Logistic regression analysis of potential prognostic factors for pulmonary thromboembolism

Objective: To identify potential prognostic factors for pulmonary thromboembolism (PTE), establishing a mathematical model to predict the risk for fatal PTE and nonfatal PTE.Method: the reports on 4,813 consecutive autopsies performed from 1979 to 1998 in a Brazilian tertiary referral medical school were reviewed for a retrospective study. From the medical records and autopsy reports of the 512 patients found with macroscopically and/or microscopically,documented PTE, data on demographics, underlying diseases, and probable PTE site of origin were gathered and studied by multiple logistic regression. Thereafter, the jackknife method, a statistical cross-validation technique that uses the original study patients to validate a clinical prediction rule, was performed.Results: the autopsy rate was 50.2%, and PTE prevalence was 10.6%. In 212 cases, PTE was the main cause of death (fatal PTE). The independent variables selected by the regression significance criteria that were more likely to be associated with fatal PTE were age (odds ratio [OR], 1.02; 95% confidence interval [CI], 1.00 to 1.03), trauma (OR, 8.5; 95% CI, 2.20 to 32.81), right-sided cardiac thrombi (OR, 1.96; 95% CI, 1.02 to 3.77), pelvic vein thrombi (OR, 3.46; 95% CI, 1.19 to 10.05); those most likely to be associated with nonfatal PTE were systemic arterial hypertension (OR, 0.51; 95% CI, 0.33 to 0.80), pneumonia (OR, 0.46; 95% CI, 0.30 to 0.71), and sepsis (OR, 0.16; 95% CI, 0.06 to 0.40). The results obtained from the application of the equation in the 512 cases studied using logistic regression analysis suggest the range in which logit p > 0.336 favors the occurrence of fatal PTE, logit p < - 1.142 favors nonfatal PTE, and logit P with intermediate values is not conclusive. The cross-validation prediction misclassification rate was 25.6%, meaning that the prediction equation correctly classified the majority of the cases (74.4%).Conclusions: Although the usefulness of this method in everyday medical practice needs to be confirmed by a prospective study, for the time being our results suggest that concerning prevention, diagnosis, and treatment of PTE, strict attention should be given to those patients presenting the variables that are significant in the logistic regression model.

IL-1ra anti-inflammatory cytokine polymorphism is associated with risk of gastric cancer and chronic gastritis in a Brazilian population, but the TNF-beta pro-inflammatory cytokine is not

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Associação de polimorfismos nos genes TLR2 e TLR4 com risco de câncer colorretal esporádico e influência na expressão gênica

Pós-graduação em Genética - IBILCE

Imagens hiperespectrais no monitoramento da nutrição em citros

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Clinical evaluation of multiple-surface ART restorations: three-year follow-up

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Growth hormone pharmacogenetics: the interactive effect of a microsatellite in the IGF1 promoter region with the GHR-exon 3 and-202 A/C IGFBP3 variants on treatment outcomes of children with severe GH deficiency

Insulin-like growth factor type 1 (IGF1) is a mediator of growth hormone (GH) action, and therefore, IGF1 is a candidate gene for recombinant human GH (rhGH) pharmacogenetics. Lower serum IGF1 levels were found in adults homozygous for 19 cytosine-adenosine (CA) repeats in the IGF1 promoter. The aim of this study was to evaluate the influence of (CA)n IGF1 polymorphism, alone or in combination with GH receptor (GHR)-exon 3 and -202 A/C insulin-like growth factor binding protein-3 (IGFBP3) polymorphisms, on the growth response to rhGH therapy in GH-deficient (GHD) patients. Eighty-four severe GHD patients were genotyped for (CA) n IGF1, -202 A/C IGFBP3 and GHR-exon 3 polymorphisms. Multiple linear regressions were performed to estimate the effect of each genotype, after adjustment for other influential factors. We assessed the influence of genotypes on the first year growth velocity (1st y GV) (n = 84) and adult height standard deviation score (SDS) adjusted for target-height SDS (AH-TH SDS) after rhGH therapy (n = 37). Homozygosity for the IGF1 19CA repeat allele was negatively correlated with 1st y GV (P = 0.03) and AH-TH SDS (P = 0.002) in multiple linear regression analysis. In conjunction with clinical factors, IGF1 and IGFBP3 genotypes explain 29% of the 1st y GV variability, whereas IGF1 and GHR polymorphisms explain 59% of final height-target-height SDS variability. We conclude that homozygosity for IGF1 (CA) 19 allele is associated with less favorable short-and long-term growth outcomes after rhGH treatment in patients with severe GHD. Furthermore, this polymorphism exhibits a non-additive interaction with -202 A/C IGFBP3 genotype on the 1st y GV and with GHR-exon 3 genotype on adult height. The Pharmacogenomics Journal (2012) 12, 439-445; doi:10.1038/tpj.2011.13; published online 5 April 2011

