167 resultados para structured prediction


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BACKGROUND: A simple prognostic model could help identify patients with pulmonary embolism who are at low risk of death and are candidates for outpatient treatment. METHODS: We randomly allocated 15,531 retrospectively identified inpatients who had a discharge diagnosis of pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our rule to predict 30-day mortality using classification tree analysis and patient data routinely available at initial examination as potential predictor variables. We used data from a European prospective study to externally validate the rule among 221 inpatients with pulmonary embolism. We determined mortality and nonfatal adverse medical outcomes across derivation and validation samples. RESULTS: Our final model consisted of 10 patient factors (age > or = 70 years; history of cancer, heart failure, chronic lung disease, chronic renal disease, and cerebrovascular disease; and clinical variables of pulse rate > or = 110 beats/min, systolic blood pressure < 100 mm Hg, altered mental status, and arterial oxygen saturation < 90%). Patients with none of these factors were defined as low risk. The 30-day mortality rates for low-risk patients were 0.6%, 1.5%, and 0% in the derivation, internal validation, and external validation samples, respectively. The rates of nonfatal adverse medical outcomes were less than 1% among low-risk patients across all study samples. CONCLUSIONS: This simple prediction rule accurately identifies patients with pulmonary embolism who are at low risk of short-term mortality and other adverse medical outcomes. Prospective validation of this rule is important before its implementation as a decision aid for outpatient treatment.

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BACKGROUND: Recanalization in acute ischemic stroke with large-vessel occlusion is a potent indicator of good clinical outcome. OBJECTIVE: To identify easily available clinical and radiologic variables predicting recanalization at various occlusion sites. METHODS: All consecutive, acute stroke patients from the Acute STroke Registry and Analysis of Lausanne (2003-2011) who had a large-vessel occlusion on computed tomographic angiography (CTA) (< 12 h) were included. Recanalization status was assessed at 24 h (range: 12-48 h) with CTA, magnetic resonance angiography, or ultrasonography. Complete and partial recanalization (corresponding to the modified Treatment in Cerebral Ischemia scale 2-3) were grouped together. Patients were categorized according to occlusion site and treatment modality. RESULTS: Among 439 patients, 51% (224) showed complete or partial recanalization. In multivariate analysis, recanalization of any occlusion site was most strongly associated with endovascular treatment, including bridging therapy (odds ratio [OR] 7.1, 95% confidence interval [CI] 2.2-23.2), and less so with intravenous thrombolysis (OR 1.6, 95% CI 1.0-2.6) and recanalization treatments performed beyond guidelines (OR 2.6, 95% CI 1.2-5.7). Clot location (large vs. intermediate) and tandem pathology (the combination of intracranial occlusion and symptomatic extracranial stenosis) were other variables discriminating between recanalizers and non-recanalizers. For patients with intracranial occlusions, the variables significantly associated with recanalization after 24 h were: baseline National Institutes of Health Stroke Scale (NIHSS) (OR 1.04, 95% CI 1.02-1.1), Alberta Stroke Program Early CT Score (ASPECTS) on initial computed tomography (OR 1.2, 95% CI 1.1-1.3), and an altered level of consciousness (OR 0.2, 95% CI 0.1-0.5). CONCLUSIONS: Acute endovascular treatment is the single most important factor promoting recanalization in acute ischemic stroke. The presence of extracranial vessel stenosis or occlusion decreases recanalization rates. In patients with intracranial occlusions, higher NIHSS score and ASPECTS and normal vigilance facilitate recanalization. Clinical use of these predictors could influence recanalization strategies in individual patients.

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Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

