978 resultados para Prediction os mortality


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Thesis (Master's)--University of Washington, 2016-06

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The extent of abnormality in patients with positive do-butamine echocardiography (DE) is predictive of risk, but the wall motion score (WMS) has low concordance among observers. We sought whether quantifying the extent of abnormal wall motion using tissue Doppler (TD) could guide risk assessment in patients with abnormal DE in 576 patients with known or suspected coronary artery disease; standard DE was combined with color TD imaging at peak dose. WMS was assessed by an expert observer and studies were identified as abnormal in the presence of 2:1 segments with resting or stress-induced wall motion abnormalities. Patients with abnormal DE had peak systolic velocity measured in each segment. Tissue tracking was used to measure myocardial displacement. Follow-up for death or infarction was per-formed after. 16 +/- 12 months. Of 251 patients with abnormal DE, 22 patients died (20 from cardiac causes) and 7 had nonfatal myocardial infarctionis. The average WMS in patients with events was 1.8 +/- 0.5, compared with 1.7 +/- 0.5 in patients without events (p = NS). The average systolic velocity in patients with events was 4.9 +/- 1.7 cm/s and 6.4 +/- 6.5 cm/s in the patients without events (p <0.001). The average tissue tracking in patients with events was 4.5 +/- 1.5 mm and was significant. (5.7 +/- 3.1 mm),in those,without events (p <0.001). Thus, TD is an alternative to WMS for quantifying the total extent of abnormal left ventricular function-at DE, and appears to be superior for predicting adverse outcomes. (C) 2004 by Excerpta Medica, Inc.

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Aims Prior research is limited with regard to the diagnostic and prognostic accuracy of commonplace cardiac imaging modalities in women. The aim of this study was to examine 5-year mortality in 4234 women and 6898 men undergoing exercise or dobutamine stress echocardiography at three hospitals. Methods and results Univariable and multivariable Cox proportional hazards models were used to estimate time to cardiac death in this multi-centre, observational registry. Of the 11 132 patients, women had a greater frequency of cardiac risk factors (P < 0.0001). However, men more often had a history of coronary disease including a greater frequency of echocardiographic wall motion abnormalities (P < 0.0001). During 5 years of follow-up, 103 women and 226 men died from ischaernic heart disease (P < 0.0001). Echocardiographic estimates of left ventricular function (P < 0.0001) and the extent of ischaernic watt motion abnormalities (P < 0.0001) were highly predictive of cardiac death. Risk-adjusted 5-year survival was 99.4, 97.6, and 95% for exercising women with no, single, and multi-vessel ischaemia (P < 0.0001). For women undergoing dobutamine stress, 5-year survival was 95, 89, and 86.6% for those with 0, 1, and 2-3 vessel ischaemia (P < 0.0001). Exercising men had a 2.0-fold higher risk at every level of worsening ischaemia (P < 0.0001). Significantly worsening cardiac survival was noted for the 1568 men undergoing dobutamine stress echocardiography (P < 0.0001); no ischaemia was associated with 92% 5-year survival as compared with death rates of &GE; 16% for men with ischaemia on dobutamine stress echocardiography (P < 0.0001). Conclusion Echocardiographic measures of inducible wall motion abnormalities and global and regional left ventricutar function are highly predictive of long-term outcome for women and men alike.

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Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

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AIMS: Our aims were to evaluate the distribution of troponin I concentrations in population cohorts across Europe, to characterize the association with cardiovascular outcomes, to determine the predictive value beyond the variables used in the ESC SCORE, to test a potentially clinically relevant cut-off value, and to evaluate the improved eligibility for statin therapy based on elevated troponin I concentrations retrospectively.

METHODS AND RESULTS: Based on the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project, we analysed individual level data from 10 prospective population-based studies including 74 738 participants. We investigated the value of adding troponin I levels to conventional risk factors for prediction of cardiovascular disease by calculating measures of discrimination (C-index) and net reclassification improvement (NRI). We further tested the clinical implication of statin therapy based on troponin concentration in 12 956 individuals free of cardiovascular disease in the JUPITER study. Troponin I remained an independent predictor with a hazard ratio of 1.37 for cardiovascular mortality, 1.23 for cardiovascular disease, and 1.24 for total mortality. The addition of troponin I information to a prognostic model for cardiovascular death constructed of ESC SCORE variables increased the C-index discrimination measure by 0.007 and yielded an NRI of 0.048, whereas the addition to prognostic models for cardiovascular disease and total mortality led to lesser C-index discrimination and NRI increment. In individuals above 6 ng/L of troponin I, a concentration near the upper quintile in BiomarCaRE (5.9 ng/L) and JUPITER (5.8 ng/L), rosuvastatin therapy resulted in higher absolute risk reduction compared with individuals <6 ng/L of troponin I, whereas the relative risk reduction was similar.

CONCLUSION: In individuals free of cardiovascular disease, the addition of troponin I to variables of established risk score improves prediction of cardiovascular death and cardiovascular disease.

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Thesis (Master's)--University of Washington, 2016-08

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Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem. Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study. Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields. Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study. Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting.

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Climate may affect broiler production, especially where there are heat waves, which may cause high mortality rates due to the heat stress. Heat wave prediction and characterization may allow early mitigation actions to be taken. Data Mining is one of the tools used for such a characterization, particularly when a large number of variables is involved. The objective of this study was to classify heat waves that promote broiler chicken mortality in poultry houses equipped with minimal environmental control. A single day of heat, a heat-shock day, is capable of producing high broiler mortality. In poultry houses equipped with fans and evaporative cooling, the characterization of heat waves affecting broiler mortality between 29 days of age and market age presented 89.34% Model Accuracy and 0.73 Class Precision for high mortality. There was no influence on high mortality (HM) of birds between 29 and 31 days of age. Maximum temperature humidity index (THI) above 30.6 ºC was the main characteristic of days when there was a heat wave, causing high mortality in broilers older than 31 days. The high mortality of broilers between 31 and 40 days of age occurred when maximum THI was above 30.6 ºC and maximum temperature of the day was above 34.4 ºC. There were two main causes of high mortality of broilers older than 40 days: 1) maximum THI above 30.6 ºC and minimum THI equal or lower than 15.5 ºC; 2) maximum THI above 30.6 ºC, minimum THI lower than 15.5 ºC, and the time of maximum temperature later than 15:00h. The heat wave influence on broiler mortality lasted an average of 2.7 days.