955 resultados para Multivariate risk model
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Objective: to identify risk factors associated with neonatal transfers from a free-standing birth centre to a hospital. Design: epidemiological case-control study. Setting: midwifery-led free-standing birth centre in Sao Paulo, Brazil. Participants: 96 newborns were selected from 2840 births between September 1998 and August 2005. Cases were defined as all new borns transferred from the birth centre to a hospital (n = 32), and controls were defined as new borns delivered at the same birth centre, during the same time period, and who had not been transferred to a hospital (n = 64). Measurements and findings: data were collected from medical records available at the birth centre. Univariate and multivariate analyses were performed using logistic regression. The multivariate analysis included outcomes with p<0.25, specifically: smoking during pregnancy, prenatal care appointments, labour complications, weight in relation to gestational age, and one-minute Apgar score. Of the foregoing outcomes, those that remained in the full regression model as a risk factor associated with neonatal transfer were: smoking during pregnancy [p = 0.009, odds ratio (OR) = 4.1,95% confidence interval (CI) 1.03-16.33], labour complications (p<0.001, OR = 5.5, 95% CI 1.06-28.26) and one-minute Apgar score <= 7 (p<0.001, OR = 7.8,95% CI 1.62-37.03). Key conclusions and implications for practice: smoking during pregnancy, labour complications and one-minute Apgar score <= 7 were confirmed as risk factors for neonatal transfer from the birth centre to a hospital. The identified risk factors can help to improve institutional protocols and formulate hypotheses for other studies. (C) 2009 Elsevier Ltd. All rights reserved.
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Background: Previous work showed that daily ingestion of an aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416, supplemented or not with isoflavones, reduced the total cholesterol and non-HDL-cholesterol levels, increased the high-density lipoprotein (HDL) concentration and inhibited the raising of autoantibody against oxidized low-density lipoprotein (ox-LDL Ab) and the development of atherosclerotic lesions. Objective: The aim of this study was to characterize the fecal microbiota in order to investigate the possible correlation between fecal microbiota, serum lipid parameters and atherosclerotic lesion development in rabbits with induced hypercholesterolemia, that ingested the aqueous soy extract fermented with Enterococcus faecium CRL 183 and Lactobacillus helveticus 416. Methods: The rabbits were randomly allocated to five experimental groups (n = 6): control (C), hypercholesterolemic (H), hypercholesterolemic plus unfermented soy product (HUF), hypercholesterolemic plus fermented soy product (HF) and hypercholesterolemic plus isoflavone-supplemented fermented soy product (HIF). Lipid parameters and microbiota composition were analyzed on days 0 and 60 of the treatment and the atherosclerotic lesions were quantified at the end of the experiment. The fecal microbiota was characterized by enumerating the Lactobacillus spp., Bifidobacterium spp., Enterococcus spp., Enterobacteria and Clostridium spp. populations. Results: After 60 days of the experiment, intake of the probiotic soy product was correlated with significant increases (P < 0.05) on Lactobacillus spp., Bifidobacterium spp. and Enterococcus spp. and a decrease in the Enterobacteria population. A strong correlation was observed between microbiota composition and lipid profile. Populations of Enterococcus spp., Lactobacillus spp. and Bifidobacterium spp. were negatively correlated with total cholesterol, non-HDL-cholesterol, autoantibodies against oxidized LDL (ox-LDL Ab) and lesion size. HDL-C levels were positively correlated with Lactobacillus spp., Bifidobacterium spp., and Enterococcus spp. populations. Conclusion: In conclusion, daily ingestion of the probiotic soy product, supplemented or not with isoflavones, may contribute to a beneficial balance of the fecal microbiota and this modulation is associated with an improved cholesterol profile and inhibition of atherosclerotic lesion development.
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The CASMIN Project is arguably the most influential contemporary study of class mobility in the world. However, CASMIN results with respect to weak vertical status effects on class mobility have been extensively criticized. Drawing on arguments about how to model vertical mobility, Hout and Hauser (1992) show that class mobility is strongly determined by vertical socioeconomic differences. This paper extends these arguments by estimating the CASMIN model while explicitly controlling for individual determinants of socioeconomic attainment. Using the 1972 Oxford Mobility Data and the 1979 and 1983 British Election Studies, the paper employs mixed legit models to show how individual socioeconomic factors and categorical differences between classes shape intergenerational mobility. The findings highlight the multidimensionality of class mobility and its irreducibility to vertical movement up and down a stratification hierarchy.
