17 resultados para Risk models
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Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.
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Background & aims: Altered intestinal permeability has been shown to be associated with metabolic alterations in animal models of obesity, but not in humans. The aim of this study was to assess intestinal permeability in obese women and verify if there is any association with anthropometric measurements, body composition or biochemical variables. Methods: Twenty lean and twenty obese females participated in the study. Anthropometric measurements, body composition and blood pressure were assessed and biochemical analyses were performed. Administration of lactulose and mannitol followed by their quantification in urine was used to assess the intestinal permeability of volunteers. Results: The obese group showed lower HDL (p < 0.05), higher fasting glucose, insulin, HOMA index and lactulose excretion than the lean group (p < 0.05), suggesting increased paracellular permeability. Lactulose excretion showed positive correlation (p < 0.05) with waist and abdominal circumference. Blood insulin and the HOMA index also increased with the increase in mannitol and lactulose excretion and in the L/M ratio (p < 0.05). L/M ratio presented a negative correlation with HDL concentration (p < 0.05). Conclusions: We demonstrated that intestinal permeability parameters in obese women are positively correlated with anthropometric measurements and metabolic variables. Therapeutic interventions focused on intestine health and the modulation of intestinal permeability should be explored in the context of obesity. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Physical and psychosocial risk factors for musculoskeletal disorders in Brazilian and Italian nurses
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As part of the international CUPID investigation, we compared physical and psychosocial risk factors for musculoskeletal disorders among nurses in Brazil and Italy. Using questionnaires, we collected information on musculoskeletal disorders and potential risk factors from 751 nurses employed in public hospitals. By fitting country-specific multiple logistic regression models, we investigated the association of stressful physical activities and psychosocial characteristics with site-specific and multisite pain, and associated sickness absence. We found no clear relationship between low back pain and occupational lifting, but neck and shoulder pain were more common among nurses who reported prolonged work with the arms in an elevated position. After adjustment for potential confounding variables, pain in the low back, neck and shoulder, multisite pain, and sickness absence were all associated with somatizing tendency in both countries. Our findings support a role of somatizing tendency in predisposition to musculoskeletal disorders, acting as an important mediator of the individual response to triggering exposures, such as work-load.
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Background: Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Methods: Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed. Results: Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846), Barnetson (0.850), MMRpro (0.821) and Wijnen (0.807) models did not present significant statistical difference. The Myriad model presented lower AUC (0.704) than the four other models evaluated. Considering thresholds of >= 5%, the models sensitivity varied between 1 (Myriad) and 0.87 (Wijnen) and specificity ranged from 0 (Myriad) to 0.38 (Barnetson). Conclusions: The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.
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Background: The complex natural history of human papillomavirus (HPV) infections following a single HPV test can be modeled as competing-risks events (i.e., no-, transient- or persistent infection) in a longitudinal setting. The covariates associated with these compet ng events have not been previously assessed using competing-risks regression models. Objectives: To gain further insights in the outcomes of cervical HPV infections, we used univariate- and multivariate competing-risks regression models to assess the covariaies associated with these competing events. Study Design and Methods: Covariates associated with three competing outcomes (no-, transient- or persistent HR-HPV infection) were analysed in a sub-cohort of 1,865 women prospectively followed-up in the NIS (n = 3,187) and LAMS Study (n = 12,114). Results: In multivariate competing-risks models (with two other outcomes as competing events), permanently HR-HPV negative outcome was significantly predicted only by the clearance of ASCUS+Pap during FU, while three independent covariates predicted transient HR-HPV infections: i) number of recent (< 12 months) sexual partners (risk increased), ii) previous Pap screening history (protective), and history of previous CIN (increased risk). The two most powerful predictors of persistent HR-HPV infections were persistent ASCUS+Pap (risk increased), and previous Pap screening history (protective). In pair-wise comparisons, number of recent sexual partners and previous CIN history increase the probability of transient HR-HPV infection against the HR-HPV negative competing event, while previous Pap screening history is protective. Persistent ASCUS+Pap during FU and no previous Pap screening history are significantly associated with the persistent HR-HPV outcome (compared both with i) always negative, and ii) transient events), whereas multiparity is protective. Conclusions: Different covariates are associated with the three main outcomes of cervical HPV infections. The most significant covariates of each competing events are probably distinct enough to enable constructing of a risk-profile for each main outcome.
