-01

We sought to identify relationship and individual psychological factors that related to four profiles of intimate partner violence (IPV) among pregnant adolescent couples: no IPV, male IPV victim only, female IPV victim only, mutual IPV, and how associations differ by sex. Using data from a longitudinal study of pregnant adolescents and partners (n = 291 couples), we used a multivariate profile analysis using multivariate analysis of covariance with between and within-subjects effects to compare IPV groups and sex on relationship and psychological factors. Analyses were conducted at the couple level, with IPV groups as a between-subjects couple level variable and sex as a within-subjects variable that allowed us to model and compare the outcomes of both partners while controlling for the correlated nature of the data. Analyses controlled for age, race, income, relationship duration, and gestational age. Among couples, 64% had no IPV; 23% male IPV victim only; 7% mutual IPV; 5% female IPV victim only. Relationship (F = 3.61, P < .001) and psychological (F = 3.17, P < .001) factors differed by IPV group, overall. Attachment anxiety, attachment avoidance, relationship equity, perceived partner infidelity, depression, stress, and hostility each differed by IPV profile (all P < .01). Attachment anxiety, equity, depression and stress had a significant IPV profile by sex interaction (all P < .05). Couples with mutual IPV had the least healthy relationship and psychological characteristics; couples with no IPV had the healthiest characteristics. Females in mutually violent relationships were at particularly high risk. Couple-level interventions focused on relational issues might protect young families from developing IPV behaviors. Aggr. Behav. 43:26-36, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Determination of dominant biogeochemical processes in a contaminated aquifer-wetland system using multivariate statistical analysis

USGS Publications Warehouse

Baez-Cazull, S. E.; McGuire, J.T.; Cozzarelli, I.M.; Voytek, M.A.

2008-01-01

Determining the processes governing aqueous biogeochemistry in a wetland hydrologically linked to an underlying contaminated aquifer is challenging due to the complex exchange between the systems and their distinct responses to changes in precipitation, recharge, and biological activities. To evaluate temporal and spatial processes in the wetland-aquifer system, water samples were collected using cm-scale multichambered passive diffusion samplers (peepers) to span the wetland-aquifer interface over a period of 3 yr. Samples were analyzed for major cations and anions, methane, and a suite of organic acids resulting in a large dataset of over 8000 points, which was evaluated using multivariate statistics. Principal component analysis (PCA) was chosen with the purpose of exploring the sources of variation in the dataset to expose related variables and provide insight into the biogeochemical processes that control the water chemistry of the system. Factor scores computed from PCA were mapped by date and depth. Patterns observed suggest that (i) fermentation is the process controlling the greatest variability in the dataset and it peaks in May; (ii) iron and sulfate reduction were the dominant terminal electron-accepting processes in the system and were associated with fermentation but had more complex seasonal variability than fermentation; (iii) methanogenesis was also important and associated with bacterial utilization of minerals as a source of electron acceptors (e.g., barite BaSO4); and (iv) seasonal hydrological patterns (wet and dry periods) control the availability of electron acceptors through the reoxidation of reduced iron-sulfur species enhancing iron and sulfate reduction. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Analysis of National Trends in Hospital Acquired Conditions Following Major Urological Surgery Before and After Implementation of the Hospital Acquired Condition Reduction Program,,✰✰✰.

PubMed

Rude, Tope L; Donin, Nicholas M; Cohn, Matthew R; Meeks, William; Gulig, Scott; Patel, Samir N; Wysock, James S; Makarov, Danil V; Bjurlin, Marc A

2018-06-07

To define the rates of common Hospital Acquired Conditions (HACs) in patients undergoing major urological surgery over a period of time encompassing the implementation of the Hospital Acquired Condition Reduction program, and to evaluate whether implementation of the HAC reimbursement penalties in 2008 was associated with a change in the rate of HACs. Using American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data, we determined rates of HACs in patients undergoing major inpatient urological surgery from 2005 to 2012. Rates were stratified by procedure type and approach (open vs. laparoscopic/robotic). Multivariable logistic regression was used to determine the association between year of surgery and HACs. We identified 39,257 patients undergoing major urological surgery, of whom 2300 (5.9%) had at least one hospital acquired condition. Urinary tract infection (UTI, 2.6%) was the most common, followed by surgical site infection (SSI, 2.5%) and venous thrombotic events (VTE, 0.7%). Multivariable logistic regression analysis demonstrated that open surgical approach, diabetes, congestive heart failure, chronic obstructive pulmonary disease, weight loss, and ASA class were among the variables associated with higher likelihood of HAC. We observed a non-significant secular trend of decreasing rates of HAC from 7.4% to 5.8% HACs during the study period, which encompassed the implementation of the Hospital Acquired Condition Reduction Program. HACs occurred at a rate of 5.9% after major urological surgery, and are significantly affected by procedure type and patient health status. The rate of HAC appeared unaffected by national reduction program in this cohort. Better understanding of the factors associated with HACs is critical in developing effective reduction programs. Copyright © 2018. Published by Elsevier Inc.

The incidence and prevalence of pterygium in South Korea: A 10-year population-based Korean cohort study.

PubMed

Rim, Tyler Hyungtaek; Kang, Min Jae; Choi, Moonjung; Seo, Kyoung Yul; Kim, Sung Soo

2017-01-01

Although numerous population-based studies have reported the prevalences and risk factors for pterygium, information regarding the incidence of pterygium is scarce. This population-based cohort study aimed to evaluate the South Korean incidence and prevalence of pterygium. We retrospectively obtained data from a nationally representative sample of 1,116,364 South Koreans in the Korea National Health Insurance Service National Sample Cohort (NHIS-NSC). The associated sociodemographic factors were evaluated using multivariable Cox regression analysis, and the hazard ratios and confidence intervals were calculated. Pterygium was defined based on the Korean Classification of Diseases code, and surgically removed pterygium was defined as cases that required surgical removal. We identified 21,465 pterygium cases and 8,338 surgically removed pterygium cases during the study period. The overall incidences were 2.1 per 1,000 person-years for pterygium and 0.8 per 1,000 person-years for surgically removed pterygium. Among subjects who were ≥40 years old, the incidences were 4.3 per 1,000 person-years for pterygium and 1.7 per 1,000 person-years for surgically removed pterygium. The overall prevalences were 1.9% for pterygium and 0.6% for surgically removed pterygium, and the prevalences increased to 3.8% for pterygium and 1.4% for surgically removed pterygium among subjects who were ≥40 years old. The incidences of pterygium decreased according to year. The incidence and prevalence of pterygium were highest among 60-79-year-old individuals. Increasing age, female sex, and living in a relatively rural area were associated with increased risks of pterygium and surgically removed pterygium in the multivariable Cox regression analysis. Our analyses of South Korean national insurance claims data revealed a decreasing trend in the incidence of pterygium during the study period.

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Toward a Periodic Table of Niches, or Exploring the Lizard Niche Hypervolume.

PubMed

Pianka, Eric R; Vitt, Laurie J; Pelegrin, Nicolás; Fitzgerald, Daniel B; Winemiller, Kirk O

2017-11-01

Widespread niche convergence suggests that species can be organized according to functional trait combinations to create a framework analogous to a periodic table. We compiled ecological data for lizards to examine patterns of global and regional niche diversification, and we used multivariate statistical approaches to develop the beginnings for a periodic table of niches. Data (50+ variables) for five major niche dimensions (habitat, diet, life history, metabolism, defense) were compiled for 134 species of lizards representing 24 of the 38 extant families. Principal coordinates analyses were performed on niche dimensional data sets, and species scores for the first three axes were used as input for a principal components analysis to ordinate species in continuous niche space and for a regression tree analysis to separate species into discrete niche categories. Three-dimensional models facilitate exploration of species positions in relation to major gradients within the niche hypervolume. The first gradient loads on body size, foraging mode, and clutch size. The second was influenced by metabolism and terrestrial versus arboreal microhabitat. The third was influenced by activity time, life history, and diet. Natural dichotomies are activity time, foraging mode, parity mode, and habitat. Regression tree analysis identified 103 cases of extreme niche conservatism within clades and 100 convergences between clades. Extending this approach to other taxa should lead to a wider understanding of niche evolution.

Islet product characteristics and factors related to successful human islet transplantation from the Collaborative Islet Transplant Registry (CITR) 1999-2010.

PubMed

Balamurugan, A N; Naziruddin, B; Lockridge, A; Tiwari, M; Loganathan, G; Takita, M; Matsumoto, S; Papas, K; Trieger, M; Rainis, H; Kin, T; Kay, T W; Wease, S; Messinger, S; Ricordi, C; Alejandro, R; Markmann, J; Kerr-Conti, J; Rickels, M R; Liu, C; Zhang, X; Witkowski, P; Posselt, A; Maffi, P; Secchi, A; Berney, T; O'Connell, P J; Hering, B J; Barton, F B

2014-11-01

The Collaborative Islet Transplant Registry (CITR) collects data on clinical islet isolations and transplants. This retrospective report analyzed 1017 islet isolation procedures performed for 537 recipients of allogeneic clinical islet transplantation in 1999-2010. This study describes changes in donor and islet isolation variables by era and factors associated with quantity and quality of final islet products. Donor body weight and BMI increased significantly over the period (p<0.001). Islet yield measures have improved with time including islet equivalent (IEQ)/particle ratio and IEQs infused. The average dose of islets infused significantly increased in the era of 2007-2010 when compared to 1999-2002 (445.4±156.8 vs. 421.3±155.4×0(3) IEQ; p<0.05). Islet purity and total number of β cells significantly improved over the study period (p<0.01 and <0.05, respectively). Otherwise, the quality of clinical islets has remained consistently very high through this period, and differs substantially from nonclinical islets. In multivariate analysis of all recipient, donor and islet factors, and medical management factors, the only islet product characteristic that correlated with clinical outcomes was total IEQs infused. This analysis shows improvements in both quantity and some quality criteria of clinical islets produced over 1999-2010, and these parallel improvements in clinical outcomes over the same period. © 2014 The Authors. American Journal of Transplantation Published by Wiley Periodicals, Inc. on behalf of American Society of Transplant Surgeons.

Spatial gender-age-period-cohort analysis of pancreatic cancer mortality in Spain (1990–2013)

PubMed Central

Etxeberria, Jaione; Goicoa, Tomás; López-Abente, Gonzalo; Riebler, Andrea

2017-01-01

Recently, the interest in studying pancreatic cancer mortality has increased due to its high lethality. In this work a detailed analysis of pancreatic cancer mortality in Spanish provinces was performed using recent data. A set of multivariate spatial gender-age-period-cohort models was considered to look for potential candidates to analyze pancreatic cancer mortality rates. The selected model combines features of APC (age-period-cohort) models with disease mapping approaches. To ensure model identifiability sum-to-zero constraints were applied. A fully Bayesian approach based on integrated nested Laplace approximations (INLA) was considered for model fitting and inference. Sensitivity analyses were also conducted. In general, estimated average rates by age, cohort, and period are higher in males than in females. The higher differences according to age between males and females correspond to the age groups [65, 70), [70, 75), and [75, 80). Regarding the cohort, the greatest difference between men and women is observed for those born between the forties and the sixties. From there on, the younger the birth cohort is, the smaller the difference becomes. Some cohort differences are also identified by regions and age-groups. The spatial pattern indicates a North-South gradient of pancreatic cancer mortality in Spain, the provinces in the North being the ones with the highest effects on mortality during the studied period. Finally, the space-time evolution shows that the space pattern has changed little over time. PMID:28199327

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

In this work, the effect of temperature on charcoal structure and chemical composition is investigated for four tree species. Wood charcoal carbonized at various temperatures is analyzed by mid infrared spectroscopy coupled with multivariate analysis and by thermogravimetric analysis to characterize the chemical composition during the carbonization process. The...

Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.

PubMed

Horner, Fleur; Bilzon, James L; Rayson, Mark; Blacker, Sam; Richmond, Victoria; Carter, James; Wright, Anthony; Nevill, Alan

2013-01-01

This study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r (2) = 0.65, SE = 462 kcal · d(-1) (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r (2) = 0.41, SE = 490 kcal · d(-1) (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.

Incidence of retinopathy of prematurity in the United States: 1997 through 2005.

PubMed

Lad, Eleonora M; Hernandez-Boussard, Tina; Morton, John M; Moshfeghi, Darius M

2009-09-01

To determine the incidence of retinopathy of prematurity (ROP) based on a national database and to identify baseline characteristics, demographic information, comorbidities, and surgical interventions. Retrospective study based on the National Inpatient Sample from 1997 through 2005. The National Inpatient Sample was queried for all newborn infants with and without ROP. Multivariate logistic regression was used to predict risk factors for ROP. Thirty-four million live births were recorded during the study period. The total ROP incidence was 0.17% overall and 15.58% for premature infants with length of stay of more than 28 days. Our results conclusively demonstrated the importance of low birth weight as a risk for ROP development in infants with length of stay of more than 28 days, as well as association with respiratory conditions, fetal hemorrhage, intraventricular hemorrhage, and blood transfer. An interesting finding was the protective effect conferred by hypoxia, necrotizing enterocolitis, and hemolytic disease of the newborn. Infants with ROP had a higher incidence of undergoing laser photocoagulation therapy, pars plana vitrectomy, and scleral buckle surgery. The current study represents a large, retrospective analysis of newborns with ROP. The multivariate analysis emphasizes the role of birth weight in extended-stay infants, as well as respiratory conditions, fetal hemorrhage, intraventricular hemorrhage, and blood transfer.

Use of Raman microscopy and multivariate data analysis to observe the biomimetic growth of carbonated hydroxyapatite on bioactive glass.

PubMed

Seah, Regina K H; Garland, Marc; Loo, Joachim S C; Widjaja, Effendi

2009-02-15

In the present contribution, the biomimetic growth of carbonated hydroxyapatite (HA) on bioactive glass were investigated by Raman microscopy. Bioactive glass samples were immersed in simulated body fluid (SBF) buffered solution at pH 7.40 up to 17 days at 37 degrees C. Raman microscopy mapping was performed on the bioglass samples immersed in SBF solution for different periods of time. The collected data was then analyzed using the band-target entropy minimization technique to extract the observable pure component Raman spectral information. In this study, the pure component Raman spectra of the precursor amorphous calcium phosphate, transient octacalcium phosphate, and matured HA were all recovered. In addition, pure component Raman spectra of calcite, silica glass, and some organic impurities were also recovered. The resolved pure component spectra were fit to the normalized measured Raman data to provide the spatial distribution of these species on the sample surfaces. The current results show that Raman microscopy and multivariate data analysis provide a sensitive and accurate tool to characterize the surface morphology, as well as to give more specific information on the chemical species present and the phase transformation of phosphate species during the formation of HA on bioactive glass.

Relationship of breastfeeding self-efficacy with quality of life in Iranian breastfeeding mothers.

PubMed

Mirghafourvand, Mojgan; Kamalifard, Mahin; Ranjbar, Fatemeh; Gordani, Nasrin

2017-07-20

Due to the importance of breastfeeding, we decided to conduct a study to examine the relationship between breastfeeding self-efficacy and quality of life. This study was a cross-sectional study, which was carried out on 547 breastfeeding mothers that had 2-6 months old infants. The participants were selected randomly, and the sociodemographic characteristics questionnaire, Dennis' breastfeeding self-efficacy scale, and WHO's Quality of Life (WHOQOL) questionnaire were completed through interview. The multivariate linear regression model was used for data analysis. The means (standard deviations) of breastfeeding self-efficacy score and quality of life score were 134.5 (13.3) and 67.7 (13.7), respectively. Quality of life and all of its dimensions were directly and significantly related to breastfeeding self-efficacy. According to the results of multivariate linear regression analysis, there was a relationship between breastfeeding self-efficacy and the following variables: environmental dimension of quality of life, education, spouse's age, spouse's job, average duration of previous breastfeeding period and receiving breastfeeding training. Findings showed that there is direct and significant relationship between breastfeeding self-efficacy and quality of life. Moreover, it seems that the development of appropriate training programs is necessary for improving the quality of life of pregnant women, as it consequently enhances breastfeeding self-efficacy.

Reasons for job separations in a cohort of workers with psychiatric disabilities.

PubMed

Cook, Judith A; Burke-Miller, Jane K

2015-01-01

We explored the relative effects of adverse working conditions, job satisfaction, wages, worker characteristics, and local labor markets in explaining voluntary job separations (quits) among employed workers with psychiatric disabilities. Data come from the Employment Intervention Demonstration Program in which 2,086 jobs were ended by 892 workers during a 24 mo observation period. Stepped multivariable logistic regression analysis examined the effect of variables on the likelihood of quitting. Over half (59%) of all job separations were voluntary while 41% were involuntary, including firings (17%), temporary job endings (14%), and layoffs (10%). In multivariable analysis, workers were more likely to quit positions at which they were employed for 20 h/wk or less, those with which they were dissatisfied, low-wage jobs, non-temporary positions, and jobs in the structural (construction) occupations. Voluntary separation was less likely for older workers, members of racial and ethnic minority groups, and those residing in regions with lower unemployment rates. Patterns of job separations for workers with psychiatric disabilities mirrored some findings regarding job leaving in the general labor force but contradicted others. Job separation antecedents reflect the concentration of jobs for workers with psychiatric disabilities in the secondary labor market, characterized by low-salaried, temporary, and part-time employment.

Using video and theater to increase knowledge and change attitudes-Why are gorillas important to the world and to Congo?

PubMed

Breuer, Thomas; Mavinga, Franck Barrel; Evans, Ron; Lukas, Kristen E

2017-10-01

Applying environmental education in primate range countries is an important long-term activity to stimulate pro-conservation behavior. Within captive settings, mega-charismatic species, such as great apes are often used to increase knowledge and positively influence attitudes of visitors. Here, we evaluate the effectiveness of a short-term video and theater program developed for a Western audience and adapted to rural people living in two villages around Nouabalé-Ndoki National Park, Republic of Congo. We assessed the knowledge gain and attitude change using oral evaluation in the local language (N = 111). Overall pre-program knowledge about Western gorillas (Gorilla gorilla) was high. Detailed multivariate analysis of pre-program knowledge revealed differences in knowledge between two villages and people with different jobs while attitudes largely were similar between groups. The short-term education program was successful in raising knowledge, particularly of those people with less pre-program knowledge. We also noted an overall significant attitude improvement. Our data indicate short-term education programs are useful in quickly raising knowledge as well improving attitudes. Furthermore, education messages need to be clearly adapted to the daily livelihood realities of the audience, and multi-variate analysis can help to identify potential target groups for education programs. © 2017 Wiley Periodicals, Inc.

Land Use and Family Formation in the Settlement of the U.S. Great Plains

PubMed Central

Gutmann, Myron P.; Pullum-Piñón, Sara M.; Witkowski, Kristine; Deane, Glenn D.; Merchant, Emily

2014-01-01

In agricultural settings, environment shapes patterns of settlement and land use. Using the Great Plains of the United States during the period of its initial Euro-American settlement (1880–1940) as an analytical lens, this article explores whether the same environmental factors that determine settlement timing and land use—those that indicate suitability for crop-based agriculture—also shape initial family formation, resulting in fewer and smaller families in areas that are more conducive to livestock raising than to cropping. The connection between family size and agricultural land availability is now well known, but the role of the environment has not previously been explicitly tested. Descriptive analysis offers initial support for a distinctive pattern of family formation in the western Great Plains, where precipitation is too low to support intensive cropping. However, multivariate analysis using county-level data at 10-year intervals offers only partial support to the hypothesis that environmental characteristics produce these differences. Rather, this analysis has found that the region was also subject to the same long-term social and demographic changes sweeping the rest of the country during this period. PMID:24634550

Molecular key to understand the gastric cancer biology in elderly patients-The role of microsatellite instability.

PubMed

Polom, Karol; Marrelli, Daniele; Roviello, Giandomenico; Pascale, Valeria; Voglino, Costantino; Rho, Henry; Marini, Mario; Macchiarelli, Raffaele; Roviello, Franco

2017-03-01

Microsatellite instability (MSI) in gastric cancer (GC) is associated with older age. We present the clinicopathological results of younger and older patients with MSI GC. We analyzed 472 patients with GC. MSI analysis was done on fresh frozen tissue using five quasimonomorphic mononucleotide repeats: NR-21, NR-24, NR-27, BAT-25, and BAR-26. Clinical and pathological analysis was performed for different age groups. We observed better survival in elderly MSI GC patients compared to younger patients. The percentage of MSI GC increases gradually with increasing age, accounting for 48% of patients over the age of 85 years. A difference in survival was seen between MSI and MSS groups of patients older than 65 years, while no statistical difference was seen for younger groups. Multivariate analysis revealed that MSI status has a significant prognostic factor in patients aged over 70 years (MSS vs. MSI; HR 1.82, P = 0.013). MSI is an important prognostic factor above all in elderly GC patients. It is associated with favorable prognosis and may help in planning different approaches to treatment in this subgroup. J. Surg. Oncol. 2017;115:344-350. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Cycling Empirical Antibiotic Therapy in Hospitals: Meta-Analysis and Models

PubMed Central

Abel, Sören; Viechtbauer, Wolfgang; Bonhoeffer, Sebastian

2014-01-01

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings. PMID:24968123

Providing long-term trend and gravimetric factor at Chandler period from superconducting gravimeter records by using Singular Spectrum Analysis along with its multivariate extension

NASA Astrophysics Data System (ADS)

Gruszczynska, M.; Rosat, S.; Klos, A.; Bogusz, J.

2017-12-01

In this study, Singular Spectrum Analysis (SSA) along with its multivariate extension MSSA (Multichannel SSA) were used to estimate long-term trend and gravimetric factor at the Chandler wobble frequency from superconducting gravimeter (SG) records. We have used data from seven stations located worldwide and contributing to the International Geodynamics and Earth Tides Service (IGETS). The timespan ranged from 15 to 19 years. Before applying SSA and MSSA, we had removed local tides, atmospheric (ECMWF data), hydrological (MERRA2 products) loadings and non-tidal ocean loading (ECCO2 products) effects. In the first part of analysis, we used the SSA approach in order to estimate the long-term trends from SG observations. We use the technique based on the classical Karhunen-Loève spectral decomposition of time series into long-term trend, oscillations and noise. In the second part, we present the determination of common time-varying pole tide (annual and Chandler wobble) to estimate gravimetric factor from SG time series using the MSSA approach. The presented method takes advantage over traditional methods like Least Squares Estimation by determining common modes of variability which reflect common geophysical field. We adopted a 6-year lag-window as the optimal length to extract common seasonal signals and the Chandler components of the Earth polar motion. The signals characterized by annual and Chandler wobble account for approximately 62% of the total variance of residual SG data. Then, we estimated the amplitude factors and phase lags of Chandler wobble with respect to the IERS (International Earth Rotation and Reference Systems Service) polar motion observations. The resulting gravimetric factors at the Chandler Wobble period are finally compared with previously estimates. A robust estimate of the gravimetric Earth response to the Chandlerian component of the polar motion is required to better constrain the mantle anelasticity at this frequency and hence the attenuation models of the Earth interior.

Robotic-assisted colorectal surgery in the United States: a nationwide analysis of trends and outcomes.

PubMed

Halabi, Wissam J; Kang, Celeste Y; Jafari, Mehraneh D; Nguyen, Vinh Q; Carmichael, Joseph C; Mills, Steven; Stamos, Michael J; Pigazzi, Alessio

2013-12-01

While robotic-assisted colorectal surgery (RACS) is becoming increasingly popular, data comparing its outcomes to other established techniques remain limited to small case series. Moreover, there are no large studies evaluating the trends of RACS at the national level. The Nationwide Inpatient Sample 2009-2010 was retrospectively reviewed for robotic-assisted and laparoscopic colorectal procedures performed for cancer, benign polyps, and diverticular disease. Trends in different settings, indications, and demographics were analyzed. Multivariate regression analysis was used to compare selected outcomes between RACS and conventional laparoscopic surgery (CLS). An estimated 128,288 colorectal procedures were performed through minimally invasive techniques over the study period, and RACS was used in 2.78 % of cases. From 2009 to 2010, the use of robotics increased in all hospital settings but was still more common in large, urban, and teaching hospitals. Rectal cancer was the most common indication for RACS, with a tendency toward its selective use in male patients. On multivariate analysis, robotic surgery was associated with higher hospital charges in colonic ($11,601.39; 95 % CI 6,921.82-16,280.97) and rectal cases ($12,964.90; 95 % CI 6,534.79-19,395.01), and higher rates of postoperative bleeding in colonic cases (OR = 2.15; 95 % CI 1.27- 3.65). RACS was similar to CLS with respect to length of hospital stay, morbidity, anastomotic leak, and ileus. Conversion to open surgery was significantly lower in robotic colonic and rectal procedures (0.41; 95 % CI 0.25-0.67) and (0.10; 95 % CI 0.06-0.16), respectively. The use of RACS is still limited in the United States. However, its use increased over the study period despite higher associated charges and no real advantages over laparoscopy in terms of outcome. The one advantage is lower conversion rates.

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

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

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Lower early postnatal oxygen saturation target and risk of ductus arteriosus closure failure.

PubMed

Inomata, Kei; Taniguchi, Shinji; Yonemoto, Hiroki; Inoue, Takeshi; Kawase, Akihiko; Kondo, Yuichi

2016-11-01

Early postnatal hyperoxia is a major risk factor for retinopathy of prematurity (ROP) in extremely premature infants. To reduce the occurrence of ROP, we adopted a lower early postnatal oxygen saturation (SpO 2 ) target range (85-92%) from April 2011. Lower SpO 2 target range, however, may lead to hypoxemia and an increase in the risk of ductus arteriosus (DA) closure failure. The aim of this study was therefore to determine whether a lower SpO 2 target range, during the early postnatal stage, increases the risk of DA closure failure. Infants born at <28 weeks' gestation were enrolled in this study. Oxygen saturation target range during the first postnatal 72 h was 84-100% in study period 1 and 85-92% in period 2. Eighty-two infants were included in period 1, and 61 were included in period 2. The lower oxygen saturation target range increased the occurrence of hypoxemia during the first postnatal 72 h. Prevalence of DA closure failure in period 2 (21%) was significantly higher than that in period 1 (1%). On multivariate logistic regression analysis, the lower oxygen saturation target range was an independent risk factor for DA closure failure. Lower early postnatal oxygen saturation target range increases the risk of DA closure failure. © 2016 Japan Pediatric Society.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Associations of ikigai as a positive psychological factor with all-cause mortality and cause-specific mortality among middle-aged and elderly Japanese people: findings from the Japan Collaborative Cohort Study.

PubMed

Tanno, Kozo; Sakata, Kiyomi; Ohsawa, Masaki; Onoda, Toshiyuki; Itai, Kazuyoshi; Yaegashi, Yumi; Tamakoshi, Akiko

2009-07-01

To determine whether presence of ikigai as a positive psychological factor is associated with decreased risks for all-cause and cause-specific mortality among middle-aged and elderly Japanese men and women. From 1988 to 1990, a total of 30,155 men and 43,117 women aged 40 to 79 years completed a lifestyle questionnaire including a question about ikigai. Mortality follow-up was available for a mean of 12.5 years and was classified as having occurred in the first 5 years or the subsequent follow-up period. Associations between ikigai and all-cause and cause-specific mortality were assessed using a Cox's regression model. Multivariate hazard ratios (HRs) were adjusted for age, body mass index, drinking and smoking status, physical activity, sleep duration, education, occupation, marital status, perceived mental stress, and medical history. During the follow-up period, 10,021 deaths were recorded. Men and women with ikigai had decreased risks of mortality from all causes in the long-term follow-up period; multivariate HRs (95% confidence intervals, CIs) were 0.85 (0.80-0.90) for men and 0.93 (0.86-1.00) for women. The risk of cardiovascular mortality was reduced in men with ikigai; the multivariate HR (95% CI) was 0.86 (0.76-0.97). Furthermore, men and women with ikigai had a decreased risk for mortality from external causes; multivariate HRs (95% CIs) were 0.74 (0.59-0.93) for men and 0.67 (0.51-0.88) for women. The findings suggest that a positive psychological factor such as ikigai is associated with longevity among Japanese people.

Generation of multivariate near shore extreme wave conditions based on an extreme value copula for offshore boundary conditions.

NASA Astrophysics Data System (ADS)

Leyssen, Gert; Mercelis, Peter; De Schoesitter, Philippe; Blanckaert, Joris

2013-04-01

Near shore extreme wave conditions, used as input for numerical wave agitation simulations and for the dimensioning of coastal defense structures, need to be determined at a harbour entrance situated at the French North Sea coast. To obtain significant wave heights, the numerical wave model SWAN has been used. A multivariate approach was used to account for the joint probabilities. Considered variables are: wind velocity and direction, water level and significant offshore wave height and wave period. In a first step a univariate extreme value distribution has been determined for the main variables. By means of a technique based on the mean excess function, an appropriate member of the GPD is selected. An optimal threshold for peak over threshold selection is determined by maximum likelihood optimization. Next, the joint dependency structure for the primary random variables is modeled by an extreme value copula. Eventually the multivariate domain of variables was stratified in different classes, each of which representing a combination of variable quantiles with a joint probability, which are used for model simulation. The main variable is the wind velocity, as in the area of concern extreme wave conditions are wind driven. The analysis is repeated for 9 different wind directions. The secondary variable is water level. In shallow waters extreme waves will be directly affected by water depth. Hence the joint probability of occurrence for water level and wave height is of major importance for design of coastal defense structures. Wind velocity and water levels are only dependent for some wind directions (wind induced setup). Dependent directions are detected using a Kendall and Spearman test and appeared to be those with the longest fetch. For these directions, wind velocity and water level extreme value distributions are multivariately linked through a Gumbel Copula. These distributions are stratified into classes of which the frequency of occurrence can be calculated. For the remaining directions the univariate extreme wind velocity distribution is stratified, each class combined with 5 high water levels. The wave height at the model boundaries was taken into account by a regression with the extreme wind velocity at the offshore location. The regression line and the 95% confidence limits where combined with each class. Eventually the wave period is computed by a new regression with the significant wave height. This way 1103 synthetic events were selected and simulated with the SWAN wave model, each of which a frequency of occurrence is calculated for. Hence near shore significant wave heights are obtained with corresponding frequencies. The statistical distribution of the near shore wave heights is determined by sorting the model results in a descending order and accumulating the corresponding frequencies. This approach allows determination of conditional return periods. For example, for the imposed univariate design return periods of 100 years for significant wave height and 30 years for water level, the joint return period for a simultaneous exceedance of both conditions can be computed as 4000 years. Hence, this methodology allows for a probabilistic design of coastal defense structures.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

NASA Astrophysics Data System (ADS)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-07-01

Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation.

