scholarly journals A novel Vascular Leak Index identifies sepsis patients with a higher risk for in-hospital death and fluid accumulation

2021 ◽  
Author(s):  
Jay Chandra ◽  
Miguel Angel Armengol ◽  
Gwendolyn Lee ◽  
Alexandria Lee ◽  
Patrick Thoral ◽  
...  
Keyword(s):  
Fluid Balance ◽  
Generalized Additive Models ◽  
Severity Of Illness ◽  
Continuous Variable ◽  
Additive Models ◽  
Hospital Death ◽  
Fluid Accumulation ◽  
Vascular Leak ◽  
Increased Risk ◽  
The Relationship

Purpose: Sepsis is a leading cause of morbidity and mortality worldwide and is characterized by vascular leak. Treatment for sepsis, specifically intravenous fluids, may worsen deterioration in the context of vascular leak. Methods: We performed a retrospective cohort study of sepsis patients in four ICU databases in North America, Europe, and Asia. We developed an intuitive vascular leak index (VLI) and explored the relationship between VLI and in-hospital death and fluid balance using generalized additive models (GAM). Results: Using GAM, we found that increased VLI is associated with an increased risk of in-hospital death. Patients with a VLI in the highest quartile (Q4), across the four datasets, had a 1.61-2.31 times increased odds of dying in the hospital compared to patients with a VLI in the lowest quartile (Q1). VLI Q2 and Q3 were also associated with increased odds of dying. The relationship between VLI, treated as a continuous variable, and in-hospital death and fluid balance were statistically significant in the three datasets with large sample sizes. Specifically, we observed that as VLI increased, there was increase in the risk for in-hospital death and 36h-84h fluid balance. Conclusions: Our VLI identifies groups of patients who may be at higher risk for in-hospital death or for fluid accumulation. This relationship persisted in models developed to control for severity of illness and chronic comorbidities.

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

ENVIRONMENTAL DISASTERS IN NORTHEAST BRAZIL: HYDROMETEOROLOGICAL, SOCIAL AND SANITARY FACTORS

2021 ◽  
Author(s):  
Marcos Samuel Matias Ribeiro ◽  
Lara de Melo Barbosa Andrade ◽  
Maria Helena Constantino Spyrides ◽  
Kellen Carla Lima ◽  
Pollyane Evangelista da Silva ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Flash Floods ◽  
Additive Models ◽  
Northeast Brazil ◽  
Waste Collection ◽  
Climate Conditions ◽  
Environmental Disasters ◽  
Basic Services ◽  
The Relationship ◽  
Drought Occurrence

AbstractThe occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model’s estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.

scholarly journals A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents

Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 91
Author(s):  
Jean-Philippe Boucher ◽  
Roxane Turcotte
Keyword(s):  
Poisson Distribution ◽  
Fixed Effects ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Panel Count Data ◽  
Insurance Company ◽  
Smooth Functions ◽  
Claim Frequency ◽  
The Impact ◽  
The Relationship

Using telematics data, we study the relationship between claim frequency and distance driven through different models by observing smooth functions. We used Generalized Additive Models (GAM) for a Poisson distribution, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) that we generalize for panel count data. To correctly observe the relationship between distance driven and claim frequency, we show that a Poisson distribution with fixed effects should be used because it removes residual heterogeneity that was incorrectly captured by previous models based on GAM and GAMLSS theory. We show that an approximately linear relationship between distance driven and claim frequency can be derived. We argue that this approach can be used to compute the premium surcharge for additional kilometers the insured wants to drive, or as the basis to construct Pay-as-you-drive (PAYD) insurance for self-service vehicles. All models are illustrated using data from a major Canadian insurance company.

Both low birthweight and high birthweight are associated with cognitive impairment in persons with schizophrenia and their first-degree relatives

2013 ◽  
Vol 43 (11) ◽  
pp. 2361-2367 ◽  
Author(s):  
M. Torniainen ◽  
A. Wegelius ◽  
A. Tuulio-Henriksson ◽  
J. Lönnqvist ◽  
J. Suvisaari
Keyword(s):  
Low Birthweight ◽  
Neuropsychological Test ◽  
Estimating Equation ◽  
Population Based ◽  
Continuous Variable ◽  
First Degree Relatives ◽  
Increased Risk ◽  
Axis I ◽  
Persons With Schizophrenia ◽  
The Relationship