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Objective To assess several baseline risk factors that may predict patellofemoral and tibiofemoral cartilage loss during a 6-month period. Methods For 177 subjects with chronic knee pain, 3T magnetic resonance imaging (MRI) of both knees was performed at baseline and followup. Knees were semiquantitatively assessed, evaluating cartilage morphology, subchondral bone marrow lesions, meniscal morphology/extrusion, synovitis, and effusion. Age, sex, and body mass index (BMI), bone marrow lesions, meniscal damage/extrusion, synovitis, effusion, and prevalent cartilage damage in the same subregion were evaluated as possible risk factors for cartilage loss. Logistic regression models were applied to predict cartilage loss. Models were adjusted for age, sex, treatment, and BMI. Results Seventy-nine subregions (1.6%) showed incident or worsening cartilage damage at followup. None of the demographic risk factors was predictive of future cartilage loss. Predictors of patellofemoral cartilage loss were effusion, with an adjusted odds ratio (OR) of 3.5 (95% confidence interval [95% CI] 1.39.4), and prevalent cartilage damage in the same subregion with an adjusted OR of 4.3 (95% CI 1.314.1). Risk factors for tibiofemoral cartilage loss were baseline meniscal extrusion (adjusted OR 3.6 [95% CI 1.310.1]), prevalent bone marrow lesions (adjusted OR 4.7 [95% CI 1.119.5]), and prevalent cartilage damage (adjusted OR 15.3 [95% CI 4.947.4]). Conclusion Cartilage loss over 6 months is rare, but may be detected semiquantitatively by 3T MRI and is most commonly observed in knees with Kellgren/Lawrence grade 3. Predictors of patellofemoral cartilage loss were effusion and prevalent cartilage damage in the same subregion. Predictors of tibiofemoral cartilage loss were prevalent cartilage damage, bone marrow lesions, and meniscal extrusion.
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Background: Percutaneous coronary intervention (PCI) has increased as the initial revascularization strategy in chronic coronary artery disease. Consequently, more patients undergoing coronary artery bypass grafting (CABG) have history of coronary stent. Objective: Evaluate the impact of previous PCI on in-hospital mortality after CABG in patients with multivessel coronary artery disease. Methods: Between May/2007 and June/2009, 1099 consecutive patients underwent CABG on cardiopulmonary bypass. Patients with no PCI (n=938, 85.3%) were compared with patients with previous PCI (n=161, 14.6%). Logistic regression models and propensity score matching analysis were used to assess the risk-adjusted impact of previous PCI on in-hospital mortality. Results: Both groups were similar, except for the fact that patients with previous PCI were more likely to have unstable angina (16.1% x 9.9%, p=0.019). In-hospital mortality after CABG was higher in patients with previous PCI (9.3% x 5.1%, p=0.034) and it was comparable with EuroSCORE and 2000 Bernstein-Parsonnet risk score. Using multivariate logistic regression analysis, previous PCI emerged as an independent predictor of postoperative in-hospital mortality (odds ratio 1.94, 95% CI 1.02-3.68, p=0.044) as strong as diabetes (odds ratio 1.86, 95% CI 1.07-3.24, p=0.028). After computed propensity score matching based on preoperative risk factors, in-hospital mortality remained higher among patients with previous PCI (odds ratio 3.46, 95% CI 1.10-10.93, p=0.034). Conclusions: Previous PCI in patients with multivessel coronary artery disease is an independent risk factor for in-hospital mortality after CABG. This fact must be considered when PCI is indicated as initial alternative in patients with more severe coronary artery disease. (Arq Bras Cardiol 2012;99(1):586-595)
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In this paper, we proposed a new three-parameter long-term lifetime distribution induced by a latent complementary risk framework with decreasing, increasing and unimodal hazard function, the long-term complementary exponential geometric distribution. The new distribution arises from latent competing risk scenarios, where the lifetime associated scenario, with a particular risk, is not observable, rather we observe only the maximum lifetime value among all risks, and the presence of long-term survival. The properties of the proposed distribution are discussed, including its probability density function and explicit algebraic formulas for its reliability, hazard and quantile functions and order statistics. The parameter estimation is based on the usual maximum-likelihood approach. A simulation study assesses the performance of the estimation procedure. We compare the new distribution with its particular cases, as well as with the long-term Weibull distribution on three real data sets, observing its potential and competitiveness in comparison with some usual long-term lifetime distributions.
