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Predictors for 5‐year survival in a prospective cohort of elderly stroke patients

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Whiting R, Shen Q, Hung WT, Cordato D, Chan DKY. Predictors for 5‐year survival in a prospective cohort of elderly stroke patients. Acta Neurol Scand: 2011: 124: 309–316. © 2011 John Wiley & Sons A/S.

Objectives –  To examine predictors for 5‐year survival in elderly stroke patients.

Materials and Methods –  Prospective cohort study of 186 consecutive acute stroke patients aged ≥65 years admitted to Bankstown‐Lidcombe Hospital, Australia 03/2002 to 03/2003. All subjects were followed up in 2007/8, at 5 years post‐stroke, for outcome measures. Logistic regression analysis was performed to predict 5‐year survival using covariables, including functional status, age, stroke type and severity and vascular risk factors. Patients lost to follow‐up (n = 20) were excluded from the analyses.

Results –  One hundred patients (60%) were dead at study end. Predictors for survival in final logistic regression model were as follows: Glasgow Coma Scale (GCS) on admission (OR 1.49, 95%CI 1.1–2.0, P = 0.01), preadmission functional independence measure (FIM) score (OR 1.04, 95%CI 1.0–1.1, P = 0.01), age (OR 0.93, 95%CI 0.87–0.98, P = 0.01) and atrial fibrillation (OR 0.43, 95% CI 0.19–0.95, P = 0.04). For 5‐year survivors, mean Modified Rankin Scale was 3.1 ± 1.5, total FIM score 85 ± 32, mini‐mental state examination (MMSE) 22 ± 8 and Hospital Anxiety and Depression (HAD) scores 5.4 ± 3.4 and 5.2 ± 3.9, respectively. FIM cognition score was significantly lower at 5 years when compared to baseline (24 ± 8 vs 29 ± 8, P < 0.05) (all scores expressed as mean ± SD). In contrast, MMSE, HAD and total FIM scores were not significantly different at 5 years when compared to baseline.

Conclusions –  The study identified lower GCS on admission, lower preadmission FIM score, age and atrial fibrillation as negative predictors for 5‐year survival following stroke.
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Document Type: Research Article

Affiliations: Key University Research Centre in Health Technologies, University of Technology, Sydney, NSW, Australia

Publication date: 01 November 2011

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