Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials
- PMID: 18403738
- DOI: 10.1161/STROKEAHA.107.505867
Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials
Abstract
Background and purpose: An early and reliable prognosis for recovery in stroke patients is important for initiation of individual treatment and for informing patients and relatives. We recently developed and validated models for predicting survival and functional independence within 3 months after acute stroke, based on age and the National Institutes of Health Stroke Scale score assessed within 6 hours after stroke. Herein we demonstrate the applicability of our models in an independent sample of patients from controlled clinical trials.
Methods: The prognostic models were used to predict survival and functional recovery in 5419 patients from the Virtual International Stroke Trials Archive (VISTA). Furthermore, we tried to improve the accuracy by adapting intercepts and estimating new model parameters.
Results: The original models were able to correctly classify 70.4% (survival) and 72.9% (functional recovery) of patients. Because the prediction was slightly pessimistic for patients in the controlled trials, adapting the intercept improved the accuracy to 74.8% (survival) and 74.0% (functional recovery). Novel estimation of parameters, however, yielded no relevant further improvement.
Conclusions: For acute ischemic stroke patients included in controlled trials, our easy-to-apply prognostic models based on age and National Institutes of Health Stroke Scale score correctly predicted survival and functional recovery after 3 months. Furthermore, a simple adaptation helps to adjust for a different prognosis and is recommended if a large data set is available.
Comment in
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Predictions models in acute stroke: potential uses and limitations.Stroke. 2008 Jun;39(6):1665-6. doi: 10.1161/STROKEAHA.107.510271. Epub 2008 Apr 10. Stroke. 2008. PMID: 18403744 No abstract available.
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