955 resultados para Multivariate risk model
Resumo:
PURPOSE: To derive a prediction rule by using prospectively obtained clinical and bone ultrasonographic (US) data to identify elderly women at risk for osteoporotic fractures. MATERIALS AND METHODS: The study was approved by the Swiss Ethics Committee. A prediction rule was computed by using data from a 3-year prospective multicenter study to assess the predictive value of heel-bone quantitative US in 6174 Swiss women aged 70-85 years. A quantitative US device to calculate the stiffness index at the heel was used. Baseline characteristics, known risk factors for osteoporosis and fall, and the quantitative US stiffness index were used to elaborate a predictive rule for osteoporotic fracture. Predictive values were determined by using a univariate Cox model and were adjusted with multivariate analysis. RESULTS: There were five risk factors for the incidence of osteoporotic fracture: older age (>75 years) (P < .001), low heel quantitative US stiffness index (<78%) (P < .001), history of fracture (P = .001), recent fall (P = .001), and a failed chair test (P = .029). The score points assigned to these risk factors were as follows: age, 2 (3 if age > 80 years); low quantitative US stiffness index, 5 (7.5 if stiffness index < 60%); history of fracture, 1; recent fall, 1.5; and failed chair test, 1. The cutoff value to obtain a high sensitivity (90%) was 4.5. With this cutoff, 1464 women were at lower risk (score, <4.5) and 4710 were at higher risk (score, >or=4.5) for fracture. Among the higher-risk women, 6.1% had an osteoporotic fracture, versus 1.8% of women at lower risk. Among the women who had a hip fracture, 90% were in the higher-risk group. CONCLUSION: A prediction rule obtained by using quantitative US stiffness index and four clinical risk factors helped discriminate, with high sensitivity, women at higher versus those at lower risk for osteoporotic fracture.
Resumo:
We hypothesized that combining clinical risk factors (CRF) with the heel stiffness index (SI) measured via quantitative ultrasound (QUS) would improve the detection of women both at low and high risk for hip fracture. Categorizing women by risk score improved the specificity of detection to 42.4%, versus 33.8% using CRF alone and 38.4% using the SI alone. This combined CRF-SI score could be used wherever and whenever DXA is not readily accessible. INTRODUCTION AND HYPOTHESIS: Several strategies have been proposed to identify women at high risk for osteoporosis-related fractures; we wanted to investigate whether combining clinical risk factors (CRF) and heel QUS parameters could provide a more accurate tool to identify women at both low and high risk for hip fracture than either CRF or QUS alone. METHODS: We pooled two Caucasian cohorts, EPIDOS and SEMOF, into a large database named "EPISEM", in which 12,064 women, 70 to 100 years old, were analyzed. Amongst all the CRF available in EPISEM, we used only the ones which were statistically significant in a Cox multivariate model. Then, we constructed a risk score, by combining the QUS-derived heel stiffness index (SI) and the following seven CRF: patient age, body mass index (BMI), fracture history, fall history, diabetes history, chair-test results, and past estrogen treatment. RESULTS: Using the composite SI-CRF score, 42% of the women who did not report a hip fracture were found to be at low risk at baseline, and 57% of those who subsequently sustained a fracture were at high risk. Using the SI alone, corresponding percentages were 38% and 52%; using CRF alone, 34% and 53%. The number of subjects in the intermediate group was reduced from 5,400 (including 112 hip fractures) and 5,032 (including 111 hip fractures) to 4,549 (including 100 including fractures) for the CRF and QUS alone versus the combination score. CONCLUSIONS: Combining clinical risk factors to heel bone ultrasound appears to correctly identify more women at low risk for hip fracture than either the stiffness index or the CRF alone; it improves the detection of women both at low and high risk.
Resumo:
AIM: Genetic polymorphisms of the human angiotensinogen gene are frequent and may induce up to 30% increase of plasma angiotensinogen concentrations with a blood pressure increase of up to 5mmHg. Their role for the pathogenesis of human arterial hypertension remains unclear. High plasma angiotensinogen levels could increase the sensitivity to other blood pressure stressors. METHODS: Male transgenic rats with a 9-fold increase of plasma angiotensinogen concentrations and male non-transgenic rats aged 10 weeks were treated or not with NG-Nitro-L-arginine-methyl ester for 3 weeks in their drinking water (n=3/group). Systolic blood pressure and body weight were measured at baseline and at the end of the study when left ventricular weight and ventricular expression of angiotensin I-converting enzyme and procollagen Iα1 were determined (polymerase chain reaction). RESULTS: At baseline, transgenic rats had +18mmHg higher bood pressure and -8% lower body weight compared to non-transgenic rats (P<0.05) without significant changes for the vehicle groups throughout the study (P>0.05). NG-Nitro-L-arginine-methyl ester increased blood pressure, left ventricular weight and left ventricular weight indexed for body weight by +41%, +17.6% and +18.6% (P<0.05) in transgenic and +25%, +5.3% and +6.7% (P>0.05) in non-transgenic rats compared to untreated animals, respectively. Cardiac gene expression showed no differences between groups (P>0.05). CONCLUSION: Increased plasma angiotensinogen levels may sensitize to additional blood pressure stressors. Our preliminary results point towards an independent role of angiotensinogen in the pathogenesis of human hypertension and associated end-organ damage.
