Background and Purpose-There has been substantial interest in identifying p
redictors of survival for stroke patients. Current instruments used for mea
suring stroke severity are confined to either neurological, functional, or
disability measures. The purpose of this study was to develop a stroke surv
ival score that combines instruments from different domains to better predi
ct long-term survival.
Methods-We took advantage of a particularly broad array of clinical and phy
siological variables collected during the Stroke Treatment with Ancrod Tria
l. 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 w
ith respect to sex, race, or educational level. The best model for predicti
ng survival was the Ischemic Stroke Survival Score. This model included the
Scandinavian Stroke Scale, Rapid Disability Rating Scale, age, and prior s
troke. This model had substantially greater predictive power (R-2=0.30, c s
tatistic=0.86) than the Scandinavian Stroke Scale alone (R-2=0.20, c statis
tic=0.78).
Conclusions-This study demonstrates that combining day 7 poststroke informa
tion from multiple domains substantially improves the ability to predict 12
-month survival of ischemic stroke patients compared with data from a singl
e domain. The high mortality rate emphasizes the importance of preventive m
easures for a disease that has identifiable and modifiable risk factors.