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Background: Several markers of atherosclerosis and of inflammation have been shown to predict coronary heart disease (CHD) individually. However, the utility of markers of atherosclerosis and of inflammation on prediction of CHD over traditional risk factors has not been well established, especially in the elderly. Methods: We studied 2202 men and women, aged 70-79, without baseline cardiovascular disease over 6-year follow-up to assess the risk of incident CHD associated with baseline noninvasive measures of atherosclerosis (ankle-arm index [AAI], aortic pulse wave velocity [aPWV]) and inflammatory markers (interleukin-6 [IL-6], C-reactive protein [CRP], tumor necrosis factor-a [TNF-a]). CHD events were studied as either nonfatal myocardial infarction or coronary death ("hard" events), and "hard" events plus hospitalization for angina, or the need for coronary-revascularization procedures (total CHD events). Results: During the 6-year follow-up, 283 participants had CHD events (including 136 "hard" events). IL-6, TNF-a and AAI independently predicted CHD events above Framingham Risk Score (FRS) with hazard ratios [HR] for the highest as compared with the lowest quartile for IL-6 of 1.95 (95%CI: 1.38-2.75, p for trend <0.001), TNF-a of 1.45 (95%CI: 1.04-2.02, p for trend 0.03), of 1.66 (95%CI: 1.19-2.31) for AAI 0.9, as compared to AAI 1.01-1.30. CRP and aPWV were not independently associated with CHD events. Results were similar for "hard" CHD events. Addition of IL-6 and AAI to traditional cardiovascular risk factors yielded the greatest improvement in the prediction of CHD; C-index for "hard"/total CHD events increased from 0.62/0.62 for traditional risk factors to 0.64/0.64 for IL-6 addition, 0.65/0.63 for AAI, and 0.66/0.64 for IL-6 combined with AAI. Being in the highest quartile of IL-6 combined with an AAI 0.90 or >1.40 yielded an HR of 2.51 (1.50-4.19) and 4.55 (1.65-12.50) above FRS, respectively. With use of CHD risk categories, risk prediction at 5 years was more accurate in models that included IL-6, AAI or both, with 8.0, 8.3 and 12.1% correctly reclassified, respectively. Conclusions: Among older adults, markers of atherosclerosis and of inflammation, particularly IL-6 and AAI, are independently associated with CHD. However, these markers only modestly improve cardiovascular risk prediction beyond traditional risk factors.

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OBJECTIVES: After structured treatment interruption (STI) of treatment for HIV-1, a fraction of patients maintain suppressed viral loads. Prospective identification of such patients might improve HIV-1 treatment, if selected patients are offered STI. METHODS: We analysed the effect of previously identified genetic modulators of HIV-1 disease progression on patients' ability to suppress viral replication after STI. Polymorphisms in the genes killer cell immunoglobulin-like receptor 3DLI (KIR3DL1)/KIR3DS1, human leucocyte antigen B (HLA-B) and HLA Complex P5 (HCP5), and a polymorphism affecting HLA-C surface expression were analysed in 130 Swiss HIV Cohort Study patients undergoing STI. Genotypes were correlated with viral load levels after STI. RESULTS: We observed a statistically significant reduction in viral load after STI in carriers of HLA-B alleles containing either the Bw480Thr or the Bw480Ile epitope (mean adjusted effect on post-STI viral load: -0.82 log HIV-1 RNA copies/ml, P < 0.001; and -1.12 log copies/ml, P < 0.001, respectively). No significant effects were detected for the other polymorphisms analysed. The likelihood of being able to control HIV-1 replication using a prespecified cut-off (viral load increase < 1000 copies/ml) increased from 39% in Bw4-negative patients to 53% in patients carrying Bw4-80Thr, and to 65% in patients carrying Bw4-80Ile (P = 0.02). CONCLUSIONS: These data establish a significant impact of HLA-Bw4 on the control of viral replication after STI.

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BACKGROUND: The Outpatient Bleeding Risk Index (OBRI) and the Kuijer, RIETE and Kearon scores are clinical prognostic scores for bleeding in patients receiving oral anticoagulants for venous thromboembolism (VTE). We prospectively compared the performance of these scores in elderly patients with VTE. METHODS: In a prospective multicenter Swiss cohort study, we studied 663 patients aged ≥ 65 years with acute VTE. The outcome was a first major bleeding at 90 days. We classified patients into three categories of bleeding risk (low, intermediate and high) according to each score and dichotomized patients as high vs. low or intermediate risk. We calculated the area under the receiver-operating characteristic (ROC) curve, positive predictive values and likelihood ratios for each score. RESULTS: Overall, 28 out of 663 patients (4.2%, 95% confidence interval [CI] 2.8-6.0%) had a first major bleeding within 90 days. According to different scores, the rate of major bleeding varied from 1.9% to 2.1% in low-risk, from 4.2% to 5.0% in intermediate-risk and from 3.1% to 6.6% in high-risk patients. The discriminative power of the scores was poor to moderate, with areas under the ROC curve ranging from 0.49 to 0.60 (P = 0.21). The positive predictive values and positive likelihood ratios were low and varied from 3.1% to 6.6% and from 0.72 to 1.59, respectively. CONCLUSION: In elderly patients with VTE, existing bleeding risk scores do not have sufficient accuracy and power to discriminate between patients with VTE who are at a high risk of short-term major bleeding and those who are not.