Multivariate carbon and nitrogen stable isotope model for the reconstruction of prehistoric human diet.

PubMed

Froehle, A W; Kellner, C M; Schoeninger, M J

2012-03-01

Using a sample of published archaeological data, we expand on an earlier bivariate carbon model for diet reconstruction by adding bone collagen nitrogen stable isotope values (δ(15) N), which provide information on trophic level and consumption of terrestrial vs. marine protein. The bivariate carbon model (δ(13) C(apatite) vs. δ(13) C(collagen) ) provides detailed information on the isotopic signatures of whole diet and dietary protein, but is limited in its ability to distinguish between C(4) and marine protein. Here, using cluster analysis and discriminant function analysis, we generate a multivariate diet reconstruction model that incorporates δ(13) C(apatite) , δ(13) C(collagen) , and δ(15) N holistically. Inclusion of the δ(15) N data proves useful in resolving protein-related limitations of the bivariate carbon model, and splits the sample into five distinct dietary clusters. Two significant discriminant functions account for 98.8% of the sample variance, providing a multivariate model for diet reconstruction. Both carbon variables dominate the first function, while δ(15) N most strongly influences the second. Independent support for the functions' ability to accurately classify individuals according to diet comes from a small sample of experimental rats, which cluster as expected from their diets. The new model also provides a statistical basis for distinguishing between food sources with similar isotopic signatures, as in a previously analyzed archaeological population from Saipan (see Ambrose et al.: AJPA 104(1997) 343-361). Our model suggests that the Saipan islanders' (13) C-enriched signal derives mainly from sugarcane, not seaweed. Further development and application of this model can similarly improve dietary reconstructions in archaeological, paleontological, and primatological contexts. Copyright © 2011 Wiley Periodicals, Inc.

Stature and jumping height are required in female volleyball, but motor coordination is a key factor for future elite success.

PubMed

Pion, Johan A; Fransen, Job; Deprez, Dieter N; Segers, Veerle I; Vaeyens, Roel; Philippaerts, Renaat M; Lenoir, Matthieu

2015-06-01

It was hypothesized that differences in anthropometry, physical performance, and motor coordination would be found between Belgian elite and sub-elite level female volleyball players using a retrospective analysis of test results gathered over a 5-year period. The test sample in this study consisted of 21 young female volleyball players (15.3 ± 1.5 years) who were selected to train at the Flemish Top Sports Academy for Volleyball in 2008. All players (elite, n = 13; sub-elite, n = 8) were included in the same talent development program, and the elite-level athletes were of a high to very high performance levels according to European competition level in 2013. Five multivariate analyses of variance were used. There was no significant effect of playing level on measures of anthropometry (F = 0.455, p = 0.718, (Equation is included in full-text article.)= 0.07), flexibility (F = 1.861, p = 0.188, (Equation is included in full-text article.)= 0.19), strength (F = 1.218, p = 0.355, (Equation is included in full-text article.)= 0.32); and speed and agility (F = 1.176, p = 0.350, (Equation is included in full-text article.)= 0.18). Multivariate analyses of variance revealed significant multivariate effects between playing levels for motor coordination (F = 3.470, p = 0.036, (Equation is included in full-text article.)= 0.59). A Mann-Whitney U test and a sequential discriminant analysis confirmed these results. Previous research revealed that stature and jump height are prerequisites for talent identification in female volleyball. In addition, the results show that motor coordination is an important factor in determining inclusion into the elite level in female volleyball.

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

NASA Astrophysics Data System (ADS)

Allen, J. I.; Somerfield, P. J.; Gilbert, F. J.

2007-01-01

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988-1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.

Antimicrobial resistance: the major contribution of poor governance and corruption to this growing problem.

PubMed

Collignon, Peter; Athukorala, Prema-Chandra; Senanayake, Sanjaya; Khan, Fahad

2015-01-01

To determine how important governmental, social, and economic factors are in driving antibiotic resistance compared to the factors usually considered the main driving factors-antibiotic usage and levels of economic development. A retrospective multivariate analysis of the variation of antibiotic resistance in Europe in terms of human antibiotic usage, private health care expenditure, tertiary education, the level of economic advancement (per capita GDP), and quality of governance (corruption). The model was estimated using a panel data set involving 7 common human bloodstream isolates and covering 28 European countries for the period 1998-2010. Only 28% of the total variation in antibiotic resistance among countries is attributable to variation in antibiotic usage. If time effects are included the explanatory power increases to 33%. However when the control of corruption indicator is included as an additional variable, 63% of the total variation in antibiotic resistance is now explained by the regression. The complete multivariate regression only accomplishes an additional 7% in terms of goodness of fit, indicating that corruption is the main socioeconomic factor that explains antibiotic resistance. The income level of a country appeared to have no effect on resistance rates in the multivariate analysis. The estimated impact of corruption was statistically significant (p< 0.01). The coefficient indicates that an improvement of one unit in the corruption indicator is associated with a reduction in antibiotic resistance by approximately 0.7 units. The estimated coefficient of private health expenditure showed that one unit reduction is associated with a 0.2 unit decrease in antibiotic resistance. These findings support the hypothesis that poor governance and corruption contributes to levels of antibiotic resistance and correlate better than antibiotic usage volumes with resistance rates. We conclude that addressing corruption and improving governance will lead to a reduction in antibiotic resistance.

The effects of aminosalicylates or thiopurines on the risk of colorectal cancer in inflammatory bowel disease.

PubMed

Carrat, F; Seksik, P; Colombel, J-F; Peyrin-Biroulet, L; Beaugerie, L

2017-02-01

Whether aminosalicylates or thiopurines reduce the risk of colorectal cancer (CRC) in inflammatory bowel (IBD) disease is controversial. To assess simultaneously the chemopreventive effect of aminosalicylates or thiopurines in a case-control study nested in the CESAME observational cohort that enrolled consecutive patients with IBD between May 2004 and June 2005. Patients were followed up to December 2007. Study population comprised 144 case patients who developed CRC from the diagnosis of IBD (65 and 79 cases diagnosed, respectively, before and from 2004, starting year of the prospective observational period of CESAME) and 286 controls matched for gender, age, IBD subtype and year of diagnosis, and cumulative extent of colitis. Exposure to aminosalicylates or thiopurines was defined by an exposure to the treatment during the year of the diagnosis of cancer. The propensity of receiving 5-ASA and thiopurines was quantified by a composite score taking into account patient and IBD characteristics. The role of aminosalicylates or thiopurines was assessed by multivariate analysis. Propensity scores and the history of primary sclerosing cholangitis were entered into the multivariate model for adjustment. By multivariate analysis adjusted for propensity, a significant protective effect of exposure to drugs during the year of cancer was found for aminosalicylates (OR = 0.587, 95% CI: 0.367-0.937, P = 0.0257), but not for thiopurines (OR = 0.762, 95% CI: 0.432-1.343, P = 0.3468). In a case-control study nested in the CESAME cohort, a significant decrease in the risk of colorectal cancer in IBD was associated with exposure to aminosalicylates, not to thiopurines. © 2016 John Wiley & Sons Ltd.

Association of Acetaminophen and Ibuprofen Use With Wheezing in Children With Acute Febrile Illness.

PubMed

Matok, Ilan; Elizur, Arnon; Perlman, Amichai; Ganor, Shani; Levine, Hagai; Kozer, Eran

2017-03-01

Many infants and children receive acetaminophen and/or ibuprofen during febrile illness. Previously, some studies have linked acetaminophen and ibuprofen use to wheezing and exacerbation of asthma symptoms in infants and children. To assess whether acetaminophen or ibuprofen use are associated with wheezing in children presenting to the emergency department (ED) with febrile illness. This was a cross-sectional study of children who presented with fever to the pediatric ED between 2009 and 2013. The data were collected from questionnaires and from the children's medical files. Patients with wheezing in the ED were compared with nonwheezing patients. Associations between medication use and wheezing were assessed using univariate and multivariate analyses. The multivariate analysis adjusted for potential confounding variables (ie, age, atopic dermatitis, allergies, smoking, antibiotics use, etc) via propensity scores. During the study period, 534 children admitted to the ED met our inclusion criteria, of whom 347 (65%) were included in the study. The use of acetaminophen was similar in children diagnosed with wheezing compared with those without wheezing (n = 39, 81.3%, vs n = 229, 82.7%, respectively). Ibuprofen use was significantly lower in children diagnosed with wheezing (n = 22, 52.4%, vs n = 168, 69.4%, respectively). In multivariate analysis, acetaminophen was not associated with a higher rate of wheezing during acute febrile illness (adjusted odds ratio [OR] = 0.76, 95% CI = 0.24- 2.39), whereas ibuprofen was associated with a lower risk of wheezing (adjusted OR = 0.36, 95% CI = 0.13-0.96). Our study suggests that acetaminophen and ibuprofen are not associated with increased risk for wheezing during acute febrile illness.

1H NMR Spectroscopy and MVA Analysis of Diplodus sargus Eating the Exotic Pest Caulerpa cylindracea.

PubMed

De Pascali, Sandra A; Del Coco, Laura; Felline, Serena; Mollo, Ernesto; Terlizzi, Antonio; Fanizzi, Francesco P

2015-06-05

The green alga Caulerpa cylindracea is a non-autochthonous and invasive species that is severely affecting the native communities in the Mediterranean Sea. Recent researches show that the native edible fish Diplodus sargus actively feeds on this alga and cellular and physiological alterations have been related to the novel alimentary habits. The complex effects of such a trophic exposure to the invasive pest are still poorly understood. Here we report on the metabolic profiles of plasma from D. sargus individuals exposed to C. cylindracea along the southern Italian coast, using 1H NMR spectroscopy and multivariate analysis (Principal Component Analysis, PCA, Orthogonal Partial Least Square, PLS, and Orthogonal Partial Least Square Discriminant Analysis, OPLS-DA). Fish were sampled in two seasonal periods from three different locations, each characterized by a different degree of algal abundance. The levels of the algal bisindole alkaloid caulerpin, which is accumulated in the fish tissues, was used as an indicator of the trophic exposure to the seaweed and related to the plasma metabolic profiles. The profiles appeared clearly influenced by the sampling period beside the content of caulerpin, while the analyses also supported a moderate alteration of lipid and choline metabolism related to the Caulerpa-based diet.

MULTIVARIATE CURVE RESOLUTION OF NMR SPECTROSCOPY METABONOMIC DATA

EPA Science Inventory

Sandia National Laboratories is working with the EPA to evaluate and develop mathematical tools for analysis of the collected NMR spectroscopy data. Initially, we have focused on the use of Multivariate Curve Resolution (MCR) also known as molecular factor analysis (MFA), a tech...

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Impact of aggressive management and palliative care on cancer costs in the final month of life.

PubMed

Cheung, Matthew C; Earle, Craig C; Rangrej, Jagadish; Ho, Thi H; Liu, Ning; Barbera, Lisa; Saskin, Refik; Porter, Joan; Seung, Soo Jin; Mittmann, Nicole

2015-09-15

A significant share of the cost of cancer care is concentrated in the end-of-life period. Although quality measures of aggressive treatment may guide optimal care during this timeframe, little is known about whether these metrics affect costs of care. This study used population data to identify a cohort of patients who died of cancer in Ontario, Canada (2005-2009). Individuals were categorized as having received or having not received aggressive end-of-life care according to quality measures related to acute institutional care or chemotherapy administration in the end-of-life period. Costs (2009 Canadian dollars) were collected over the last month of life through the linkage of health system administrative databases. Multivariate quantile regression was used to identify predictors of increased costs. Among 107,253 patients, the mean per-patient cost over the final month was $18,131 for patients receiving aggressive care and $12,678 for patients receiving nonaggressive care (P < .0001). Patients who received chemotherapy in the last 2 weeks of life also sustained higher costs than those who did not (P < .0001). For individuals receiving end-of-life care in the highest cost quintile, early and repeated palliative care consultation was associated with reduced mean per-patient costs. In a multivariate analysis, chemotherapy in the 2 weeks of life remained predictive of increased costs (median increase, $536; P < .0001), whereas access to palliation remained predictive for lower costs (median decrease, $418; P < .0001). Cancer patients who receive aggressive end-of-life care incur 43% higher costs than those managed nonaggressively. Palliative consultation may partially offset these costs and offer resultant savings. © 2015 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

Quantifying long-term human impact in contrasting environments: Statistical analysis of modern and fossil pollen records

NASA Astrophysics Data System (ADS)

Broothaerts, Nils; López-Sáez, José Antonio; Verstraeten, Gert

2017-04-01

Reconstructing and quantifying human impact is an important step to understand human-environment interactions in the past. Quantitative measures of human impact on the landscape are needed to fully understand long-term influence of anthropogenic land cover changes on the global climate, ecosystems and geomorphic processes. Nevertheless, quantifying past human impact is not straightforward. Recently, multivariate statistical analysis of fossil pollen records have been proposed to characterize vegetation changes and to get insights in past human impact. Although statistical analysis of fossil pollen data can provide useful insights in anthropogenic driven vegetation changes, still it cannot be used as an absolute quantification of past human impact. To overcome this shortcoming, in this study fossil pollen records were included in a multivariate statistical analysis (cluster analysis and non-metric multidimensional scaling (NMDS)) together with modern pollen data and modern vegetation data. The information on the modern pollen and vegetation dataset can be used to get a better interpretation of the representativeness of the fossil pollen records, and can result in a full quantification of human impact in the past. This methodology was applied in two contrasting environments: SW Turkey and Central Spain. For each region, fossil pollen data from different study sites were integrated, together with modern pollen data and information on modern vegetation. In this way, arboreal cover, grazing pressure and agricultural activities in the past were reconstructed and quantified. The data from SW Turkey provides new integrated information on changing human impact through time in the Sagalassos territory, and shows that human impact was most intense during the Hellenistic and Roman Period (ca. 2200-1750 cal a BP) and decreased and changed in nature afterwards. The data from central Spain shows for several sites that arboreal cover decreases bellow 5% from the Feudal period onwards (ca. 850 cal a BP) related to increasing human impact in the landscape. At other study sites arboreal cover remained above 25% beside significant human impact. Overall, the presented examples from two contrasting environments shows how cluster analysis and NMDS of modern and fossil pollen data can help to provide quantitative insights in anthropogenic land cover changes. Our study extensively discuss and illustrate the possibilities and limitations of statistical analysis of pollen data to quantify human induced land use changes.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

Localized sinonasal mucosal melanoma: Outcomes and associations with stage, radiotherapy, and positron emission tomography response.

PubMed

Samstein, Robert M; Carvajal, Richard D; Postow, Michael A; Callahan, Margaret K; Shoushtari, Alexander N; Patel, Snehal G; Lee, Nancy Y; Barker, Christopher A

2016-09-01

Sinonasal mucosal melanoma is a rare neoplasm with a poor prognosis. Retrospective analysis was conducted on 78 patients with localized sinonasal mucosal melanoma treated at Memorial Sloan Kettering Cancer Center (MSKCC from 1998-2013). Demographic, tumor, imaging, and treatment factors were recorded and survival and disease-control outcomes were analyzed. Median overall survival (OS) and disease-specific survival (DSS) were 32 and 50 months, respectively. Median locoregional recurrence-free survival (LRFS) and distant recurrence-free survival (DRFS) were 43 and 12 months, respectively. Multivariate analysis demonstrated greater OS in nasal cavity tumors and earlier T classification. Radiotherapy (RT) was associated with significantly greater LRFS (5-years; 35% vs 59%; p = .01), but no difference in OS. Post-RT positron emission tomography (PET) response was associated with greater OS. Distant metastasis is the predominant mode of recurrence in sinonasal mucosal melanoma, but local recurrence remains common. RT is associated with improved local control, but no survival benefit. The prognostic value of post-RT PET imaging warrants further investigation. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1310-1317, 2016. © 2016 Wiley Periodicals, Inc.

The demand for distilled spirits: an empirical investigation.

PubMed

McCornac, D C; Filante, R W

1984-03-01

Economic and social factors that explain variations in the consumption of distilled spirits among political jurisdictions are examined. Particular emphasis is placed on the economic roles of price and the unemployment rate. Using multivariate-analysis regression, equations are estimated for three separate time periods of 1970-1975. In addition, a pooled cross-sectional time-series analysis is undertaken for the entire time period. The dependent variable is the apparent per capita consumption of distilled spirits. The independent variables include price, availability and socioeconomic factors that determine consumption patterns. The results indicate that the price elasticity of demand for distilled spirits inelastic, and implies that a 1% change in price will result in a less than 1% change in the amount purchased, everything else being equal. A rise in price will increase total revenue. Thus, a tax increase on the commodity will generate an increase in tax revenue. The unemployment rate is shown to have a significant impact on the consumption of distilled spirits. The results suggest that further study into the relationship between unemployment and the consumption of distilled spirits is desirable.

Importance of lymphovascular invasion and invasive front on survival in floor of mouth cancer.

PubMed

Fives, Cassie; Feeley, Linda; O'Leary, Gerard; Sheahan, Patrick

2016-04-01

The floor of mouth (FOM) is a common site of oral squamous cell carcinoma (SCC). The purpose of this study was to investigate pathological predictors of survival in FOM SCC. We conducted a retrospective study of 54 consecutive patients undergoing surgery for FOM SCC. Pathological parameters were extracted from histological reports with original pathology slides re-reviewed by 2 pathologists for missing data. On univariate analysis, depth of invasion >10 mm (p = .009), lymphovascular invasion (LVI; p < .001), noncohesive invasive front (p = .006), perineural invasion (PNI; p = .003), and nodal metastases (p = .02) were significant predictors of overall survival. On multivariate analysis, LVI (p = .009) and invasive front (p < .001) remained significant. Postoperative radiotherapy improved survival in patients with LVI, PNI, and nodal metastases, and was just outside significance for noncohesive invasive front (p = .06). LVI is an adverse prognosticator in FOM SCC and indicates postoperative radiotherapy. Further study is required to investigate the importance of invasive front. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1528-E1534, 2016. © 2015 Wiley Periodicals, Inc.

[Influence of neonatal diseases and treatments on the development of cerebral palsy in preterm infant].

PubMed

Yu, Tao; Rong, Luo; Wang, Qiu; You, Yi; Fu, Jun-Xian; Kang, Lin-Min; Wu, Yan-Qiao

2013-03-01

To investigated the risk factors of cerebral palsy development in preterm infants. This study included 203 preterm infants (gestation age < 37 weeks) diagnosed with cerebral palsy (CP) and 220 preterm infants without cerebral palsy or any other severe neurological disorders during April 2005 to August 2011. The risk factors in the development of cerebral palsy, including the diseases of premature infants and the treatments in neonatal period, were analyzed by multiple logistic regression analysis. Multivariate logistic analysis for the risk factors associated with cerebral palsy in neonatal period found significant differences in the occurrence of periventricular leukomalacia (PVL, OR = 39.87, P < 0.05), hypoxia-ischemic encephalopathy (HIE, OR = 4.24, P < 0.05), hypoglycemia of neonatal (OR = 2.18, P < 0.05), neonatal hyperbilirubinemia (OR = 1.72, P < 0.05), continuous positive airway pressure (CPAP, OR = 0.21, P < 0.05). The factors including PLV, HIE, hypoglycemia, and neonatal jaundice may increase the risk in the development of CP in preterm infant, while CPAP may decrease the risk of cerebral palsy.

Lactate dehydrogenase predicts combined progression-free survival after sequential therapy with abiraterone and enzalutamide for patients with castration-resistant prostate cancer.

PubMed

Mori, Keiichiro; Kimura, Takahiro; Onuma, Hajime; Kimura, Shoji; Yamamoto, Toshihiro; Sasaki, Hiroshi; Miki, Jun; Miki, Kenta; Egawa, Shin

2017-07-01

An array of clinical issues remains to be resolved for castration-resistant prostate cancer (CRPC), including the sequence of drug use and drug cross-resistance. At present, no clear guidelines are available for the optimal sequence of use of novel agents like androgen-receptor axis-targeted (ARAT) agents, particularly enzalutamide, and abiraterone. This study retrospectively analyzed a total of 69 patients with CRPC treated with sequential therapy using enzalutamide followed by abiraterone or vice versa. The primary outcome measure was the comparative combined progression-free survival (PFS) comprising symptomatic and/or radiographic PFS. Patients were also compared for total prostate-specific antigen (PSA)-PFS, overall survival (OS), and PSA response. The predictors of combined PFS and OS were analyzed with a backward-stepwise multivariate Cox model. Of the 69 patients, 46 received enzalutamide first, followed by abiraterone (E-A group), and 23 received abiraterone, followed by enzalutamide (A-E group). The two groups were not significantly different with regard to basic data, except for hemoglobin values. In a comparison with the E-A group, the A-E group was shown to be associated with better combined PFS in Kaplan-Meier analysis (P = 0.043). Similar results were obtained for total PSA-PFS (P = 0.049), while OS did not differ between groups (P = 0.62). Multivariate analysis demonstrated that pretreatment lactate dehydrogenase (LDH) values and age were significant predictors of longer combined PFS (P < 0.05). Likewise, multivariate analysis demonstrated that pretreatment hemoglobin values and performance status were significant predictors of longer OS (P < 0.05). The results of this study suggested the A-E sequence had longer combined PSA and total PSA-PFS compared to the E-A sequence in patients with CRPC. LDH values in sequential therapy may serve as a predictor of longer combined PFS. © 2017 Wiley Periodicals, Inc.

Detectable end of radiation prostate specific antigen assists in identifying men with unfavorable intermediate-risk prostate cancer at high risk of distant recurrence and cancer-specific mortality.

PubMed

Hayman, Jonathan; Phillips, Ryan; Chen, Di; Perin, Jamie; Narang, Amol K; Trieu, Janson; Radwan, Noura; Greco, Stephen; Deville, Curtiland; McNutt, Todd; Song, Daniel Y; DeWeese, Theodore L; Tran, Phuoc T

2018-06-01

Undetectable End of Radiation PSA (EOR-PSA) has been shown to predict improved survival in prostate cancer (PCa). While validating the unfavorable intermediate-risk (UIR) and favorable intermediate-risk (FIR) stratifications among Johns Hopkins PCa patients treated with radiotherapy, we examined whether EOR-PSA could further risk stratify UIR men for survival. A total of 302 IR patients were identified in the Johns Hopkins PCa database (178 UIR, 124 FIR). Kaplan-Meier curves and multivariable analysis was performed via Cox regression for biochemical recurrence free survival (bRFS), distant metastasis free survival (DMFS), and overall survival (OS), while a competing risks model was used for PCa specific survival (PCSS). Among the 235 patients with known EOR-PSA values, we then stratified by EOR-PSA and performed the aforementioned analysis. The median follow-up time was 11.5 years (138 months). UIR was predictive of worse DMFS and PCSS (P = 0.008 and P = 0.023) on multivariable analysis (MVA). Increased radiation dose was significant for improved DMFS (P = 0.016) on MVA. EOR-PSA was excluded from the models because it did not trend towards significance as a continuous or binary variable due to interaction with UIR, and we were unable to converge a multivariable model with a variable to control for this interaction. However, when stratifying by detectable versus undetectable EOR-PSA, UIR had worse DMFS and PCSS among detectable EOR-PSA patients, but not undetectable patients. UIR was significant on MVA among detectable EOR-PSA patients for DMFS (P = 0.021) and PCSS (P = 0.033), while RT dose also predicted PCSS (P = 0.013). EOR-PSA can assist in predicting DMFS and PCSS among UIR patients, suggesting a clinically meaningful time point for considering intensification of treatment in clinical trials of intermediate-risk men. © 2018 Wiley Periodicals, Inc.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

A quarter century experience in liver trauma: a plea for early computed tomography and conservative management for all hemodynamically stable patients.

PubMed

Petrowsky, Henrik; Raeder, Susanne; Zuercher, Lucia; Platz, Andreas; Simmen, Hans Peter; Puhan, Milo A; Keel, Marius J; Clavien, Pierre-Alain

2012-02-01

Advances in diagnostic imaging and the introduction of damage control strategy in trauma have influenced our approach to treating liver trauma patients. The objective of the present study was to investigate the impact of change in liver trauma management on outcome. A total of 468 consecutive patients with liver trauma treated between 1986 and 2010 at a single level 1 trauma center were reviewed. Mechanisms of injury, diagnostic imaging, hepatic and associated injuries, management (operative [OM] vs. nonoperative [NOM]), and outcome were evaluated. The main outcome analysis compared mortality for the early study period (1986-1996) versus the later study period (1997-2010). 395 patients (84%) presented with blunt liver trauma and 73 (16%) with penetrating liver trauma. Of these, 233 patients were treated with OM (50%) versus 235 with NOM (50%). The mortality rate was 33% for the early period and 20% for the later period (odds ratio 0.19; 95% CI 0.07-0.50, P = 0.001). A significantly increased use of computed tomography (CT) as the initial diagnostic modality was observed in the late period, which almost completely replaced peritoneal lavage and ultrasound. There was a significant shift to NOM in the later period (early 15%, late 63%) with a low conversion rate to OM of 4.2%. Age, degree of hepatic and head injury, injury severity, intubation at admission, and early period were independent predictors of mortality in the multivariate analysis. Integration of CT in early trauma-room management and shift to NOM in hemodynamically stable patients resulted in improved survival and should be the gold standard management for liver trauma.

Moving beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis

ERIC Educational Resources Information Center

Barton, Mitch; Yeatts, Paul E.; Henson, Robin K.; Martin, Scott B.

2016-01-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

Predictors of Consistent Condom Use Among Young African American Women

PubMed Central

DiClemente, Ralph J.; Salazar, Laura F.; Wingood, Gina M.; McDermott-Sales, Jessica; Young, April M.; Rose, Eve

2012-01-01

The purpose of this study was to determine the predictive value of selected factors to the consistent use of condoms among high-risk young African American women. A clinic-based, prospective, study of 242 young, African-American women (ages 15–21) was conducted. In multivariate analysis, consistent condom use was predicted by having greater perceptions of condom negotiation self-efficacy, lower fear of negotiating condom use, and having communicated with sex partners (during the recall period) about condom use. Relational variables were predictive of consistent condom use among young African American women. STD/HIV preventive interventions should target these factors, perhaps in dyad-level interventions. PMID:21796442

Sleep and nutritional deprivation and performance of house officers.

PubMed

Hawkins, M R; Vichick, D A; Silsby, H D; Kruzich, D J; Butler, R

1985-07-01

A study was conducted by the authors to compare cognitive functioning in acutely and chronically sleep-deprived house officers. A multivariate analysis of variance revealed significant deficits in primary mental tasks involving basic rote memory, language, and numeric skills as well as in tasks requiring high-order cognitive functioning and traditional intellective abilities. These deficits existed only for the acutely sleep-deprived group. The finding of deficits in individuals who reported five hours or less of sleep in a 24-hour period suggests that the minimum standard of four hours that has been considered by some to be adequate for satisfactory performance may be insufficient for more complex cognitive functioning.

Relinquishment of premarital births: evidence from national survey data.

PubMed

Bachrach, C A; Stolley, K S; London, K A

1992-01-01

According to 1982 and 1988 NSFG data, unmarried white women are far less likely than they were in the early 1970s to place their children for adoption. The levels of relinquishment among black women have remained low throughout this period, and relinquishment among Hispanic women may be virtually nonexistent. Multivariate analysis of the determinants of relinquishment among unmarried non-Hispanic white women suggests that having a well-educated mother, being in school at the time of conception, having no labor force experience, and being older are positively associated with placing a child for adoption. Sons were found to be less likely to be relinquished than daughters.

Predictors of consistent condom use among young African American women.

PubMed

Crosby, Richard A; DiClemente, Ralph J; Salazar, Laura F; Wingood, Gina M; McDermott-Sales, Jessica; Young, April M; Rose, Eve

2013-03-01

The purpose of this study was to determine the predictive value of selected factors to the consistent use of condoms among high-risk young African American women. A clinic-based, prospective, study of 242 young, African-American women (ages 15-21) was conducted. In multivariate analysis, consistent condom use was predicted by having greater perceptions of condom negotiation self-efficacy, lower fear of negotiating condom use, and having communicated with sex partners (during the recall period) about condom use. Relational variables were predictive of consistent condom use among young African American women. STD/HIV preventive interventions should target these factors, perhaps in dyad-level interventions.

Characterization of spatial and temporal variability in hydrochemistry of Johor Straits, Malaysia.

PubMed

Abdullah, Pauzi; Abdullah, Sharifah Mastura Syed; Jaafar, Othman; Mahmud, Mastura; Khalik, Wan Mohd Afiq Wan Mohd

2015-12-15

Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of proximal contact loss between implant-supported fixed dental prostheses and adjacent teeth in relation to influential factors and effects. A cross-sectional study.

PubMed

Byun, Soo-Jung; Heo, Seok-Mo; Ahn, Seung-Geun; Chang, Moontaek

2015-06-01

The aim was to analyze influential factors and effects of proximal contact loss between implant-supported fixed dental prostheses (FDP) and adjacent teeth. Ninety-four subjects treated with 135 FDPs supported by 188 implants were included. Degree of proximal contact tightness, food impaction, and periodontal/peri-implant tissue conditions were assessed in 191 proximal embrasures between implant-supported FDPs and adjacent teeth. Potential factors influencing proximal contact loss were estimated with the generalized estimation equation (GEE) procedure. Thirty-four percent of the proximal embrasures between implant-supported FDPs and teeth lost a proximal contact. The proximal contact loss rate continuously increased over the follow-up periods. A longer follow-up period, splinted implants, and mesial aspect of proximal contact were significant factors influencing the proximal contact loss in the univariate GEE analysis, whereas a longer follow-up period was the only significant factor in the multivariate GEE analysis. Food impaction was more frequently reported in the proximal contact loss group than the proximal contact group (odds ratio: 2.2). However, the proximal contact loss did not appear to affect the periodontal/peri-implant tissue conditions. Proximal contact loss between implant-supported FDPs and teeth occurred frequently and increased continuously over the follow-up period. The proximal contact loss significantly affected food impaction, but not the periodontal/peri-implant tissue conditions. Proximal contact loss should be carefully monitored during follow-up examinations in relation to food impaction. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

A Century Trend of Precipitation in Forest Watersheds from the Lower Mississippi River Basin

NASA Astrophysics Data System (ADS)

Feng, G.; Ouyang, Y.; Leininger, T.; Han, Y.

