A risk score based on get with the guidelines-stroke program data works in patients with acute ischemic stroke in China

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Abstract

Background and Purpose-There are few validated models for prediction of in-hospital mortality after acute ischemic stroke. In 2010, Smith et al developed and internally validated models for predicting in-hospital mortality based on Get With the Guidelines-Stroke program data. We demonstrate the applicability of this Get With the Guidelines risk model in Chinese patients. Methods-The prognostic model was used to predict survival in 7015 patients with acute ischemic stroke from China National Stroke Registry data set. Model discrimination was quantified by calculating C statistic. To clarify the role of National Institutes of Health Stroke Scale (NIHSS), we also calculated the C statistics for NIHSS alone and for the model without NIHSS. Results-The C statistic was 0.867 (95% CI, 0.839-0.895) through the Get With the Guidelines risk model, suggesting good discrimination in the China National Stroke Registry. The model without NIHSS produced significantly lower C statistic (0.735; 95% CI, 0.701-0.770; P<0.001), indicating the important role of NIHSS in the prediction of survival. Furthermore, a model with NIHSS alone also provided significant discrimination (C statistic, 0.847; 95% CI, 0.816-0.879). A plot of observed versus predicted mortality showed excellent model calibration in the external validation sample from the China National Stroke Registry. Conclusions-The Get With the Guidelines risk model could correctly predict in-hospital mortality in Chinese patients with ischemic stroke. In addition, the NIHSS provides substantial incremental information on a patient's short-term mortality risk and is the strongest predictor of mortality. © 2012 American Heart Association, Inc.

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Wang, Y., Zhang, N., Liu, G., Zhang, G., Fang, J., Wang, Y., … Guo, L. (2012, November). A risk score based on get with the guidelines-stroke program data works in patients with acute ischemic stroke in China. Stroke. https://doi.org/10.1161/STROKEAHA.112.669085

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