G R Williams1, J G Jiang. 1. Department of Health Economics and Reimbursement, Knoll Pharmaceutical Company, Mount Olive, NJ, USA.
Abstract
BACKGROUND AND PURPOSE: There has been substantial interest in identifying predictors of survival for stroke patients. Current instruments used for measuring stroke severity are confined to either neurological, functional, or disability measures. The purpose of this study was to develop a stroke survival score that combines instruments from different domains to better predict long-term survival. METHODS: We took advantage of a particularly broad array of clinical and physiological variables collected during the Stroke Treatment with Ancrod Trial. Four hundred fifty-three patients completed a battery of instruments at day 7 after stroke and then were followed for 1 year. RESULTS: Of the 453 patients, 53% were male, 77% were aged 65 years or older, and 89% were white. One hundred nine patients (24%) died during the study period. Age was a highly significant predictor of mortality (P<0.001), but there were no statistically significant differences in 12-month survival with respect to sex, race, or educational level. The best model for predicting survival was the Ischemic Stroke Survival Score. This model included the Scandinavian Stroke Scale, Rapid Disability Rating Scale, age, and prior stroke. This model had substantially greater predictive power (R(2)=0.30, c statistic=0.86) than the Scandinavian Stroke Scale alone (R(2)=0.20, c statistic=0.78). CONCLUSIONS: This study demonstrates that combining day 7 poststroke information from multiple domains substantially improves the ability to predict 12-month survival of ischemic stroke patients compared with data from a single domain. The high mortality rate emphasizes the importance of preventive measures for a disease that has identifiable and modifiable risk factors.
BACKGROUND AND PURPOSE: There has been substantial interest in identifying predictors of survival for strokepatients. Current instruments used for measuring stroke severity are confined to either neurological, functional, or disability measures. The purpose of this study was to develop a stroke survival score that combines instruments from different domains to better predict long-term survival. METHODS: We took advantage of a particularly broad array of clinical and physiological variables collected during the Stroke Treatment with Ancrod Trial. Four hundred fifty-three patients completed a battery of instruments at day 7 after stroke and then were followed for 1 year. RESULTS: Of the 453 patients, 53% were male, 77% were aged 65 years or older, and 89% were white. One hundred nine patients (24%) died during the study period. Age was a highly significant predictor of mortality (P<0.001), but there were no statistically significant differences in 12-month survival with respect to sex, race, or educational level. The best model for predicting survival was the Ischemic Stroke Survival Score. This model included the Scandinavian Stroke Scale, Rapid Disability Rating Scale, age, and prior stroke. This model had substantially greater predictive power (R(2)=0.30, c statistic=0.86) than the Scandinavian Stroke Scale alone (R(2)=0.20, c statistic=0.78). CONCLUSIONS: This study demonstrates that combining day 7 poststroke information from multiple domains substantially improves the ability to predict 12-month survival of ischemic strokepatients compared with data from a single domain. The high mortality rate emphasizes the importance of preventive measures for a disease that has identifiable and modifiable risk factors.
Authors: Amy J H Kind; Maureen A Smith; Jinn-Ing Liou; Nancy Pandhi; Jennifer R Frytak; Michael D Finch Journal: J Am Geriatr Soc Date: 2008-04-18 Impact factor: 5.562