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Concept: Multivariate statistics


BACKGROUND: The mortality rate of patients complicated with sepsis-associated organ failure remains high in spite of intensive care treatment. The purpose of this study was to define the duration of systemic inflammatory response syndrome (SIRS) before organ failure (DSOF) and determine the value of DSOF as a prognostic factor in septic patients. METHODS: This retrospective cohort study was conducted in an 11-bed medical and surgical intensive care unit (ICU) in a university hospital. The primary endpoint was in-hospital mortality of the septic patients. RESULTS: One hundred ten septic patients with organ failure and/or shock were enrolled in this study. The in-hospital mortality rate was 36.9%. The median DSOF was 28.5 h. As a metric variable, DSOF was a statistically significant prognostic factor according to univariate analysis (survivor: 74.7 +/- 9.6 h, non-survivor: 58.8 +/- 16.5 h, p = 0.015). On the basis of the ROC curve, we defined an optimal cutoff of 24 h, with which we divided the patients as follows: group 1 (n = 50) comprised patients with a DSOF <=24 h, and group 2 (n = 60) contained patients with a DSOF >24 h. There were statistically significant differences in the in-hospital mortality rate between the two groups (52.0% vs. 25.0%, p = 0.004). Furthermore, by multivariate analysis, DSOF <=24 h (odds ratio: 5.89, 95% confidence interval: 1.46-23.8, p = 0.013) was a significant independent prognostic factor. CONCLUSION: DSOF may be a useful prognostic factor for severe sepsis.

Concepts: Inflammation, Cohort study, Statistics, Systemic inflammatory response syndrome, Intensive care medicine, Multivariate statistics, Septic shock, Sepsis


BACKGROUND: Trachoma is the leading cause of preventable blindness worldwide. It is common in areas where the people are socio-economically deprived. The aim of this study was to assess active trachoma and associated risk factors among children 1–9 years in East Gojjam. METHODS: Community-based cross-sectional study was conducted in Baso Liben District from February to April 2012. A two-stage random cluster-sampling technique was employed and all children 1–9 years old from each household were clinically assessed for trachoma based on simplified WHO 1983 classification. Data were collected by using semi-structured interview, pre-tested questionnaire and observation. The data were entered and analyzed using SPSS version 16 statistical package.Result: From a total of 792 children screened for trachoma (of which 50.6% were girls), the overall prevalence of active trachoma was 24.1% consisting of only 17.2% [95% CI: 14.8, 20.1] TF and 6.8% TI. There were variations among children living in low land (29.3%) and in medium land (21.4%). In multivariate analysis, low monthly income (AOR= adjusted odds ratio) 2.98; 95% CI (confidence interval): 1.85-7.85), illiterate family (AOR =5.18; 95% CI: 2.92-9.17); unclean face (AOR =18.68; 95% CI :1.98-175.55); access to water source (AOR=2.01;95% CI: 1.27-3.15); less than 20 liters of water use (AOR=4.88; 95% CI:1.51-15.78); not using soap for face washing (AOR=5.84; 95%CI :1.98-17.19); not using latrine frequently (AOR=1.75; 95% CI:0.01-0.42); density of flies (AOR=3.77; 95%CI: 2.26-6.29); less knowledgeable family (AOR=3.91; 95%CI :2.40-6.38) and average monthly income (AOR=2.98; 95%CI : 1.85-7.85) were found independently associated with trachoma. CONCLUSION: Active trachoma is a major public problem among 1–9 years children and significantly associated with a number of risky factors. Improvement in awareness of facial hygiene, environmental conditions, mass antibiotic distribution and health education on trachoma transmission and prevention should be strengthened in the District.

Concepts: Epidemiology, Medical statistics, Cross-sectional study, Risk, Multivariate statistics, Odds ratio, SPSS


BACKGROUND: Elevated Glasgow Prognostic Score (GPS) has been related to poor prognosis in patients with hepatocellular carcinoma (HCC) undergoing surgical resection or receiving sorafenib. The aim of this study was to investigate the prognostic value of GPS in patients with various stages of the disease and with different liver functional status. METHODS: One hundred and fifty patients with newly diagnosed HCC were prospectively evaluated. Patients were divided according to their GPS scores. Univariate and multivariate analyses were performed to identify clinicopathological variables associated with overall survival; the identified variables were then compared with those of other validated staging systems. RESULTS: Elevated GPS were associated with increased asparate aminotransferase ( P<0.0001), total bilirubin ( P<0.0001), decreased albumin (P<0.0001), alpha-fetoprotein ( P=0.008), larger tumor diameter ( P=0.003), tumor number ( P=0.041), vascular invasion ( P=0.0002), extra hepatic metastasis ( P=0.02), higher Child-Pugh scores (P<0.0001), and higher Cancer Liver Italian Program scores (P<0.0001). On multivariate analysis, the elevated GPS was independently associated with worse overall survival. CONCLUSIONS: Our results demonstrate that the GPS can serve as an independent marker of poor prognosis in patients with HCC in various stages of disease and different liver functional status.

