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We aimed to develop and validate a nomogram for the individualized prediction of the risk of post-stroke fatigue (PSF) after discharge. Fatigue was measured using the Fatigue Assessment Scale. Multivariable logistic regression analysis was applied to build a prediction model incorporating the feature selected in the least absolute shrinkage and selection operator regression model. Discrimination, calibration, and clinical usefulness of the predictive model were assessed using the C-index, calibration plot, and decision curve analysis. I
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