BackgroundBoth low birthweight and high birthweight have been associated with an increased risk for schizophrenia and cognitive impairments in the general population. We assessed the association between birthweight and cognitive performance in persons with schizophrenia and their unaffected first-degree relatives.MethodWe investigated a population-based family sample comprising persons with schizophrenia (n = 142) and their unaffected first-degree relatives (n = 277). Both patients and relatives were interviewed with the Structured Clinical Interview for DSM-IV Axis I Disorders, Clinician Version (SCID-CV) and a comprehensive neuropsychological test battery was administered. Information on birthweight was obtained from obstetric records. We used generalized estimating equation (GEE) models to investigate the effect of birthweight, as a continuous variable, on cognitive functioning, adjusting for within-family correlation and relevant covariates.ResultsBoth low birthweight and high birthweight were associated with lower performance in visuospatial reasoning, processing speed, set-shifting and verbal and visual working memory among persons with schizophrenia and their unaffected first-degree relatives compared to individuals with birthweight in the intermediate range. The group × birthweight interactions were non-significant.ConclusionsBoth low birthweight and high birthweight are associated with deficits in cognition later in life. Schizophrenia does not seem to modify the relationship between birthweight and cognition in families with schizophrenia.

Effect of renal function (RF) on outcomes in the adjuvant treatment of older women with breast cancer (>65 years): CALGB/CTSU 49907 (CC) ancillary data study.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 9515-9515
Author(s):  
Stuart M. Lichtman ◽  
Constance Cirrincione ◽  
Arti Hurria ◽  
Aminah Jatoi ◽  
Maria Theodoulou ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Renal Function ◽  
Renal Insufficiency ◽  
Continuous Variable ◽  
Hematologic Toxicity ◽  
Logrank Test ◽  
Dose Modification ◽  
Increased Risk ◽  
Therapy Completion ◽  
The Relationship

9515 Background: CC 49907 showed superiority of standard therapy (cyclophosphamide/doxorubicin [AC] or cyclophosphamide/methotrexate/5-fluorouracil [CMF]) over capecitabine[C]. Dose adjustments made for renal insufficiency (RI) for methotrexate and C; ideal body weight used. Purpose was to analyze the relationship between RF at baseline and 5 endpoints: toxicity, dose modification, therapy completion, relapse-free survival [RFS] and overall survival [OS]. Methods: Pre-treatment RF was calculated (Cockcroft-Gault). Endpoints assessed by regimen. RF was tested as a dichotomous and continuous variable of stages 1,2 vs. 3,4 kidney disease (National Kidney Foundation). Logistic regression modeled the relationship between renal stage and the first three endpoints of toxicity, dose modification and therapy completion. Toxicity divided by hematologic or not. The relationship of RFS and OS with RF was assessed with the logrank test and as a continuous variable with Wald chi square. Results: 619 patients; incidence of stage 3/4 RI(<60 ml/min) was: CMF=72%; AC=64%; C=75%. With AC the incidence of toxicity differed by renal function. 31% of patients with poorer function >grade 3 non-hematologic toxicity vs. 14% with better function(p=0.011). There was a suggestion of effect of RF on OS and RFS for C-treated patients. RF was not associated with dose modification, premature therapy termination, RFS or OS for the CMF-treated patients. Conclusions: 1) AC: declining RF was associated with increased non-hematologic toxicity. 2)Patients with RI who received dose modifications were not at increased risk for complications in comparison to those who did not have renal insufficiency and received full dose. 3)Declining RF did not affect therapy completion. 4)C: suggestion that worse RF was related to poorer RFS or OS. 5)Exclusion of patients from clinical trials with RI based on concern of excessive hematologic toxicity may not be justified with appropriate modification. 6)Results should be considered in the design of clinical trials for older patients.

Application of generalized additive models to examine ontogenetic and seasonal distributions of spiny dogfish (Squalus acanthias) in the Northeast (US) shelf large marine ecosystem

2014 ◽  
Vol 71 (6) ◽  
pp. 847-877 ◽  
Author(s):  
Skyler R. Sagarese ◽  
Michael G. Frisk ◽  
Robert M. Cerrato ◽  
Kathy A. Sosebee ◽  
John A. Musick ◽  
...  
Keyword(s):  
Generalized Additive Models ◽  
Marine Ecosystem ◽  
Additive Models ◽  
Squalus Acanthias ◽  
Seasonal Occurrence ◽  
Spiny Dogfish ◽  
Science Center ◽  
Large Marine Ecosystem ◽  
Northeast Us ◽  
The Relationship