Concepts: Cancer, Lung cancer, Cirrhosis, Liver, Multivariate statistics, Bilirubin, Prognosis, Jaundice


BACKGROUND: Static posture, repetitive movements and lack of physical variation are known risk factors for work-related musculoskeletal disorders, and thus needs to be properly assessed in occupational studies. The aims of this study were (i) to investigate the effectiveness of a conventional exposure variation analysis (EVA) in discriminating exposure time lines and (ii) to compare it with a new cluster-based method for analysis of exposure variation. METHODS: For this purpose, we simulated a repeated cyclic exposure varying within each cycle between “low” and “high” exposure levels in a “near” or “far” range, and with “low” or “high” velocities (exposure change rates). The duration of each cycle was also manipulated by selecting a “small” or “large” standard deviation of the cycle time. Theses parameters reflected three dimensions of exposure variation, i.e. range, frequency and temporal similarity.Each simulation trace included two realizations of 100 concatenated cycles with either low (rho = 0.1), medium (rho = 0.5) or high (rho = 0.9) correlation between the realizations. These traces were analyzed by conventional EVA, and a novel cluster-based EVA (C-EVA). Principal component analysis (PCA) was applied on the marginal distributions of 1) the EVA of each of the realizations (univariate approach), 2) a combination of the EVA of both realizations (multivariate approach) and 3) C-EVA. The least number of principal components describing more than 90% of variability in each case was selected and the projection of marginal distributions along the selected principal component was calculated. A linear classifier was then applied to these projections to discriminate between the simulated exposure patterns, and the accuracy of classified realizations was determined. RESULTS: C-EVA classified exposures more correctly than univariate and multivariate EVA approaches; classification accuracy was 49%, 47% and 52% for EVA (univariate and multivariate), and C-EVA, respectively (p < 0.001). All three methods performed poorly in discriminating exposure patterns differing with respect to the variability in cycle time duration. CONCLUSION: While C-EVA had a higher accuracy than conventional EVA, both failed to detect differences in temporal similarity. The data-driven optimality of data reduction and the capability of handling multiple exposure time lines in a single analysis are the advantages of the C-EVA.

Concepts: Multivariate statistics, Factor analysis, Principal component analysis, Exposure, Singular value decomposition, Photography, Linear discriminant analysis, The Unscrambler


The effective production and usage of ginsenosides, given their distinct pharmacological effects, are receiving increasing amounts of attention. As the ginsenosides content differs in different parts of Panax ginseng, we wanted to assess and compare the ginsenosides content in the ginseng roots, leave, stems, and berries. To extract the ginsenosides, 70% (v/v) methanol was used. The optimal ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) method was used to profile various ginsenosides from the different parts of P. ginseng. The datasets were then subjected to multivariate analysis including principal component analysis (PCA) and hierarchical clustering analysis (HCA). A UPLC-QTOF/MS method with an in-house library was constructed to profile 58 ginsenosides. With this method, a total of 39 ginsenosides were successfully identified and quantified in the ginseng roots, leave, stem, and berries. PCA and HCA characterized the different ginsenosides compositions from the different parts. The quantitative ginsenoside contents were also characterized from each plant part. The results of this study indicate that the UPLC-QTOF/MS method can be an effective tool to characterize various ginsenosides from the different parts of P. ginseng.

Concepts: Mass spectrometry, Multivariate statistics, Principal component analysis, Root, Ginseng, Ginsenoside, Panax, Panax ginseng


Evaluation of Xagrid® Efficacy and Long-term Safety, a Phase IV, prospective, non interventional study performed in 13 European countries enrolled high risk essential thrombocythemia patients treated with cytoreductive therapy. Primary objectives were safety and pregnancy outcomes. Of 3721 registered patients, 3649 received cytoreductive therapy. At registration, 3611 were receiving: anagrelide (Xagrid®) (n=804), other cytoreductive therapy (n=2666), anagrelide + other cytoreductive therapy (n=141). Median age was 56 vs 70 years for anagrelide vs other cytoreductive therapy. Event rates (patients with events/100 patient years) were, for total thrombosis 1.62 vs 2.06, venous thrombosis 0.15 vs 0.53. Anagrelide was more commonly associated with hemorrhage (0.89 vs 0.43), especially with anti-aggregatory therapy (1.35 vs 0.33) and myelofibrosis (1.04 vs 0.30). Other cytoreductive therapies were more associated with acute leukemia (AL) (0.28 vs 0.07) and other malignancies (1.29 vs 0.44). Post-hoc multivariate analyses identified increased risk for thrombosis with prior thrombohemorrhagic events, age ≥65, cardiovascular risk factors, or hypertension. Risk factors for transformation were prior thrombohemorrhagic events, age ≥65, time since diagnosis, and platelet count increase. Safety analysis reflected published data and no new safety concerns for anagrelide were found. Live births occurred in 41/54 pregnancies (76%). ( #NCT00567502).