2017-12-01

Estimates of hydrological processes in forest watersheds are essential to water supply planning, water quality protection, water resources management, and ecological restoration; whereas the century precipitation variation due to climate change could exacerbate forest watershed hydrological processes and add uncertainties to the processes. In this study, the multivariate statisitcal analysis technique was employed to identify a century temporal trend of precipitation in forest watersheds from the Lower Mississippi River Basin (LMRB). Seveal surface water monitoring stations in the LMRB, located in forest watersheds with very little land use disturbance and a century record, were selected to obtain precipitation data. Using frequency distribution analysis with HYDSTRA model, we found that the mean annual precipitation in a decadal scale increased as time elapsed over a 100-year period. Our study further revealed that the precipitation intensity for one-hour duration increased sigificantly in every 10 years for a 100-year period. During this period, the annual mean dry day frequency decreased in a decadal scale, whereas the annual mean wet day frequency increased for the same scale. Results indicated the precipitation pattern has been altered in the LMRB and the selected forest watersheds in this basin seems to become wetter during the past 100 years as a result of climate change.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

A way around the Nyquist lag

NASA Astrophysics Data System (ADS)

Penland, C.

2017-12-01

One way to test for the linearity of a multivariate system is to perform Linear Inverse Modeling (LIM) to a multivariate time series. LIM yields an estimated operator by combining a lagged covariance matrix with the contemporaneous covariance matrix. If the underlying dynamics is linear, the resulting dynamical description should not depend on the particular lag at which the lagged covariance matrix is estimated. This test is known as the "tau test." The tau test will be severely compromised if the lag at which the analysis is performed is approximately half the period of an internal oscillation frequency. In this case, the tau test will fail even though the dynamics are actually linear. Thus, until now, the tau test has only been possible for lags smaller than this "Nyquist lag." In this poster, we investigate the use of Hilbert transforms as a way to avoid the problems associated with Nyquist lags. By augmenting the data with dimensions orthogonal to those spanning the original system, information that would be inaccessible to LIM in its original form may be sampled.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Power analysis for multivariate and repeated measures designs: a flexible approach using the SPSS MANOVA procedure.

PubMed

D'Amico, E J; Neilands, T B; Zambarano, R

2001-11-01

Although power analysis is an important component in the planning and implementation of research designs, it is often ignored. Computer programs for performing power analysis are available, but most have limitations, particularly for complex multivariate designs. An SPSS procedure is presented that can be used for calculating power for univariate, multivariate, and repeated measures models with and without time-varying and time-constant covariates. Three examples provide a framework for calculating power via this method: an ANCOVA, a MANOVA, and a repeated measures ANOVA with two or more groups. The benefits and limitations of this procedure are discussed.

Transecting versus avoiding incision of the anterior placenta previa during cesarean delivery.

PubMed

Verspyck, Eric; Douysset, Xavier; Roman, Horace; Marret, Stephane; Marpeau, Loïc

2015-01-01

To compare maternal outcomes after transection and after avoiding incision of the anterior placenta previa during cesarean delivery. In a retrospective study, records were reviewed for women who had anterior placenta previa and delivered by cesarean after 24 weeks of pregnancy at a tertiary center in Rouen, France. During period A (January 2000 to December 2006), the protocol was to systematically transect the placenta when it was unavoidable. During period B (January 2007 to December 2010), the technique was to avoid incision by circumventing the placenta and passing a hand around its margin. Logistic regression was used to identify independent risk factors associated with maternal transfusion of packed red blood cells. Eighty-four women were included (period A: n=43; period B: n=41). During period B, there was a reduction in frequency of intraoperative hemorrhage (>1000 mL) (P=0.02), intraoperative hemoglobin loss (P=0.005), and frequency of blood transfusion (P=0.02) as compared with period A. In multivariable analysis, period B was associated with a reduced risk of maternal transfusion (odds ratio 0.27; 95% confidence interval 0.09-0.82; P=0.02). Avoiding incision of the anterior placenta previa was found to reduce frequency of maternal blood transfusion during or after cesarean delivery. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

of Likelihood Criteria for I)fferent Hypotheses," in P. A. Krishnaiah (Ed.), Multivariate Analysis-Il, New York: Academic Press. [5] Fisher, R. A...Methods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), rultivariate Analysis-Il, New York: Academic Press. [8) Kendall, M. G. (1966...1982), Applied Multivariate Statisti- cal-Analysis, Englewood Cliffs: Prentice-Mall, Inc. [1U] Krishnaiah , P. R. (1969), "Simultaneous Test

Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis

NASA Astrophysics Data System (ADS)

Almerico, Anna Maria; Tutone, Marco; Lauria, Antonino

2008-05-01

In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.

SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

EPA Science Inventory

Recent work in factor analysis of multivariate data sets has shown that variables with little signal should not be included in the factor analysis. Work also shows that rotational ambiguity is reduced if sources impacting a receptor have both large and small contributions. Thes...

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of Vision loss caused by radiation-induced optic neuropathy after particle therapy for head-and-neck and skull-base tumors adjacent to optic nerves.

PubMed

Demizu, Yusuke; Murakami, Masao; Miyawaki, Daisuke; Niwa, Yasue; Akagi, Takashi; Sasaki, Ryohei; Terashima, Kazuki; Suga, Daisaku; Kamae, Isao; Hishikawa, Yoshio

2009-12-01

To assess the incident rates of vision loss (VL; based on counting fingers or more severe) caused by radiation-induced optic neuropathy (RION) after particle therapy for tumors adjacent to optic nerves (ONs), and to evaluate factors that may contribute to VL. From August 2001 to August 2006, 104 patients with head-and-neck or skull-base tumors adjacent to ONs were treated with carbon ion or proton radiotherapy. Among them, 145 ONs of 75 patients were irradiated and followed for greater than 12 months. The incident rate of VL and the prognostic factors for occurrence of VL were evaluated. The late effects of carbon ion and proton beams were compared on the basis of a biologically effective dose at alpha/beta = 3 gray equivalent (GyE(3)). Eight patients (11%) experienced VL resulting from RION. The onset of VL ranged from 17 to 58 months. The median follow-up was 25 months. No significant difference was observed between the carbon ion and proton beam treatment groups. On univariate analysis, age (>60 years), diabetes mellitus, and maximum dose to the ON (>110 GyE(3)) were significant, whereas on multivariate analysis only diabetes mellitus was found to be significant for VL. The time to the onset of VL was highly variable. There was no statistically significant difference between carbon ion and proton beam treatments over the follow-up period. Based on multivariate analysis, diabetes mellitus correlated with the occurrence of VL. A larger study with longer follow-up is warranted.

Factors associated with recently transmitted Mycobacterium tuberculosis strain MS0006 in Hinds County, Mississippi.

PubMed

Temple, Brian; Kwara, Awewura; Sunesara, Imran; Mena, Leandro; Dobbs, Thomas; Henderson, Harold; Holcomb, Mike; Webb, Risa

2011-12-01

The objective of this study was to investigate risk factors associated with tuberculosis (TB) transmission that was caused by Mycobacterium tuberculosis strain MS0006 from 2004 to 2009 in Hinds County, Mississippi. DNA fingerprinting using spoligotyping, mycobacterial interspersed repetitive unit, and IS6110-based restriction fragment length polymorphism of culture-confirmed cases of TB was performed. Clinical and demographic factors associated with strain MS0006 were analyzed by univariate and multivariate analysis. Of the 144 cases of TB diagnosed during the study period, 117 were culture positive with fingerprints available. There were 48 different strains, of which 6 clustered strains were distributed among 74 patients. The MS0006 strain accounted for 46.2% of all culture-confirmed cases. Risk factors for having the MS0006 strain in a univariate analysis included homelessness, HIV co-infection, sputum smear negativity, tuberculin skin test negativity, and noninjectable drug use. Multivariate analysis identified homelessness (odds ratio 7.88, 95% confidence interval 2.90-21.35) and African American race (odds ratio 5.80, 95% confidence interval 1.37-24.55) as independent predictors of having TB caused by the MS0006 strain of M. tuberculosis. Our findings suggest that a majority of recently transmitted TB in the studied county was caused by the MS0006 strain. African American race and homelessness were significant risk factors for inclusion in the cluster. Molecular epidemiology techniques continue to provide in-depth analysis of disease transmission and play a vital role in effective contact tracing and interruption of ongoing transmission.

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study

PubMed Central

2010-01-01

Background We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. Methods This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS) rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Results Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68%) presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Conclusion Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered. PMID:21182799

Is objectively measured sitting time associated with low back pain? A cross-sectional investigation in the NOMAD study.

PubMed

Gupta, Nidhi; Christiansen, Caroline Stordal; Hallman, David M; Korshøj, Mette; Carneiro, Isabella Gomes; Holtermann, Andreas

2015-01-01

Studies on the association between sitting time and low back pain (LBP) have found contrasting results. This may be due to the lack of objectively measured sitting time or because socioeconomic confounders were not considered in the analysis. To investigate the association between objectively measured sitting time (daily total, and occupational and leisure-time periods) and LBP among blue-collar workers. Two-hundred-and-one blue-collar workers wore two accelerometers (GT3X+ Actigraph) for up to four consecutive working days to obtain objective measures of sitting time, estimated via Acti4 software. Workers reported their LBP intensity the past month on a scale from 0 (no pain) to 9 (worst imaginable pain) and were categorized into either low (≤ 5) or high (> 5) LBP intensity groups. In the multivariate-adjusted binary logistic regression analysis, total sitting time, and occupational and leisure-time sitting were both modeled as continuous (hours/day) and categorical variables (i.e. low, moderate and high sitting time). The multivariate logistic regression analysis showed a significant positive association between total sitting time (per hour) and high LBP intensity (odds ratio; OR = 1.43, 95%CI = 1.15-1.77, P = 0.01). Similar results were obtained for leisure-time sitting (OR = 1.45, 95%CI = 1.10-1.91, P = 0.01), and a similar but non-significant trend was obtained for occupational sitting time (OR = 1.34, 95%CI 0.99-1.82, P = 0.06). In the analysis on categorized sitting time, high sitting time was positively associated with high LBP for total (OR = 3.31, 95%CI = 1.18-9.28, P = 0.03), leisure (OR = 5.31, 95%CI = 1.57-17.90, P = 0.01), and occupational (OR = 3.26, 95%CI = 0.89-11.98, P = 0.08) periods, referencing those with low sitting time. Sitting time is positively associated with LBP intensity among blue-collar workers. Future studies using a prospective design with objective measures of sitting time are recommended.

Is Objectively Measured Sitting Time Associated with Low Back Pain? A Cross-Sectional Investigation in the NOMAD study

PubMed Central

Gupta, Nidhi; Christiansen, Caroline Stordal; Hallman, David M.; Korshøj, Mette; Carneiro, Isabella Gomes; Holtermann, Andreas

2015-01-01

Background Studies on the association between sitting time and low back pain (LBP) have found contrasting results. This may be due to the lack of objectively measured sitting time or because socioeconomic confounders were not considered in the analysis. Objectives To investigate the association between objectively measured sitting time (daily total, and occupational and leisure-time periods) and LBP among blue-collar workers. Methods Two-hundred-and-one blue-collar workers wore two accelerometers (GT3X+ Actigraph) for up to four consecutive working days to obtain objective measures of sitting time, estimated via Acti4 software. Workers reported their LBP intensity the past month on a scale from 0 (no pain) to 9 (worst imaginable pain) and were categorized into either low (≤5) or high (>5) LBP intensity groups. In the multivariate-adjusted binary logistic regression analysis, total sitting time, and occupational and leisure-time sitting were both modeled as continuous (hours/day) and categorical variables (i.e. low, moderate and high sitting time). Results The multivariate logistic regression analysis showed a significant positive association between total sitting time (per hour) and high LBP intensity (odds ratio; OR=1.43, 95%CI=1.15-1.77, P=0.01). Similar results were obtained for leisure-time sitting (OR=1.45, 95%CI=1.10-1.91, P=0.01), and a similar but non-significant trend was obtained for occupational sitting time (OR=1.34, 95%CI 0.99-1.82, P=0.06). In the analysis on categorized sitting time, high sitting time was positively associated with high LBP for total (OR=3.31, 95%CI=1.18-9.28, P=0.03), leisure (OR=5.31, 95%CI=1.57-17.90, P=0.01), and occupational (OR=3.26, 95%CI=0.89-11.98, P=0.08) periods, referencing those with low sitting time. Conclusion Sitting time is positively associated with LBP intensity among blue-collar workers. Future studies using a prospective design with objective measures of sitting time are recommended. PMID:25806808

Prediction of Postoperative Mortality in Liver Transplantation in the Era of MELD-Based Liver Allocation: A Multivariate Analysis

PubMed Central

Schultze, Daniel; Hillebrand, Norbert; Hinz, Ulf; Büchler, Markus W.; Schemmer, Peter

2014-01-01

Background and Aims Liver transplantation is the only curative treatment for end-stage liver disease. While waiting list mortality can be predicted by the MELD-score, reliable scoring systems for the postoperative period do not exist. This study's objective was to identify risk factors that contribute to postoperative mortality. Methods Between December 2006 and March 2011, 429 patients underwent liver transplantation in our department. Risk factors for postoperative mortality in 266 consecutive liver transplantations were identified using univariate and multivariate analyses. Patients who were <18 years, HU-listings, and split-, living related, combined or re-transplantations were excluded from the analysis. The correlation between number of risk factors and mortality was analyzed. Results A labMELD ≥20, female sex, coronary heart disease, donor risk index >1.5 and donor Na+>145 mmol/L were identified to be independent predictive factors for postoperative mortality. With increasing number of these risk-factors, postoperative 90-day and 1-year mortality increased (0–1: 0 and 0%; 2: 2.9 and 17.4%; 3: 5.6 and 16.8%; 4: 22.2 and 33.3%; 5–6: 60.9 and 66.2%). Conclusions In this analysis, a simple score was derived that adequately identified patients at risk after liver transplantation. Opening a discussion on the inclusion of these parameters in the process of organ allocation may be a worthwhile venture. PMID:24905210

A data fusion-based drought index

NASA Astrophysics Data System (ADS)

Azmi, Mohammad; Rüdiger, Christoph; Walker, Jeffrey P.

2016-03-01

Drought and water stress monitoring plays an important role in the management of water resources, especially during periods of extreme climate conditions. Here, a data fusion-based drought index (DFDI) has been developed and analyzed for three different locations of varying land use and climate regimes in Australia. The proposed index comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type. In deriving the proposed index, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were employed to first derive commonly used individual standardized drought indices (SDIs), which were then grouped using an advanced clustering method. Next, three different multivariate methods (principal component analysis, factor analysis, and independent component analysis) were utilized to aggregate the SDIs located within each group. For the two clusters in which the grouped SDIs best reflected the water availability and vegetation conditions, the variables were aggregated based on an averaging between the standardized first principal components of the different multivariate methods. Then, considering those two aggregated indices as well as the classifications of months (dry/wet months and active/non-active months), the proposed DFDI was developed. Finally, the symbolic regression method was used to derive mathematical equations for the proposed DFDI. The results presented here show that the proposed index has revealed new aspects in water stress monitoring which previous indices were not able to, by simultaneously considering both hydrometeorological and ecological concepts to define the real water stress of the study areas.

Higher serum chloride concentrations are associated with acute kidney injury in unselected critically ill patients.

PubMed

Zhang, Zhongheng; Xu, Xiao; Fan, Haozhe; Li, Danyu; Deng, Hongsheng

2013-10-28

Chloride administration has been found to be harmful to the kidney in critically ill patients. However the association between plasma chloride concentration and renal function has never been investigated. This was a retrospective study conducted in a tertiary 24-bed intensive care unit from September 2010 to November 2012. Data on serum chloride for each patient during their ICU stay were abstracted from electronic database. Cl0 referred to the initial chloride on ICU entry, Cl(max), Cl(min) and Cl(mean) referred to the maximum, minimum and mean chloride values before the onset of AKI, respectively. AKI was defined according to the conventional AKIN criteria. Univariate and multivariable analysis were performed to examine the association of chloride and AKI development. A total of 1221 patients were included into analysis during study period. Three hundred and fifty-seven patients (29.2%) developed AKI. Cl(max) was significantly higher in AKI than in non-AKI group (111.8 ± 8.1 vs 107.9 ± 5.4 mmol/l; p < 0.001); Cl0 was not significantly different between AKI and non-AKI patients; Cl(mean) was significantly higher in AKI than non-AKI (104.3 ± 5.8 vs 103.4 ± 4.5;  = 0.0047) patients. Cl(max) remained to be associated with AKI in multivariable analysis (OR: 1.10, 95% CI: 1.08-1.13). Chloride overload as represented by Cl(mean) and Cl(max) is significantly associated with the development of AKI.

Effects of freezing on white perch Morone americana (Gmelin, 1789): Implications for multivariate morphometrics

USGS Publications Warehouse

Kocovsky, Patrick

2016-01-01

This study tested the hypothesis that duration of freezing differentially affects whole-body morphometrics of a derived teleost. Whole-body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole-body morphometrics changed as a result of freezing, 23 whole-body morphometrics of age-1 white perch (Morone americana) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P < 0.0001). The first canonical axis reflected long-axis morphometrics, where there was a clear pattern of positive translation along this axis with duration of preservation. Re-classification analysis demonstrated fish were typically assigned to their original preservation class except for fish frozen 100 days, which assigned mostly to frozen 200 days. Morphometric comparisons using frozen fish must be done on fish frozen for identical periods of time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin- and alcohol-preserved specimens.

Race and acute abdominal pain in a pediatric emergency department.

PubMed

Caperell, Kerry; Pitetti, Raymond; Cross, Keith P

2013-06-01

To investigate the demographic and clinical factors of children who present to the pediatric emergency department (ED) with abdominal pain and their outcomes. A review of the electronic medical record of patients 1 to 18 years old, who presented to the Children's Hospital of Pittsburgh ED with a complaint of abdominal pain over the course of 2 years, was conducted. Demographic and clinical characteristics, as well as visit outcomes, were reviewed. Subjects were grouped by age, race, and gender. Results of evaluation, treatment, and clinical outcomes were compared between groups by using multivariate analysis and recursive partitioning. There were 9424 patient visits during the study period that met inclusion and exclusion criteria. Female gender comprised 61% of African American children compared with 52% of white children. Insurance was characterized as private for 75% of white and 37% of African American children. A diagnosis of appendicitis was present in 1.9% of African American children and 5.1% of white children. Older children were more likely to be admitted and have an operation associated with their ED visit. Appendicitis was uncommon in younger children. Constipation was commonly diagnosed. Multivariate analysis by diagnosis as well as recursive partitioning analysis did not reflect any racial differences in evaluation, treatment, or outcome. Constipation is the most common diagnosis in children presenting with abdominal pain. Our data demonstrate that no racial differences exist in the evaluation, treatment, and disposition of children with abdominal pain.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Factors relating to transmission of viral hepatitis in a United States military population stationed in Thailand.

PubMed

Scott, R M; Schneider, R J; Snitbhan, R; Karwacki, J J

1981-05-01

To determine the incidence of clinical and inapparent hepatitis in a US military population stationed in Thailand, the authors prospectively studied a cohort of 326 men during one year. Clinical hepatitis A occurred in one man (clinical attack rate = 3.1/1000 men/year), and clinical hepatitis B was found in four men (clinical attack rate = 12.3/1000 men/year). No non-A, non-B hepatitis was identified. There was no serologically identified inapparent hepatitis A but inapparent hepatitis B occurred in 17 men. The apparent/inapparent ratio for hepatitis B was 1:4.25. Serotype analysis suggested that hepatitis B virus largely originated from Thai contacts, although 23% of cases were derived from western sources. To determine the relative contribution of 16 statistically significant (out of 67 studied) behavioral variables to the transmission of HBV, a factor analysis and a multivariate correlation analysis were employed. Factor analysis indicated that social and sexual contact with the indigenous population, including prostitutes, residence within the Thai community and marijuana use were behavioral areas that were associated with the acquisition of hepatitis B. Residence in the Thai community during the first four-month period in Thailand, sexual contact with a prostitute during the third four-month period, and ever having maintained a Thai mistress were found to be significant and independent risk factors by multiple regression analysis.

Diffraction-analysis-based characterization of very fine gratings

NASA Astrophysics Data System (ADS)

Bischoff, Joerg; Truckenbrodt, Horst; Bauer, Joachim J.

1997-09-01

Fine gratings with spatial periods below one micron, either ruled mechanically or patterned holographically, play a key role as encoders in high precision translational or rotational coordinate or measuring machines. Besides, the fast in-line characterization of submicron patterns is a stringent demand in recent microelectronic technology. Thus, a rapid, destruction free and highly accurate measuring technique is required to ensure the quality during manufacturing and for final testing. We propose an optical method which was already successfully introduced in semiconductor industry. Here, the inverse scatter problem inherent in this diffraction based approach is overcome by sophisticated data analysis such as multivariate regression or neural networks. Shortly sketched, the procedure is as follows: certain diffraction efficiencies are measured with an optical angle resolved scatterometer and assigned to a number of profile parameters via data analysis (prediction). Before, the specific measuring model has to be calibrated. If the wavelength-to-period rate is well below unity, it is quite easy to gather enough diffraction orders. However, for gratings with spatial periods being smaller than the probing wavelength, merely the specular reflex will propagate for perpendicular incidence (zero order grating). Consequently, it is virtually impossible to perform a regression analysis. A proper mean to tackle this bottleneck is to record the zero-order reflex as a function of the incident angle. In this paper, the measurement of submicron gratings is discussed with the examples of 0.8, 1.0 and 1.4 micron period resist gratings on silicon, etched silicon oxide on silicon (same periods) and a 512 nm pitch chromium grating on quartz. Using a He-Ne laser with 633 nm wavelength and measuring the direct reflex in both linear polarizations, it is shown that even submicron patterning processes can be monitored and the resulting profiles with linewidths below a half micron can be characterized reliably with 2(theta) - scatterometry.

Examining job tenure and lost-time claim rates in Ontario, Canada, over a 10-year period, 1999-2008.

PubMed

Morassaei, Sara; Breslin, F Curtis; Shen, Min; Smith, Peter M

2013-03-01

We sought to examine the association between job tenure and lost-time claim rates over a 10-year period in Ontario, Canada. Data were obtained from workers' compensation records and labour force survey data from 1999 to 2008. Claim rates were calculated for gender, age, industry, occupation, year and job tenure group. A multivariate analysis and examination of effect modification were performed. Differences in injury event and source of injury were also examined by job tenure. Lost-time claim rates were significantly higher for workers with shorter job tenure, regardless of other factors. Claim rates for new workers differed by gender, age and industry, but remained relatively constant at an elevated rate over the observed time period. This study is the first to examine lost-time claim rates by job tenure over a time period during which overall claim rates generally declined. Claim rates did not show a convergence by job tenure. Findings highlight that new workers are still at elevated risk, and suggest the need for improved training, reducing exposures among new workers, promoting permanent employment, and monitoring work injury trends and risk factors.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Nutritional Intervention: A Secondary Analysis of Its Effect on Malnourished Colombian Pre-Schoolers.

ERIC Educational Resources Information Center

Bejar, Isaac I.

1981-01-01

Effects of nutritional supplementation on physical development of malnourished children was analyzed by univariate and multivariate methods for the analysis of repeated measures. Results showed that the nutritional treatment was successful, but it was necessary to resort to the multivariate approach. (Author/GK)

A Multivariate Descriptive Model of Motivation for Orthodontic Treatment.

ERIC Educational Resources Information Center

Hackett, Paul M. W.; And Others

1993-01-01

Motivation for receiving orthodontic treatment was studied among 109 young adults, and a multivariate model of the process is proposed. The combination of smallest scale analysis and Partial Order Scalogram Analysis by base Coordinates (POSAC) illustrates an interesting methodology for health treatment studies and explores motivation for dental…

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Univariate Analysis of Multivariate Outcomes in Educational Psychology.

ERIC Educational Resources Information Center

Hubble, L. M.

1984-01-01

The author examined the prevalence of multiple operational definitions of outcome constructs and an estimate of the incidence of Type I error rates when univariate procedures were applied to multiple variables in educational psychology. Multiple operational definitions of constructs were advocated and wider use of multivariate analysis was…

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Evaluation of Meterorite Amono Acid Analysis Data Using Multivariate Techniques

NASA Technical Reports Server (NTRS)

McDonald, G.; Storrie-Lombardi, M.; Nealson, K.

1999-01-01

The amino acid distributions in the Murchison carbonaceous chondrite, Mars meteorite ALH84001, and ice from the Allan Hills region of Antarctica are shown, using a multivariate technique known as Principal Component Analysis (PCA), to be statistically distinct from the average amino acid compostion of 101 terrestrial protein superfamilies.

MULTIVARIATE ANALYSIS ON LEVELS OF SELECTED METALS, PARTICULATE MATTER, VOC, AND HOUSEHOLD CHARACTERISTICS AND ACTIVITIES FROM THE MIDWESTERN STATES NHEXAS

EPA Science Inventory

Microenvironmental and biological/personal monitoring information were collected during the National Human Exposure Assessment Survey (NHEXAS), conducted in the six states comprising U.S. EPA Region Five. They have been analyzed by multivariate analysis techniques with general ...

The maternal and neonatal outcomes for an urban Indigenous population compared with their non-Indigenous counterparts and a trend analysis over four triennia.

PubMed

Kildea, Sue; Stapleton, Helen; Murphy, Rebecca; Kosiak, Machellee; Gibbons, Kristen

2013-08-30

Indigenous Australians experience significantly disproportionate poorer health outcomes compared to their non-Indigenous counterparts. Despite the recognised importance of maternal infant health (MIH), there is surprisingly little empirical research to guide service redesign that successfully addresses the disparities. This paper reports on a service evaluation that also compared key MIH indicators for Indigenous and non-Indigenous mothers and babies over a 12-year period 1998-2009. Trend analysis with logistic regression, using the independent variables of ethnicity and triennia, explored changes over time (1998-2009) between two cohorts: 1,523 births to Indigenous mothers and 43,693 births to non-Indigenous mothers. We included bivariate and multivariate analysis on key indicators (e.g. teenage births, preterm birth, low birth weight, smoking) and report odds ratios (ORs), 95% CIs and logistic regression adjusting for important confounders. We excluded transfers in from other areas which are identified within the database. Bivariate analysis revealed Indigenous women were statistically more likely to have spontaneous onset of labour and a non-instrumental vaginal birth. They were less likely to take epidurals for pain relief in labour, have assisted births, caesarean sections or perineal trauma. Despite better labour outcomes, Indigenous babies were more likely to be born preterm (< 37 weeks) and be low birth weight (< 2500 g); these differences remained significant in multivariate analysis. The trend analysis revealed relatively stable rates for teenage pregnancy, small for gestational age, low birth weight babies, and perinatal mortality for both cohorts, with the gap between cohorts consistent over time. A statistical widening of the gap in preterm birth and smoking rates was found with preterm birth demonstrating a relative increase of 51% over this period. The comprehensive database from a large urban hospital allowed a thorough examination of outcomes and contributing factors. The gap between both cohorts remains static in several areas but in some cases worsened. Alternative models for delivering care to Indigenous women and their babies have shown improved outcomes, including preterm birth, though not all have been sustained over time and none are available Australia-wide. New models of care, which recognise the heterogeneity of Indigenous communities, incorporate a multiagency approach, and are set within a research framework, are urgently needed.

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

Morphologic Features of Magnetic Resonance Imaging as a Surrogate of Capsular Contracture in Breast Cancer Patients With Implant-based Reconstructions.

PubMed

Tyagi, Neelam; Sutton, Elizabeth; Hunt, Margie; Zhang, Jing; Oh, Jung Hun; Apte, Aditya; Mechalakos, James; Wilgucki, Molly; Gelb, Emily; Mehrara, Babak; Matros, Evan; Ho, Alice

2017-02-01

Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. Currently, no objective methods are available for assessing CC. The goal of the present study was to identify image-based surrogates of CC using magnetic resonance imaging (MRI). We analyzed a retrospective data set of 50 patients who had undergone both a diagnostic MRI scan and a plastic surgeon's evaluation of the CC score (Baker's score) within a 6-month period after mastectomy and reconstructive surgery. The MRI scans were assessed for morphologic shape features of the implant and histogram features of the pectoralis muscle. The shape features, such as roundness, eccentricity, solidity, extent, and ratio length for the implant, were compared with the Baker score. For the pectoralis muscle, the muscle width and median, skewness, and kurtosis of the intensity were compared with the Baker score. Univariate analysis (UVA) using a Wilcoxon rank-sum test and multivariate analysis with the least absolute shrinkage and selection operator logistic regression was performed to determine significant differences in these features between the patient groups categorized according to their Baker's scores. UVA showed statistically significant differences between grade 1 and grade ≥2 for morphologic shape features and histogram features, except for volume and skewness. Only eccentricity, ratio length, and volume were borderline significant in differentiating grade ≤2 and grade ≥3. Features with P<.1 on UVA were used in the multivariate least absolute shrinkage and selection operator logistic regression analysis. Multivariate analysis showed a good level of predictive power for grade 1 versus grade ≥2 CC (area under the receiver operating characteristic curve 0.78, sensitivity 0.78, and specificity 0.82) and for grade ≤2 versus grade ≥3 CC (area under the receiver operating characteristic curve 0.75, sensitivity 0.75, and specificity 0.79). The morphologic shape features described on MR images were associated with the severity of CC. MRI has the potential to further improve the diagnostic ability of the Baker score in breast cancer patients who undergo implant reconstruction. Copyright © 2016 Elsevier Inc. All rights reserved.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Clinical correlates and prognostic value of different metastatic sites in patients with malignant melanoma of the skin: a SEER database analysis.