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Background We present a method (The CHD Prevention Model) for modelling the incidence of fatal and nonfatal coronary heart disease (CHD) within various CHD risk percentiles of an adult population. The model provides a relatively simple tool for lifetime risk prediction for subgroups within a population. It allows an estimation of the absolute primary CHD risk in different populations and will help identify subgroups of the adult population where primary CHD prevention is most appropriate and cost-effective. Methods The CHD risk distribution within the Australian population was modelled, based on the prevalence of CHD risk, individual estimates of integrated CHD risk, and current CHD mortality rates. Predicted incidence of first fatal and nonfatal myocardial infarction within CHD risk strata of the Australian population was determined. Results Approximately 25% of CHD deaths were predicted to occur amongst those in the top 10 percentiles of integrated CHD risk, regardless of age group or gender. It was found that while all causes survival did not differ markedly between percentiles of CHD risk before the ages of around 50-60, event-free survival began visibly to differ about 5 years earlier. Conclusions The CHD Prevention Model provides a means of predicting future CHD incidence amongst various strata of integrated CHD risk within an adult population. It has significant application both in individual risk counselling and in the identification of subgroups of the population where drug therapy to reduce CHD risk is most cost-effective. J Cardiovasc Risk 8:31-37 (C) 2001 Lippincott Williams & Wilkins.
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Background: Insulin resistance and obesity are recognized as left ventricular (LV) mass determinants independent of blood pressure (BP). Prevalence of LV hypertrophy (LVH) and the relationship between LV mass to body composition and metabolic variables were evaluated in normotensive individuals as participants of a population-based study. Methods: LV mass was measured using the second harmonic image by M-mode 2D guided echocardiography in 326 normotensive subjects (mean 47 +/- 9.4 years). Fasting serum lipids and glucose, BP, body composition and waist circumference (WC) were recorded during a clinic visit. Results: Applying a normalization criterion not related to body weight (g/height raised to the power 2.7) and the cut-off points of 47.7 (men) and 46.6 g/m(2.7) (women), LVH was found in 7.9% of the sample. Univariate analysis showed LV mass (g/m(2.7)) related to age, body mass index (BMI), WC, fat and lean body mass, systolic and diastolic BP, and metabolic variables (cholesterol, HDL-c, triglycerides and glucose). In multivariate analysis only BMI and age-adjusted systolic BP remained as independent predictors of LV mass, explaining 31% and 5% of its variability. Removing BMI from the model, WC, age-adjusted systolic BP and lean mass remained independent predictors, explaining 25.0%, 4.0% and 1.5% of LV mass variability, respectively. After sex stratification, LV mass predictors were WC (8%) and systolic BP (5%) in men and WC (36%) and systolic BP (3%) in women. Conclusion: BMI in general and particularly increased abdominal adiposity (WC as surrogate) seems to account for most of LV mass increase in normotensive individuals, mainly in women. (C) 2008 Elsevier Ireland Ltd. All rights reserved.
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Objective. The purpose of this study was to estimate the Down syndrome detection and false-positive rates for second-trimester sonographic prenasal thickness (PT) measurement alone and in combination with other markers. Methods. Multivariate log Gaussian modeling was performed using numerical integration. Parameters for the PT distribution, in multiples of the normal gestation-specific median (MoM), were derived from 105 Down syndrome and 1385 unaffected pregnancies scanned at 14 to 27 weeks. The data included a new series of 25 cases and 535 controls combined with 4 previously published series. The means were estimated by the median and the SDs by the 10th to 90th range divided by 2.563. Parameters for other markers were obtained from the literature. Results. A log Gaussian model fitted the distribution of PT values well in Down syndrome and unaffected pregnancies. The distribution parameters were as follows: Down syndrome, mean, 1.334 MoM; log(10) SD, 0.0772; unaffected pregnancies, 0.995 and 0.0752, respectively. The model-predicted detection rates for 1%, 3%, and 5% false-positive rates for PT alone were 35%, 51%, and 60%, respectively. The addition of PT to a 4 serum marker protocol increased detection by 14% to 18% compared with serum alone. The simultaneous sonographic measurement of PT and nasal bone length increased detection by 19% to 26%, and with a third sonographic marker, nuchal skin fold, performance was comparable with first-trimester protocols. Conclusions. Second-trimester screening with sonographic PT and serum markers is predicted to have a high detection rate, and further sonographic markers could perform comparably with first-trimester screening protocols.
