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The aim of this study was to develop and validate a nomogram model to predict the risk of decreased activities of daily living (ADLs) in patients with moyamoya disease (MMD) following revascularization. The nomogram model was constructed based on data from 292 patients with MMD that were treated at Qilu Hospital of Shandong University from January 2018 to June 2019. The prediction model was assessed using a dataset of 119 patients with MMD collected from July 2019 to June 2020. Patients were evaluated with a general information questionnaire and the Mini Mental Status Examination, Hospital Anxiety and Depression Scale, Social Support Rating Scale, and ADL Scale. Multivariable logistic regression analysis was applied to build a prediction model incorporating the features selected in the least absolute shrinkage and selection operator regression model. Discrimination, calibration, and clinical usefulness of the prediction model were assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis. Predictors contained in the nomogram included gender, age, monthly income, hypertension, and cognitive function and depression scores. The areas under the ROC curves of the training and testing datasets were 0.938 and 0.853, respectively. The prediction model displayed good calibration, and the decision curve analysis showed that it had a wide range of clinical applications. This novel predictive could be conveniently used to predict the risk of the decreased living activity ability in patients with MMD.

biomed research international

Predicting Decreased Activities of Daily Living in Patients with Moyamoya Disease after Revascularization: Development and Assessment of a New Predictive Nomogram