PubMed

Abdel-Rahman, Omar

2018-03-01

Population-based data on the clinical correlates and prognostic value of the pattern of metastases among patients with cutaneous melanoma are needed. Surveillance, Epidemiology and End Results (SEER) database (2010-2013) has been explored through SEER*Stat program. For each of six distant metastatic sites (bone, brain, liver, lung, distant lymph nodes, and skin/subcutaneous), relevant correlation with baseline characteristics were reported. Survival analysis has been conducted through Kaplan-Meier analysis, and multivariate analysis has been conducted through a Cox proportional hazard model. A total of 2691 patients with metastatic cutaneous melanoma were identified in the period from 2010 to 2013. Patients with isolated skin/subcutaneous metastases have the best overall and melanoma-specific survival (MSS) followed by patients with isolated distant lymph node metastases followed by patients with isolated lung metastases. Patients with isolated liver, bone, or brain metastases have the worst overall and MSS (p < .0001 for both end points). Multivariate analysis revealed that age more than 70 at diagnosis (p = .012); multiple sites of metastases (p <.0001), no surgery to the primary tumor (p <.0001), and no surgery to the metastatic disease (p < .0001) were associated with worse overall survival (OS). For MSS, nodal positivity (p = .038), multiple sites of metastases (p < .0001), no surgery to the primary tumor (p < .0001), and no surgery to the metastatic disease (p < .0001) were associated with worse survival. The prognosis of metastatic cutaneous melanoma patients differs considerably according to the site of distant metastases. Further prospective studies are required to evaluate the role of local treatment in the management of metastatic disease.

Effects of Green Tea Gargling on the Prevention of Influenza Infection: An Analysis Using Bayesian Approaches.

PubMed

Ide, Kazuki; Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi

2017-02-01

The aim of this study is to analyze the data obtained from a randomized trial on the prevention of influenza by gargling with green tea, which gave nonsignificant results based on frequentist approaches, by using Bayesian approaches. The posterior proportion, with 95% credible interval (CrI), of influenza in each group was calculated. The Bayesian index θ is the probability that a hypothesis is true. In this case, θ is the probability that the hypothesis that green tea gargling reduced influenza compared with water gargling is true. Univariate and multivariate logistic regression analyses were also performed by using the Markov chain Monte Carlo method. The full analysis set included 747 participants. During the study period, influenza occurred in 44 participants (5.9%). The difference between the two independent binominal proportions was -0.019 (95% CrI, -0.054 to 0.015; θ = 0.87). The partial regression coefficients in the univariate analysis were -0.35 (95% CrI, -1.00 to 0.24) with use of a uniform prior and -0.34 (95% CrI, -0.96 to 0.27) with use of a Jeffreys prior. In the multivariate analysis, the values were -0.37 (95% CrI, -0.96 to 0.30) and -0.36 (95% CrI, -1.03 to 0.21), respectively. The difference between the two independent binominal proportions was less than 0, and θ was greater than 0.85. Therefore, green tea gargling may slightly reduce influenza compared with water gargling. This analysis suggests that green tea gargling can be an additional preventive measure for use with other pharmaceutical and nonpharmaceutical measures and indicates the need for additional studies to confirm the effect of green tea gargling.

Treatment of a long-acting anticoagulant rodenticide poisoning cohort with vitamin K1 during the maintenance period

PubMed Central

Long, Jianhai; Peng, Xiaobo; Luo, Yuan; Sun, Yawei; Lin, Guodong; Wang, Yongan; Qiu, Zewu

2016-01-01

Abstract Currently, there are few guidelines for the use of vitamin K1 in the maintenance treatment of long-acting anticoagulant rodenticide (LAAR) poisonings. We explored factors in the treatment of LAAR poisoning during the maintenance period in order to suggest feasible treatment models. Data from 24 cases of anticoagulant rodenticide poisoning in our hospital were collected from January 2013 to May 2016. The patients’ sex, age, coagulation function, total time from poisoning to treatment with vitamin K1 (prehospital time), vitamin K1 sustained treatment time (VKSTT), anticoagulant rodenticide category, and specific poison dosage were collected. Multivariate analysis was used to evaluate the correlation between vitamin K1 dosage and other factors during the maintenance period. Only VKSTT (partial regression coefficient −1.133, 0.59, P = 0.035) had an obvious influence on the therapeutic dose of vitamin K1 required during the maintenance period. After an initial pulse therapy, the bleeding and coagulation functions were stabilized, and the patients were subsequently treated with vitamin K1 during the maintenance period. Over time, the maintenance dose of vitamin K1 (10–120 mg/d, intravenous drip) was gradually decreased and was not related to toxicant concentration. PMID:28002326

A novel multivariate STeady-state index during general ANesthesia (STAN).

PubMed

Castro, Ana; de Almeida, Fernando Gomes; Amorim, Pedro; Nunes, Catarina S

2017-08-01

The assessment of the adequacy of general anesthesia for surgery, namely the nociception/anti-nociception balance, has received wide attention from the scientific community. Monitoring systems based on the frontal EEG/EMG, or autonomic state reactions (e.g. heart rate and blood pressure) have been developed aiming to objectively assess this balance. In this study a new multivariate indicator of patients' steady-state during anesthesia (STAN) is proposed, based on wavelet analysis of signals linked to noxious activation. A clinical protocol was designed to analyze precise noxious stimuli (laryngoscopy/intubation, tetanic, and incision), under three different analgesic doses; patients were randomized to receive either remifentanil 2.0, 3.0 or 4.0 ng/ml. ECG, PPG, BP, BIS, EMG and [Formula: see text] were continuously recorded. ECG, PPG and BP were processed to extract beat-to-beat information, and [Formula: see text] curve used to estimate the respiration rate. A combined steady-state index based on wavelet analysis of these variables, was applied and compared between the three study groups and stimuli (Wilcoxon signed ranks, Kruskal-Wallis and Mann-Whitney tests). Following institutional approval and signing the informed consent thirty four patients were enrolled in this study (3 excluded due to signal loss during data collection). The BIS index of the EEG, frontal EMG, heart rate, BP, and PPG wave amplitude changed in response to different noxious stimuli. Laryngoscopy/intubation was the stimulus with the more pronounced response [Formula: see text]. These variables were used in the construction of the combined index STAN; STAN responded adequately to noxious stimuli, with a more pronounced response to laryngoscopy/intubation (18.5-43.1 %, [Formula: see text]), and the attenuation provided by the analgesic, detecting steady-state periods in the different physiological signals analyzed (approximately 50 % of the total study time). A new multivariate approach for the assessment of the patient steady-state during general anesthesia was developed. The proposed wavelet based multivariate index responds adequately to different noxious stimuli, and attenuation provided by the analgesic in a dose-dependent manner for each stimulus analyzed in this study.

Decreased Surgical Site Infection Rate in Hysterectomy: Effect of a Gynecology-Specific Bundle.

PubMed

Andiman, Sarah E; Xu, Xiao; Boyce, John M; Ludwig, Elizabeth M; Rillstone, Heidi R W; Desai, Vrunda B; Fan, Linda L

2018-06-01

We implemented a hysterectomy-specific surgical site infection prevention bundle after a higher-than-expected surgical site infection rate was identified at our institution. We evaluate how this bundle affected the surgical site infection rate, length of hospital stay, and 30-day postoperative readmission rate. This is a quality improvement study featuring retrospective analysis of a prospectively implemented, multidisciplinary team-designed surgical site infection prevention bundle that consisted of chlorhexidine-impregnated preoperative wipes, standardized aseptic surgical preparation, standardized antibiotic dosing, perioperative normothermia, surgical dressing maintenance, and direct feedback to clinicians when the protocol was breached. There were 2,099 hysterectomies completed during the 33-month study period. There were 61 surgical site infections (4.51%) in the pre-full bundle implementation period and 14 (1.87%) in the post-full bundle implementation period; we found a sustained reduction in the proportion of patients experiencing surgical site infection during the last 8 months of the study period. After adjusting for clinical characteristics, patients who underwent surgery after full implementation were less likely to develop a surgical site infection (adjusted odds ratio [OR] 0.46, P=.01) than those undergoing surgery before full implementation. Multivariable regression analysis showed no statistically significant difference in postoperative days of hospital stay (adjusted mean ratio 0.95, P=.09) or rate of readmission for surgical site infection-specific indication (adjusted OR 2.65, P=.08) between the before and after full-bundle implementation periods. The multidisciplinary implementation of a gynecologic perioperative surgical site infection prevention bundle was associated with a significant reduction in surgical site infection rate in patients undergoing hysterectomy.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

principle, Applications of Statistics, P. R. Krishnaiah , ed., North-Holland: Amsterdam, 27-41. Anderson, T. W. (1971). The Statistical Analysis of Time Series...E. (1969). Multiple Time Series Modeling, Multivariate Analysis II, edited by P. Krishnaiah , Academic Press: New York, 389-409. Parzen, E. (1981...Newton, H. J. (1980). Multiple Time Series Modeling, II Multivariate Analysis - V, edited by P. Krishnaiah , North Holland: Amsterdam, 181-197. Shibata, R

Genomic Analysis of Complex Microbial Communities in Wounds

DTIC Science & Technology

2012-01-01

thoroughly in the ecology literature. Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no...difference between the bacterial communities found within a single wound compared to those from different patients (α = 0.05). PerMANOVA is a...permutation-based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and

Period of residence in prefabricated temporary housing and psychological distress after the Great East Japan Earthquake: a longitudinal study

PubMed Central

Tanji, Fumiya; Tomata, Yasutake; Sekiguchi, Takuya; Tsuji, Ichiro

2018-01-01

Objectives Previous studies have reported that displacement from one’s own home after a natural disaster is associated with a higher degree of psychological distress. The present study investigated the longitudinal association between the period of residence in prefabricated temporary housing and psychological distress after the Great East Japan Earthquake. Design, setting and participants We conducted a longitudinal observation of 284 adults (aged ≥18 years) who had lived in prefabricated temporary housing in Miyagi, Northeastern Japan. The period of residence in prefabricated temporary housing was classified into three categories: <3, 3–4 and >4 years (ie, still living in prefabricated temporary housing). Outcomes The Kessler 6-item Psychological Distress Scale (K6) was assessed in both a baseline survey (2011) and a follow-up survey (2016). Higher psychological distress was defined by a K6 score of ≥5. We used Firth’s penalised likelihood method in the multivariate logistic regression model to estimate the adjusted ORs and 95% CIs. Results Among the total participants, the proportion of individuals with higher psychological distress at the follow-up survey was significantly higher in the >4 years category (multivariate OR=4.00, 95% CI 1.67 to 10.16) than in the <3 years category. Among participants who had a lower degree of psychological distress at the baseline, the proportion of those whose psychological distress deteriorated was significantly higher in the >4 years category (multivariate OR=4.87, 95% CI 1.26 to 20.28) than in the <3 years category. On the other hand, among the participants who had a higher degree of psychological distress at the baseline, the proportion of those whose psychological distress ameliorated was significantly lower in the >4 years category (multivariate OR=0.26, 95% CI 0.06 to 0.85) than in the <3 years category. Conclusions The proportion of individuals with more severe psychological distress was higher among participants who had lived in prefabricated temporary housing for a long period. PMID:29730612

Islet Product Characteristics and Factors Related to Successful Human Islet Transplantation From the Collaborative Islet Transplant Registry (CITR) 1999–2010

PubMed Central

Balamurugan, A N; Naziruddin, B; Lockridge, A; Tiwari, M; Loganathan, G; Takita, M; Matsumoto, S; Papas, K; Trieger, M; Rainis, H; Kin, T; Kay, T W; Wease, S; Messinger, S; Ricordi, C; Alejandro, R; Markmann, J; Kerr-Conti, J; Rickels, M R; Liu, C; Zhang, X; Witkowski, P; Posselt, A; Maffi, P; Secchi, A; Berney, T; O’Connell, P J; Hering, B J; Barton, F B

2014-01-01

The Collaborative Islet Transplant Registry (CITR) collects data on clinical islet isolations and transplants. This retrospective report analyzed 1017 islet isolation procedures performed for 537 recipients of allogeneic clinical islet transplantation in 1999–2010. This study describes changes in donor and islet isolation variables by era and factors associated with quantity and quality of final islet products. Donor body weight and BMI increased significantly over the period (p < 0.001). Islet yield measures have improved with time including islet equivalent (IEQ)/particle ratio and IEQs infused. The average dose of islets infused significantly increased in the era of 2007–2010 when compared to 1999–2002 (445.4 ± 156.8 vs. 421.3 ± 155.4 ×103 IEQ; p < 0.05). Islet purity and total number of β cells significantly improved over the study period (p < 0.01 and <0.05, respectively). Otherwise, the quality of clinical islets has remained consistently very high through this period, and differs substantially from nonclinical islets. In multivariate analysis of all recipient, donor and islet factors, and medical management factors, the only islet product characteristic that correlated with clinical outcomes was total IEQs infused. This analysis shows improvements in both quantity and some quality criteria of clinical islets produced over 1999–2010, and these parallel improvements in clinical outcomes over the same period. PMID:25278159

In situ X-ray diffraction analysis of (CF x) n batteries: signal extraction by multivariate analysis

DOE PAGES

Rodriguez, Mark A.; Keenan, Michael R.; Nagasubramanian, Ganesan

2007-11-10

In this study, (CF x) n cathode reaction during discharge has been investigated using in situ X-ray diffraction (XRD). Mathematical treatment of the in situ XRD data set was performed using multivariate curve resolution with alternating least squares (MCR–ALS), a technique of multivariate analysis. MCR–ALS analysis successfully separated the relatively weak XRD signal intensity due to the chemical reaction from the other inert cell component signals. The resulting dynamic reaction component revealed the loss of (CF x) n cathode signal together with the simultaneous appearance of LiF by-product intensity. Careful examination of the XRD data set revealed an additional dynamicmore » component which may be associated with the formation of an intermediate compound during the discharge process.« less

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Modelling uncertainties and possible future trends of precipitation and temperature for 10 sub-basins in Columbia River Basin (CRB)

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Rana, A.; Qin, Y.; Moradkhani, H.

2014-12-01

Trends and changes in future climatic parameters, such as, precipitation and temperature have been a central part of climate change studies. In the present work, we have analyzed the seasonal and yearly trends and uncertainties of prediction in all the 10 sub-basins of Columbia River Basin (CRB) for future time period of 2010-2099. The work is carried out using 2 different sets of statistically downscaled Global Climate Model (GCMs) projection datasets i.e. Bias correction and statistical downscaling (BCSD) generated at Portland State University and The Multivariate Adaptive Constructed Analogs (MACA) generated at University of Idaho. The analysis is done for with 10 GCM downscaled products each from CMIP5 daily dataset totaling to 40 different downscaled products for robust analysis. Summer, winter and yearly trend analysis is performed for all the 10 sub-basins using linear regression (significance tested by student t test) and Mann Kendall test (0.05 percent significance level), for precipitation (P), temperature maximum (Tmax) and temperature minimum (Tmin). Thereafter, all the parameters are modelled for uncertainty, across all models, in all the 10 sub-basins and across the CRB for future scenario periods. Results have indicated in varied degree of trends for all the sub-basins, mostly pointing towards a significant increase in all three climatic parameters, for all the seasons and yearly considerations. Uncertainty analysis have reveled very high change in all the parameters across models and sub-basins under consideration. Basin wide uncertainty analysis is performed to corroborate results from smaller, sub-basin scale. Similar trends and uncertainties are reported on the larger scale as well. Interestingly, both trends and uncertainties are higher during winter period than during summer, contributing to large part of the yearly change.

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

ERIC Educational Resources Information Center

Tchumtchoua, Sylvie; Dey, Dipak K.

2012-01-01

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

The association between body mass index and severe biliary infections: a multivariate analysis.

PubMed

Stewart, Lygia; Griffiss, J McLeod; Jarvis, Gary A; Way, Lawrence W

2012-11-01

Obesity has been associated with worse infectious disease outcomes. It is a risk factor for cholesterol gallstones, but little is known about associations between body mass index (BMI) and biliary infections. We studied this using factors associated with biliary infections. A total of 427 patients with gallstones were studied. Gallstones, bile, and blood (as applicable) were cultured. Illness severity was classified as follows: none (no infection or inflammation), systemic inflammatory response syndrome (fever, leukocytosis), severe (abscess, cholangitis, empyema), or multi-organ dysfunction syndrome (bacteremia, hypotension, organ failure). Associations between BMI and biliary bacteria, bacteremia, gallstone type, and illness severity were examined using bivariate and multivariate analysis. BMI inversely correlated with pigment stones, biliary bacteria, bacteremia, and increased illness severity on bivariate and multivariate analysis. Obesity correlated with less severe biliary infections. BMI inversely correlated with pigment stones and biliary bacteria; multivariate analysis showed an independent correlation between lower BMI and illness severity. Most patients with severe biliary infections had a normal BMI, suggesting that obesity may be protective in biliary infections. This study examined the correlation between BMI and biliary infection severity. Published by Elsevier Inc.

Multivariate meta-analysis using individual participant data.

PubMed

Riley, R D; Price, M J; Jackson, D; Wardle, M; Gueyffier, F; Wang, J; Staessen, J A; White, I R

2015-06-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Multivariate Analysis As a Support for Diagnostic Flowcharts in Allergic Bronchopulmonary Aspergillosis: A Proof-of-Concept Study.

PubMed

Vitte, Joana; Ranque, Stéphane; Carsin, Ania; Gomez, Carine; Romain, Thomas; Cassagne, Carole; Gouitaa, Marion; Baravalle-Einaudi, Mélisande; Bel, Nathalie Stremler-Le; Reynaud-Gaubert, Martine; Dubus, Jean-Christophe; Mège, Jean-Louis; Gaudart, Jean

2017-01-01

Molecular-based allergy diagnosis yields multiple biomarker datasets. The classical diagnostic score for allergic bronchopulmonary aspergillosis (ABPA), a severe disease usually occurring in asthmatic patients and people with cystic fibrosis, comprises succinct immunological criteria formulated in 1977: total IgE, anti- Aspergillus fumigatus ( Af ) IgE, anti- Af "precipitins," and anti- Af IgG. Progress achieved over the last four decades led to multiple IgE and IgG(4) Af biomarkers available with quantitative, standardized, molecular-level reports. These newly available biomarkers have not been included in the current diagnostic criteria, either individually or in algorithms, despite persistent underdiagnosis of ABPA. Large numbers of individual biomarkers may hinder their use in clinical practice. Conversely, multivariate analysis using new tools may bring about a better chance of less diagnostic mistakes. We report here a proof-of-concept work consisting of a three-step multivariate analysis of Af IgE, IgG, and IgG4 biomarkers through a combination of principal component analysis, hierarchical ascendant classification, and classification and regression tree multivariate analysis. The resulting diagnostic algorithms might show the way for novel criteria and improved diagnostic efficiency in Af -sensitized patients at risk for ABPA.

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

Multivariate analysis of longitudinal rates of change.

PubMed

Bryan, Matthew; Heagerty, Patrick J

2016-12-10

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed in the literature. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, 'accelerated time' methods have been developed which assume that covariates rescale time in longitudinal models for disease progression. In this manuscript, we detail an alternative multivariate model formulation that directly structures longitudinal rates of change and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of pure laparoscopic versus open left hemihepatectomy by multivariate analysis: a retrospective cohort study.

PubMed

Cho, Hwui-Dong; Kim, Ki-Hun; Hwang, Shin; Ahn, Chul-Soo; Moon, Deok-Bog; Ha, Tae-Yong; Song, Gi-Won; Jung, Dong-Hwan; Park, Gil-Chun; Lee, Sung-Gyu

2018-02-01

To compare the outcomes of pure laparoscopic left hemihepatectomy (LLH) versus open left hemihepatectomy (OLH) for benign and malignant conditions using multivariate analysis. All consecutive cases of LLH and OLH between October 2007 and December 2013 in a tertiary referral hospital were enrolled in this retrospective cohort study. All surgical procedures were performed by one surgeon. The LLH and OLH groups were compared in terms of patient demographics, preoperative data, clinical perioperative outcomes, and tumor characteristics in patients with malignancy. Multivariate analysis of the prognostic factors associated with severe complications was then performed. The LLH group (n = 62) had a significantly shorter postoperative hospital stay than the OLH group (n = 118) (9.53 ± 3.30 vs 14.88 ± 11.36 days, p < 0.001). Multivariate analysis revealed that the OLH group had >4 times the risk of the LLH group in terms of developing severe complications (Clavien-Dindo grade ≥III) (odds ratio 4.294, 95% confidence intervals 1.165-15.832, p = 0.029). LLH was a safe and feasible procedure for selected patients. LLH required shorter hospital stay and resulted in less operative blood loss. Multivariate analysis revealed that LLH was associated with a lower risk of severe complications compared to OLH. The authors suggest that LLH could be a reasonable treatment option for selected patients.

Gender differences in psychological morbidity, burnout, job stress and job satisfaction among Chinese neurologists: a national cross-sectional study.

PubMed

Pu, Juncai; Zhou, Xinyu; Zhu, Dan; Zhong, Xiaoni; Yang, Lining; Wang, Haiyang; Zhang, Yuqing; Fan, Songhua; Liu, Lanxiang; Xie, Peng

2017-07-01

Women are an important part of the medical workforce, yet little is known about gender differences in psychological morbidity, burnout, job stress and job satisfaction among neurologists. This study assessed gender differences in a large national sample of Chinese neurologists. Multivariate analyses were performed to examine associations. A total of 5558 neurologists were included in the analysis. Compared with their male counterparts, female neurologists were generally younger; were less likely to be married or to have children; had higher levels of education; were in practice for a shorter period of time; were less likely to hold senior roles; and had lower incomes. Male and female neurologists worked similar hours and spent a similar number of nights on call. No gender differences were found in psychological morbidity, burnout, and high levels of job stress for female and male, respectively. Women had higher emotional exhaustion scores, while men were more likely to have low levels of job satisfaction. The multivariate analysis showed that factors independently associated with psychological morbidity, burnout, high levels of job stress and low levels of job satisfaction were generally similar for women and men. These findings increase our understanding of gender differences in psychological morbidity, burnout, job stress, and job satisfaction among neurologists. As more women join the medical profession, these differences may be useful in designing medical training and practice.

Multifactorial analysis of renal transplants reported to the United Network for Organ Sharing Registry: a 1994 update.

PubMed

Gjertson, D W

1994-01-01

1. From a multivariate log-linear analysis of 57,303 renal transplants between 1988 and 1994, the top 10 factors influencing one-year and 3-year cadaveric graft survival rates were ranked as follows: [table: see text] 2. Center effects accounted for 30% and 28% of all assignable variations in one-year and 3-year outcomes, respectively. Although center variation dominated 32 other variables, most factors were relatively independent of transplant center. 3. Novel to our own multifactorial analyses of the UNOS Kidney Transplant Registry were 6 pretransplant factors (recipient pretransplant dialysis, pregnancy, PRA technique, donor disposition and preservation, and ABO compatibility). Survival rates over the various combinations of these new factors were not significantly different. 4. For the first time in our multivariate analyses, 4 posttransplantation factors (delayed graft function, rejection episodes prior to discharge, induction and maintenance drug therapies) were included in the log-linear model. It is noteworthy that graft survival in both transplant periods was seriously imperiled following delayed graft function or rejection prior to discharge, yet the accounting for these pseudo-outcome variables did not alter the influence of the remaining 31 transplant factors. Finally, maintenance drug therapies strongly influenced short-term outcomes but did not influence long-term results, except for a noteworthy trend toward increased survival rates for FK506 therapy.

Maximum covariance analysis to identify intraseasonal oscillations over tropical Brazil

NASA Astrophysics Data System (ADS)

Barreto, Naurinete J. C.; Mesquita, Michel d. S.; Mendes, David; Spyrides, Maria H. C.; Pedra, George U.; Lucio, Paulo S.

2017-09-01

A reliable prognosis of extreme precipitation events in the tropics is arguably challenging to obtain due to the interaction of meteorological systems at various time scales. A pivotal component of the global climate variability is the so-called intraseasonal oscillations, phenomena that occur between 20 and 100 days. The Madden-Julian Oscillation (MJO), which is directly related to the modulation of convective precipitation in the equatorial belt, is considered the primary oscillation in the tropical region. The aim of this study is to diagnose the connection between the MJO signal and the regional intraseasonal rainfall variability over tropical Brazil. This is achieved through the development of an index called Multivariate Intraseasonal Index for Tropical Brazil (MITB). This index is based on Maximum Covariance Analysis (MCA) applied to the filtered daily anomalies of rainfall data over tropical Brazil against a group of covariates consisting of: outgoing longwave radiation and the zonal component u of the wind at 850 and 200 hPa. The first two MCA modes, which were used to create the { MITB}_1 and { MITB}_2 indices, represent 65 and 16 % of the explained variance, respectively. The combined multivariate index was able to satisfactorily represent the pattern of intraseasonal variability over tropical Brazil, showing that there are periods of activation and inhibition of precipitation connected with the pattern of MJO propagation. The MITB index could potentially be used as a diagnostic tool for intraseasonal forecasting.

Predictive impact of polymorphism of PNPLA3 on HCC development after interferon therapy in Japanese patients with chronic hepatitis C.

PubMed

Moritou, Yuki; Ikeda, Fusao; Iwasaki, Yoshiaki; Baba, Nobuyuki; Takaguchi, Kouichi; Senoh, Tomonori; Nagano, Takuya; Takeuchi, Yasuto; Yasunaka, Tetsuya; Ohnishi, Hideki; Miyake, Yasuhiro; Takaki, Akinobu; Nouso, Kazuhiro; Yamamoto, Kazuhide

2013-12-01

The impact of single-nucleotide polymorphisms (SNP) of patatin-like phospholipase domain-containing protein 3 (PNPLA3) on development of hepatocellular carcinoma (HCC) is not clarified for Japanese patients with chronic hepatitis C. The present study investigated the associations of rs738409 PNPLA3 with HCC development after the antiviral therapy with peg-interferon and ribavirin for Japanese patients with hepatitis C virus serotype 1 and high viral load. Of the 271 patients enrolled in the study, 20 patients developed HCC, during a median follow-up period of 4.6 years. Multivariate analysis in the proportional hazards models revealed that sex, body mass index, platelet counts, and alpha feroprotein (AFP) had significant associations with HCC development (p = 0.011, 0.029, 0.0002, and 0.046, respectively). Multivariate regression analysis revealed that PNPLA3 148 M was significantly associated with serum AFP level (p = 0.032), other than body mass index, platelet count, and alanine aminotransferase (p = 0.0006, 0.0002, and 0.037, respectively), and that serum AFP level was significantly associated with PNPLA3 148 M (p = 0.017). Serum AFP level is an important factor in predicting HCC development after the antiviral therapy for Japanese patients with chronic hepatitis C, the mechanism of which might involve its significant associations with the SNP genotype of PNPLA3.

Transected thin melanoma: Implications for sentinel lymph node staging.

PubMed

Herbert, Garth; Karakousis, Giorgos C; Bartlett, Edmund K; Zaheer, Salman; Graham, Danielle; Czerniecki, Brian J; Fraker, Douglas L; Ariyan, Charlotte; Coit, Daniel G; Brady, Mary S

2018-03-01

Indications for sentinel lymph node (SLN) biopsy in patients with thin melanoma (≤1 mm thick) are controversial. We asked whether deep margin (DM) positivity at initial biopsy of thin melanoma is associated with SLN positivity. Cases were identified using prospectively maintained databases at two melanoma centers. Patients who had undergone SLN biopsy for melanoma ≤1 mm were included. DM status was assessed for association with SLN metastasis in univariate and multivariate analyses. 1413 cases were identified, but only 1129 with known DM status were included. 39% of patients had a positive DM on original biopsy. DM-positive and DM-negative patients did not differ significantly in primary thickness, ulceration, or mitotic activity. DM-positive and DM-negative patients had similar incidence of SLN metastasis (5.7% vs 3.5%; P = 0.07). Positive DM was not associated with SLN metastasis on univariate analysis (OR 1.69, 95% CI: 0.95-3.00, P = 0.07) or on multivariate analysis adjusted for Breslow depth, Clark level, mitotic rate, and ulceration (OR = 1.59, 95% CI: 0.89-2.85; P = 0.12). For patients with thin melanoma, a positive DM on initial biopsy is not associated with risk of SLN metastasis, so DM positivity should not be considered an indication for SLN staging in an otherwise low-risk patient. © 2017 Wiley Periodicals, Inc.

Impact of scalp location on survival in head and neck melanoma: A retrospective cohort study.

PubMed

Xie, Charles; Pan, Yan; McLean, Catriona; Mar, Victoria; Wolfe, Rory; Kelly, John

2017-03-01

Scalp melanomas have more aggressive clinicopathological features than other melanomas and mortality rates more than twice that of melanoma located elsewhere. We sought to describe the survival of patients with scalp melanoma versus other cutaneous head and neck melanoma (CHNM), and explore a possible independent negative impact of scalp location on CHNM survival. A retrospective cohort study was performed of all invasive primary CHNM cases seen at a tertiary referral center over a 20-year period. Melanoma-specific survival (MSS) was compared between scalp melanoma and other invasive CHNM. Multivariable Cox proportional hazards regression was performed to determine associations with survival. On univariate analysis, patients with scalp melanoma had worse MSS than other CHNM (hazard ratio 2.22, 95% confidence interval 1.59-3.11). Scalp location was not associated with MSS in CHNM on multivariable analysis (hazard ratio 1.11, 95% confidence interval 0.77-1.61) for all tumors together, but remained independently associated with MSS for the 0.76- to 1.50-mm thickness stratum (hazard ratio 5.51, 95% confidence interval 1.55-19.59). Disease recurrence was not assessed because of unavailable data. The poorer survival of scalp melanoma is largely explained by greater Breslow thickness and a higher proportion of male patients. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Impact of an Early Decrease in Systolic Blood Pressure on The Risk of Contrast-Induced Nephropathy after Percutaneous Coronary Intervention.