Concepts: Scientific method, Blood, Observational study, Platelet, Multivariate statistics, Essential thrombocytosis, Phase IV, Anagrelide


The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets.

Concepts: DNA, Scientific method, Regression analysis, Multivariate statistics, Psychometrics, Autism, Asperger syndrome, Autism spectrum


We estimate models of consumer food waste awareness and attitudes using responses from a national survey of U.S. residents. Our models are interpreted through the lens of several theories that describe how pro-social behaviors relate to awareness, attitudes and opinions. Our analysis of patterns among respondents' food waste attitudes yields a model with three principal components: one that represents perceived practical benefits households may lose if food waste were reduced, one that represents the guilt associated with food waste, and one that represents whether households feel they could be doing more to reduce food waste. We find our respondents express significant agreement that some perceived practical benefits are ascribed to throwing away uneaten food, e.g., nearly 70% of respondents agree that throwing away food after the package date has passed reduces the odds of foodborne illness, while nearly 60% agree that some food waste is necessary to ensure meals taste fresh. We identify that these attitudinal responses significantly load onto a single principal component that may represent a key attitudinal construct useful for policy guidance. Further, multivariate regression analysis reveals a significant positive association between the strength of this component and household income, suggesting that higher income households most strongly agree with statements that link throwing away uneaten food to perceived private benefits.

Concepts: Regression analysis, Statistics, Multivariate statistics, Household, Linear discriminant analysis, Household income in the United States, Food safety, Income quintiles


BACKGROUND: The aim of this study was to determine factors associated with the severity of cancer related fatigue (CRF) and predictors of improvement of CRF at the first follow-up visit in patients with advanced cancer referred to outpatient palliative care clinic (OPC). METHODS: We reviewed the records of consecutive patients with advanced cancer presenting to OPC. Edmonton Symptom Assessment System (ESAS) scores were obtained at the initial and subsequent visits between January 2003 and December 2008. All patients received interdisciplinary care led by palliative medicine specialists following an institutional protocol. Fatigue improvement was defined as a reduction of >=2 points in ESAS score relative to the baseline. Descriptive statistics were used to summarize patient characterstics. Univariate analyses were performed and only significant variables were included in multivariate regression analysis to determine factors associated with severity and improvement in CRF. RESULTS: A total of 1778 evaluable patients were analyzed (median age, 59 years; 52% male). The median time between visits was 15 days. Median fatigue scores on the ESAS were 6 at baseline and 5 at follow-up. Severity of all ESAS items and low serum albumin were associated with fatigue at baseline (p < 0.0001). The improvement of fatigue was observed in 586 patients (33%). The hierarchical model showed that fatigue improved over time (b = -0.009; p = 0.0009). low appetite (odds ratio [OR] = 1.09 per point; p = 0.0113) and genitourinary cancer (OR = 1.74 per point; p = 0.0458) were significantly associated with improvement of fatigue. CONCLUSIONS: CRF is strongly associated with physical and emotional symptoms. Genitourinary cancer and low appetite at baseline were associated with successful improvement of fatigue.

Concepts: Regression analysis, Cancer, Oncology, Chemotherapy, Palliative care, Multivariate statistics, Symptomatic treatment, Palliative medicine


The study of how long-term changes affect metacommunities is a relevant topic, that involves the evaluation of connections among biological assemblages across different spatio-temporal scales, in order to fully understand links between global changes and macroevolutionary patterns. We applied multivariate statistical analyses and diversity tests using a large data matrix of rodent fossil sites in order to analyse long-term faunal changes. Late Miocene rodent faunas from southwestern Europe were classified into metacommunities, presumably sharing ecological affinities, which followed temporal and environmental non-random assembly and disassembly patterns. Metacommunity dynamics of these faunas were driven by environmental changes associated with temperature variability, but there was also some influence from the aridity shifts described for this region during the late Miocene. Additionally, while variations in the structure of rodent assemblages were directly influenced by global climatic changes in the southern province, the northern sites showed a pattern of climatic influence mediated by diversity-dependent processes.

Concepts: Statistics, Mathematics, Ecology, Multivariate statistics, Climate change, Europe, Pattern, Miocene