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Performance of models to predict poor outcome after stroke.

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Figshare2015-12-02 更新2026-05-11 收录
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https://figshare.com/articles/dataset/_Performance_of_models_to_predict_poor_outcome_after_stroke_/555772
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Performance of six simple variables model (age, living alone, independent of activities of daily living prior to stroke, normal verbal GCS, able to lift arms from bed, able to walk) and addition of IL-6, CRP, and white cell count as continuous variables.aThe likelihood ratio test compares a goodness of fit between models with and without biomarker data. pbThe Hosmer Lemeshow test compares the observed number of people with events to that predicted by the model. p>0.05 indicates that the model is well calibrated.cAUC = 1 indicates perfect discrimination of a model between patients with good and bad outcomes. p
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