PubMed

Li, Hualong; Huang, Shuijin; He, Yiting; Liu, Yong; Liu, Yuanhui; Chen, Jiyan; Zhou, Yingling; Tan, Ning; Duan, Chongyang; Chen, Pingyan

2016-02-01

The early postprocedural period was thought to be the rush hour of contrast media excretion, causing rapid and prolonged renal hypoperfusion, which was the critical time window for contrast-induced nephropathy (CIN). 349 consecutive patients were enrolled into the study. The relation between an early postprocedural decrease in systolic blood pressure (SBP) and the risk of CIN was assessed using multivariate logistic regression. A postprocedural decrease in SBP was observed in 63% of patients and CIN developed in 28 (8.0%) patients. The CIN group had a lower postprocedural SBP (114.5±13.5 vs. 123.7±15.6mmHg, P=0.003) and a greater postprocedural decrease in SBP (16.2±19.1 vs. 5.9±18.7mmHg, P=0.005) than the no-CIN group. ROC analysis revealed that the optimum cutoff value for the SBP decrease in detecting CIN was >10mmHg (sensitivity 60.7%, specificity 59.5%, AUC=0.66). Multivariate logistic regression analysis found that a postprocedural decrease in SBP >10mmHg was a significant independent predictor of CIN (OR 2.368, 95%CI: 1.043-5.379, P=0.039), after adjustment for other risk factors. An early moderate postprocedural decrease in SBP may increase the risk of CIN in patients undergoing PCI. Copyright © 2015. Published by Elsevier B.V.

Comorbid renal tubular damage and hypoalbuminemia exacerbate cardiac prognosis in patients with chronic heart failure.

PubMed

Otaki, Yoichiro; Watanabe, Tetsu; Takahashi, Hiroki; Funayama, Akira; Kinoshita, Daisuke; Yokoyama, Miyuki; Takahashi, Tetsuya; Nishiyama, Satoshi; Arimoto, Takanori; Shishido, Tetsuro; Miyamoto, Takuya; Konta, Tsuneo; Kubota, Isao

2016-02-01

Renal tubular damage (RTD) and hypoalbuminemia are risks for poor prognosis in patients with chronic heart failure (CHF). Renal tubules play a pivotal role in amino acid and albumin reabsorption, which maintain serum albumin levels. The aims of the present study were to (1) examine the association of RTD with hypoalbuminemia, and (2) assess the prognostic importance of comorbid RTD and hypoalbuminemia in patients with CHF. We measured N-acetyl-β-D-glucosamidase (NAG) levels and the urinary β2-microglobulin to creatinine ratio (UBCR) in 456 patients with CHF. RTD was defined as UBCR ≥ 300 μg/g or NAG ≥ 14.2 U/g. There were moderate correlations between RTD markers and serum albumin (NAG, r = -0.428, P < 0.0001; UBCR, r = -0.399, P < 0.0001). Multivariate logistic analysis showed that RTD was significantly related to hypoalbuminemia in patients with CHF. There were 134 cardiac events during a median period of 808 days. The comorbidity of RTD and hypoalbuminemia was increased with advancing New York Heart Association functional class. Multivariate Cox proportional hazard regression analysis showed that the presence of RTD and hypoalbuminemia was associated with cardiac events. The net reclassification index was significantly improved by adding RTD and hypoalbuminemia to the basic risk factors. Comorbid RTD and hypoalbuminemia are frequently observed and increase the risk for extremely poor outcome in patients with CHF.

Impact of Pacemaker Lead Characteristics on Pacemaker Related Infection and Heart Perforation: A Nationwide Population-Based Cohort Study.

PubMed

Lin, Yu-Sheng; Chen, Tien-Hsing; Hung, Sheng-Ping; Chen, Dong Yi; Mao, Chun-Tai; Tsai, Ming-Lung; Chang, Shih-Tai; Wang, Chun-Chieh; Wen, Ming-Shien; Chen, Mien-Cheng

2015-01-01

Several risk factors for pacemaker (PM) related complications have been reported. However, no study has investigated the impact of lead characteristics on pacemaker-related complications. Patients who received a new pacemaker implant from January 1997 to December 2011 were selected from the Taiwan National Health Insurance Database. This population was grouped according to the pacemaker lead characteristics in terms of fixation and insulation. The impact of the characteristics of leads on early heart perforation was analyzed by multivariable logistic regression analysis, while the impact of the lead characteristics on early and late infection and late heart perforation over a three-year period were analyzed using Cox regression. This study included 36,104 patients with a mean age of 73.4±12.5 years. In terms of both early and late heart perforations, there were no significant differences between groups across the different types of fixation and insulations. In the multivariable Cox regression analysis, the pacemaker-related infection rate was significantly lower in the active fixation only group compared to either the both fixation (OR, 0.23; 95% CI, 0.07-0.80; P = 0.020) or the passive fixation group (OR, 0.26; 95% CI, 0.08-0.83; P = 0.023). There was no difference in heart perforation between active and passive fixation leads. Active fixation leads were associated with reduced risk of pacemaker-related infection.

Comparative study of bacteremias caused by Enterococcus spp. with and without high-level resistance to gentamicin. The Grupo Andaluz para el estudio de las Enfermedades Infecciosas.

PubMed

Caballero-Granado, F J; Cisneros, J M; Luque, R; Torres-Tortosa, M; Gamboa, F; Díez, F; Villanueva, J L; Pérez-Cano, R; Pasquau, J; Merino, D; Menchero, A; Mora, D; López-Ruz, M A; Vergara, A

1998-02-01

A prospective, multicenter study was carried out over a period of 10 months. All patients with clinically significant bacteremia caused by Enterococcus spp. were included. The epidemiological, microbiological, clinical, and prognostic features and the relationship of these features to the presence of high-level resistance to gentamicin (HLRG) were studied. Ninety-three patients with enterococcal bacteremia were included, and 31 of these cases were caused by HLRG (33%). The multivariate analysis selected chronic renal failure, intensive care unit stay, previous use of antimicrobial agents, and Enterococcus faecalis species as the independent risk factors that influenced the development of HLRG. The strains with HLRG showed lower levels of susceptibility to penicillin and ciprofloxacin. Clinical features (except for chronic renal failure) were similar in both groups of patients. HLRG did not influence the prognosis for patients with enterococcal bacteremia in terms of either the crude mortality rate (29% for patients with bacteremia caused by enterococci with HLRG and 28% for patients not infected with strains with HLRG) or the hospital stay after the acquisition of enterococcal bacteremia. Hemodynamic compromise, inappropriate antimicrobial therapy, and mechanical ventilation were revealed in the multivariate analysis to be the independent risk factors for mortality. Prolonged hospitalization was associated with the nosocomial acquisition of bacteremia and polymicrobial infections.

No Relationship Between Hamstring Flexibility and Hamstring Injuries in Male Amateur Soccer Players: A Prospective Study.

PubMed

van Doormaal, Mitchell C M; van der Horst, Nick; Backx, Frank J G; Smits, Dirk-Wouter; Huisstede, Bionka M A

2017-01-01

In soccer, although hamstring flexibility is thought to play a major role in preventing hamstring injuries, the relationship between hamstring flexibility and hamstring injuries remains unclear. To investigate the relationship between hamstring flexibility and hamstring injuries in male amateur soccer players. Case-control study; Level of evidence, 3. This study included 450 male first-class amateur soccer players (mean age, 24.5 years). Hamstring flexibility was measured by performing the sit-and-reach test (SRT). The relationship between hamstring flexibility and the occurrence of hamstring injuries in the following year, while adjusting for the possible confounding effects of age and previous hamstring injuries, was determined with a multivariate logistic regression analysis. Of the 450 soccer players, 21.8% reported a hamstring injury in the previous year. The mean (±SD) baseline score for the SRT was 21.2 ± 9.2 cm. During the 1-year follow-up period, 23 participants (5.1%) suffered a hamstring injury. In the multivariate analysis, while adjusting for age and previous injuries, no significant relationship was found between hamstring flexibility and hamstring injuries ( P = .493). In this group of soccer players, hamstring flexibility (measured with the SRT) was not related to hamstring injuries. Age and previous hamstring injuries as possible confounders did not appear to influence this relationship. Other etiological factors need to be examined to further elucidate the mechanism of hamstring injuries.

Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence and estimation.

PubMed

Cain, Meghan K; Zhang, Zhiyong; Yuan, Ke-Hai

2017-10-01

Nonnormality of univariate data has been extensively examined previously (Blanca et al., Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(2), 78-84, 2013; Miceeri, Psychological Bulletin, 105(1), 156, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of nonnormality, this study examined 1,567 univariate distriubtions and 254 multivariate distributions collected from authors of articles published in Psychological Science and the American Education Research Journal. We found that 74 % of univariate distributions and 68 % multivariate distributions deviated from normal distributions. In a simulation study using typical values of skewness and kurtosis that we collected, we found that the resulting type I error rates were 17 % in a t-test and 30 % in a factor analysis under some conditions. Hence, we argue that it is time to routinely report skewness and kurtosis along with other summary statistics such as means and variances. To facilitate future report of skewness and kurtosis, we provide a tutorial on how to compute univariate and multivariate skewness and kurtosis by SAS, SPSS, R and a newly developed Web application.

A multivariate ecogeographic analysis of macaque craniodental variation.

PubMed

Grunstra, Nicole D S; Mitteroecker, Philipp; Foley, Robert A

2018-06-01

To infer the ecogeographic conditions that underlie the evolutionary diversification of macaques, we investigated the within- and between-species relationships of craniodental dimensions, geography, and environment in extant macaque species. We studied evolutionary processes by contrasting macroevolutionary patterns, phylogeny, and within-species associations. Sixty-three linear measurements of the permanent dentition and skull along with data about climate, ecology (environment), and spatial geography were collected for 711 specimens of 12 macaque species and analyzed by a multivariate approach. Phylogenetic two-block partial least squares was used to identify patterns of covariance between craniodental and environmental variation. Phylogenetic reduced rank regression was employed to analyze spatial clines in morphological variation. Between-species associations consisted of two distinct multivariate patterns. The first represents overall craniodental size and is negatively associated with temperature and habitat, but positively with latitude. The second pattern shows an antero-posterior tooth size contrast related to diet, rainfall, and habitat productivity. After controlling for phylogeny, however, the latter dimension was diminished. Within-species analyses neither revealed significant association between morphology, environment, and geography, nor evidence of isolation by distance. We found evidence for environmental adaptation in macaque body and craniodental size, primarily driven by selection for thermoregulation. This pattern cannot be explained by the within-species pattern, indicating an evolved genetic basis for the between-species relationship. The dietary signal in relative tooth size, by contrast, can largely be explained by phylogeny. This cautions against adaptive interpretations of phenotype-environment associations when phylogeny is not explicitly modelled. © 2018 Wiley Periodicals, Inc.

Determinants of the lethality of climate-related disasters in the Caribbean Community (CARICOM): a cross-country analysis

PubMed Central

Andrewin, Aisha N.; Rodriguez-Llanes, Jose M.; Guha-Sapir, Debarati

2015-01-01

Floods and storms are climate-related hazards posing high mortality risk to Caribbean Community (CARICOM) nations. However risk factors for their lethality remain untested. We conducted an ecological study investigating risk factors for flood and storm lethality in CARICOM nations for the period 1980–2012. Lethality - deaths versus no deaths per disaster event- was the outcome. We examined biophysical and social vulnerability proxies and a decadal effect as predictors. We developed our regression model via multivariate analysis using a generalized logistic regression model with quasi-binomial distribution; removal of multi-collinear variables and backward elimination. Robustness was checked through subset analysis. We found significant positive associations between lethality, percentage of total land dedicated to agriculture (odds ratio [OR] 1.032; 95% CI: 1.013–1.053) and percentage urban population (OR 1.029, 95% CI 1.003–1.057). Deaths were more likely in the 2000–2012 period versus 1980–1989 (OR 3.708, 95% CI 1.615–8.737). Robustness checks revealed similar coefficients and directions of association. Population health in CARICOM nations is being increasingly impacted by climate-related disasters connected to increasing urbanization and land use patterns. Our findings support the evidence base for setting sustainable development goals (SDG). PMID:26153115

Correlation of maple sap composition with bacterial and fungal communities determined by multiplex automated ribosomal intergenic spacer analysis (MARISA).

PubMed

Filteau, Marie; Lagacé, Luc; LaPointe, Gisèle; Roy, Denis

2011-08-01

During collection, maple sap is contaminated by bacteria and fungi that subsequently colonize the tubing system. The bacterial microbiota has been more characterized than the fungal microbiota, but the impact of both components on maple sap quality remains unclear. This study focused on identifying bacterial and fungal members of maple sap and correlating microbiota composition with maple sap properties. A multiplex automated ribosomal intergenic spacer analysis (MARISA) method was developed to presumptively identify bacterial and fungal members of maple sap samples collected from 19 production sites during the tapping period. Results indicate that the fungal community of maple sap is mainly composed of yeast related to Mrakia sp., Mrakiella sp., Guehomyces pullulans, Cryptococcus victoriae and Williopsis saturnus. Mrakia, Mrakiella and Guehomyces peaks were identified in samples of all production sites and can be considered dominant and stable members of the fungal microbiota of maple sap. A multivariate analysis based on MARISA profiles and maple sap chemical composition data showed correlations between Candida sake, Janthinobacterium lividum, Williopsis sp., Leuconostoc mesenteroides, Mrakia sp., Rhodococcus sp., Pseudomonas tolaasii, G. pullulans and maple sap composition at different flow periods. This study provides new insights on the relationship between microbial community and maple sap quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Incidence of and risk factors for bile duct stones after living donor liver transplantation: An analysis of 100 patients.

PubMed

Senoo, Takemasa; Ichikawa, Tatsuki; Taura, Naota; Miyaaki, Hisamitsu; Miuma, Satoshi; Shibata, Hidetaka; Honda, Takuya; Takatsuki, Mitsuhisa; Hidaka, Masaaki; Soyama, Akihiko; Eguchi, Susumu; Nakao, Kazuhiko

2015-09-01

Although bile duct stone (BDS) is one of the biliary complications of liver transplantation, analytical studies, particularly on living donor liver transplantation (LDLT) cases, are rare. This study aimed to clarify the incidence of and risk factors for BDS following LDLT. We retrospectively reviewed the medical records of 100 patients who underwent LDLT at our institute from August 2000 to May 2012, and analyzed their clinical characteristics and risk factors for BDS. Of these, 10 patients (10.0%) developed BDS during the observation period. The median follow-up period to BDS diagnosis was 45.5 months (range, 5-84) after LDLT. Univariate analysis revealed male sex, right lobe graft and bile duct strictures as factors that significantly correlated with BDS formation. Multivariate analysis revealed bile duct strictures (odds ratio, 7.17; P = 0.011) and right lobe graft (odds ratio, 10.20; P = 0.040) to be independent risk factors for BDS formation. One patient with BDS and biliary strictures succumbed to sepsis from cholangitis. In the present study, right lobe graft and bile duct strictures are independent risk factors for BDS formation after LDLT. More careful observation and monitoring are required in the patients with high-risk factors. © 2014 The Japan Society of Hepatology.

Effect of in-painting on cortical thickness measurements in multiple sclerosis: A large cohort study.

PubMed

Govindarajan, Koushik A; Datta, Sushmita; Hasan, Khader M; Choi, Sangbum; Rahbar, Mohammad H; Cofield, Stacey S; Cutter, Gary R; Lublin, Fred D; Wolinsky, Jerry S; Narayana, Ponnada A

2015-10-01

A comprehensive analysis of the effect of lesion in-painting on the estimation of cortical thickness using magnetic resonance imaging was performed on a large cohort of 918 relapsing-remitting multiple sclerosis patients who participated in a phase III multicenter clinical trial. An automatic lesion in-painting algorithm was developed and implemented. Cortical thickness was measured using the FreeSurfer pipeline with and without in-painting. The effect of in-painting was evaluated using FreeSurfer's paired analysis pipeline. Multivariate regression analysis was also performed with field strength and lesion load as additional factors. Overall, the estimated cortical thickness was different with in-painting than without. The effect of in-painting was observed to be region dependent, more significant in the left hemisphere compared to the right, was more prominent at 1.5 T relative to 3 T, and was greater at higher lesion volumes. Our results show that even for data acquired at 1.5 T in patients with high lesion load, the mean cortical thickness difference with and without in-painting is ∼2%. Based on these results, it appears that in-painting has only a small effect on the estimated regional and global cortical thickness. Hum Brain Mapp 36:3749-3760, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

Is Heart Rate Variability Better Than Routine Vital Signs for Prehospital Identification of Major Hemorrhage

DTIC Science & Technology

2015-01-01

different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and routine vital signs to test the hypothesis that...study sponsors did not have any role in the study design, data collection, analysis and interpretation of data, report writing, or the decision to...primary outcome was hemorrhagic injury plus different PRBC transfusion volumes. We performed multivariate regression analysis using HRV metrics and

Multivariate optimum interpolation of surface pressure and winds over oceans

NASA Technical Reports Server (NTRS)

Bloom, S. C.

1984-01-01

The observations of surface pressure are quite sparse over oceanic areas. An effort to improve the analysis of surface pressure over oceans through the development of a multivariate surface analysis scheme which makes use of surface pressure and wind data is discussed. Although the present research used ship winds, future versions of this analysis scheme could utilize winds from additional sources, such as satellite scatterometer data.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Impact of needleless connector change frequency on central line-associated bloodstream infection rate.

PubMed

Sandora, Thomas J; Graham, Dionne A; Conway, Margaret; Dodson, Brenda; Potter-Bynoe, Gail; Margossian, Steven P

2014-05-01

Bloodstream infection is the most common pediatric health care-associated infection and is strongly associated with catheter use. These infections greatly increase the cost of hospital stay. To assess the association between needleless connector (NC) change frequency and central line-associated bloodstream infection (CLABSI) rate, we modeled monthly pediatric stem cell transplant (SCT) CLABSI rate in 3 periods: baseline period during which NC were changed every 96 hours regardless of infusate (period 1); trial period in which NC were changed every 24 hours with blood or lipid infusions (period 2); and a return to NC change every 96 hours regardless of infusate (period 3). Data on potential confounders were collected retrospectively. Autocorrelated segmented regression models were used to compare SCT CLABSI rates in each period, adjusting for potential confounders. CLABSI rates were also assessed for a nonequivalent control group (oncology unit) in which NC were changed every 24 hours with blood or lipid use in periods 2 and 3. SCT CLABSI rates were 0.41, 3.56, and 0.03 per 1,000 central line-days in periods 1, 2, and 3, respectively. In multivariable analysis, the CLABSI rate was significantly higher in period 2 compared with both period 1 (P = .01) and period 3 (P = .003). In contrast, CLABSI rates on the oncology unit were not significantly different among periods. In pediatric SCT patients, changing needleless connectors every 24 hours when blood or lipids are infused is associated with increased CLABSI rates. National recommendations regarding NC change frequency should be clarified. Copyright © 2014 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Mosby, Inc. All rights reserved.

Analysis and assessment on heavy metal sources in the coastal soils developed from alluvial deposits using multivariate statistical methods.

PubMed

Li, Jinling; He, Ming; Han, Wei; Gu, Yifan

2009-05-30

An investigation on heavy metal sources, i.e., Cu, Zn, Ni, Pb, Cr, and Cd in the coastal soils of Shanghai, China, was conducted using multivariate statistical methods (principal component analysis, clustering analysis, and correlation analysis). All the results of the multivariate analysis showed that: (i) Cu, Ni, Pb, and Cd had anthropogenic sources (e.g., overuse of chemical fertilizers and pesticides, industrial and municipal discharges, animal wastes, sewage irrigation, etc.); (ii) Zn and Cr were associated with parent materials and therefore had natural sources (e.g., the weathering process of parent materials and subsequent pedo-genesis due to the alluvial deposits). The effect of heavy metals in the soils was greatly affected by soil formation, atmospheric deposition, and human activities. These findings provided essential information on the possible sources of heavy metals, which would contribute to the monitoring and assessment process of agricultural soils in worldwide regions.

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

PubMed

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

PYCHEM: a multivariate analysis package for python.

PubMed

Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston

2006-10-15

We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Multivariate longitudinal data analysis with censored and intermittent missing responses.

PubMed

Lin, Tsung-I; Lachos, Victor H; Wang, Wan-Lun

2018-05-08

The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach. Copyright © 2018 John Wiley & Sons, Ltd.

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

A critical analysis of early death after adult liver transplants.

PubMed

Rana, Abbas; Kaplan, Bruce; Jie, Tun; Porubsky, Marian; Habib, Shahid; Rilo, Horacio; Gruessner, Angelika C; Gruessner, Rainer W G

2013-01-01

The 15% mortality rate of liver transplant recipients at one yr may be viewed as a feat in comparison with the waiting list mortality, yet it nonetheless leaves room for much improvement. Our aim was to critically examine the mortality rates to identify high-risk periods and to incorporate cause of death into the analysis of post-transplant survival. We performed a retrospective analysis on United Network for Organ Sharing data for all adult recipients of liver transplants from January 1, 2002 to October 31, 2011. Our analysis included multivariate logistic regression where the primary outcome measure was patient death of 49,288 recipients. The highest mortality rate by day post-transplant was on day 0 (0.9%). The most significant risk factors were as follows: for one-d mortality from technical failure, intensive care unit admission odds ratio (OR 3.2); for one-d mortality from graft failure, warm ischemia >75 min (OR 5.6); for one-month mortality from infection, a previous transplant (OR 3.3); and for one-month mortality from graft failure, a previous transplant (OR 3.7). We found that the highest mortality rate after liver transplantation is within the first day and the first month post-transplant. Those two high-risk periods have common, as well as different, risk factors for mortality. © 2013 John Wiley & Sons A/S.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Multivariate geometry as an approach to algal community analysis

USGS Publications Warehouse

Allen, T.F.H.; Skagen, S.

1973-01-01

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.

The effect of an intervention aimed at reducing errors when administering medication through enteral feeding tubes in an institution for individuals with intellectual disability.

PubMed

Idzinga, J C; de Jong, A L; van den Bemt, P M L A

2009-11-01

Previous studies, both in hospitals and in institutions for clients with an intellectual disability (ID), have shown that medication errors at the administration stage are frequent, especially when medication has to be administered through an enteral feeding tube. In hospitals a specially designed intervention programme has proven to be effective in reducing these feeding tube-related medication errors, but the effect of such a programme within an institution for clients with an ID is unknown. Therefore, a study was designed to measure the influence of such an intervention programme on the number of medication administration errors in clients with an ID who also have enteral feeding tubes. A before-after study design with disguised observation to document administration errors was used. The study was conducted from February to June 2008 within an institution for individuals with an ID in the Western part of The Netherlands. Included were clients with enteral feeding tubes. The intervention consisted of advice on medication administration through enteral feeding tubes by the pharmacist, a training programme and introduction of a 'medication through tube' box containing proper materials for crushing and suspending tablets. The outcome measure was the frequency of medication administration errors, comparing the pre-intervention period with the post-intervention period. A total of 245 medication administrations in six clients (by 23 nurse attendants) have been observed in the pre-intervention measurement period and 229 medication administrations in five clients (by 20 nurse attendants) have been observed in the post-intervention period. Before the intervention, 158 (64.5%) medication administration errors were observed, and after the intervention, this decreased to 69 (30.1%). Of all potential confounders and effect modifiers, only 'medication dispensed in automated dispensing system ("robot") packaging' contributed to the multivariate model; effect modification was shown for this determinant. Multilevel analysis using this multivariate model resulted in an odds ratio of 0.33 (95% confidence interval 0.13-0.71) for the error percentage in the post-intervention period compared with the pre-intervention period. The intervention was found to be effective in an institution for clients with an ID. However, additional efforts are needed to reduce the proportion of administration errors which is still high after the intervention.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1984-01-01

The objective of this investigation is to develop a state-of-the-art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies. A three-dimensional multivariate O/I analysis scheme has been developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Comparison of Optimum Interpolation and Cressman Analyses

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

The development of a state of the art optimum interpolation (O/I) objective analysis procedure for use in numerical weather prediction studies was investigated. A three dimensional multivariate O/I analysis scheme was developed. Some characteristics of the GLAS O/I compared with those of the NMC and ECMWF systems are summarized. Some recent enhancements of the GLAS scheme include a univariate analysis of water vapor mixing ratio, a geographically dependent model prediction error correlation function and a multivariate oceanic surface analysis.

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Functional Path Analysis as a Multivariate Technique in Developing a Theory of Participation in Adult Education.

ERIC Educational Resources Information Center

Martin, James L.

This paper reports on attempts by the author to construct a theoretical framework of adult education participation using a theory development process and the corresponding multivariate statistical techniques. Two problems are identified: the lack of theoretical framework in studying problems, and the limiting of statistical analysis to univariate…

Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance

ERIC Educational Resources Information Center

Finch, W. Holmes

2016-01-01

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Web-Based Tools for Modelling and Analysis of Multivariate Data: California Ozone Pollution Activity

ERIC Educational Resources Information Center

Dinov, Ivo D.; Christou, Nicolas

2011-01-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting…

Bias and Precision of Measures of Association for a Fixed-Effect Multivariate Analysis of Variance Model

ERIC Educational Resources Information Center

Kim, Soyoung; Olejnik, Stephen

2005-01-01

The sampling distributions of five popular measures of association with and without two bias adjusting methods were examined for the single factor fixed-effects multivariate analysis of variance model. The number of groups, sample sizes, number of outcomes, and the strength of association were manipulated. The results indicate that all five…

Factors predicting recurrence of chronic subdural haematoma: the influence of intraoperative irrigation and low-molecular-weight heparin thromboprophylaxis.

PubMed

Tahsim-Oglou, Yasemin; Beseoglu, Kerim; Hänggi, Daniel; Stummer, Walter; Steiger, Hans-Jakob

2012-06-01

Burr-hole drainage has become the accepted treatment of choice for chronic subdural haematoma (cSDH), although still burdened with a major recurrence rate. The current analysis was initiated to determine management-related risk factors for recurrence, i.e. postoperative low-molecular-weight heparin thromboprophylaxis, and the importance of rinsing the subdural space. Two-hundred and forty-seven patients with computerised tomography (CT) defined symptomatic cSDH were managed by two burr-hole trepanations and drainage between January 2005 and November 2008. Postoperative thromboprophylaxis with 40 mg enoxaparine daily was given only during the first half of the study period. For the current analysis the amount of rinsing fluid, postoperative low-dose thromboprophylaxis, as well as age and gender, bilaterality, preoperative and postoperative blood coagulation studies, platelet counts and decrease of subdural fluid on early postoperative CT, were recorded and correlated with recurrence. Statistical calculation was done by univariate and multivariate analysis. A total of 62 of 247 patients needed revision surgery for recurrence (25.1 %). Recurrence rates were significantly lower in the patients treated without postoperative enoxaparine (18.84 %) than in the group with postoperative low-dose enoxaparine thromboprophylaxis (32.11 %) and enoxaparine was administered in a higher proportion of the patients suffering recurrence (P = 0.013). A median intraoperative irrigation volume of 863 ml saline was used in the patients suffering recurrence and 1,500 ml in patients without recurrence (P < 0.001). The median age was slightly higher in the patients suffering from recurrence. Male gender predominated in both groups but was slightly more pronounced in the recurrence group. Preoperative and postoperative platelet counts and plasmatic coagulation indices did not differ significantly between the groups. Relative residual subdural fluid collection on early postoperative CT remained larger in patients finally suffering recurrence (P = 0.03). Multivariate analysis confirmed a small amount of rinsing fluid, male gender and the use of enoxaparine as the most important risk factors for recurrence, although that latter factor did not reach statistical significance in the multivariate analysis. The investigation provides evidence that copious intraoperative irrigation and avoidance of postoperative low-molecular-weight heparin thromboprophylaxis may reduce the recurrence rate of cSDH.

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study

PubMed Central

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance. PMID:26196398

Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.

PubMed

Neupane, Binod; Beyene, Joseph

2015-01-01

In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously) than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE) of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when the missing data in the endpoint are imputed with null effects and quite large variance.

MULTIVARIATE ANALYSES (CONONICAL CORRELATION AND PARTIAL LEAST SQUARE, PLS) TO MODEL AND ASSESS THE ASSOCIATION OF LANDSCAPE METRICS TO SURFACE WATER CHEMICAL AND BIOLOGICAL PROPERTIES USING SAVANNAH RIVER BASIN DATA.

EPA Science Inventory

Many multivariate methods are used in describing and predicting relation; each has its unique usage of categorical and non-categorical data. In multivariate analysis of variance (MANOVA), many response variables (y's) are related to many independent variables that are categorical...

Multivariate Density Estimation and Remote Sensing

NASA Technical Reports Server (NTRS)

Scott, D. W.

1983-01-01

Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Longitudinal relationship between traumatic brain injury and the risk of incident optic neuropathy: A 10-year follow-up nationally representative Taiwan survey

PubMed Central

Chen, Ying-Jen; Liang, Chang-Min; Tai, Ming-Cheng; Chang, Yun-Hsiang; Lin, Tzu-Yu; Chung, Chi-Hsiang; Lin, Fu-Huang; Tsao, Chang-Huei; Chien, Wu-Chien

2017-01-01

Accumulating evidences had shown that traumatic brain injury was associated with visual impairment or vision loss. However, there were a limited number of empirical studies regarding the longitudinal relationship between traumatic brain injury and incident optic neuropathy. We studied a cohort from the Taiwanese National Health Insurance data comprising 553918 participants with traumatic brain injury and optic neuropathy-free in the case group and 1107836 individuals without traumatic brain injury in the control group from 1st January 2000. After the index date until the end of 2010, Cox proportional hazards analysis was used to compare the risk of incident optic neuropathy. During the follow-up period, case group was more likely to develop incident optic neuropathy (0.24%) than the control group (0.11%). Multivariate Cox regression analysis demonstrated that the case group had a 3-fold increased risk of optic neuropathy (HR = 3.017, 95% CI = 2.767–3.289, p < 0.001). After stratification by demographic information, traumatic brain injury remained a significant factor for incident optic neuropathy. Our study provided evidence of the increased risk of incident optic neuropathy after traumatic brain injury during a 10-year follow-up period. Patients with traumatic brain injury required periodic and thorough eye examinations for incident optic neuropathy to prevent potentially irreversible vision loss. PMID:29156847

Longitudinal relationship between traumatic brain injury and the risk of incident optic neuropathy: A 10-year follow-up nationally representative Taiwan survey.