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Status epilepticus (SE) is associated with significant mortality and morbidity. A reliable prognosis may help better manage medical resources and treatment strategies. We examined the role of preexisting comorbidities on the outcome of patients with SE, an aspect that has received little attention to date. We prospectively studied incident SE episodes in 280 adults occurring over 55 months in our tertiary care hospital, excluding patients with postanoxic encephalopathy. Different models predicting mortality and return to clinical baseline at hospital discharge were compared, which included demographics, SE etiology, a validated clinical Status Epilepticus Severity Score (STESS), and comorbidities (assessed with the Charlson Comorbidity Index) as independent variables. The overall short-term mortality was 14%, and only half of patients returned to their clinical baseline. On bivariate analyses, age, STESS, potentially fatal etiologies, and number of preexisting comorbidities were all significant predictors of both mortality and return to clinical baseline. As compared with the simplest predictive model (including demographics and deadly etiology), adding SE severity and comorbidities resulted in an improved predictive performance (C statistics 0.84 vs. 0.77 for mortality, and 0.86 vs. 0.82. for return to clinical baseline); comorbidities, however, were not independently related to outcome. Considering comorbidities and clinical presentation, in addition to age and etiology, slightly improves the prediction of SE outcome with respect to both survival and functional status. This analysis also emphasizes the robust predictive role of etiology and age.

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SUMMARY: BMD and clinical risk factors predict hip and other osteoporotic fractures. The combination of clinical risk factors and BMD provide higher specificity and sensitivity than either alone. INTRODUCTION AND HYPOTHESES: To develop a risk assessment tool based on clinical risk factors (CRFs) with and without BMD. METHODS: Nine population-based studies were studied in which BMD and CRFs were documented at baseline. Poisson regression models were developed for hip fracture and other osteoporotic fractures, with and without hip BMD. Fracture risk was expressed as gradient of risk (GR, risk ratio/SD change in risk score). RESULTS: CRFs alone predicted hip fracture with a GR of 2.1/SD at the age of 50 years and decreased with age. The use of BMD alone provided a higher GR (3.7/SD), and was improved further with the combined use of CRFs and BMD (4.2/SD). For other osteoporotic fractures, the GRs were lower than for hip fracture. The GR with CRFs alone was 1.4/SD at the age of 50 years, similar to that provided by BMD (GR = 1.4/SD) and was not markedly increased by the combination (GR = 1.4/SD). The performance characteristics of clinical risk factors with and without BMD were validated in eleven independent population-based cohorts. CONCLUSIONS: The models developed provide the basis for the integrated use of validated clinical risk factors in men and women to aid in fracture risk prediction.

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OsteoLaus is a cohort of 1400 women 50 to 80 years living in Lausanne, Switzerland. Clinical risk factors for osteoporosis, bone ultrasound of the heel, lumbar spine and hip bone mineral density (BMD), assessment of vertebral fracture by DXA, and microarchitecture evaluation by TBS (Trabecular Bone Score) will be recorded. TBS is a new parameter obtained after a re-analysis of a DXA exam. TBS is correlated with parameters of microarchitecture. His reproducibility is good. TBS give an added diagnostic value to BMD, and predict osteoporotic fracture (partially) independently to BMD. The position of TBS in clinical routine in complement to BMD and clinical risk factors will be evaluated in the OsteoLaus cohort.

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The blood pressure (BP) lowering effect of the orally active angiotensin converting enzyme inhibitor, captopril (SQ14225), was studied in 59 hypertensive patients maintained on a constant sodium intake. Within 2 hours of the first dose of captopril BP fell from 171/107 to a maximum low of 142/92 mm Hg (p less than 0.001), and after 4 to 8 days to treatment BP averaged 145/94 mm Hg (p less than 0.001). The magnitude of BP drop induced by captopril was significantly correlated to baseline plasma renin activity (PRA) both during the acute phase (r = -0.38, p less than 0.01) and after the 4 to 8-day interval (r = -0.33, p less than 0.01). Because of considerable scatter in individual data, renin profiling was not precisely predictive of the immediate or delayed BP response of separate patients. However, the BP levels achieved following the initial dose of captopril were closely correlated to BP measured after 4 to 8 days of therapy, and appeared to have greater predictive value than control PRA of the long-term efficacy of chronic captopril therapy despite marked BP changes occurring in some patients during the intermediate period. Because of these intermediate BP changes, addition of a diuretic to enhance antihypertensive effectiveness of angiotensin blockade should be restrained for several days after initiation of captopril therapy.

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Here we present a processing route to produce multi-structured ceramic foams based on the combination of particle-stabilized foams with polymeric sponges to produce positive and negative templating structures. Polyester sponges are infiltrated with freshly produced calcium aluminate alumina foams and upon sintering either positive templating structures are produced when wetting the sponges, or negative templating foams with a percolating pore network are obtained when completely filling the sponges. Additionally, by combining different layers of these particle-stabilized foam infiltrated sponges, various different structures can be produced, including sandwich structures, pore size gradients, and ceramic bone-like structures applying to different types of bone. The particle-stabilized foams used were in situ self-hardening calcium aluminate cement enriched alumina foams to obtain crack-free samples with pore interconnections and tailorable pore sizes.