Increased commercial importance of spiny dogfish (Squalus acanthias) combined with an often debated, and controversial, ecological impact has warranted an investigation of the relationship among distribution, environment, and prey to better understand the species ecology and inform management. To elucidate mechanisms behind distributional changes, we modeled seasonal occurrence and abundance of neonate, immature, and mature spiny dogfish as functions of abiotic and biotic factors using generalized additive models and Northeast Fisheries Science Center bottom trawl survey data. Significant nonlinear relationships were widespread throughout dogfish stages and seasons. Seasonal occurrence was tightly linked to depth and bottom temperature, with year and Julian day influential for some stages. While these factors also influenced abundance, ecological factors (e.g., squid abundances) significantly contributed to trends for many stages. Potential impacts of climate change were evaluated by forecasting distributions under different temperature scenarios, which revealed higher regional probabilities of occurrence for most stages during a warmer than average year. Our results can be used to better understand the relationship between sampling periods and movement drivers to survey catchability of the population in the Northeast (US) shelf large marine ecosystem.

scholarly journals The association of sleep duration and metabolic syndrome in the Bandare-Kong cohort study, a cross-sectional survey (finding from PERSIAN cohort study)

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shideh Rafati ◽  
Maryam Isheh ◽  
Abnoos Azarbad ◽  
Farhad Ghadiri Soufi ◽  
Arash Rahimi ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Cohort Study ◽  
Sleep Duration ◽  
Severity Score ◽  
Additive Models ◽  
Cross Sectional Survey ◽  
Short Sleep Duration ◽  
Cross Sectional ◽  
Increased Risk ◽  
The Relationship

Abstract Background A variety of health problems, such as metabolic syndrome (MetS), have been linked to sleep disorders. While numerous epidemiological studies have shown a U-shaped relationship between sleep duration and poor health outcomes, the results were limited and inconsistent. This study was designed to evaluate the relationship between sleep duration and MetS. Methods This population-based study was conducted on the participants aged 35–70 of Bandare-Kong Non-Communicable Diseases (BKNCD) Cohort Study, a part of Prospective Epidemiological Research Studies in IrAN (PERSIAN). MetS was diagnosed according to the National Cholesterol Education Program (NCEP) criteria and the Iranian-specific cut-off for waist circumference (≥ 95 cm). Sleep information was extracted through a standard questionnaire based on self-reported information. Data were analyzed by R software using generalized additive models (GAMs). A statistically significant level was considered as P < 0.05. Results A total of 3695 participants were included in the analyses. The mean age was 48.05 years (SD 9.36), and 2067 (55.9%) were female. The estimated Prevalence of MetS was 35.9%, and women appeared to be more likely to have MetS than men (P < 0.001). There was a non-linear and linear association between sleep duration and the risk of MetS in women and men, respectively. The lowest risk was observed among those with 7–7.5 h of sleep duration per night. Conclusion Long sleep duration was associated with increased risk of MetS and higher MetS severity score in both genders, while the short sleep duration increased the risk of Mets as well as MetS severity score just in women. The longitudinal studies would be suggested to assess the relationship between sleep quality and quantity components and MetS.

scholarly journals A Decision Support Model for the Necessity of Cardio-Angiography, A Result of Generalized Additive and logistic Regression Model

2021 ◽  
Author(s):  
Fatemeh Rezaeisharif ◽  
Azadeh Saki ◽  
Ali Taghipour ◽  
Mohammad Tajfard
Keyword(s):  
Coronary Artery ◽  
Blood Sugar ◽  
Logistic Regression Model ◽  
Generalized Additive Models ◽  
Coronary Artery Occlusion ◽  
Artery Occlusion ◽  
Additive Models ◽  
Evidence Based ◽  
Hs Crp ◽  
The Relationship