Protective and risk factors in amateur equestrians and description of injury patterns: A retrospective data analysis and a case - control survey

Background In Switzerland there are about 150,000 equestrians. Horse related injuries, including head and spinal injuries, are frequently treated at our level I trauma centre. Objectives To analyse injury patterns, protective factors, and risk factors related to horse riding, and to define groups of safer riders and those at greater risk Methods We present a retrospective and a case-control survey at conducted a tertiary trauma centre in Bern, Switzerland. Injured equestrians from July 2000 - June 2006 were retrospectively classified by injury pattern and neurological symptoms. Injured equestrians from July-December 2008 were prospectively collected using a questionnaire with 17 variables. The same questionnaire was applied in non-injured controls. Multiple logistic regression was performed, and combined risk factors were calculated using inference trees. Results Retrospective survey A total of 528 injuries occured in 365 patients. The injury pattern revealed as follows: extremities (32%: upper 17%, lower 15%), head (24%), spine (14%), thorax (9%), face (9%), pelvis (7%) and abdomen (2%). Two injuries were fatal. One case resulted in quadriplegia, one in paraplegia. Case-control survey 61 patients and 102 controls (patients: 72% female, 28% male; controls: 63% female, 37% male) were included. Falls were most frequent (65%), followed by horse kicks (19%) and horse bites (2%). Variables statistically significant for the controls were: Older age (p = 0.015), male gender (p = 0.04) and holding a diploma in horse riding (p = 0.004). Inference trees revealed typical groups less and more likely to suffer injury. Conclusions Experience with riding and having passed a diploma in horse riding seem to be protective factors. Educational levels and injury risk should be graded within an educational level-injury risk index.

Genome-wide identification of quantitative trait loci in a cross between Hampshire and Landrace I: carcass traits

We report the identification of quantitative trait loci (QTL) affecting carcass composition, carcass length, fat deposition and lean meat content using a genome scan across 462 animals from a combined intercross and backcross between Hampshire and Landrace pigs. Data were analysed using multiple linear regression fitting additive and dominance effects. This model was compared with a model including a parent-of-origin effect to spot evidence of imprinting. Several precisely defined muscle phenotypes were measured in order to dissect body composition in more detail. Three significant QTL were detected in the study at the 1% genome-wide level, and twelve significant QTL were detected at the 5% genome-wide level. These QTL comprise loci affecting fat deposition and lean meat content on SSC1, 4, 9, 10, 13 and 16, a locus on SSC2 affecting the ratio between weight of meat and bone in back and weight of meat and bone in ham and two loci affecting carcass length on SSC12 and 17. The well-defined phenotypes in this study enabled us to detect QTL for sizes of individual muscles and to obtain information of relevance for the description of the complexity underlying other carcass traits.

