Maree L Hackett1, Craig S Anderson. 1. Neurological and Mental Health Division, The George Institute for International Health, The University of Sydney and Royal Prince Alfred Hospital, PO Box M201, Missenden Road, Sydney, NSW 2050, Australia. mhackett@thegeorgeinstitute.org
Abstract
BACKGROUND AND PURPOSE: Mood disorders are an important consequence of stroke. We aimed to identify significant, clinically useful predictors of abnormal mood after stroke. METHODS: The Auckland Regional Community Stroke (ARCOS) study was a prospective population-based stroke incidence study conducted in Auckland, New Zealand, over a 12-month period from 2002 to 2003. All patients were followed up 6 months after stroke onset and abnormal mood was assessed using the 28-item General Health Questionnaire (GHQ-28) administered as part of a structured telephone interview. Multivariate stepwise logistic regression was used to develop a predictive model for "caseness" (score of > or = 5 on the GHQ-28) based on several premorbid patient and clinical variables assessed at baseline and 28 days of follow up. RESULTS: Of patients available at 6 months (n=1172), complete data on mood was available from 739 (60%) patients and 27% (95% confidence interval, 24 to 30%) were defined as cases. Key baseline predictors of abnormal mood were disability and history of depression after adjustment for sex, age, and comorbidity, but the model failed to predict a large amount of the variation in caseness (C statistic 0.587). CONCLUSIONS: This study emphasizes the complex nature of mood disturbance after stroke and that multiple factors are likely to contribute to mood disorders. A simple, clinically applicable, predictive model in stroke care appears difficult to develop.
BACKGROUND AND PURPOSE:Mood disorders are an important consequence of stroke. We aimed to identify significant, clinically useful predictors of abnormal mood after stroke. METHODS: The Auckland Regional Community Stroke (ARCOS) study was a prospective population-based stroke incidence study conducted in Auckland, New Zealand, over a 12-month period from 2002 to 2003. All patients were followed up 6 months after stroke onset and abnormal mood was assessed using the 28-item General Health Questionnaire (GHQ-28) administered as part of a structured telephone interview. Multivariate stepwise logistic regression was used to develop a predictive model for "caseness" (score of > or = 5 on the GHQ-28) based on several premorbid patient and clinical variables assessed at baseline and 28 days of follow up. RESULTS: Of patients available at 6 months (n=1172), complete data on mood was available from 739 (60%) patients and 27% (95% confidence interval, 24 to 30%) were defined as cases. Key baseline predictors of abnormal mood were disability and history of depression after adjustment for sex, age, and comorbidity, but the model failed to predict a large amount of the variation in caseness (C statistic 0.587). CONCLUSIONS: This study emphasizes the complex nature of mood disturbance after stroke and that multiple factors are likely to contribute to mood disorders. A simple, clinically applicable, predictive model in stroke care appears difficult to develop.
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