PubMed

Chen, Ying-Jen; Liang, Chang-Min; Tai, Ming-Cheng; Chang, Yun-Hsiang; Lin, Tzu-Yu; Chung, Chi-Hsiang; Lin, Fu-Huang; Tsao, Chang-Huei; Chien, Wu-Chien

2017-10-17

Accumulating evidences had shown that traumatic brain injury was associated with visual impairment or vision loss. However, there were a limited number of empirical studies regarding the longitudinal relationship between traumatic brain injury and incident optic neuropathy. We studied a cohort from the Taiwanese National Health Insurance data comprising 553918 participants with traumatic brain injury and optic neuropathy-free in the case group and 1107836 individuals without traumatic brain injury in the control group from 1st January 2000. After the index date until the end of 2010, Cox proportional hazards analysis was used to compare the risk of incident optic neuropathy. During the follow-up period, case group was more likely to develop incident optic neuropathy (0.24%) than the control group (0.11%). Multivariate Cox regression analysis demonstrated that the case group had a 3-fold increased risk of optic neuropathy (HR = 3.017, 95% CI = 2.767-3.289, p < 0.001). After stratification by demographic information, traumatic brain injury remained a significant factor for incident optic neuropathy. Our study provided evidence of the increased risk of incident optic neuropathy after traumatic brain injury during a 10-year follow-up period. Patients with traumatic brain injury required periodic and thorough eye examinations for incident optic neuropathy to prevent potentially irreversible vision loss.

Effect of Contact Damage on the Strength of Ceramic Materials.

DTIC Science & Technology

1982-10-01

variables that are important to erosion, and a multivariate , linear regression analysis is used to fit the data to the dimensional analysis. The...of Equations 7 and 8 by a multivariable regression analysis (room tem- perature data) Exponent Regression Standard error Computed coefficient of...1980) 593. WEAVER, Proc. Brit. Ceram. Soc. 22 (1973) 125. 39. P. W. BRIDGMAN, "Dimensional Analaysis ", (Yale 18. R. W. RICE, S. W. FREIMAN and P. F

Study and interpretation of chemical composition of rainwater in selected urban and rural locations in India using multivariate analysis

NASA Astrophysics Data System (ADS)

Chakraborty, Bidisha; Gupta, Abhik

2018-04-01

Rainwater is an important untapped resource for all water managers and can be collected and used personally for all uses and simultaneously diverted to ground for recharge of depleting aquifers. Rain water is the most purest form of water until it is contaminated by the atmospheric pollution. Evaluation of rainwater quality analysis is also essential for non-potable applications and to match quality to specific uses. Rainwater quality analysis is, therefore, carried out to understand the problems of rainwater contamination with various pollutants. Rainwater samples were collected from the pre-monsoon season of March 2010 to post-monsoon of October 2013, from seven sampling sites namely Irongmara, Badarpur, Bongaigaon, Dolaigaon, BGR Township, Kolkata and Kharagpur, which characterised typical suburban, urban and industrialised locations respectively. A total of 943 samples were collected during this period from the sampling sites, taking utmost care in sampling and storage were analysed for heavy metals determination. Results for pH, EC, Pb, Cd, Ni, Zn, Cr and Co were reported in this study. The samples were collected using PVC bottles. The highest concentration of elements was observed at the beginning of the rainfall season when large amounts of dust accumulated in the atmosphere scavenged by rain. The values of pH in rainwater samples were relatively within the World Health Organization (WHO) standard for drinking water. Multivariate statistical analysis especially varimax rotation was applied to bring to focus the hidden yet important variables which influence the rainwater quality. It is also observed that rainwater contamination may not be restricted to industrial areas alone but vehicular emission may also contribute significantly in certain areas.

[Treatment duration of extra-pulmonary tuberculosis: 6 months or more? TB-INFO database analysis].

PubMed

Bouchikh, S; Stirnemann, J; Prendki, V; Porcher, R; Kesthmand, H; Morin, A-S; Cruaud, P; Rouaghe, S; Farge, D; Fain, O

2012-12-01

The recommended duration of pulmonary tuberculosis therapy is 6 months. For extrapulmonary tuberculosis, treatment duration depends on tuberculosis involvement and HIV status. The objective of this study was to describe the main characteristics of a cohort of extrapulmonary tuberculosis patients, to compare patients with a 6-month treatment to those with more than a 6-month treatment, and to analyze the compliance of medical centres with recommended duration of treatment. A retrospective cohort study of 210 patients with extrapulmonary tuberculosis was carried from January 1999 to December 2006 in two hospitals in the north-east of Paris. These patients were treated with quadruple therapy during two months, followed by dual therapy during 4 months (n=77) or more (n=66). The characteristics of each group were compared by uni- and multivariate analysis. The primary endpoint was the rate of relapse or treatment failure at 24-month follow-up after treatment completion. No relapse was observed after 24 months of follow-up after the end of treatment in the two groups. In univariate analysis, patients with lymph node tuberculosis were more often treated for 6 months than at other sites of tuberculosis (respectively 61% versus 40.9%; P=0.02); the decision of treatment duration was related to medical practices (79.2% treated 6 months in one hospital versus 20.7% in the other, P<0.001); patients living in private residence were more often treated during 6 months than patients living in residence (24.2% versus 10.3%, P=0.042). In multivariate analysis, only hospital (P=0.046), sex (P=0.007) and private residence were significantly different in each group. A period of 6 months seems to be sufficient to treat extrapulmonary tuberculosis (except for neuromeningeal localization). Copyright © 2012. Published by Elsevier SAS.

Analysis of Vision Loss Caused by Radiation-Induced Optic Neuropathy After Particle Therapy for Head-and-Neck and Skull-Base Tumors Adjacent to Optic Nerves

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

Demizu, Yusuke, E-mail: y_demizu@nifty.co; Murakami, Masao; Miyawaki, Daisuke

2009-12-01

Purpose: To assess the incident rates of vision loss (VL; based on counting fingers or more severe) caused by radiation-induced optic neuropathy (RION) after particle therapy for tumors adjacent to optic nerves (ONs), and to evaluate factors that may contribute to VL. Methods and Materials: From August 2001 to August 2006, 104 patients with head-and-neck or skull-base tumors adjacent to ONs were treated with carbon ion or proton radiotherapy. Among them, 145 ONs of 75 patients were irradiated and followed for greater than 12 months. The incident rate of VL and the prognostic factors for occurrence of VL were evaluated.more » The late effects of carbon ion and proton beams were compared on the basis of a biologically effective dose at alpha/beta = 3 gray equivalent (GyE{sub 3}). Results: Eight patients (11%) experienced VL resulting from RION. The onset of VL ranged from 17 to 58 months. The median follow-up was 25 months. No significant difference was observed between the carbon ion and proton beam treatment groups. On univariate analysis, age (>60 years), diabetes mellitus, and maximum dose to the ON (>110 GyE{sub 3}) were significant, whereas on multivariate analysis only diabetes mellitus was found to be significant for VL. Conclusions: The time to the onset of VL was highly variable. There was no statistically significant difference between carbon ion and proton beam treatments over the follow-up period. Based on multivariate analysis, diabetes mellitus correlated with the occurrence of VL. A larger study with longer follow-up is warranted.« less

Ventricular fibrillation in acute myocardial infarction in Spanish patients: Results of the ARIAM database.

PubMed

Ruiz-Bailén, Manuel; Aguayo de Hoyos, Eduardo; Ruiz-Navarro, Silvia; Issa-Khozouz, Ziad; Reina-Toral, Antonio; Díaz-Castellanos, Miguel Angel; Rodríguez-García, Juan-José; Torres-Ruiz, Juan Miguel; Cárdenas-Cruz, Antonio; Camacho-Víctor, Angel

2003-08-01

The aim of this study has been to investigate the factors predisposing to primary or secondary ventricular fibrillation (VF) and the prognosis in Spanish patients with acute myocardial infarction (AMI) during their admission to the intensive care unit or the coronary care unit. A retrospective, observational study. The intensive care units and coronary care units of 119 Spanish hospitals. A retrospective cohort study including all the AMI patients listed in the ARIAM registry (Analysis of Delay in Acute Myocardial Infarction), a Spanish multicenter study. The study period was January 1995 to January 2001. Factors associated with the onset of VF were studied by univariate analysis. Multivariate analysis was used to evaluate the independent factors for the onset of VF and for mortality. A total of 17,761 patients with AMI were included in the study; 964 (5.4%) developed VF (primary in 735 patients, secondary in 229). In multivariate analysis, the variables that continued to show an association with the development of VF were the Killip and Kimball class, peak creatine kinase, APACHE II score, age, and time from the onset of symptoms to the initiation of thrombolysis. The mortality in the patients with any VF was 31.8% (27.8% in patients with primary VF and 49.1% in patients with secondary VF). The development of VF is an independent predictive factor for mortality in patients with AMI, with a crude odds ratio of 5.12 (95% confidence interval, 4.41-5.95) and an adjusted odds ratio of 2.73 (95% confidence interval, 2.12-3.51). Despite the considerable improvement in the treatment of AMI in recent years, the onset of either primary or secondary VF is associated with a poor prognosis. It is usually accompanied by extensive necrosis.

Causes of death and competing risk analysis of the associated factors for non-small cell lung cancer using the Surveillance, Epidemiology, and End Results database.

PubMed

Wei, Shenhai; Tian, Jintao; Song, Xiaoping; Wu, Bingqun; Liu, Limin

2018-01-01

To investigate the probability of death (POD) from any causes by time after diagnosis of non-small cell lung cancer (NSCLC) and the factors associated with survival for NSCLC patients. A total of 202,914 patients with NSCLC from 2004 to 2013 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The overall survival (OS) and lung cancer-specific survival (LCSS) were calculated and POD from any causes at different time periods after diagnosis was explored. The predictive factors for OS, LCSS and survival from non-lung cancer deaths were investigated using multivariate analysis with Cox proportional hazards regression and competing risk regression analysis. The 5- and 10-year OS were 20.4% and 11.5%, accordingly that for LCSS were 25.5% and 18.4%, respectively. Lung cancer contributed 88.3% (n = 128,402) of the deaths. The POD from lung cancer decreased with time after diagnosis. In multivariate analysis, advanced age and advanced stage of NSCLC were associated with decreased OS and LCSS. Comparing to no surgery, any kind of resection conferred lower risk of death from lung cancer and higher risk of dying from non-lung cancer conditions except lobectomy or bilobectomy, which was associated with lower risk of death from both lung cancer and non-lung cancer conditions. Most of the patients with NSCLC died from lung cancer. Rational surveillance and treatment policies should be made for them. Early stage and lobectomy or bilobectomy were associated with improved OS and LCSS. It is reasonable to focus on early detection and optimal surgical treatment for NSCLC.

Monotherapy versus Combination Therapy against Nonbacteremic Carbapenem-resistant Gram-negative Infections: A Retrospective Observational Study.

PubMed

Ghafur, Abdul; Devarajan, Vidyalakshmi; Raja, T; Easow, Jose; Raja, M A; Sreenivas, Sankar; Ramakrishnan, Balasubramaniam; Raman, S G; Devaprasad, Dedeepiya; Venkatachalam, Balaji; Nimmagadda, Ramesh

2017-12-01

Superiority of colistin-carbapenem combination therapy (CCCT) over colistin monotherapy (CMT) against carbapenem-resistant Gram-negative bacterial (CRGNB) infections is not conclusively proven. The aim of the current study was to analyze the effectiveness of both strategies against CRGNB nonbacteremic infections. This was a retrospective observational cohort study. Case record analysis of patients who had CRGNB nonbacteremic infections identified over a period of 4 years (January 2012-December 2015) was done by medical record review at a tertiary care center in India. P < 0.05 was considered as significant. Multivariate analysis was performed using Cox regression. Out of 153 patients (pneumonia 115, urinary tract infection 17, complicated skin and soft-tissue infection 18, intra-abdominal infection 1, and meningitis 2), 92 patients received CCCT and 61 received CMT. Univariate analysis revealed higher Acute Physiology and Chronic Health Evaluation II (APACHE II) score, pneumonia as the diagnosis, and Klebsiella as the causative organism to be the risk factors for higher 28-day mortality ( P = 0.036, 0.006, 0.016, respectively). Combination therapy had no significant impact on mortality (odds ratio [OR] = 0.91, 95% confidence interval [CI] = 0.327-2.535, P = 0.857). Multivariate analysis revealed that higher APACHE II score and infection due to Klebsiella were found to be independent risk factors for higher mortality (OR = 3.16 and 4.9, 95% CI = 1.34-7.4 and 2.19-11.2, P = 0.008 and 0.0001, respectively). In our retrospective single-center series of CRGNB nonbacteremic infections, CCCT was not superior to CMT. Multicenter large observational studies or prospective randomized clinical trials are the need of the hour.

Preoperative Detection of Sarcopenic Obesity Helps to Predict the Occurrence of Gastric Leak After Sleeve Gastrectomy.

PubMed

Gaillard, Martin; Tranchart, Hadrien; Maitre, Sophie; Perlemuter, Gabriel; Lainas, Panagiotis; Dagher, Ibrahim

2018-03-02

Sleeve gastrectomy (SG) has become the primary procedure for many bariatric teams and staple-line leak represents its most feared complication. Sarcopenic obesity combines the risks of obesity and depleted lean mass leading possibly to an inferior surgical outcome after abdominal surgery. The aim of this study was to evaluate the existence of a potential link between radiologically determined sarcopenic obesity and staple-line leak risk after SG. A retrospective analysis of a prospective database was performed in consecutive patients undergoing SG as primary procedure. Total psoas muscles (TPA) and total visible muscles (TMA) areas were measured on a preoperative computed tomography (CT). Sarcopenia was defined as lowest tertile of skeletal muscular mass indexes (muscular areas over square of height) in each gender (using TPA or TMA). Multivariate analysis was performed to determine preoperative risk factors for staple-line leak. During the study period, 205 patients were included in the analysis. Median BMI was 40.8 kg/m 2 (34.2-49.6), and 9 patients (4.4%) presented a gastric leak. The sex-specific cut-offs for skeletal muscular mass index according to TPA were 8.2 cm 2 /m 2 for men and 6.08 cm 2 /m 2 for women. After multivariate analysis, preoperative weight (OR = 1043) and sarcopenia (TPA) (OR = 5204) were independent predictive factors for gastric leak. The present series suggests that CT scan-determined sarcopenic obesity is associated with increased risk of gastric leak after SG. This preoperatively radiological examination would be a useful clinical tool to tailor patient management according to gastric leak risk.

Pregnancy complications in women with inherited thrombophilia.

PubMed

Weintraub, Adi Y; Sheiner, Eyal; Levy, Amalia; Yerushalmi, Ronit; Mazor, Moshe

2006-06-01

The purpose of this study was to examine whether women with inherited thrombophilia have an increased risk of developing pregnancy complications. All singleton pregnancies with known inherited thrombophilia were compared to those without inherited thrombophilia for deliveries during the years 2000-2002 in a tertiary medical center. Data regarding inherited thrombophilia (International Classification of Disease 9th revision, Clinical Modification code 286.3) were available from the perinatal database in our center. Women lacking prenatal care were excluded from the analysis. Stratified analysis, using a multiple logistic regression model, was performed to control for confounders. Out of 32,763 singleton deliveries that occurred during the study period, 0.2% (n=57) of the women were diagnosed with inherited thrombophilia. Using a multivariate analysis, with backward elimination, the following conditions were significantly associated with inherited thrombophilia: previous fetal losses [odds ratio (OR)=5.5; 95% confidence interval (CI) 2.9-10.3; P<0.001], recurrent abortions (OR=9.5; 95% CI 5.5-16.3; P<0.001), fertility treatments (OR=3.7; 95% CI 1.3-10.6; P=0.014), and intrauterine growth restriction (OR=7.2; 95% CI 3.4-15; P<0.001). Perinatal mortality was significantly higher in women with inherited thrombophilia than in those without known thrombophilia 5.3% (3/57) versus 0.6% (477/32,763) P=0.017. However, inherited thrombophilia was not found to be an independent risk factor for perinatal mortality (OR=3.05; 95% CI 0.90-10.3; P<0.073) in a multivariate analysis with perinatal mortality as the outcome variable, controlling for recurrent abortions, IUGR, and gestational age. Inherited thrombophilia, associated with previous fetal losses, recurrent abortions, fertility treatments, and intrauterine growth restriction, was not an independent risk factor for perinatal mortality.

Coma and Stroke Following Surgical Treatment of Unruptured Intracranial Aneurysm: An American College of Surgeons National Surgical Quality Improvement Program Study.

PubMed

McCutcheon, Brandon A; Kerezoudis, Panagiotis; Porter, Amanda L; Rinaldo, Lorenzo; Murphy, Meghan; Maloney, Patrick; Shepherd, Daniel; Hirshman, Brian R; Carter, Bob S; Lanzino, Giuseppe; Bydon, Mohamad; Meyer, Fredric

2016-07-01

A large national surgical registry was used to establish national benchmarks and associated predictors of major neurologic complications (i.e., coma and stroke) after surgical clipping of unruptured intracranial aneurysms. The American College of Surgeons National Surgical Quality Improvement Program data set between 2007 and 2013 was used for this retrospective cohort analysis. Demographic, comorbidity, and operative characteristics associated with the development of a major neurologic complication (i.e., coma or stroke) were elucidated using a backward selection stepwise logistic regression analysis. This model was subsequently used to fit a predictive score for major neurologic complications. Inclusion criteria were met by 662 patients. Of these patients, 57 (8.61%) developed a major neurologic complication (i.e., coma or stroke) within the 30-day postoperative period. On multivariable analysis, operative time (log odds 0.004 per minute; 95% confidence interval [CI], 0.002-0.007), age (log odds 0.05 per year; 95% CI, 0.02-0.08), history of chronic obstructive pulmonary disease (log odds 1.26; 95% CI, 0.43-2.08), and diabetes (log odds 1.15; 95% CI, 0.38-1.91) were associated with an increased odds of major neurologic complications. When patients were categorized according to quartile of a predictive score generated from the multivariable analysis, rates of major neurologic complications were 1.8%, 4.3%, 6.7%, and 21.2%. Using a large, national multi-institutional cohort, this study established representative national benchmarks and a predictive scoring system for major neurologic complications following operative management of unruptured intracranial aneurysms. The model may assist with risk stratification and tailoring of decision making in surgical candidates. Copyright © 2016 Elsevier Inc. All rights reserved.

Factors associated with adult poisoning in northern Malaysia: a case-control study.

PubMed

Fathelrahman, A I; Ab Rahman, A F; Zain, Z Mohd; Tengku, M A

2006-04-01

Data on adult risk factors associated with drug or chemical poisonings in Malaysia are scarce. The objective of the study was to identify possible risk factors associated with adult admissions to the Penang General Hospital (PGH) due to chemical poisoning and/or drug overdose. The present study was a case-control study, conducted over 18 weeks. One hundred acutely poisoned adult patients admitted to PGH during the period from September 2003 to February 2004 were considered as cases. Two hundred patients admitted to the same medical wards for other illnesses, during the same period, were matched for age and gender with the poisoned cases and thus selected as controls. McNemar test and binary logistic were used for univariate analysis and logistic regression analysis for multivariate analyses. The odds ratio (OR) and its 95% confidence interval (95% CI) were calculated for each predictor variable. Positive histories of psychiatric illness and previous poisoning, problems in boy/girl friend relationships, family problems, marital problems, Indian ethnicity, Chinese ethnicity, living in rented houses and living in a household with less than five people were significant risk factors associated with adult admissions due to poisoning.

A Framework for Establishing Standard Reference Scale of Texture by Multivariate Statistical Analysis Based on Instrumental Measurement and Sensory Evaluation.

PubMed

Zhi, Ruicong; Zhao, Lei; Xie, Nan; Wang, Houyin; Shi, Bolin; Shi, Jingye

2016-01-13

A framework of establishing standard reference scale (texture) is proposed by multivariate statistical analysis according to instrumental measurement and sensory evaluation. Multivariate statistical analysis is conducted to rapidly select typical reference samples with characteristics of universality, representativeness, stability, substitutability, and traceability. The reasonableness of the framework method is verified by establishing standard reference scale of texture attribute (hardness) with Chinese well-known food. More than 100 food products in 16 categories were tested using instrumental measurement (TPA test), and the result was analyzed with clustering analysis, principal component analysis, relative standard deviation, and analysis of variance. As a result, nine kinds of foods were determined to construct the hardness standard reference scale. The results indicate that the regression coefficient between the estimated sensory value and the instrumentally measured value is significant (R(2) = 0.9765), which fits well with Stevens's theory. The research provides reliable a theoretical basis and practical guide for quantitative standard reference scale establishment on food texture characteristics.

A Course in... Multivariable Control Methods.

ERIC Educational Resources Information Center

Deshpande, Pradeep B.

1988-01-01

Describes an engineering course for graduate study in process control. Lists four major topics: interaction analysis, multiloop controller design, decoupling, and multivariable control strategies. Suggests a course outline and gives information about each topic. (MVL)

Evolving Epidemiology of Staphylococcus aureus Bacteremia.

PubMed

Rhee, Yoona; Aroutcheva, Alla; Hota, Bala; Weinstein, Robert A; Popovich, Kyle J

2015-12-01

Methicillin-resistant Staphylococcus aureus (MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type. To examine the epidemiology of S. aureus BSIs, including USA300 and non-USA300 MRSA strains. Retrospective observational study with molecular analysis. Large urban public hospital. Individuals with S. aureus BSIs from January 1, 2007 through December 31, 2013. We used electronic surveillance data to identify cases of S. aureus BSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors. A total of 1,015 cases of S. aureus BSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO- and HO- methicillin-susceptible S. aureus infections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains. USA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.

Analysis of fracture healing in osteopenic bone caused by disuse: experimental study.

PubMed

Paiva, A G; Yanagihara, G R; Macedo, A P; Ramos, J; Issa, J P M; Shimano, A C

2016-03-01

Osteoporosis has become a serious global public health issue. Hence, osteoporotic fracture healing has been investigated in several previous studies because there is still controversy over the effect osteoporosis has on the healing process. The current study aimed to analyze two different periods of bone healing in normal and osteopenic rats. Sixty, 7-week-old female Wistar rats were randomly divided into four groups: unrestricted and immobilized for 2 weeks after osteotomy (OU2), suspended and immobilized for 2 weeks after osteotomy (OS2), unrestricted and immobilized for 6 weeks after osteotomy (OU6), and suspended and immobilized for 6 weeks after osteotomy (OS6). Osteotomy was performed in the middle third of the right tibia 21 days after tail suspension, when the osteopenic condition was already set. The fractured limb was then immobilized by orthosis. Tibias were collected 2 and 6 weeks after osteotomy, and were analyzed by bone densitometry, mechanical testing, and histomorphometry. Bone mineral density values from bony calluses were significantly lower in the 2-week post-osteotomy groups compared with the 6-week post-osteotomy groups (multivariate general linear model analysis, P<0.000). Similarly, the mechanical properties showed that animals had stronger bones 6 weeks after osteotomy compared with 2 weeks after osteotomy (multivariate general linear model analysis, P<0.000). Histomorphometry indicated gradual bone healing. Results showed that osteopenia did not influence the bone healing process, and that time was an independent determinant factor regardless of whether the fracture was osteopenic. This suggests that the body is able to compensate for the negative effects of suspension.

Comparison of acoustic radiation force impulse elastography and transient elastography for prediction of hepatocellular carcinoma recurrence after radiofrequency ablation.

PubMed

Yoon, Jun Sik; Lee, Yu Rim; Kweon, Young-Oh; Tak, Won Young; Jang, Se Young; Park, Soo Young; Hur, Keun; Park, Jung Gil; Lee, Hye Won; Chun, Jae Min; Han, Young Seok; Lee, Won Kee

2018-05-23

To compare the clinical value of acoustic radiation force impulse (ARFI) elastography and transient elastography (TE) for hepatocellular carcinoma (HCC) recurrence prediction after radiofrequency ablation (RFA) and to investigate other predictors of HCC recurrence. Between 2011 and 2016, 130 patients with HCC who underwent ARFI elastography and TE within 6 months before curative RFA were prospectively enrolled. Independent predictors of HCC recurrence were analyzed separately using ARFI elastography and TE. ARFI elastography and TE accuracy to predict HCC recurrence was determined by receiver operating characteristic curve analysis. Of all included patients (91 men; mean age, 63.5 years; range: 43-84 years), 51 (42.5%) experienced HCC recurrence during the follow-up period (median, 21.9 months). In multivariable analysis using ARFI velocity, serum albumin and ARFI velocity [hazard ratios: 2.873; 95% confidence interval (CI): 1.806-4.571; P<0.001] were independent predictors of recurrence, and in multivariable analysis using TE value, serum albumin and TE value (hazard ratios: 1.028; 95% CI: 1.013-1.043; P<0.001) were independent predictors of recurrence. The area under the receiver operating characteristic curve of ARFI elastography (0.821; 95% CI: 0.747-0.895) was not statistically different from that of TE (0.793; 95% CI: 0.712-0.874) for predicting HCC recurrence (P=0.827). The optimal ARFI velocity and TE cutoff values were 1.6 m/s and 14 kPa, respectively. ARFI elastography and TE yield comparable predictors of HCC recurrence after RFA.

Risk factors for Staphylococcus aureus postpartum breast abscess.

PubMed

Branch-Elliman, Westyn; Golen, Toni H; Gold, Howard S; Yassa, David S; Baldini, Linda M; Wright, Sharon B

2012-01-01

Staphylococcus aureus (SA) breast abscesses are a complication of the postpartum period. Risk factors for postpartum SA breast abscesses are poorly defined, and literature is conflicting. Whether risk factors for methicillin-resistant SA (MRSA) and methicillin-susceptible SA (MSSA) infections differ is unknown. We describe novel risk factors associated with postpartum breast abscesses and the changing epidemiology of this infection. We conducted a cohort study with a nested case-control study (n = 216) involving all patients with culture-confirmed SA breast abscess among >30 000 deliveries at our academic tertiary care center from 2003 through 2010. Data were collected from hospital databases and through abstraction from medical records. All SA cases were compared with both nested controls and full cohort controls. A subanalysis was completed to determine whether risk factors for MSSA and MRSA breast abscess differ. Univariate analysis was completed using Student's t test, Wilcoxon rank-sum test, and analysis of variance, as appropriate. A multivariable stepwise logistic regression was used to determine final adjusted results for both the case-control and the cohort analyses. Fifty-four cases of culture-confirmed abscess were identified: 30 MRSA and 24 MSSA. Risk factors for postpartum SA breast abscess in multivariable analysis include in-hospital identification of a mother having difficulty breastfeeding (odds ratio, 5.00) and being a mother employed outside the home (odds ratio, 2.74). Risk factors did not differ between patients who developed MRSA and MSSA infections. MRSA is an increasingly important pathogen in postpartum women; risk factors for postpartum SA breast abscess have not changed with the advent of community-associated MRSA.

LGE Provides Incremental Prognostic Information Over Serum Biomarkers in AL Cardiac Amyloidosis.

PubMed

Boynton, Samuel J; Geske, Jeffrey B; Dispenzieri, Angela; Syed, Imran S; Hanson, Theodore J; Grogan, Martha; Araoz, Philip A

2016-06-01

This study sought to determine the prognostic value of cardiac magnetic resonance (CMR) late gadolinium enhancement (LGE) in amyloid light chain (AL) cardiac amyloidosis. Cardiac involvement is the major determinant of mortality in AL amyloidosis. CMR LGE is a marker of amyloid infiltration of the myocardium. The purpose of this study was to evaluate retrospectively the prognostic value of CMR LGE for determining all-cause mortality in AL amyloidosis and to compare the prognostic power with the biomarker stage. Seventy-six patients with histologically proven AL amyloidosis underwent CMR LGE imaging. LGE was categorized as global, focal patchy, or none. Global LGE was considered present if it was visualized on LGE images or if the myocardium nulled before the blood pool on a cine multiple inversion time (TI) sequence. CMR morphologic and functional evaluation, echocardiographic diastolic evaluation, and cardiac biomarker staging were also performed. Subjects' charts were reviewed for all-cause mortality. Cox proportional hazards analysis was used to evaluate survival in univariate and multivariate analysis. There were 40 deaths, and the median study follow-up period was 34.4 months. Global LGE was associated with all-cause mortality in univariate analysis (hazard ratio = 2.93; p < 0.001). In multivariate modeling with biomarker stage, global LGE remained prognostic (hazard ratio = 2.43; p = 0.01). Diffuse LGE provides incremental prognosis over cardiac biomarker stage in patients with AL cardiac amyloidosis. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Exploring the relationship between entheseal changes and physical activity: a multivariate study.

PubMed

Milella, Marco; Cardoso, Francisca Alves; Assis, Sandra; Lopreno, Geneviève Perréard; Speith, Nivien

2015-02-01

Analyses of entheseal changes (EC) in identified skeletal samples employ a common research strategy based on the comparison between occupations grouped on the basis of shared biomechanical and/or social characteristics. Results from this approach are often ambiguous, with some studies that point to differences in EC between occupational samples and others failing to provide evidence of behavioral effects on EC. Here we investigate patterns of EC among documented occupations by means of a multivariate analysis of robusticity scores in nine postcranial entheses from a large (N = 372) contemporary skeletal sample including specimens from one Italian and two Portuguese identified collections. Data on entheseal robusticity, analyzed by pooled sides as well by separated sides and levels of asymmetry, are converted in binary scores and then analyzed through nonlinear principal component analysis and hierarchical cluster analysis. Results of these analyses are then used for the classification of occupations. Differences between occupational classes are tested by MANOVA and pairwise Hotelling's test. Results evidence three classes which separate occupations related to farming, physically demanding but generalized occupation, and physically undemanding occupations, with the more consistent differences between the first and the last classes. Our results are consistent with differences in biomechanical behavior between the occupations included in each class, and point to the physical and social specificity of farming activities. On the other hand, our study exemplifies the usefulness of alternative analytical protocols for the investigation of EC, and the value of research designs devoid of a priori assumptions for the test of biocultural hypotheses. Copyright © 2014 Wiley Periodicals, Inc.

