11 resultados para credit risk model.

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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BACKGROUND: Many HIV-infected patients on highly active antiretroviral therapy (HAART) experience metabolic complications including dyslipidaemia and insulin resistance, which may increase their coronary heart disease (CHD) risk. We developed a prognostic model for CHD tailored to the changes in risk factors observed in patients starting HAART. METHODS: Data from five cohort studies (British Regional Heart Study, Caerphilly and Speedwell Studies, Framingham Offspring Study, Whitehall II) on 13,100 men aged 40-70 and 114,443 years of follow up were used. CHD was defined as myocardial infarction or death from CHD. Model fit was assessed using the Akaike Information Criterion; generalizability across cohorts was examined using internal-external cross-validation. RESULTS: A parametric model based on the Gompertz distribution generalized best. Variables included in the model were systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, triglyceride, glucose, diabetes mellitus, body mass index and smoking status. Compared with patients not on HAART, the estimated CHD hazard ratio (HR) for patients on HAART was 1.46 (95% CI 1.15-1.86) for moderate and 2.48 (95% CI 1.76-3.51) for severe metabolic complications. CONCLUSIONS: The change in the risk of CHD in HIV-infected men starting HAART can be estimated based on typical changes in risk factors, assuming that HRs estimated using data from non-infected men are applicable to HIV-infected men. Based on this model the risk of CHD is likely to increase, but increases may often be modest, and could be offset by lifestyle changes.

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The highly pathogenic avian influenza (HPAI) H5N1 virus that emerged in southern China in the mid-1990s has in recent years evolved into the first HPAI panzootic. In many countries where the virus was detected, the virus was successfully controlled, whereas other countries face periodic reoccurrence despite significant control efforts. A central question is to understand the factors favoring the continuing reoccurrence of the virus. The abundance of domestic ducks, in particular free-grazing ducks feeding in intensive rice cropping areas, has been identified as one such risk factor based on separate studies carried out in Thailand and Vietnam. In addition, recent extensive progress was made in the spatial prediction of rice cropping intensity obtained through satellite imagery processing. This article analyses the statistical association between the recorded HPAI H5N1 virus presence and a set of five key environmental variables comprising elevation, human population, chicken numbers, duck numbers, and rice cropping intensity for three synchronous epidemic waves in Thailand and Vietnam. A consistent pattern emerges suggesting risk to be associated with duck abundance, human population, and rice cropping intensity in contrast to a relatively low association with chicken numbers. A statistical risk model based on the second epidemic wave data in Thailand is found to maintain its predictive power when extrapolated to Vietnam, which supports its application to other countries with similar agro-ecological conditions such as Laos or Cambodia. The model’s potential application to mapping HPAI H5N1 disease risk in Indonesia is discussed.

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OBJECTIVE The aim of this study was to assess the association between frailty and risk for heart failure (HF) in older adults. BACKGROUND Frailty is common in the elderly and is associated with adverse health outcomes. Impact of frailty on HF risk is not known. METHODS We assessed the association between frailty, using the Health ABC Short Physical Performance Battery (HABC Battery) and the Gill index, and incident HF in 2825 participants aged 70 to 79 years. RESULTS Mean age of participants was 74 ± 3 years; 48% were men and 59% were white. During a median follow up of 11.4 (7.1-11.7) years, 466 participants developed HF. Compared to non-frail participants, moderate (HR 1.36, 95% CI 1.08-1.71) and severe frailty (HR 1.88, 95% CI 1.02-3.47) by Gill index was associated with a higher risk for HF. HABC Battery score was linearly associated with HF risk after adjusting for the Health ABC HF Model (HR 1.24, 95% CI 1.13-1.36 per SD decrease in score) and remained significant when controlled for death as a competing risk (HR 1.30; 95% CI 1.00-1.55). Results were comparable across age, sex, and race, and in sub-groups based on diabetes mellitus or cardiovascular disease at baseline. Addition of HABC Battery scores to the Health ABC HF Risk Model improved discrimination (change in C-index, 0.014; 95% CI 0.018-0.010) and appropriately reclassified 13.4% (net-reclassification-improvement 0.073, 95% CI 0.021-0.125; P = .006) of participants (8.3% who developed HF and 5.1% who did not). CONCLUSIONS Frailty is independently associated with risk of HF in older adults.