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Background: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data - particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. Methodology/Principal Findings: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (beta +/- SE) on which to base inference. Residence area (beta(Village) = 2.93 +/- 0.41; beta(Upland) = -0.56 +/- 0.33, beta(Riverbanks) = -2.37 +/- 0.55) and bednet use (beta = -0.95 +/- 0.28) were the most important factors, followed by crop-plot ownership (beta = 0.39 +/- 0.22) and regular use of a closed toilet/latrine (beta = 0.19 +/- 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. Conclusions/Significance: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.
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The extent to which the hypothalamic-pituitary-adrenal axis is activated by short-term and long-term consequences of stress is still open to investigation. This study aimed to determine (i) the correlation between plasma corticosterone and exploratory behavior exhibited by rats subjected to the elevated plus maze (EPM) following different periods of social isolation, (ii) the effects of the corticosterone synthesis blocker, metyrapone, on the behavioral consequences of isolation, and (iii) whether corticosterone produces its effects through an action on the anterior cingulate cortex, area 1 (Cg1). Rats were subjected to 30-min, 2-h, 24-h, or 7-day isolation periods before EPM exposure and plasma corticosterone assessments. Isolation for longer periods of time produced greater anxiogenic-like effects on the EPM. However, stretched attend posture (SAP) and plasma corticosterone concentrations were increased significantly after 30 min of isolation. Among all of the behavioral categories measured in the EPM, only SAP positively correlated with plasma corticosterone. Metyrapone injected prior to the 24 h isolation period reversed the anxiogenic effects of isolation. Moreover, corticosterone injected into the Cg1 produced a selective increase in SAP. These findings indicate that risk assessment behavior induced by the action of corticosterone on Cg1 neurons initiates a cascade of defensive responses during exposure to stressors.
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Congenital heart disease (CHD) occurs in similar to 1% of newborns. CHD arises from many distinct etiologies, ranging from genetic or genomic variation to exposure to teratogens, which elicit diverse cell and molecular responses during cardiac development. To systematically explore the relationships between CHD risk factors and responses, we compiled and integrated comprehensive datasets from studies of CHD in humans and model organisms. We examined two alternative models of potential functional relationships between genes in these datasets: direct convergence, in which CHD risk factors significantly and directly impact the same genes and molecules and functional convergence, in which risk factors significantly impact different molecules that participate in a discrete heart development network. We observed no evidence for direct convergence. In contrast, we show that CHD risk factors functionally converge in protein networks driving the development of specific anatomical structures (e.g., outflow tract, ventricular septum, and atrial septum) that are malformed by CHD. This integrative analysis of CHD risk factors and responses suggests a complex pattern of functional interactions between genomic variation and environmental exposures that modulate critical biological systems during heart development.
