
A study of 1,748 fracture patients from the NHANES data and 360 additional patients from a medical center led to the development and validation of a nomogram for predicting depression risk. Key predictors identified included drinking, insomnia, poverty-to-income ratio, education level, and white blood cell count. The nomogram demonstrated strong predictive accuracy with an area under the curve (AUC) of 0.734 in the training NHANES cohort, 0.740 in validation, and 0.711 in external hospital validation. Calibration curves and decision analysis confirmed its clinical value, offering a reliable tool for the early detection and intervention of depression in fracture patients
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