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Objective: To identify prediction factors for the development of leptospirosis-associated pulmonary hemorrhage syndrome (LPHS). Methods: We conducted a prospective cohort study. The study comprised of 203 patients, aged >= 14 years, admitted with complications of the severe form of leptospirosis at the Emilio Ribas Institute of Infectology (Sao Paulo, Brazil) between 1998 and 2004. Laboratory and demographic data were obtained and the severity of illness score and involvement of the lungs and others organs were determined. Logistic regression was performed to identify independent predictors of LPHS. A prospective validation cohort of 97 subjects with severe form of leptospirosis admitted at the same hospital between 2004 and 2006 was used to independently evaluate the predictive value of the model. Results: The overall mortality rate was 7.9%. Multivariate logistic regression revealed that five factors were independently associated with the development of LPHS: serum potassium (mmol/L) (OR = 2.6; 95% CI = 1.1-5.9); serum creatinine (mmol/L) (OR = 1.2; 95% CI = 1.1-1.4); respiratory rate (breaths/min) (OR = 1.1; 95% CI = 1.1-1.2); presenting shock (OR = 69.9; 95% CI = 20.1-236.4), and Glasgow Coma Scale Score (GCS) < 15 (OR = 7.7; 95% CI = 1.3-23.0). We used these findings to calculate the risk of LPHS by the use of a spreadsheet. In the validation cohort, the equation classified correctly 92% of patients (Kappa statistic = 0.80). Conclusions: We developed and validated a multivariate model for predicting LPHS. This tool should prove useful in identifying LPHS patients, allowing earlier management and thereby reducing mortality. (C) 2009 The British Infection Society. Published by Elsevier Ltd. All rights reserved.
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Objective: Bronchial typical carcinoid tumors are tow-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. Methods: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. Results: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to mate gender. Discussion: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. Conclusion: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.
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Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.
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A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.
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The incidence of melanoma increases markedly in the second decade of life but almost nothing is known of the causes of melanoma in this age group. We report on the first population-based case-control study of risk factors for melanoma in adolescents (15-19 years). Data were collected through personal interviews with cases, controls and parents. A single examiner conducted full-body nevus counts and blood samples were collected from cases for analysis of the CDKN2A melanoma predisposition gene. A total of 201 (80%) of the 250 adolescents with melanoma diagnosed between 1987 and 1994 and registered with the Queensland Cancer Registry and 205 (79%) of 258 age-, gender- and location-matched controls who were contacted agreed to participate. The strongest risk factor associated with melanoma in adolescents in a multivariate model was the presence of more than 100 nevi 2 mm or more in diameter (odds ratio [OR] = 46.5, 95% confidence interval [Cl] = 11.4-190.8). Other risk factors were red hair (OR = 5.4, 95%Cl = 1.0-28.4); blue eyes (OR = 4.5, 95%Cl = 1.5- 13.6); inability to tan after prolonged sun exposure (OR = 4.7, 95%Cl = 0.9-24.6); heavy facial freckling (OR = 3.2, 95% Cl = 0.9-12.3); and family history of melanoma (OR = 4.0, 95%Cl = 0.8-18.9). Only 2 of 147 cases tested had germline variants or mutations in CDKN2A. There was no association with sunscreen use overall, however, never/rare use of sunscreen at home under the age of 5 years was associated with increased risk (OR = 2.2, 95%Cl = 0.7-7.1). There was no difference between cases and controls in cumulative sun exposure in this high-exposure environment. Factors indicating genetic susceptibility to melanoma, in particular, the propensity to develop nevi and freckles, red hair, blue eyes, inability to tan and a family history of the disease are the primary determinants of melanoma among adolescents in this high solar radiation environment. Lack of association with reported sun exposure is consistent with the high genetic susceptibility in this group. (C) 2002 Wiley-Liss, Inc.
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The growth experimented in recent years in both the variety and volume of structured products implies that banks and other financial institutions have become increasingly exposed to model risk. In this article we focus on the model risk associated with the local volatility (LV) model and with the Variance Gamma (VG) model. The results show that the LV model performs better than the VG model in terms of its ability to match the market prices of European options. Nevertheless, both models are subject to significant pricing errors when compared with the stochastic volatility framework.