Resumo:
Using a large prospective cohort of over 12,000 women, we determined 2 thresholds (high risk and low risk of hip fracture) to use in a 10-yr hip fracture probability model that we had previously described, a model combining the heel stiffness index measured by quantitative ultrasound (QUS) and a set of easily determined clinical risk factors (CRFs). The model identified a higher percentage of women with fractures as high risk than a previously reported risk score that combined QUS and CRF. In addition, it categorized women in a way that was quite consistent with the categorization that occurred using dual X-ray absorptiometry (DXA) and the World Health Organization (WHO) classification system; the 2 methods identified similar percentages of women with and without fractures in each of their 3 categories, but the 2 identified only in part the same women. Nevertheless, combining our composite probability model with DXA in a case findings strategy will likely further improve the detection of women at high risk of fragility hip fracture. We conclude that the currently proposed model may be of some use as an alternative to the WHO classification criteria for osteoporosis, at least when access to DXA is limited.
Resumo:
BACKGROUND: Workers with persistent disabilities after orthopaedic trauma may need occupational rehabilitation. Despite various risk profiles for non-return-to-work (non-RTW), there is no available predictive model. Moreover, injured workers may have various origins (immigrant workers), which may either affect their return to work or their eligibility for research purposes. The aim of this study was to develop and validate a predictive model that estimates the likelihood of non-RTW after occupational rehabilitation using predictors which do not rely on the worker's background. METHODS: Prospective cohort study (3177 participants, native (51%) and immigrant workers (49%)) with two samples: a) Development sample with patients from 2004 to 2007 with Full and Reduced Models, b) External validation of the Reduced Model with patients from 2008 to March 2010. We collected patients' data and biopsychosocial complexity with an observer rated interview (INTERMED). Non-RTW was assessed two years after discharge from the rehabilitation. Discrimination was assessed by the area under the receiver operating curve (AUC) and calibration was evaluated with a calibration plot. The model was reduced with random forests. RESULTS: At 2 years, the non-RTW status was known for 2462 patients (77.5% of the total sample). The prevalence of non-RTW was 50%. The full model (36 items) and the reduced model (19 items) had acceptable discrimination performance (AUC 0.75, 95% CI 0.72 to 0.78 and 0.74, 95% CI 0.71 to 0.76, respectively) and good calibration. For the validation model, the discrimination performance was acceptable (AUC 0.73; 95% CI 0.70 to 0.77) and calibration was also adequate. CONCLUSIONS: Non-RTW may be predicted with a simple model constructed with variables independent of the patient's education and language fluency. This model is useful for all kinds of trauma in order to adjust for case mix and it is applicable to vulnerable populations like immigrant workers.
Resumo:
This study aimed to develop a hip screening tool that combines relevant clinical risk factors (CRFs) and quantitative ultrasound (QUS) at the heel to determine the 10-yr probability of hip fractures in elderly women. The EPISEM database, comprised of approximately 13,000 women 70 yr of age, was derived from two population-based white European cohorts in France and Switzerland. All women had baseline data on CRFs and a baseline measurement of the stiffness index (SI) derived from QUS at the heel. Women were followed prospectively to identify incident fractures. Multivariate analysis was performed to determine the CRFs that contributed significantly to hip fracture risk, and these were used to generate a CRF score. Gradients of risk (GR; RR/SD change) and areas under receiver operating characteristic curves (AUC) were calculated for the CRF score, SI, and a score combining both. The 10-yr probability of hip fracture was computed for the combined model. Three hundred seven hip fractures were observed over a mean follow-up of 3.2 yr. In addition to SI, significant CRFs for hip fracture were body mass index (BMI), history of fracture, an impaired chair test, history of a recent fall, current cigarette smoking, and diabetes mellitus. The average GR for hip fracture was 2.10 per SD with the combined SI + CRF score compared with a GR of 1.77 with SI alone and of 1.52 with the CRF score alone. Thus, the use of CRFs enhanced the predictive value of SI alone. For example, in a woman 80 yr of age, the presence of two to four CRFs increased the probability of hip fracture from 16.9% to 26.6% and from 52.6% to 70.5% for SI Z-scores of +2 and -3, respectively. The combined use of CRFs and QUS SI is a promising tool to assess hip fracture probability in elderly women, especially when access to DXA is limited.
Resumo:
ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.