Use of hydroclimatic forecasts for improved water management in central Texas

Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

Are there risk factors in alpine skiing? A controlled multicentre survey of 1278 skiers

OBJECTIVE: To analyse risk factors in alpine skiing. DESIGN: A controlled multicentre survey of injured and non-injured alpine skiers. SETTING: One tertiary and two secondary trauma centres in Bern, Switzerland. PATIENTS AND METHODS: All injured skiers admitted from November 2007 to April 2008 were analysed using a completed questionnaire incorporating 15 parameters. The same questionnaire was distributed to non-injured controls. Multiple logistic regression was performed. Patterns of combined risk factors were calculated by inference trees. A total of 782 patients and 496 controls were interviewed. RESULTS: Parameters that were significant for the patients were: high readiness for risk (p = 0.0365, OR 1.84, 95% CI 1.04 to 3.27); low readiness for speed (p = 0.0008, OR 0.29, 95% CI 0.14 to 0.60); no aggressive behaviour on slopes (p<0.0001, OR 0.19, 95% CI 0.09 to 0.37); new skiing equipment (p = 0.0228, OR 59, 95% CI 0.37 to 0.93); warm-up performed (p = 0.0015, OR 1.79, 95% CI 1.25 to 2.57); old snow compared with fresh snow (p = 0.0155, OR 0.31, 95% CI 0.12 to 0.80); old snow compared with artificial snow (p = 0.0037, OR 0.21, 95% CI 0.07 to 0.60); powder snow compared with slushy snow (p = 0.0035, OR 0.25, 95% CI 0.10 to 0.63); drug consumption (p = 0.0044, OR 5.92, 95% CI 1.74 to 20.11); and alcohol abstinence (p<0.0001, OR 0.14, 95% CI 0.05 to 0.34). Three groups at risk were detected: (1) warm-up 3-12 min, visual analogue scale (VAS)(speed) >4 and bad weather/visibility; (2) VAS(speed) 4-7, icy slopes and not wearing a helmet; (3) warm-up >12 min and new skiing equipment. CONCLUSIONS: Low speed, high readiness for risk, new skiing equipment, old and powder snow, and drug consumption are significant risk factors when skiing. Future work should aim to identify more precisely specific groups at risk and develop recommendations--for example, a snow weather index at valley stations.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Euphausiid respiration model revamped, link to model results

Euphausiids constitute major biomass component in shelf ecosystems and play a fundamental role in the rapid vertical transport of carbon from the ocean surface to the deeper layers during their daily vertical migration (DVM). DVM depth and migration patterns depend on oceanographic conditions with respect to temperature, light and oxygen availability at depth, factors that are highly dependent on season in most marine regions. Changes in the abiotic conditions also shape Euphausiid metabolism including aerobic and anaerobic energy production. Here we introduce a global krill respiration model which includes the effect of latitude (LAT), the day of the year of interest (DoY), and the number of daylight hours on the day of interest (DLh), in addition to the basal variables that determine ectothermal oxygen consumption (temperature, body mass and depth) in the ANN model (Artificial Neural Networks). The newly implemented parameters link space and time in terms of season and photoperiod to krill respiration. The ANN model showed a better fit (r**2=0.780) when DLh and LAT were included, indicating a decrease in respiration with increasing LAT and decreasing DLh. We therefore propose DLh as a potential variable to consider when building physiological models for both hemispheres. We also tested for seasonality the standard respiration rate of the most common species that were investigated until now in a large range of DLh and DoY with Multiple Linear Regression (MLR) or General Additive model (GAM). GAM successfully integrated DLh (r**2= 0.563) and DoY (r**2= 0.572) effects on respiration rates of the Antarctic krill, Euphausia superba, yielding the minimum metabolic activity in mid-June and the maximum at the end of December. Neither the MLR nor the GAM approach worked for the North Pacific krill Euphausia pacifica, and MLR for the North Atlantic krill Meganyctiphanes norvegica remained inconclusive because of insufficient seasonal data coverage. We strongly encourage comparative respiration measurements of worldwide Euphausiid key species at different seasons to improve accuracy in ecosystem modelling.

Avaliação do impacto do horizonte temporal nas estimativas de EAD de linhas de crédito com limites explícitos a PME

Tese de mestrado em Matemática Aplicada à Economia e Gestão, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016