BACKGROUND AND PURPOSE: Few studies have evaluated the factors influencing or predicting long-term survival after stroke in an unselected series of patients in whom the underlying cerebrovascular pathology is clearly defined. Moreover, the relative importance of risk factors for stroke, including sociodemographic and premorbid variables, has not been described in detail. METHODS: The study cohort consisted of 492 patients with stroke who were registered with a population-based study of acute cerebrovascular disease undertaken in Perth, Western Australia, during an 18-month period in 1989 and 1990. Objective evidence of the pathological basis of the stroke was obtained in 86% of cases, and all deaths among patients during a follow-up of 1 year were reviewed. RESULTS: One hundred twenty patients (24%) died within 28 days of the onset of stroke. Among the different subtypes of stroke, the 1-year case fatality (mean, 38%) varied from 6% and 16% for boundary zone infarction and lacunar infarction, respectively, to 42% and 46% for subarachnoid hemorrhage and primary intracerebral hemorrhage, respectively. Using Cox proportional-hazards analysis, a predictive model was developed on 321 patients with acute stroke (test sample). The best model contained five baseline variables that were independent predictors of death within 1 year: coma (relative risk [RR], 3.0; 95% confidence interval [CI], 1.1 to 8.4), urinary incontinence (RR, 3.9; 95% CI, 1.4 to 10.6), cardiac failure (RR, 6.5; 95% CI, 2.8 to 15.1), severe paresis (RR, 4.9; 95% CI, 1.6 to 15.5), and atrial fibrillation (RR, 2.0; 95% CI, 1.1 to 3.5). The sensitivity, specificity, and negative predictive value of this model for predicting death were 90%, 83%, and 95%, respectively. When applied to a second randomly selected validation sample of 171 events, sensitivity was 94%, specificity 62%, and negative predictive value 92%, indicating stability of the model. CONCLUSIONS: Although the case fatality, timing, and cause of death vary considerably among the different pathological subtypes of stroke, simple clinical measures that reflect the severity of the neurological deficit and associated cardiac disease at onset independently predict death by 1 year and may help to direct management.
RCT Entities:
BACKGROUND AND PURPOSE: Few studies have evaluated the factors influencing or predicting long-term survival after stroke in an unselected series of patients in whom the underlying cerebrovascular pathology is clearly defined. Moreover, the relative importance of risk factors for stroke, including sociodemographic and premorbid variables, has not been described in detail. METHODS: The study cohort consisted of 492 patients with stroke who were registered with a population-based study of acute cerebrovascular disease undertaken in Perth, Western Australia, during an 18-month period in 1989 and 1990. Objective evidence of the pathological basis of the stroke was obtained in 86% of cases, and all deaths among patients during a follow-up of 1 year were reviewed. RESULTS: One hundred twenty patients (24%) died within 28 days of the onset of stroke. Among the different subtypes of stroke, the 1-year case fatality (mean, 38%) varied from 6% and 16% for boundary zone infarction and lacunar infarction, respectively, to 42% and 46% for subarachnoid hemorrhage and primary intracerebral hemorrhage, respectively. Using Cox proportional-hazards analysis, a predictive model was developed on 321 patients with acute stroke (test sample). The best model contained five baseline variables that were independent predictors of death within 1 year: coma (relative risk [RR], 3.0; 95% confidence interval [CI], 1.1 to 8.4), urinary incontinence (RR, 3.9; 95% CI, 1.4 to 10.6), cardiac failure (RR, 6.5; 95% CI, 2.8 to 15.1), severe paresis (RR, 4.9; 95% CI, 1.6 to 15.5), and atrial fibrillation (RR, 2.0; 95% CI, 1.1 to 3.5). The sensitivity, specificity, and negative predictive value of this model for predicting death were 90%, 83%, and 95%, respectively. When applied to a second randomly selected validation sample of 171 events, sensitivity was 94%, specificity 62%, and negative predictive value 92%, indicating stability of the model. CONCLUSIONS: Although the case fatality, timing, and cause of death vary considerably among the different pathological subtypes of stroke, simple clinical measures that reflect the severity of the neurological deficit and associated cardiac disease at onset independently predict death by 1 year and may help to direct management.
Authors: Sunil A Sheth; Songmi Lee; Steven J Warach; Jan Gralla; Reza Jahan; Mayank Goyal; Raul G Nogueira; Osama O Zaidat; Vitor M Pereira; Adnan Siddiqui; Helmi Lutsep; David S Liebeskind; Louise D McCullough; Jeffrey L Saver Journal: Stroke Date: 2019-08-15 Impact factor: 7.914
Authors: Daniel Bodmer; Kerry A Vaughan; Brad E Zacharia; Zachary L Hickman; E Sander Connolly Journal: Transl Stroke Res Date: 2012-04-12 Impact factor: 6.829