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Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch.

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Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.

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BACKGROUND: Several markers of atherosclerosis and of inflammation have been shown to predict coronary heart disease (CHD) individually. However, the utility of markers of atherosclerosis and of inflammation on prediction of CHD over traditional risk factors has not been well established, especially in the elderly. METHODS: We studied 2202 men and women, aged 70-79, without baseline cardiovascular disease over 6-year follow-up to assess the risk of incident CHD associated with baseline noninvasive measures of atherosclerosis (ankle-arm index [AAI], aortic pulse wave velocity [aPWV]) and inflammatory markers (interleukin-6 [IL-6], C-reactive protein [CRP], tumor necrosis factor-a [TNF-a]). CHD events were studied as either nonfatal myocardial infarction or coronary death ("hard" events), and "hard" events plus hospitalization for angina, or the need for coronary-revascularization procedures (total CHD events). RESULTS: During the 6-year follow-up, 283 participants had CHD events (including 136 "hard" events). IL-6, TNF-a and AAI independently predicted CHD events above Framingham Risk Score (FRS) with hazard ratios [HR] for the highest as compared with the lowest quartile for IL-6 of 1.95 (95%CI: 1.38-2.75, p for trend<0.001), TNF-a of 1.45 (95%CI: 1.04-2.02, p for trend 0.03), of 1.66 (95%CI: 1.19-2.31) for AAI £0.9, as compared to AAI 1.01-1.30. CRP and aPWV were not independently associated with CHD events. Results were similar for "hard" CHD events. Addition of IL-6 and AAI to traditional cardiovascular risk factors yielded the greatest improvement in the prediction of CHD; C-index for "hard"/total CHD events increased from 0.62/0.62 for traditional risk factors to 0.64/0.64 for IL-6 addition, 0.65/0.63 for AAI, and 0.66/0.64 for IL-6 combined with AAI. Being in the highest quartile of IL-6 combined with an AAI £ 0.90 or >1.40 yielded an HR of 2.51 (1.50-4.19) and 4.55 (1.65-12.50) above FRS, respectively. With use of CHD risk categories, risk prediction at 5 years was more accurate in models that included IL-6, AAI or both, with 8.0, 8.3 and 12.1% correctly reclassified respectively. CONCLUSIONS: Among older adults, markers of atherosclerosis and of inflammation, particularly IL-6 and AAI, are independently associated with CHD. However, these markers only modestly improve cardiovascular risk prediction beyond traditional risk factors. Acknowledgments: This study was supported by Contracts NO1-AG-6-2101, NO1-AG-6- 2103, and NO1-AG-6-2106 of the National Institute on Aging. This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging.

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Osteoporotic hip fractures increase dramatically with age and are responsible for considerable morbidity and mortality. Several treatments to prevent the occurrence of hip fracture have been validated in large randomized trials and the current challenge is to improve the identification of individuals at high risk of fracture who would benefit from therapeutic or preventive intervention. We have performed an exhaustive literature review on hip fracture predictors, focusing primarily on clinical risk factors, dual X-ray absorptiometry (DXA), quantitative ultrasound, and bone markers. This review is based on original articles and meta-analyses. We have selected studies that aim both to predict the risk of hip fracture and to discriminate individuals with or without fracture. We have included only postmenopausal women in our review. For studies involving both men and women, only results concerning women have been considered. Regarding clinical factors, only prospective studies have been taken into account. Predictive factors have been used as stand-alone tools to predict hip fracture or sequentially through successive selection processes or by combination into risk scores. There is still much debate as to whether or not the combination of these various parameters, as risk scores or as sequential or concurrent combinations, could help to better predict hip fracture. There are conflicting results on whether or not such combinations provide improvement over each method alone. Sequential combination of bone mineral density and ultrasound parameters might be cost-effective compared with DXA alone, because of fewer bone mineral density measurements. However, use of multiple techniques may increase costs. One problem that precludes comparison of most published studies is that they use either relative risk, or absolute risk, or sensitivity and specificity. The absolute risk of individuals given their risk factors and bone assessment results would be a more appropriate model for decision-making than relative risk. Currently, a group appointed by the World Health Organization and lead by Professor John Kanis is working on such a model. It will therefore be possible to further assess the best choice of threshold to optimize the number of women needed to screen for each country and each treatment.