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OBJECTIVE: To analyze the nutritional status of pediatric patients after orthotopic liver transplantation and the relationship with short-term clinical outcome. METHOD: Anthropometric evaluations of 60 children and adolescents after orthotopic liver transplantation, during the first 24 hours in a tertiary pediatric intensive care unit. Nutritional status was determined from the Z score for the following indices: weight/age, height/age or length/age, weight/height or weight/length, body mass index/age, arm circumference/age and triceps skinfold/age. The severity of liver disease was evaluated using one of the two models which was adequated to the patients' age: 1. Pediatric End-stage Liver Disease, 2. Model for End-Stage Liver Disease. RESULTS: We found 50.0% undernutrition by height/age; 27.3% by weight/age; 11.1% by weight/height or weight/length; 10.0% by body mass index/age; 61.6% by arm circumference/age and 51.0% by triceps skinfold/age. There was no correlation between nutritional status and Pediatric End-stage Liver Disease or mortality. We found a negative correlation between arm circumference/age and length of hospitalization. CONCLUSION: Children with chronic liver diseases experience a significant degree of undernutrition, which makes nutritional support an important aspect of therapy. Despite the difficulties in assessment, anthropometric evaluation of the upper limbs is useful to evaluate nutritional status of children before or after liver transplantation.
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Background. Lung transplantation has become a standard procedure for some end-stage lung diseases, but primary graft dysfunction (PGD) is an inherent problem that impacts early and late outcomes. The aim of this study was to define the incidence, risk factors, and impact of mechanical ventilation time on mortality rates among a retrospective cohort of lung transplantations performed in a single institution. Methods. We performed a retrospective study of 118 lung transplantations performed between January 2003 and July 2010. The most severe form of PGD (grade III) as defined at 48 and 72 hours was examined for risk factors by multivariable logistic regression models using donor, recipient, and transplant variables. Results. The overall incidence of PGD at 48 hours was 19.8%, and 15.4% at 72 hours. According multivariate analysis, risk factors associated with PGD were donor smoking history for 48 hours (adjusted odds ratio [OR], 4.83; 95% confidence interval [CI], 1.236-18.896; P = .022) and older donors for 72 hours (adjusted OR, 1.046; 95% CI, 0.997-1.098; P = .022). The operative mortality was 52.9% among patients with PGD versus 20.3% at 48 hours (P = .012). At 72 hours, the mortality rate was 58.3% versus 21.2% (P = .013). The 90-days mortality was also higher among patients with PGD. The mechanical ventilation time was longer in patients with PGD III at 48 hours namely, a mean time of 72 versus 24 hours (P = .001). When PGD was defined at 72 hours, the mean ventilation time was even longer, namely 151 versus 24 hours (P < .001). The mean overall survival for patients who developed PGD at 48 hours was 490.9 versus 1665.5 days for subjects without PGD (P = .001). Considering PGD only at 72 hours, the mean survival was 177.7 days for the PGD group and 1628.9 days for the other patients (P < .001). Conclusion. PGD showed an important impacts on operative and 90-day mortality rates, mechanical ventilation time, and overall survival among lung transplant patients. PGD at 72 hours was a better predictor of lung transplant outcomes than at 48 hours. The use of donors with a smoking history or of advanced age were risk factors for the development of PGD.
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Native bees are important providers of pollination services, but there are cumulative evidences of their decline. Global changes such as habitat losses, invasions of exotic species and climate change have been suggested as the main causes of the decline of pollinators. In this study, the influence of climate change on the distribution of 10 species of Brazilian bees was estimated with species distribution modelling. We used Maxent algorithm (maximum entropy) and two different scenarios, an optimistic and a pessimistic, to the years 2050 and 2080. We also evaluated the percentage reduction of species habitat based on the future scenarios of climate change through Geographic Information System (GIS). Results showed that the total area of suitable habitats decreased for all species but one under the different future scenarios. The greatest reductions in habitat area were found for Melipona bicolor bicolor and Melipona scutellaris, which occur predominantly in areas related originally to Atlantic Moist Forest. The species analysed have been reported to be pollinators of some regional crops and the consequence of their decrease for these crops needs further clarification. (C) 2012 Elsevier B.V. All rights reserved.
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Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.