Introduction: Angiography is used as the gold standard for diagnosis of coronary artery disease (CAD). It is an invasive procedure and has several complications. Also, some patients refuse angiograms for reasons such as fear, high cost, and loss of trust in physician diagnosis. The negative results of this test is more than a third. Therefore, having a statistical predictive model for estimating the risk of CAD, as an evidence-based support system, can help the physician and patient decide on the necessity of angiography. Aims: In this study we aimed to find an evidence-based supportive model for decision making on the necessity of angiography in people who were candidates for angiography by the physician after initial tests. Methods: In this study, 1187 patients who had been referred to Ghaem Hospital of Mashhad University of Medical Sciences and diagnosed with physicians after initial tests were enrolled. Demographic data, lipid and blood sugar levels, and the history of underlying disorders were variables that were studied in the statistical model fitting. Initially, generalized additive models were used singularly for quantitative predictors, then by applying right transformations on the predictor variables we entered them simultaneously in logistic and count regression models. These two models were fitted to the data using R software and then compared in terms of predictive accuracy. Findings: Generalized additive models showed that the relationship between CAD with the hs-CRP level was not monotone. Exploratory analyzes showed that 62% of people with hs-CRP level <3 and 50% of people with hs-CRP levels between 3 and 6 were suffered from the CAD. The highest rate of CAD was seen in the range of 6-8 (93%) but with increasing the hs-CRP level to above 8 it decreased to 70%. The relationship between age and the risk of CAD was S-shaped. Risk of CAD in diabetic subjects with normal FBS was equal to that of nondiabetic subjects with normal fasting blood sugar. The age, gender, diabetes, FBS, and hs-CRP were significant in both models (p <0.05). The area under the ROC curve was upgraded to 81 for the logistic model. Conclusion: The most important finding of this exploratory study was that out of 232 patients with hs-CRP level between 6 to 8, 217 (93%) had coronary artery occlusion, for these subjects the probability of occluding a coronary artery was 0.93. The present study also showed that if the blood sugar is controlled in patients with diabetes, then this disease will not be a risk factor for patients with coronary artery occlusion. The logistic regression model presented in this study is recommended as the final model to support decision-making about the necessity of angiography.

scholarly journals Altered Lipid Profile is a Risk Factor for the Progression Andrecurrenceof COVID-19: From Two Retrospective Cohorts

2020 ◽  
Author(s):  
Hui Jin ◽  
Junji He ◽  
Chuan Dong ◽  
Luhong Cao ◽  
Xing Qi ◽  
...  
Keyword(s):  
Risk Factor ◽  
Lipid Profile ◽  
Cox Regression ◽  
Lipid Lowering ◽  
Hospital Death ◽  
Lipid Lowering Therapy ◽  
Clinical Endpoints ◽  
Increased Risk ◽  
The Impact ◽  
The Relationship

Abstract Background The COVID-19 pandemic has spread worldwide. However, the impact of lipid profile and lipid-lowering treatment on clinical endpoints in COVID-19 have not previously been investigated. Methods In this retrospective, multicenter cohort study, we consecutively enrolled 430 adult COVID-19 patients from two Chinese hospitals (one each in Chengdu and Wuhan) admitted during February 2020 and followed-up until April 30. Demographic, metabolic profile, laboratory, treatment and clinical endpoint data including in-hospital death and recurrence of COVID-19, were collected. Results In Chengdu patients, univariable and multivariable Cox regression showed that the low-density lipoprotein cholesterol (LDL-C) dyslipidemia on admission was associated with the recurrence of COVID-19 during the follow-up period. In Wuhan cohort, the patients with triglycerides hyperlipemia had an increased risk of in-hospital death. However, in both cohorts, statin therapy during COVID-19 course did not affect these clinical endpoints. Compared to the Chengdu cohort, the Wuhan patients tended to have more severe COVID-19 but, unexpectedly, had lower levels of serum lipid. It is of interesting to notice that the relationship between the observed biomarkers of inflammation and lipid do not match the relationship between the organ function measures and this lipid. Conclusions The baseline dyslipidemia should be considered as a risk factor for poor prognosis and recurrence of COVID-19. The lipid level may be altered during COVID-19 course, since lipidology may be distinctly affected by both inflammation and organic damage for SARS-CoV-2. Further investigation is needed on the role of use of lipid-lowering therapy among patients with COVID-19 infections.

scholarly journals Distributional Regression Techniques in Socioeconomic Research on the Inequality of Health with an Application on the Relationship between Mental Health and Income

2019 ◽  
Vol 16 (20) ◽  
pp. 4009 ◽  
Author(s):  
Alexander Silbersdorff ◽  
Kai Sebastian Schneider
Keyword(s):  
Mental Health ◽  
Health Inequalities ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Mental Health Score ◽  
Cross Sectional ◽  
Regression Techniques ◽  
German Socioeconomic Panel ◽  
The Relationship ◽  
Distributional Regression

This study addresses the much-discussed issue of the relationship between health and income. In particular, it focuses on the relation between mental health and household income by using generalized additive models of location, scale and shape and thus employing a distributional perspective. Furthermore, this study aims to give guidelines to applied researchers interested in taking a distributional perspective on health inequalities. In our analysis we use cross-sectional data of the German socioeconomic Panel (SOEP). We find that when not only looking at the expected mental health score of an individual but also at other distributional aspects, like the risk of moderate and severe mental illness, that the relationship between income and mental health is much more pronounced. We thus show that taking a distributional perspective, can add to and indeed enrich the mostly mean-based assessment of existent health inequalities.

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