Resumo:
BACKGROUND: Due to the underlying diseases and the need for immunosuppression, patients after lung transplantation are particularly at risk for gastrointestinal (GI) complications that may negatively influence long-term outcome. The present study assessed the incidences and impact of GI complications after lung transplantation and aimed to identify risk factors. METHODS: Retrospective analysis of all 227 consecutively performed single- and double-lung transplantations at the University hospitals of Lausanne and Geneva was performed between January 1993 and December 2010. Logistic regressions were used to test the effect of potentially influencing variables on the binary outcomes overall, severe, and surgery-requiring complications, followed by a multiple logistic regression model. RESULTS: Final analysis included 205 patients for the purpose of the present study, and 22 patients were excluded due to re-transplantation, multiorgan transplantation, or incomplete datasets. GI complications were observed in 127 patients (62 %). Gastro-esophageal reflux disease was the most commonly observed complication (22.9 %), followed by inflammatory or infectious colitis (20.5 %) and gastroparesis (10.7 %). Major GI complications (Dindo/Clavien III-V) were observed in 83 (40.5 %) patients and were fatal in 4 patients (2.0 %). Multivariate analysis identified double-lung transplantation (p = 0.012) and early (1993-1998) transplantation period (p = 0.008) as independent risk factors for developing major GI complications. Forty-three (21 %) patients required surgery such as colectomy, cholecystectomy, and fundoplication in 6.8, 6.3, and 3.9 % of the patients, respectively. Multivariate analysis identified Charlson comorbidity index of ≥3 as an independent risk factor for developing GI complications requiring surgery (p = 0.015). CONCLUSION: GI complications after lung transplantation are common. Outcome was rather encouraging in the setting of our transplant center.
Resumo:
OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.
Resumo:
Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.
Resumo:
Fusarium Head Blight (FHB) is a disease of great concern in wheat (Triticum aestivum). Due to its relatively narrow susceptible phase and environmental dependence, the pathosystem is suitable for modeling. In the present work, a mechanistic model for estimating an infection index of FHB was developed. The model is process-based driven by rates, rules and coefficients for estimating the dynamics of flowering, airborne inoculum density and infection frequency. The latter is a function of temperature during an infection event (IE), which is defined based on a combination of daily records of precipitation and mean relative humidity. The daily infection index is the product of the daily proportion of susceptible tissue available, infection frequency and spore cloud density. The model was evaluated with an independent dataset of epidemics recorded in experimental plots (five years and three planting dates) at Passo Fundo, Brazil. Four models that use different factors were tested, and results showed all were able to explain variation for disease incidence and severity. A model that uses a correction factor for extending host susceptibility and daily spore cloud density to account for post-flowering infections was the most accurate explaining 93% of the variation in disease severity and 69% of disease incidence according to regression analysis.
Resumo:
The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.
Resumo:
Few data are available on the prevalence and risk factors of Chlamydophila abortus infection in goats in Brazil. A cross-sectional study was carried out to determine the flock-level prevalence of C. abortus infection in goats from the semiarid region of the Paraíba State, Northeast region of Brazil, as well as to identify risk factors associated with the infection. Flocks were randomly selected and a pre-established number of female goats > 12 mo old were sampled in each of these flocks. A total of 975 serum samples from 110 flocks were collected, and structured questionnaire focusing on risk factors for C. abortus infection was given to each farmer at the time of blood collection. For the serological diagnosis the complement fixation test (CFT) using C. abortus S26/3 strain as antigen was performed. The flock-level factors for C. abortus prevalence were tested using multivariate logistic regression model. Fifty-five flocks out of 110 presented at least one seropositive animal with an overall prevalence of 50.0% (95%; CI: 40.3%, 59.7%). Ninety-one out of 975 dairy goats examined were seropositive with titers >32, resulting in a frequency of 9.3%. Lend buck for breeding (odds ratio = 2.35; 95% CI: 1.04-5.33) and history of abortions (odds ratio = 3.06; 95% CI: 1.37-6.80) were associated with increased flock prevalence.
Resumo:
This thesis was carried out as a case study of a company YIT in order to clarify the sev-erest risks for the company and to build a method for project portfolio evaluation. The target organization creates new living environment by constructing residential buildings, business premises, infrastructure and entire areas worth for EUR 1.9 billion in the year 2013. Company has noted project portfolio management needs more information about the structure of project portfolio and possible influences of market shock situation. With interviews have been evaluated risks with biggest influence and most appropriate metrics to examine. The major risks for the company were evaluated by interviewing the executive staff. At the same time, the most appropriate risk metrics were considered. At the moment sales risk was estimated to have biggest impact on company‟s business. Therefore project port-folio evaluation model was created and three different scenarios for company‟s future were created in order to identify the scale of possible market shock situation. The created model is tested with public and descriptive figures of YIT in a one-year-long market shock and the impact on different metrics was evaluated. Study was conducted using con-structive research methodology. Results indicate that company has notable sales risk in certain sections of business portfolio.