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BACKGROUND Conventional factors do not fully explain the distribution of cardiovascular outcomes. Biomarkers are known to participate in well-established pathways associated with cardiovascular disease, and may therefore provide further information over and above conventional risk factors. This study sought to determine whether individual and/or combined assessment of 9 biomarkers improved discrimination, calibration and reclassification of cardiovascular mortality. METHODS 3267 patients (2283 men), aged 18-95 years, at intermediate-to-high-risk of cardiovascular disease were followed in this prospective cohort study. Conventional risk factors and biomarkers were included based on forward and backward Cox proportional stepwise selection models. RESULTS During 10-years of follow-up, 546 fatal cardiovascular events occurred. Four biomarkers (interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D) were retained during stepwise selection procedures for subsequent analyses. Simultaneous inclusion of these biomarkers significantly improved discrimination as measured by the C-index (0.78, P = 0.0001), and integrated discrimination improvement (0.0219, P<0.0001). Collectively, these biomarkers improved net reclassification for cardiovascular death by 10.6% (P<0.0001) when added to the conventional risk model. CONCLUSIONS In terms of adverse cardiovascular prognosis, a biomarker panel consisting of interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D offered significant incremental value beyond that conveyed by simple conventional risk factors.

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Background During the Soviet era, malaria was close to eradication in Tajikistan. Since the early 1990s, the disease has been on the rise and has become endemic in large areas of southern and western Tajikistan. The standard national treatment for Plasmodium vivax is based on primaquine. This entails the risk of severe haemolysis for patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency. Seasonal and geographical distribution patterns as well as G6PD deficiency frequency were analysed with a view to improve understanding of the current malaria situation in Tajikistan. Methods Spatial and seasonal distribution was analysed, applying a risk model that included key environmental factors such as temperature and the availability of mosquito breeding sites. The frequency of G6PD deficiency was studied at the health service level, including a cross-sectional sample of 382 adult men. Results Analysis revealed high rates of malaria transmission in most districts of the southern province of Khatlon, as well as in some zones in the northern province of Sughd. Three categories of risk areas were identified: (i) zones at relatively high malaria risk with high current incidence rates, where malaria control and prevention measures should be taken at all stages of the transmission cycle; (ii) zones at relatively high malaria risk with low current incidence rates, where malaria prevention measures are recommended; and (iii) zones at intermediate or low malaria risk with low current incidence rates where no particular measures appear necessary. The average prevalence of G6PD deficiency was 2.1% with apparent differences between ethnic groups and geographical regions. Conclusion The study clearly indicates that malaria is a serious health issue in specific regions of Tajikistan. Transmission is mainly determined by temperature. Consequently, locations at lower altitude are more malaria-prone. G6PD deficiency frequency is too moderate to require fundamental changes in standard national treatment of cases of P. vivax.

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Despite the fact that bone mineral density (BMD) is an important fracture risk predictor in human medicine, studies in equine orthopedic research are still lacking. We hypothesized that BMD correlates with bone failure and fatigue fractures of this bone. Thus, the objectives of this study were to measure the structural and mechanical properties of the proximal phalanx with dual energy X-ray absorptiometry (DXA), to correlate the data obtained from DXA and computer tomography (CT) measurements to those obtained by loading pressure examination and to establish representative region of interest (ROI) for in vitro BMD measurements of the equine proximal phalanx for predicting bone failure force. DXA was used to measure the whole bone BMD and additional three ROI sites in 14 equine proximal phalanges. Following evaluation of the bone density, whole bone, cortical width and area in the mid-diaphyseal plane were measured on CT images. Bones were broken using a manually controlled universal bone crusher to measure bone failure force and reevaluated for the site of fractures on follow-up CT images. Compressive load was applied at a constant displacement rate of 2 mm/min until failure, defined as the first clear drop in the load measurement. The lowest BMD was measured at the trabecular region (mean +/- SD: 1.52 +/- 0.12 g/cm2; median: 1.48 g/cm2; range: 1.38-1.83 g/cm2). There was a significant positive linear correlation between trabelcular BMD and the breaking strength (P = 0.023, r = 0.62). The trabecular region of the proximal phalanx appears to be the only significant indicator of failure of strength in vitro. This finding should be reassessed to further reveal the prognostic value of trabecular BMD in an in vivo fracture risk model.

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Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical aortic valve replacement (SAVR) for patients with symptomatic severe aortic stenosis (AS) and a high operative risk. Risk stratification plays a decisive role in the optimal selection of therapeutic strategies for AS patients. The accuracy of contemporary surgical risk algorithms for AS patients has spurred considerable debate especially in the higher risk patient population. Future trials will explore TAVI in patients at intermediate operative risk. During the design of the SURgical replacement and Transcatheter Aortic Valve Implantation (SURTAVI) trial, a novel concept of risk stratification was proposed based upon age in combination with a fixed number of predefined risk factors, which are relatively prevalent, easy to capture and with a reasonable impact on operative mortality. Retrospective application of this algorithm to a contemporary academic practice dealing with clinically significant AS patients allocates about one-fourth of these patients as being at intermediate operative risk. Further testing is required for validation of this new paradigm in risk stratification. Finally, the Heart Team, consisting of at least an interventional cardiologist and cardiothoracic surgeon, should have the decisive role in determining whether a patient could be treated with TAVI or SAVR.