National Trends of Simple Prostatectomy for Benign Prostatic Hyperplasia With an Analysis of Risk Factors for Adverse Perioperative Outcomes.

PubMed

Pariser, Joseph J; Pearce, Shane M; Patel, Sanjay G; Bales, Gregory T

2015-10-01

To examine the national trends of simple prostatectomy (SP) for benign prostatic hyperplasia (BPH) focusing on perioperative outcomes and risk factors for complications. The National Inpatient Sample (2002-2012) was utilized to identify patients with BPH undergoing SP. Analysis included demographics, hospital details, associated procedures, and operative approach (open, robotic, or laparoscopic). Outcomes included complications, length of stay, charges, and mortality. Multivariate logistic regression was used to determine the risk factors for perioperative complications. Linear regression was used to assess the trends in the national annual utilization of SP. The study population included 35,171 patients. Median length of stay was 4 days (interquartile range 3-6). Cystolithotomy was performed concurrently in 6041 patients (17%). The overall complication rate was 28%, with bleeding occurring most commonly. In total, 148 (0.4%) patients experienced in-hospital mortality. On multivariate analysis, older age, black race, and overall comorbidity were associated with greater risk of complications while the use of a minimally invasive approach and concurrent cystolithotomy had a decreased risk. Over the study period, the national use of simple prostatectomy decreased, on average, by 145 cases per year (P = .002). By 2012, 135/2580 procedures (5%) were performed using a minimally invasive approach. The nationwide utilization of SP for BPH has decreased. Bleeding complications are common, but perioperative mortality is low. Patients who are older, black race, or have multiple comorbidities are at higher risk of complications. Minimally invasive approaches, which are becoming increasingly utilized, may reduce perioperative morbidity. Copyright © 2015 Elsevier Inc. All rights reserved.

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Copula Multivariate analysis of Gross primary production and its hydro-environmental driver; A BIOME-BGC model applied to the Antisana páramos

NASA Astrophysics Data System (ADS)

Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Galarraga, Remigio; Mynett, Arthur

2014-05-01

Simulations of carbon cycling are prone to uncertainties from different sources, which in general are related to input data, parameters and the model representation capacities itself. The gross carbon uptake in the cycle is represented by the gross primary production (GPP), which deals with the spatio-temporal variability of the precipitation and the soil moisture dynamics. This variability associated with uncertainty of the parameters can be modelled by multivariate probabilistic distributions. Our study presents a novel methodology that uses multivariate Copulas analysis to assess the GPP. Multi-species and elevations variables are included in a first scenario of the analysis. Hydro-meteorological conditions that might generate a change in the next 50 or more years are included in a second scenario of this analysis. The biogeochemical model BIOME-BGC was applied in the Ecuadorian Andean region in elevations greater than 4000 masl with the presence of typical vegetation of páramo. The change of GPP over time is crucial for climate scenarios of the carbon cycling in this type of ecosystem. The results help to improve our understanding of the ecosystem function and clarify the dynamics and the relationship with the change of climate variables. Keywords: multivariate analysis, Copula, BIOME-BGC, NPP, páramos

Multivariate analysis of cytokine profiles in pregnancy complications.

PubMed

Azizieh, Fawaz; Dingle, Kamaludin; Raghupathy, Raj; Johnson, Kjell; VanderPlas, Jacob; Ansari, Ali

2018-03-01

The immunoregulation to tolerate the semiallogeneic fetus during pregnancy includes a harmonious dynamic balance between anti- and pro-inflammatory cytokines. Several earlier studies reported significantly different levels and/or ratios of several cytokines in complicated pregnancy as compared to normal pregnancy. However, as cytokines operate in networks with potentially complex interactions, it is also interesting to compare groups with multi-cytokine data sets, with multivariate analysis. Such analysis will further examine how great the differences are, and which cytokines are more different than others. Various multivariate statistical tools, such as Cramer test, classification and regression trees, partial least squares regression figures, 2-dimensional Kolmogorov-Smirmov test, principal component analysis and gap statistic, were used to compare cytokine data of normal vs anomalous groups of different pregnancy complications. Multivariate analysis assisted in examining if the groups were different, how strongly they differed, in what ways they differed and further reported evidence for subgroups in 1 group (pregnancy-induced hypertension), possibly indicating multiple causes for the complication. This work contributes to a better understanding of cytokines interaction and may have important implications on targeting cytokine balance modulation or design of future medications or interventions that best direct management or prevention from an immunological approach. © 2018 The Authors. American Journal of Reproductive Immunology Published by John Wiley & Sons Ltd.

Characterization of Interfacial Chemistry of Adhesive/Dentin Bond Using FTIR Chemical Imaging With Univariate and Multivariate Data Processing

PubMed Central

Wang, Yong; Yao, Xiaomei; Parthasarathy, Ranganathan

2008-01-01

Fourier transform infrared (FTIR) chemical imaging can be used to investigate molecular chemical features of the adhesive/dentin interfaces. However, the information is not straightforward, and is not easily extracted. The objective of this study was to use multivariate analysis methods, principal component analysis and fuzzy c-means clustering, to analyze spectral data in comparison with univariate analysis. The spectral imaging data collected from both the adhesive/healthy dentin and adhesive/caries-affected dentin specimens were used and compared. The univariate statistical methods such as mapping of intensities of specific functional group do not always accurately identify functional group locations and concentrations due to more or less band overlapping in adhesive and dentin. Apart from the ease with which information can be extracted, multivariate methods highlight subtle and often important changes in the spectra that are difficult to observe using univariate methods. The results showed that the multivariate methods gave more satisfactory, interpretable results than univariate methods and were conclusive in showing that they can discriminate and classify differences between healthy dentin and caries-affected dentin within the interfacial regions. It is demonstrated that the multivariate FTIR imaging approaches can be used in the rapid characterization of heterogeneous, complex structure. PMID:18980198

Multivariate Analysis of Longitudinal Rates of Change

PubMed Central

Bryan, Matthew; Heagerty, Patrick J.

2016-01-01

Longitudinal data allow direct comparison of the change in patient outcomes associated with treatment or exposure. Frequently, several longitudinal measures are collected that either reflect a common underlying health status, or characterize processes that are influenced in a similar way by covariates such as exposure or demographic characteristics. Statistical methods that can combine multivariate response variables into common measures of covariate effects have been proposed by Roy and Lin [1]; Proust-Lima, Letenneur and Jacqmin-Gadda [2]; and Gray and Brookmeyer [3] among others. Current methods for characterizing the relationship between covariates and the rate of change in multivariate outcomes are limited to select models. For example, Gray and Brookmeyer [3] introduce an “accelerated time” method which assumes that covariates rescale time in longitudinal models for disease progression. In this manuscript we detail an alternative multivariate model formulation that directly structures longitudinal rates of change, and that permits a common covariate effect across multiple outcomes. We detail maximum likelihood estimation for a multivariate longitudinal mixed model. We show via asymptotic calculations the potential gain in power that may be achieved with a common analysis of multiple outcomes. We apply the proposed methods to the analysis of a trivariate outcome for infant growth and compare rates of change for HIV infected and uninfected infants. PMID:27417129

[Acute effect of daily mean temperature on ischemic heart disease mortality: a multivariable meta-analysis from 12 counties across Hubei Province, China].

PubMed

Zhang, Y Q; Yu, C H; Bao, J Z

2016-11-06

Objective: To evaluate the acute effects of daily mean temperature on ischemic heart disease (IHD) mortality in 12 counties across Hubei Province, China. Methods: We obtained the daily IHD mortality data and meteorological data of the 12 counties for 2009-2012. The distributed lag nonlinear model (DLNM) was used to estimate the community-specific association between mean temperature and IHD mortality. A multivariate meta-analysis was then applied to pool the community-specific relationship between temperature and IHD mortality, and the effects of cold and heat on mortality risk. Results: In 2009-2012, of the 6 702 012 people included in this study, 19 688 died of IHD. A daily average of 1.2 IHD deaths occurred in each community. The annual average mean temperature was 16.6 ℃ during the study period. A nonlinear temperature-IHD mortality relationship was observed for different cumulative lag days at the provincial level. The pooled heat effect was acute but attenuated within 2 days. In contrast, the cold effect was delayed and persisted for more than 2 weeks. Compared with a reference temperature (25 th percentile of mean temperature during the study period, P 25 ), the cold effect for P 10 of mean temperature was associated with IHD mortality, the RR (95% CI ) was 1.084 (1.008-1.167) at lag 0-14, and 1.149 (1.053-1.253) at lag 0-21. For the P 1 cold temperature, the mortality RR (95% CI ) values were 1.116 (0.975-1.276) and 1.220 (1.04-1.428), respectively. We found no significant association between high temperatures and IHD mortality in the present study at different lag days. Conclusion: In Hubei Province, low temperature was associated with increased IHD mortality risk, and cold effects lasted for several days; no significant effect of high temperature was observed.

Towards a contemporary, comprehensive scoring system for determining technical outcomes of hybrid percutaneous chronic total occlusion treatment: The RECHARGE score.

PubMed

Maeremans, Joren; Spratt, James C; Knaapen, Paul; Walsh, Simon; Agostoni, Pierfrancesco; Wilson, William; Avran, Alexandre; Faurie, Benjamin; Bressollette, Erwan; Kayaert, Peter; Bagnall, Alan J; Smith, Dave; McEntegart, Margaret B; Smith, William H T; Kelly, Paul; Irving, John; Smith, Elliot J; Strange, Julian W; Dens, Jo

2018-02-01

This study sought to create a contemporary scoring tool to predict technical outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) from patients treated by hybrid operators with differing experience levels. Current scoring systems need regular updating to cope with the positive evolutions regarding materials, techniques, and outcomes, while at the same time being applicable for a broad range of operators. Clinical and angiographic characteristics from 880 CTO-PCIs included in the REgistry of CrossBoss and Hybrid procedures in FrAnce, the NetheRlands, BelGium and UnitEd Kingdom (RECHARGE) were analyzed by using a derivation and validation set (2:1 ratio). Variables significantly associated with technical failure in the multivariable analysis were incorporated in the score. Subsequently, the discriminatory capacity was assessed and the validation set was used to compare with the J-CTO score and PROGRESS scores. Technical success in the derivation and validation sets was 83% and 85%, respectively. Multivariate analysis identified six parameters associated with technical failure: blunt stump (beta coefficient (b) = 1.014); calcification (b = 0.908); tortuosity ≥45° (b = 0.964); lesion length 20 mm (b = 0.556); diseased distal landing zone (b = 0.794), and previous bypass graft on CTO vessel (b = 0.833). Score variables remained significant after bootstrapping. The RECHARGE score showed better discriminatory capacity in both sets (area-under-the-curve (AUC) = 0.783 and 0.711), compared to the J-CTO (AUC = 0.676) and PROGRESS (AUC = 0.608) scores. The RECHARGE score is a novel, easy-to-use tool for assessing the risk for technical failure in hybrid CTO-PCI and has the potential to perform well for a broad community of operators. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Prognostic factors in patients with hepatitis B virus-related hepatocellular carcinoma undergoing nucleoside analog antiviral therapy

PubMed Central

NISHIKAWA, HIROKI; NISHIJIMA, NORIHIRO; ARIMOTO, AKIRA; INUZUKA, TADASHI; KITA, RYUICHI; KIMURA, TORU; OSAKI, YUKIO

2013-01-01

In the present era of entecavir (ETV) use for chronic hepatitis B (CHB), the prognostic factors in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) remain unclear. The aims of the present study were to investigate the prognostic factors in patients with HBV-related HCC treated with ETV who underwent curative therapy. A total of 74 HBV-related HCC patients treated with ETV who underwent curative therapy were analyzed. Predictive factors associated with overall survival (OS) and recurrence-free survival (RFS) were examined using univariate and multivariate analysis. Our study population included 49 males and 25 females with a median age of 62 years. The median observation period was 3.4 years (range, 0.2–11.5 years). The 1-, 3- and 5-year cumulative OS rates were 100, 89.8 and 89.8%, respectively. The corresponding RFS rates were 82.8, 52.1 and 25.6%, respectively. In this study, 73 patients (98.6%) achieved an HBV DNA level of <400 copies/ml during the follow-up period. No viral breakthrough hepatitis, as defined by 1 log increase from nadir, was observed during ETV therapy. According to multivariate analysis, only hepatitis B e antigen (HBeAg) positivity was significantly associated with OS [hazard ratio (HR), 0.058; 95% confidence interval (CI), 0.005–0.645; P=0.020)], whereas HCC stage (HR, 0.359; 95% CI, 0.150–0.859; P=0.021), HBeAg positivity (HR, 0.202; 95% CI, 0.088–0.463; P<0.001) and γ-glutamyl transpeptidase ≥50 IU/l (HR, 0.340; 95% CI, 0.152–0.760; P=0.009) were significant predictive factors linked to RFS. In conclusion, HBeAg positivity was significantly associated with OS and RFS in HBV-related HCC patients treated with ETV who underwent curative therapy. In such patients, close observation is required, even after curative therapy for HCC. PMID:24179497

[Psychosocial aspects associated with excessive attendance in primary care paediatric clinics].

PubMed

Martín Martín, Raquel; Sánchez Bayle, Marciano; Teruel de Francisco, Carmen

2018-04-20

Hyper-attendance is a significant problem in paediatric Primary Care clinics. The aim of our study was to analyse the level of attendance in these clinics and its relationship with certain psychosocial aspects of the families attending them. Observational descriptive study was conducted using questionnaires collected during a period of 6months, as well as recording the frequency of attendance in the previous 6months. A total of 346 questionnaires of children between 6months and 13years of age belonging to 2 urban Primary Care clinics in Madrid were completed. The raw data was analysed, and comparisons between groups and multivariate analysis were performed. The mean number of consultations in the last 6months, of the total included in the study, was 3.06 in the Primary Care centre, and 0.77 in the emergency services. It was considered over-frequent for those who had attended the Primary Care health centre 6 or more times in this period (>p90), of which there were 33 children (9.53%). In the multivariate analysis, the variables related to being frequent users of Primary Care clinics were: the presence of high level of anxiety in the parents (OR=5.50; 95%CI: 2.49-12.17, P<.0001), and the age of the children (OR=0.73; 95%CI: 0.58-0.91, P=.005). The model presented an area under the curve of 0.761 (95%CI: 0.678-0.945, P<.0001). The frequency of visits in paediatric Primary Care clinics is directly related to the high level of anxiety of the parents, and inversely to the age of the children. It would be advisable to detect and, if possible, intervene in cases of high parental anxiety in order to try to reduce the over-frequency in the paediatric primary health care. Copyright © 2018. Publicado por Elsevier España, S.L.U.

Rural residence, farming environment, and allergic diseases in Argentinean adolescents.

PubMed

Han, Yueh-Ying; Badellino, Hèctor A; Forno, Erick; Celedón, Juan C

2017-01-01

Little is known about residence in a rural or farming environment and allergic diseases in Latin America. Cross-sectional study of rural residence and current wheeze, current asthma and current symptoms of allergic rhino-conjunctivitis in 1,804 adolescents (ages 13-14 years) attending 31 schools in urban and rural areas of San Francisco (Córdoba, Argentina). Rural residence was classified as never, previous, and current. Duration of rural residence was categorized as 0, >0 but ≤5 years, and >5 years. Current wheeze, current asthma, and current allergic rhino-conjunctivitis were defined on the basis of responses to an extensively validated questionnaire from the International Study of Asthma and Allergies in Childhood. Logistic regression was used for the multivariable analysis of rural residence and the outcomes of interest. After adjustment for current smoking and other covariates, current rural residence (odds ratio [OR] = 0.15, 95% confidence interval [CI] = 0.03-0.81) and rural residence for >5 years (OR = 0.32, 95%CI = 0.12-0.84) were significantly associated with reduced odds of current wheeze. In a multivariable analysis, current residence in a rural area (OR = 0.52, 95%CI = 0.32-0.86) and rural residence for >5 years (OR = 0.44, 95%CI = 0.26-0.73) were significantly associated with reduced odds of allergic rhino-conjunctivitis. This association was no longer significant after additional adjustment for current residence in a dairy farm, which was significantly associated with reduced odds of allergic rhino-conjunctivitis. Similarly, current regular contact with farm animals was significantly associated with reduced odds of allergic rhino-conjunctivitis. Among Argentinean adolescents, current rural residence and rural residence for >5 years were associated with reduced odds of current wheeze and allergic rhino-conjunctivitis. These potential protective effects may be explained by a dairy farm environment, including regular contact with farm animals. Pediatr Pulmonol. 2017;52:21-28. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Managerial and environmental factors in the continuity of mental health care across institutions.

PubMed

Greenberg, Greg A; Rosenheck, Robert A

2003-04-01

The authors examined the association of continuity of care with factors assumed to be under the control of health care administrators and environmental factors not under managerial control. The authors used a facility-level administrative data set for 139 Department of Veterans Affairs medical centers over a six-year period and supplemental data on environmental factors to conduct two types of analysis. First, simple correlations were used to examine bivariate associations between eight continuity-of-care measures and nine measures of the institutional environment and the social context. Second, to control for potential autocorrelation, multivariate hierarchical linear models with all nine independent measures were created. The strongest predictors of continuity of care were per capita outpatient expenditure and the degree of emphasis on outpatient care as measured by the percentage of all mental health expenditures devoted to outpatient care. The former was significantly associated with greater continuity of care on six of eight measures and the latter on seven of eight measures. The environmental factor of social capital (the degree of civic involvement and trust at the state level) was associated with greater continuity of care on five measures. The degree to which non-VA mental health services were funded in a state was unexpectedly found to be positively associated with greater continuity of care. In multivariate analysis using hierarchical linear modeling, significant relationships with continuity of care remained for per capita outpatient expenditures, overall outpatient emphasis, and social capital, but not for non-VA mental health funding. A linear term representing the year was positively and significantly associated with six of the eight examined continuity-of-care measures, indicating improvement in continuity of care for the period under study, although the explanation for this trend over time is unclear. Several factors potentially under managerial control are associated with increased mental health continuity of care.

Influence of interpersonal violence on maternal anxiety, depression, stress and parenting morale in the early postpartum: a community based pregnancy cohort study.

PubMed

Malta, Lise A; McDonald, Sheila W; Hegadoren, Kathy M; Weller, Carol A; Tough, Suzanne C

2012-12-15

Research has shown that exposure to interpersonal violence is associated with poorer mental health outcomes. Understanding the impact of interpersonal violence on mental health in the early postpartum period has important implications for parenting, child development, and delivery of health services. The objective of the present study was to determine the impact of interpersonal violence on depression, anxiety, stress, and parenting morale in the early postpartum. Women participating in a community-based prospective cohort study (n = 1319) completed questionnaires prior to 25 weeks gestation, between 34-36 weeks gestation, and at 4 months postpartum. Women were asked about current and past abuse at the late pregnancy data collection time point. Postpartum depression, anxiety, stress, and parenting morale were assessed at 4 months postpartum using the Edinburgh Postnatal Depression Scale, the Spielberger State Anxiety Index, the Cohen Perceived Stress Scale, and the Parenting Morale Index, respectively. The relationship between interpersonal violence and postpartum psychosocial health status was examined using Chi-square analysis (p < 0.05) and multivariable logistic regression. Approximately 30% of women reported one or more experience of interpersonal violence. Sixteen percent of women reported exposure to child maltreatment, 12% reported intimate partner violence, and 12% reported other abuse. Multivariable logistic regression analysis found that a history of child maltreatment had an independent effect on depression in the postpartum, while both child maltreatment and intimate partner violence were associated with low parenting morale. Interpersonal violence did not have an independent effect on anxiety or stress in the postpartum. The most robust relationships were seen for the influence of child maltreatment on postpartum depression and low parenting morale. By identifying women at risk for depression and low parenting morale, screening and treatment in the prenatal period could have far-reaching effects on postpartum mental health thus benefiting new mothers and their families in the long term.

Associations between Soluble Receptor for Advanced Glycation End Products (sRAGE) and S100A12 (EN-RAGE) with Mortality in Long-term Hemodialysis Patients.

PubMed

Jung, Eul Sik; Chung, Wookyung; Kim, Ae Jin; Ro, Han; Chang, Jae Hyun; Lee, Hyun Hee; Jung, Ji Yong

2017-01-01

Hemodialysis (HD) patients experience vascular calcification, ultimately leading to high mortality rates. Previously, we reported associations between soluble receptor for advanced glycation end products (sRAGEs) and extracellular newly identified RAGE-binding protein S100A12 (EN-RAGE) and vascular calcification. Here, we extended our observations, investigating whether these biomarkers may be useful for predicting cardiovascular morbidity and mortality in these subjects. Thus, we evaluated the relationship between sRAGE and S100A12 and mortality in long-term HD patients. This was a prospective observational cohort study in 199 HD patients from an extended analysis of our previous study. Plasma sRAGE, S100A12, comorbidities, and other traditional risk factors were investigated. The cumulative incidences for death using Cox proportional hazards regression were evaluated in multivariable analyses. The observation period was 44 months. During the observation period, 27 (13.6%) patients died. Univariate analysis demonstrated that S100A12 was correlated with diabetes (P = 0.040) and high-sensitivity C-reactive protein (hsCRP) (P = 0.006). In multivariable analyses, plasma sRAGE (hazard ratio [HR] = 1.155; 95% confidence interval [CI] = 0.612-2.183; P = 0.656) and S100A12 (HR = 0.960; 95% CI = 0.566-1.630; P = 0.881) were not associated with mortality in HD patients, although traditional predictors of mortality, including age, history of cardiovascular diseases (CVDs), and serum levels of albumin and hsCRP were related to mortality. Powerful predictors of mortality were age, CVD, and albumin levels. Plasma sRAGE and S100A12 may be weak surrogate markers for predicting all-cause mortality in patients undergoing HD, although S100A12 was partly related to diabetes and inflammation.

Age and Other Risk Factors Influencing Long-Term Mortality in Patients With Traumatic Cervical Spine Fracture.

PubMed

Bank, Matthew; Gibbs, Katie; Sison, Cristina; Kutub, Nawshin; Paptheodorou, Angelos; Lee, Samuel; Stein, Adam; Bloom, Ona

2018-01-01

To identify clinical or demographic variables that influence long-term mortality, as well as in-hospital mortality, with a particular focus on the effects of age. Cervical spine fractures with or without spinal cord injury (SCI) disproportionately impact the elderly who constitute an increasing percentage of the US population. We analyzed data collected for 10 years at a state-designated level I trauma center to identify variables that influenced in-hospital and long-term mortality among elderly patients with traumatic cervical spine fracture with or without SCI. Acute in-hospital mortality was determined from hospital records and long-term mortality within the study period (2003-2013) was determined from the National Death Index. Univariate and multivariate regression analyses were used to identify factors influencing survival. Data from patients (N = 632) with cervical spine fractures were analyzed, the majority (66%) of whom were geriatric (older than age 64). Most patients (62%) had a mild/moderate injury severity score (ISS; median, interquartile range: 6, 5). Patients with SCI had significantly longer lengths of stay (14.1 days), days on a ventilator (3.5 days), and higher ISS (14.9) than patients without SCI ( P < .0001 for all). Falls were the leading mechanism of injury for patients older than age 64. Univariate analysis identified that long-term survival decreased significantly for all patients older than age 65 (hazard ratio [HR]: 1.07; P < .0001). Multivariate analysis demonstrated age (HR: 1.08; P < .0001), gender (HR: 1.60; P < .0007), and SCI status (HR: 1.45, P < .02) significantly influenced survival during the study period. This study identified age, gender, and SCI status as significant variables for this study population influencing long-term survival among patients with cervical spine fractures. Our results support the growing notion that cervical spine injuries in geriatric patients with trauma may warrant additional research.

Trends in initiation of direct oral anticoagulant therapies for atrial fibrillation in a national population-based cross-sectional study in the French health insurance databases

PubMed Central

Huiart, Laetitia; Ferdynus, Cyril; Renoux, Christel; Beaugrand, Amélie; Lafarge, Sophie; Bruneau, Léa; Suissa, Samy; Maillard, Olivier; Ranouil, Xavier

2018-01-01

Objective Unlike several other national health agencies, French health authorities recommended that the newer direct oral anticoagulant (DOAC) agents only be prescribed as second choice for the treatment of newly diagnosed non-valvular atrial fibrillation (NVAF), with vitamin K antagonists (VKA) remaining the first choice. We investigated the patterns of use of DOACs versus VKA in the treatment of NVAF in France over the first 5 years of DOAC availability. We also identified the changes in patient characteristics of those who initiated DOAC treatment over this time period. Methods Based on the French National Health Administrative Database, we constituted a population-based cohort of all patients who were newly treated for NVAF between January 2011 and December 2015. Trends in drug use were described as the percentage of patients initiating each drug at the time of treatment initiation. A multivariate analysis using logistic regression model was performed to identify independent sociodemographic and clinical predictors of initial anticoagulant choice. Results The cohort comprised 814 446 patients who had received a new anticoagulant treatment for NVAF. The proportion of patients using DOACs as initial anticoagulant therapy reached 54% 3 months after the Health Ministry approved the reimbursement of dabigatran for NVAF, and 61% by the end of 2015, versus VKA use. In the multivariate analysis, we found that DOAC initiators were younger and healthier overall than VKA initiators, and this tendency was reinforced over the 2011–2014 period. DOACs were more frequently prescribed by cardiologists in 2012 and after (adjusted OR in 2012: 2.47; 95% CI 2.40 to 2.54). Conclusion Despite recommendations from health authorities, DOACs have been rapidly and massively adopted as initial therapy for NVAF in France. Observational studies should account for the fact that patients selected to initiate DOAC treatment are healthier overall, as failure to do so may bias the risk–benefit assessment of DOACs. PMID:29602837

Low oxygen saturation is associated with pre-hospital mortality among non-traumatic patients using emergency medical services: A national database of Thailand.

PubMed

Sittichanbuncha, Yuwares; Savatmongkorngul, Sorrawit; Jawroongrit, Puchong; Sawanyawisuth, Kittisak

2015-09-01

Pre-hospital emergency medical services are an important network for Emergency Medicine. It has been shown to reduce morbidity and mortality of patients by medical procedures. The Thai government established pre-hospital emergency medical services in 2008 to improve emergency medical care. Since then, there are limited data at the national level on mortality rates with pre-hospital care and the risk factors associated with mortality in non-traumatic patients. To study the pre-hospital mortality rate and factors associated with mortality in non-traumatic patients using the emergency medical service in Thailand. This study retrieved medical data from the National Institute for Emergency Medicine, NIEMS. The inclusion criteria were adult patients above the age of 15 who received medical services by the emergency medical services in Thailand (except Bangkok) from April 1st, 2011 to March 31st, 2012. Patients were excluded if there was no treatment during pre-hospital period, if they were trauma patients, or if their medical data was incomplete. Patients were categorized as either in the survival or non-survival group. Factors associated with mortality were examined by multivariate logistic regression analysis. During the study period, there were 127,602 non-traumatic patients who used pre-hospital emergency medical services in Thailand. Of those, 98,587 patients met the study criteria. For the statistical analyses, there were 66,760 patients who had complete clinical investigations. The mortality rate in this group was 1.89%. Only oxygen saturation was associated with mortality by multivariate logistic regression analysis. The adjusted OR was 0.922 (95% CI 0.8550.994). Low oxygen saturation is significantly associated with pre-hospital mortality in a national database of non-traumatic patients using emergency medical services in Thailand. During pre-hospital care, oxygen level should be monitored and promptly treated. Pulse oximetry devices should be available in all pre-hospital services.

Environmental, entomological, socioeconomic and behavioural risk factors for malaria attacks in Amerindian children of Camopi, French Guiana

PubMed Central

2011-01-01

Background Malaria is a major health issue in French Guiana. Amerindian communities remain the most affected. A previous study in Camopi highlighted the predominant role of environmental factors in the occurrence of malaria. However, all parameters involved in the transmission were not clearly identified. A new survey was conducted in order to clarify the risk factors for the presence of malaria cases in Camopi. Methods An open cohort of children under seven years of age was set up on the basis of biologically confirmed malaria cases for the period 2001-2009. Epidemiological and observational environmental data were collected using two structured questionnaires. Data were analysed with a multiple failures multivariate Cox model. The influence of climate and the river level on malaria incidence was evaluated by time-series analysis. Relationships between Anopheles darlingi human biting rates and malaria incidence rates were estimated using Spearman's rank correlation. Results The global annual incidence over the nine-year period was 238 per 1,000 for Plasmodium falciparum, 514 per 1,000 for Plasmodium visa and 21 per 1,000 for mixed infections. The multivariate survival analysis associated higher malaria incidence with living on the Camopi riverside vs. the Oyapock riverside, far from the centre of the Camopi hamlet, in a home with numerous occupants and going to sleep late. On the contrary, living in a house cleared of all vegetation within 50 m and at high distance of the forest were associated with a lower risk. Meteorological and hydrological characteristics appeared to be correlated with malaria incidence with different lags. Anopheles darlingi human biting rate was also positively correlated to incident malaria in children one month later. Conclusions Malaria incidence in children remains high in young children despite the appearance of immunity in children around three years of age. The closeness environment but also the meteorological parameters play an important role in malaria transmission among children under seven years of age in Camopi. PMID:21861885

Age and Other Risk Factors Influencing Long-Term Mortality in Patients With Traumatic Cervical Spine Fracture

PubMed Central

Bank, Matthew; Gibbs, Katie; Sison, Cristina; Kutub, Nawshin; Paptheodorou, Angelos; Lee, Samuel; Stein, Adam; Bloom, Ona

2018-01-01

Objective: To identify clinical or demographic variables that influence long-term mortality, as well as in-hospital mortality, with a particular focus on the effects of age. Summary and Background Data: Cervical spine fractures with or without spinal cord injury (SCI) disproportionately impact the elderly who constitute an increasing percentage of the US population. Methods: We analyzed data collected for 10 years at a state-designated level I trauma center to identify variables that influenced in-hospital and long-term mortality among elderly patients with traumatic cervical spine fracture with or without SCI. Acute in-hospital mortality was determined from hospital records and long-term mortality within the study period (2003-2013) was determined from the National Death Index. Univariate and multivariate regression analyses were used to identify factors influencing survival. Results: Data from patients (N = 632) with cervical spine fractures were analyzed, the majority (66%) of whom were geriatric (older than age 64). Most patients (62%) had a mild/moderate injury severity score (ISS; median, interquartile range: 6, 5). Patients with SCI had significantly longer lengths of stay (14.1 days), days on a ventilator (3.5 days), and higher ISS (14.9) than patients without SCI (P < .0001 for all). Falls were the leading mechanism of injury for patients older than age 64. Univariate analysis identified that long-term survival decreased significantly for all patients older than age 65 (hazard ratio [HR]: 1.07; P < .0001). Multivariate analysis demonstrated age (HR: 1.08; P < .0001), gender (HR: 1.60; P < .0007), and SCI status (HR: 1.45, P < .02) significantly influenced survival during the study period. Conclusion: This study identified age, gender, and SCI status as significant variables for this study population influencing long-term survival among patients with cervical spine fractures. Our results support the growing notion that cervical spine injuries in geriatric patients with trauma may warrant additional research. PMID:29760965

Additive genetic variation and evolvability of a multivariate trait can be increased by epistatic gene action.

PubMed

Griswold, Cortland K

2015-12-21

Epistatic gene action occurs when mutations or alleles interact to produce a phenotype. Theoretically and empirically it is of interest to know whether gene interactions can facilitate the evolution of diversity. In this paper, we explore how epistatic gene action affects the additive genetic component or heritable component of multivariate trait variation, as well as how epistatic gene action affects the evolvability of multivariate traits. The analysis involves a sexually reproducing and recombining population. Our results indicate that under stabilizing selection conditions a population with a mixed additive and epistatic genetic architecture can have greater multivariate additive genetic variation and evolvability than a population with a purely additive genetic architecture. That greater multivariate additive genetic variation can occur with epistasis is in contrast to previous theory that indicated univariate additive genetic variation is decreased with epistasis under stabilizing selection conditions. In a multivariate setting, epistasis leads to less relative covariance among individuals in their genotypic, as well as their breeding values, which facilitates the maintenance of additive genetic variation and increases a population׳s evolvability. Our analysis involves linking the combinatorial nature of epistatic genetic effects to the ancestral graph structure of a population to provide insight into the consequences of epistasis on multivariate trait variation and evolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Housing Instability Among Current and Former Welfare Recipients

PubMed Central

Phinney, Robin; Danziger, Sheldon; Pollack, Harold A.; Seefeldt, Kristin

2007-01-01

Objectives. We examined correlates of eviction and homelessness among current and former welfare recipients from 1997 to 2003 in an urban Michigan community. Methods. Longitudinal cohort data were drawn from the Women’s Employment Study, a representative panel study of mothers who were receiving cash welfare in February 1997. We used logistic regression analysis to identify risk factors for both eviction and homelessness over the survey period. Results. Twenty percent (95% confidence interval [CI]=16%, 23%) of respondents were evicted and 12% (95% CI=10%, 15%) experienced homelessness at least once between fall 1997 and fall 2003. Multivariate analyses indicated 2 consistent risk factors: having less than a high school education and having used illicit drugs other than marijuana. Mental and physical health problems were significantly associated with homelessness but not evictions. A multivariate screening algorithm achieved 75% sensitivity and 67% specificity in identifying individuals at risk for homelessness. A corresponding algorithm for eviction achieved 75% sensitivity and 50% specificity. Conclusions. The high prevalence of housing instability among our respondents suggests the need to better target housing assistance and other social services to current and former welfare recipients with identifiable personal problems. PMID:17267717

[Modulating variables of work disability in depressive disorders].

PubMed

Catalina Romero, C; Cabrera Sierra, M; Sainz Gutiérrez, J C; Barrenechea Albarrán, J L; Madrid Conesa, A; Calvo Bonacho, E

2011-01-01

To describe the duration of sickness absence in unipolar depression and to determine the relationship of demographic, job-related and clinical variables with length of temporary work disability in depressive disorders. Prospective observational study. A total of 1,292 subjects with depressive disorder diagnosis (ICD-9-CM) were selected claiming sick leave in an Occupational Diseases and Accident sat Work Insurance Scheme (sampling on successive occasions). Descriptive analyses of sickness absence duration, and bivariate (median test) and multivariate analysis (logistic regression) were performed to find relationships between demographic, job-related and clinical variables. Mean duration of sickness absence episodes due to a depressive disorder was 120 days. After multivariate analyses, female sex (p < 0.01), higher age (p < 0.01), lower educational level (p < 0.01), method of payment according to whether self-employed or unemployed workers (p < 0.01) and being referred to both psychiatrist and psychologist (p < 0.01) remained significantly associated with sick leave length. These findings confirm a strong association of depression with long periods of work disability and high absenteeism, and also suggest the need for improvements in functional ability assessment and promotion, treatment and referral of depressed patients. Copyright © 2010 SECA. Published by Elsevier Espana. All rights reserved.

Exploring the Structure of Library and Information Science Web Space Based on Multivariate Analysis of Social Tags

ERIC Educational Resources Information Center

Joo, Soohyung; Kipp, Margaret E. I.

2015-01-01

Introduction: This study examines the structure of Web space in the field of library and information science using multivariate analysis of social tags from the Website, Delicious.com. A few studies have examined mathematical modelling of tags, mainly examining tagging in terms of tripartite graphs, pattern tracing and descriptive statistics. This…

Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental and Workflow Protocols

DTIC Science & Technology

2016-06-01

unlimited. v List of Tables Table 1 Single-lap-joint experimental parameters ..............................................7 Table 2 Survey ...Joints: Experimental and Workflow Protocols by Robert E Jensen, Daniel C DeSchepper, and David P Flanagan Approved for...TR-7696 ● JUNE 2016 US Army Research Laboratory Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental

A Multivariate Model for the Meta-Analysis of Study Level Survival Data at Multiple Times

ERIC Educational Resources Information Center

Jackson, Dan; Rollins, Katie; Coughlin, Patrick

2014-01-01

Motivated by our meta-analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta-analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and…

Atomic-scale phase composition through multivariate statistical analysis of atom probe tomography data.

PubMed

Keenan, Michael R; Smentkowski, Vincent S; Ulfig, Robert M; Oltman, Edward; Larson, David J; Kelly, Thomas F

2011-06-01

We demonstrate for the first time that multivariate statistical analysis techniques can be applied to atom probe tomography data to estimate the chemical composition of a sample at the full spatial resolution of the atom probe in three dimensions. Whereas the raw atom probe data provide the specific identity of an atom at a precise location, the multivariate results can be interpreted in terms of the probabilities that an atom representing a particular chemical phase is situated there. When aggregated to the size scale of a single atom (∼0.2 nm), atom probe spectral-image datasets are huge and extremely sparse. In fact, the average spectrum will have somewhat less than one total count per spectrum due to imperfect detection efficiency. These conditions, under which the variance in the data is completely dominated by counting noise, test the limits of multivariate analysis, and an extensive discussion of how to extract the chemical information is presented. Efficient numerical approaches to performing principal component analysis (PCA) on these datasets, which may number hundreds of millions of individual spectra, are put forward, and it is shown that PCA can be computed in a few seconds on a typical laptop computer.

Evaluation of the microscopic distribution of florfenicol in feed pellets for salmon by Fourier Transform infrared imaging and multivariate analysis.

PubMed

Bastidas, Camila Y; von Plessing, Carlos; Troncoso, José; Del P Castillo, Rosario

2018-04-15

Fourier Transform infrared imaging and multivariate analysis were used to identify, at the microscopic level, the presence of florfenicol (FF), a heavily-used antibiotic in the salmon industry, supplied to fishes in feed pellets for the treatment of salmonid rickettsial septicemia (SRS). The FF distribution was evaluated using Principal Component Analysis (PCA) and Augmented Multivariate Curve Resolution with Alternating Least Squares (augmented MCR-ALS) on the spectra obtained from images with pixel sizes of 6.25 μm × 6.25 μm and 1.56 μm × 1.56 μm, in different zones of feed pellets. Since the concentration of the drug was 3.44 mg FF/g pellet, this is the first report showing the powerful ability of the used of spectroscopic techniques and multivariate analysis, especially the augmented MCR-ALS, to describe the FF distribution in both the surface and inner parts of feed pellets at low concentration, in a complex matrix and at the microscopic level. The results allow monitoring the incorporation of the drug into the feed pellets. Copyright © 2018 Elsevier B.V. All rights reserved.

Risk factors for incidental durotomy during lumbar surgery: a retrospective study by multivariate analysis.

PubMed

Chen, Zhixiang; Shao, Peng; Sun, Qizhao; Zhao, Dong

2015-03-01

The purpose of the present study was to use a prospectively collected data to evaluate the rate of incidental durotomy (ID) during lumbar surgery and determine the associated risk factors by using univariate and multivariate analysis. We retrospectively reviewed 2184 patients who underwent lumbar surgery from January 1, 2009 to December 31, 2011 at a single hospital. Patients with ID (n=97) were compared with the patients without ID (n=2019). The influences of several potential risk factors that might affect the occurrence of ID were assessed using univariate and multivariate analyses. The overall incidence of ID was 4.62%. Univariate analysis demonstrated that older age, diabetes, lumbar central stenosis, posterior approach, revision surgery, prior lumber surgery and minimal invasive surgery are risk factors for ID during lumbar surgery. However, multivariate analysis identified older age, prior lumber surgery, revision surgery, and minimally invasive surgery as independent risk factors. Older age, prior lumber surgery, revision surgery, and minimal invasive surgery were independent risk factors for ID during lumbar surgery. These findings may guide clinicians making future surgical decisions regarding ID and aid in the patient counseling process to alleviate risks and complications. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial-temporal analysis of the of the risk of Rift Valley Fever in Kenya

NASA Astrophysics Data System (ADS)

Bett, B.; Omolo, A.; Hansen, F.; Notenbaert, A.; Kemp, S.

2012-04-01

Historical data on Rift Valley Fever (RVF) outbreaks in Kenya covering the period 1951 - 2010 were analyzed using a logistic regression model to identify factors associated with RVF occurrence. The analysis used a division, an administrative unit below a district, as the unit of analysis. The infection status of each division was defined on a monthly time scale and used as a dependent variable. Predictors investigated include: monthly precipitation (minimum, maximum and total), normalized difference vegetation index, altitude, agro-ecological zone, presence of game, livestock and human population densities, the number of times a division has had an outbreak before and time interval in months between successive outbreaks (used as a proxy for immunity). Both univariable and multivariable analyses were conducted. The models used incorporated an auto-regressive correlation matrix to account for clustering of observations in time, while dummy variables were fitted in the multivariable model to account for spatial relatedness/topology between divisions. This last procedure was followed because it is expected that the risk of RVF occurring in a given division increases when its immediate neighbor gets infected. Functional relationships between the continuous and the outcome variables were assessed to ensure that the linearity assumption was met. Deviance and leverage residuals were also generated from the final model and used for evaluating the goodness of fit of the model. Descriptive analyzes indicate that a total of 91 divisions in 42 districts (of the original 69 districts in place by 1999) reported RVF outbreaks at least once over the period. The mean interval between outbreaks was determined to be about 43 months. Factors that were positively associated with RVF occurrence include increased precipitation, high outbreak interval and the number of times a division has been infected or reported an outbreak. The model will be validated and used for developing an RVF forecasting system. This forecasting system can then be used with the existing regional RVF prediction tools such as EMPRES-i to downscale RVF risk predictions to country-specific scales and subsequently link them with decision support systems. The ultimate aim is to increase the capacity of the national institutions to formulate appropriate RVF mitigation measures.

Who died as a result of the tsunami? Risk factors of mortality among internally displaced persons in Sri Lanka: a retrospective cohort analysis.

PubMed

Nishikiori, Nobuyuki; Abe, Tomoko; Costa, Dehiwala G M; Dharmaratne, Samath D; Kunii, Osamu; Moji, Kazuhiko

2006-03-20

Describing adverse health effects and identifying vulnerable populations during and after a disaster are important aspects of any disaster relief operation. This study aimed to describe the mortality and related risk factors which affected the displaced population over a period of two and a half months after the 2004 Indian Ocean tsunami in an eastern coastal district of Sri Lanka. A cross-sectional household survey was conducted in 13 evacuation camps for internally displaced persons (IDP). Information on all pre-tsunami family members was collected from householders, and all deaths which occurred during the recall period (77 to 80 days starting from the day of the tsunami) were recorded. The distribution of mortality and associated risk factors were analysed. Logistic regression modelling using the generalized estimating equations method was applied in multivariate analysis. Overall mortality rate out of 3,533 individuals from 859 households was 12.9% (446 deaths and 11 missing persons). The majority of the deaths occurred during and immediately after the disaster. A higher mortality was observed among females (17.5% vs. 8.2% for males, p < 0.001), children and the elderly (31.8%, 23.7% and 15.3% for children aged less than 5 years, children aged 5 to 9 years and adults over 50 years, respectively, compared with 7.4% for adults aged 20 to 29 years, p < 0.001). Other risk factors, such as being indoors at the time of the tsunami (13.8% vs. 5.9% outdoors, p < 0.001), the house destruction level (4.6%, 5.5% and 14.2% in increasing order of destruction, p < 0.001) and fishing as an occupation (15.4% vs. 11.2% for other occupations, p < 0.001) were also significantly associated with increased mortality. These correlations remained significant after adjusting for the confounding effects by multivariate analysis. A significantly high mortality was observed in women and children among the displaced population in the eastern coastal district of Sri Lanka who were examined by us. Reconstruction activities should take into consideration these changes in population structure.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

Ethnicity and birth outcome: New Zealand trends 1980-2001. Part 1. Introduction, methods, results and overview.

PubMed

Craig, Elizabeth D; Mantell, Colin D; Ekeroma, Alec J; Stewart, Alistair W; Mitchell, Ed A

2004-12-01

New Zealand Government policy during the past decade has placed a high priority on closing socioeconomic and ethnic gaps in health outcome. To analyse New Zealand's trends in preterm and small for gestational age (SGA) births and late fetal deaths during 1980-2001 and to undertake ethnic specific analyses, resulting in risk factor profiles, for each ethnic group. De-identified birth registration data from 1 189 120 singleton live births and 5775 stillbirths were analysed for the period 1980-2001. Outcomes of interest included preterm birth, SGA and late fetal death while explanatory variables included maternal ethnicity, age and New Zealand Deprivation Index decile. Trend analysis was undertaken for 1980-1994 while multivariate logistic regression was used to explore risk factors for 1996-2001. During 1980-1994, preterm birth rates were highest amongst Maori women. Preterm rates increased by 30% for European/other women, in contrast to non-significant declines of 7% for Maori women and 4% for Pacific women during this period. During the same period, rates of SGA were highest amongst Maori women. Rates of SGA declined by 30% for Pacific women, 25% for Maori women and 19% for European/other women during this period. Rates of late fetal death were highest amongst Pacific women during 1980-1994, but declined by 49% during this period, the rate of decline being similar for all ethnic groups. The marked differences in both trend data and risk factor profiles for women in New Zealand's largest ethnic groups would suggest that unless ethnicity is specifically taken into account in future policy and planning initiatives, the disparities seen in this analysis might well persist into future generations.

Outcomes of limited period of adalimumab treatment in moderate to severe Crohn's disease patients: Taiwan Society of Inflammatory Bowel Disease Study

PubMed Central

Lin, Wei-Chen; Chou, Jen-Wei; Yen, Hsu-Heng; Hsu, Wen-Hung; Lin, Hung-Hsin; Lin, Jen-Kou; Chuang, Chiao-Hsiung; Huang, Tien-Yu; Wang, Horng-Yuan; Wong, Jau-Min

2017-01-01

Background/Aims In Taiwan, due to budget limitations, the National Health Insurance only allows for a limited period of biologics use in treating moderate to severe Crohn's disease (CD). We aimed to access the outcomes of CD patients following a limited period use of biologics, specifically focusing on the relapse rate and remission duration; also the response rate to second use when applicable. Methods This was a multicenter, retrospective, observational study and we enrolled CD patients who had been treated with adalimumab (ADA) according to the insurance guidelines from 2009 to 2015. Results A total of 54 CD patients, with follow-up of more than 6 months after the withdrawal of ADA, were enrolled. The average period of treatment with ADA was 16.7±9.7 months. After discontinuing ADA, 59.3% patients suffered a clinical relapse. In the univariate analysis, the reason for withdrawal was a risk factor for relapse (P=0.042). In the multivariate analysis, current smoker became an important risk factor for relapse (OR, 3.9; 95% CI, 1.2−14.8; P=0.044) and male sex was another risk factor (OR, 2.9; 95% CI, 1.1−8.6; P=0.049). For those 48 patients who received a second round of biologics, the clinical response was seen in 60.4%, and 1 anaphylaxis occurred. Conclusions Fifty-nine percent of patients experienced a relapse after discontinuing the limited period of ADA treatment, and most of them occurred within 1 year following cessation. Male sex and current smoker were risk factors for relapse. Though 60.4% of the relapse patients responded to ADA again. PMID:29142516

Trends in smoking and obesity among US adults before, during, and after the great recession and Affordable Care Act roll-out.

PubMed

Pernenkil, Vikash; Wyatt, Taylor; Akinyemiju, Tomi

2017-09-01

This study examined trends in smoking and overweight/obesity rates among United States (US) adults ages 40years and older by race and socio-economic status (SES) across three study periods; pre-recession (2003-2005), recession (2007-2009), and post-recession/Affordable Care Act (2010-2012). Data was obtained from the Behavioral Risk Factor Surveillance System (BRFSS), and multivariable regression analysis was used to examine changes in overweight/obesity, smoking, physical activity and smoking cessation rates over the study periods. There were 2,805,957 adults included in the analysis; 65.5% of the study population was overweight/obese, and 33.3% were current smokers. Smoking prevalence increased marginally among those with lower SES (income<$10,000) from pre-recession (52.5%) to post-recession (52.9%), but declined in other socio-demographic groups. The odds of overweight/obesity increased in the post-recession (OR: 1.22, 95% CI: 1.21-1.23) and recession (OR: 1.11, 95% CI: 1.11-1.12) periods compared with pre-recession, but odds of smoking overall decreased in the post-recession (OR: 0.93, 95% CI: 0.92-0.94) and recession (OR: 0.95, 95% CI: 0.94-0.97) periods. Overweight/obesity increased over the study periods, regardless of race, SES or healthcare access, while smoking rates showed significant declines post-recession compared with pre-recession, except in low SES groups. These findings suggest that strategies focused on reducing overweight/obesity and increasing access to smoking cessation services, especially among low-income adults, are needed. Prospective studies are needed to better evaluate the influence of the economic recession and Affordable Care Act on behavioral risk factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of Lifestyle on Asthma Control in Japanese Patients: Importance of Periodical Exercise and Raw Vegetable Diet

PubMed Central

Iikura, Motoyasu; Yi, Siyan; Ichimura, Yasunori; Hori, Ai; Izumi, Shinyu; Sugiyama, Haruhito; Kudo, Koichiro; Mizoue, Tetsuya; Kobayashi, Nobuyuki

2013-01-01

Background The avoidance of inhaled allergens or tobacco smoke has been known to have favorable effects on asthma control. However, it remains unclear whether other lifestyle-related factors are also related to asthma control. Therefore, a comprehensive study to examine the associations between various lifestyle factors and asthma control was conducted in Japanese asthmatic patients. Methods The study subjects included 437 stable asthmatic patients recruited from our outpatient clinic over a one-year period. A written, informed consent was obtained from each participant. Asthma control was assessed using the asthma control test (ACT), and a structured questionnaire was administered to obtain information regarding lifestyle factors, including tobacco smoking, alcohol drinking, physical exercise, and diet. Both bivariate and multivariate analyses were conducted. Results The proportions of total control (ACT = 25), well controlled (ACT = 20-24), and poorly controlled (ACT < 20) were 27.5%, 48.1%, and 24.5%, respectively. The proportions of patients in the asthma treatment steps as measured by Global Initiative for Asthma 2007 in step 1, step 2, step 3, step 4, and step 5 were 5.5%, 17.4%, 7.6%, 60.2%, and 9.4%, respectively. Body mass index, direct tobacco smoking status and alcohol drinking were not associated with asthma control. On the other hand, younger age (< 65 years old), passive smoking, periodical exercise (> 3 metabolic equivalents-h/week), and raw vegetable intake (> 5 units/week) were significantly associated with good asthma control by bivariate analysis. Younger age, periodical exercise, and raw vegetable intake were significantly associated with good asthma control by multiple linear regression analysis. Conclusions Periodical exercise and raw vegetable intake are associated with good asthma control in Japanese patients. PMID:23874577

Effect of lifestyle on asthma control in Japanese patients: importance of periodical exercise and raw vegetable diet.

PubMed

Iikura, Motoyasu; Yi, Siyan; Ichimura, Yasunori; Hori, Ai; Izumi, Shinyu; Sugiyama, Haruhito; Kudo, Koichiro; Mizoue, Tetsuya; Kobayashi, Nobuyuki

2013-01-01

The avoidance of inhaled allergens or tobacco smoke has been known to have favorable effects on asthma control. However, it remains unclear whether other lifestyle-related factors are also related to asthma control. Therefore, a comprehensive study to examine the associations between various lifestyle factors and asthma control was conducted in Japanese asthmatic patients. The study subjects included 437 stable asthmatic patients recruited from our outpatient clinic over a one-year period. A written, informed consent was obtained from each participant. Asthma control was assessed using the asthma control test (ACT), and a structured questionnaire was administered to obtain information regarding lifestyle factors, including tobacco smoking, alcohol drinking, physical exercise, and diet. Both bivariate and multivariate analyses were conducted. The proportions of total control (ACT = 25), well controlled (ACT = 20-24), and poorly controlled (ACT < 20) were 27.5%, 48.1%, and 24.5%, respectively. The proportions of patients in the asthma treatment steps as measured by Global Initiative for Asthma 2007 in step 1, step 2, step 3, step 4, and step 5 were 5.5%, 17.4%, 7.6%, 60.2%, and 9.4%, respectively. Body mass index, direct tobacco smoking status and alcohol drinking were not associated with asthma control. On the other hand, younger age (< 65 years old), passive smoking, periodical exercise (> 3 metabolic equivalents-h/week), and raw vegetable intake (> 5 units/week) were significantly associated with good asthma control by bivariate analysis. Younger age, periodical exercise, and raw vegetable intake were significantly associated with good asthma control by multiple linear regression analysis. Periodical exercise and raw vegetable intake are associated with good asthma control in Japanese patients.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

Association between polycystic ovary syndrome and hot flash presentation during the midlife period.

PubMed

Yin, Ophelia; Zacur, Howard A; Flaws, Jodi A; Christianson, Mindy S

2018-06-01

Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in reproductive-aged women; however, the impact of PCOS on menopausal symptoms remains poorly understood. This study aims to determine the influence of PCOS on hot flash presentation in midlife women. Participants were recruited from the Midlife Women's Health Study involving 780 women aged 45 to 54 years. All women completed detailed questionnaires on hot flash symptoms. Between June 2014 and March 2015, participants were screened for history of PCOS based on the Rotterdam criteria. Fisher's exact tests and Wilcoxon rank-sum tests were used for analysis. Multivariate logistic regression was performed to identify factors associated with hot flashes at midlife. In all, 453 women (69%) consented to the telephone interview and 9.3% (n = 42) met diagnostic criteria for PCOS; 411 were included as controls. Mean age was 48.0 and body mass index was 27.3 for women with PCOS. The majority of participants were white (72%). There was no difference between PCOS and control women for levels of follicle-stimulating hormone, testosterone, progesterone, or estradiol. Multivariate logistic regression demonstrated that PCOS was not associated with increased odds of hot flash incidence. Smoking was the only variable associated with experiencing hot flashes (odds ratio 2.0, 95% confidence interval 1.05-3.98). A history of PCOS was not associated with increased hot flash symptoms during the midlife period. Additional research should continue to investigate the health and quality of life associated with a history of PCOS in the aging population.

Predictive modeling of EEG time series for evaluating surgery targets in epilepsy patients.

PubMed

Steimer, Andreas; Müller, Michael; Schindler, Kaspar

2017-05-01

During the last 20 years, predictive modeling in epilepsy research has largely been concerned with the prediction of seizure events, whereas the inference of effective brain targets for resective surgery has received surprisingly little attention. In this exploratory pilot study, we describe a distributional clustering framework for the modeling of multivariate time series and use it to predict the effects of brain surgery in epilepsy patients. By analyzing the intracranial EEG, we demonstrate how patients who became seizure free after surgery are clearly distinguished from those who did not. More specifically, for 5 out of 7 patients who obtained seizure freedom (= Engel class I) our method predicts the specific collection of brain areas that got actually resected during surgery to yield a markedly lower posterior probability for the seizure related clusters, when compared to the resection of random or empty collections. Conversely, for 4 out of 5 Engel class III/IV patients who still suffer from postsurgical seizures, performance of the actually resected collection is not significantly better than performances displayed by random or empty collections. As the number of possible collections ranges into billions and more, this is a substantial contribution to a problem that today is still solved by visual EEG inspection. Apart from epilepsy research, our clustering methodology is also of general interest for the analysis of multivariate time series and as a generative model for temporally evolving functional networks in the neurosciences and beyond. Hum Brain Mapp 38:2509-2531, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Prognostic factors of non-functioning pancreatic neuroendocrine tumor revisited: The value of WHO 2010 classification.

PubMed

Bu, Jiyoung; Youn, Sangmin; Kwon, Wooil; Jang, Kee Taek; Han, Sanghyup; Han, Sunjong; You, Younghun; Heo, Jin Seok; Choi, Seong Ho; Choi, Dong Wook

2018-02-01

Various factors have been reported as prognostic factors of non-functional pancreatic neuroendocrine tumors (NF-pNETs). There remains some controversy as to the factors which might actually serve to successfully prognosticate future manifestation and diagnosis of NF-pNETs. As well, consensus regarding management strategy has never been achieved. The aim of this study is to further investigate potential prognostic factors using a large single-center cohort to help determine the management strategy of NF-pNETs. During the time period 1995 through 2013, 166 patients with NF-pNETs who underwent surgery in Samsung Medical Center were entered in a prospective database, and those factors thought to represent predictors of prognosis were tested in uni- and multivariate models. The median follow-up time was 46.5 months; there was a maximum follow-up period of 217 months. The five-year overall survival and disease-free survival rates were 88.5% and 77.0%, respectively. The 2010 WHO classification was found to be the only prognostic factor which affects overall survival and disease-free survival in multivariate analysis. Also, pathologic tumor size and preoperative image tumor size correlated strongly with the WHO grades ( p <0.001, and p <0.001). Our study demonstrates that 2010 WHO classification represents a valuable prognostic factor of NF-pNETs and tumor size on preoperative image correlated with WHO grade. In view of the foregoing, the preoperative image size is thought to represent a reasonable reference with regard to determination and development of treatment strategy of NF-pNETs.

Multivariable modeling of factors associated with spinal pain in young adolescence.

PubMed

Dolphens, Mieke; Vansteelandt, Stijn; Cagnie, Barbara; Vleeming, Andry; Nijs, Jo; Vanderstraeten, Guy; Danneels, Lieven

2016-09-01

To investigate the factors related to the 1-month period prevalence of low back pain (LBP), neck pain (NP) and thoracic spine pain (TSP) in young adolescents, thereby considering potential correlates from the physical, sociodemographic, lifestyle, psychosocial and comorbid pain domains. In this cross-sectional baseline study, 69 factors potentially associated with spinal pain were assessed among 842 healthy adolescents before pubertal peak growth. With consideration for possible sex differences in associations, multivariable analysis was used to simultaneously evaluate contributions of all variables collected in the five domains. A significantly higher odds of LBP was shown for having high levels of psychosomatic complaints (odds ratio: 4.4; 95 % confidence interval: 1.6-11.9), a high lumbar lordotic apex, retroversed pelvis, introverted personality, and high levels of negative over positive affect. Associations with a higher prevalence and odds of NP were found for psychosomatic complaints (7.8; 2.5-23.9), TSP in the last month (4.9; 2.2-10.8), backward trunk lean, high levels of negative over positive affect and depressed mood. Having experienced LBP (2.7; 1.3-5.7) or NP (5.5; 2.6-11.8) in the preceding month was associated with a higher odds of TSP, as were low self-esteem, excessive physical activity, sedentarism and not achieving the Fit-norm. Psychosomatic symptoms and pain comorbidities had the strongest association with 1-month period prevalence of spinal pain in young adolescents, followed by factors from the physical and psychosocial domains. The role that "physical factors" play in non-adult spinal pain may have been underestimated by previous studies.

Causal diagrams and multivariate analysis II: precision work.

PubMed

Jupiter, Daniel C

2014-01-01

In this Investigators' Corner, I continue my discussion of when and why we researchers should include variables in multivariate regression. My examination focuses on studies comparing treatment groups and situations for which we can either exclude variables from multivariate analyses or include them for reasons of precision. Copyright © 2014 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Multivariate optimum interpolation of surface pressure and surface wind over oceans

NASA Technical Reports Server (NTRS)

Bloom, S. C.; Baker, W. E.; Nestler, M. S.

1984-01-01

The present multivariate analysis method for surface pressure and winds incorporates ship wind observations into the analysis of surface pressure. For the specific case of 0000 GMT, on February 3, 1979, the additional data resulted in a global rms difference of 0.6 mb; individual maxima as larse as 5 mb occurred over the North Atlantic and East Pacific Oceans. These differences are noted to be smaller than the analysis increments to the first-guess fields.