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PURPOSE Rapid assessment and intervention is important for the prognosis of acutely ill patients admitted to the emergency department (ED). The aim of this study was to prospectively develop and validate a model predicting the risk of in-hospital death based on all available information available at the time of ED admission and to compare its discriminative performance with a non-systematic risk estimate by the triaging first health-care provider. METHODS Prospective cohort analysis based on a multivariable logistic regression for the probability of death. RESULTS A total of 8,607 consecutive admissions of 7,680 patients admitted to the ED of a tertiary care hospital were analysed. Most frequent APACHE II diagnostic categories at the time of admission were neurological (2,052, 24 %), trauma (1,522, 18 %), infection categories [1,328, 15 %; including sepsis (357, 4.1 %), severe sepsis (249, 2.9 %), septic shock (27, 0.3 %)], cardiovascular (1,022, 12 %), gastrointestinal (848, 10 %) and respiratory (449, 5 %). The predictors of the final model were age, prolonged capillary refill time, blood pressure, mechanical ventilation, oxygen saturation index, Glasgow coma score and APACHE II diagnostic category. The model showed good discriminative ability, with an area under the receiver operating characteristic curve of 0.92 and good internal validity. The model performed significantly better than non-systematic triaging of the patient. CONCLUSIONS The use of the prediction model can facilitate the identification of ED patients with higher mortality risk. The model performs better than a non-systematic assessment and may facilitate more rapid identification and commencement of treatment of patients at risk of an unfavourable outcome.

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We developed a model to calculate a quantitative risk score for individual aquaculture sites. The score indicates the risk of the site being infected with a specific fish pathogen (viral haemorrhagic septicaemia virus (VHSV); infectious haematopoietic necrosis virus, Koi herpes virus), and is intended to be used for risk ranking sites to support surveillance for demonstration of zone or member state freedom from these pathogens. The inputs to the model include a range of quantitative and qualitative estimates of risk factors organised into five risk themes (1) Live fish and egg movements; (2) Exposure via water; (3) On-site processing; (4) Short-distance mechanical transmission; (5) Distance-independent mechanical transmission. The calculated risk score for an individual aquaculture site is a value between zero and one and is intended to indicate the risk of a site relative to the risk of other sites (thereby allowing ranking). The model was applied to evaluate 76 rainbow trout farms in 3 countries (42 from England, 32 from Italy and 2 from Switzerland) with the aim to establish their risk of being infected with VHSV. Risk scores for farms in England and Italy showed great variation, clearly enabling ranking. Scores ranged from 0.002 to 0.254 (mean score 0.080) in England and 0.011 to 0.778 (mean of 0.130) for Italy, reflecting the diversity of infection status of farms in these countries. Requirements for broader application of the model are discussed. Cost efficient farm data collection is important to realise the benefits from a risk-based approach.

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BACKGROUND Predicting long-term survival after admission to hospital is helpful for clinical, administrative and research purposes. The Hospital-patient One-year Mortality Risk (HOMR) model was derived and internally validated to predict the risk of death within 1 year after admission. We conducted an external validation of the model in a large multicentre study. METHODS We used administrative data for all nonpsychiatric admissions of adult patients to hospitals in the provinces of Ontario (2003-2010) and Alberta (2011-2012), and to the Brigham and Women's Hospital in Boston (2010-2012) to calculate each patient's HOMR score at admission. The HOMR score is based on a set of parameters that captures patient demographics, health burden and severity of acute illness. We determined patient status (alive or dead) 1 year after admission using population-based registries. RESULTS The 3 validation cohorts (n = 2,862,996 in Ontario, 210 595 in Alberta and 66,683 in Boston) were distinct from each other and from the derivation cohort. The overall risk of death within 1 year after admission was 8.7% (95% confidence interval [CI] 8.7% to 8.8%). The HOMR score was strongly and significantly associated with risk of death in all populations and was highly discriminative, with a C statistic ranging from 0.89 (95% CI 0.87 to 0.91) to 0.92 (95% CI 0.91 to 0.92). Observed and expected outcome risks were similar (median absolute difference in percent dying in 1 yr 0.3%, interquartile range 0.05%-2.5%). INTERPRETATION The HOMR score, calculated using routinely collected administrative data, accurately predicted the risk of death among adult patients within 1 year after admission to hospital for nonpsychiatric indications. Similar performance was seen when the score was used in geographically and temporally diverse populations. The HOMR model can be used for risk adjustment in analyses of health administrative data to predict long-term survival among hospital patients.