PurposeExternal ventricular drainage (EVD) is a life-saving neurosurgical procedure, of which the most concerning complication is EVD-related infection (ERI). We aimed to construct and validate an ERI risk model and establish a monographic chart.MethodsWe retrospectively analyzed the adult EVD patients in four medical centers and split the data into a training and a validation set. We selected features via single-factor logistic regression and trained the ERI risk model using multi-factor logistic regression. We further evaluated the model discrimination, calibration, and clinical usefulness, with internal and external validation to assess the reproducibility and generalizability. We finally visualized the model as a nomogram and created an online calculator (dynamic nomogram).ResultsOur research enrolled 439 EVD patients and found 75 cases (17.1%) had ERI. Diabetes, drainage duration, site leakage, and other infections were independent risk factors that we used to fit the ERI risk model. The area under the receiver operating characteristic curve (AUC) and the Brier score of the model were 0.758 and 0.118, and these indicators' values were similar when internally validated. In external validation, the model discrimination had a moderate decline, of which the AUC was 0.720. However, the Brier score was 0.114, suggesting no degradation in overall performance. Spiegelhalter's Z-test indicated that the model had adequate calibration when validated internally or externally (P = 0.464 vs. P = 0.612). The model was transformed into a nomogram with an online calculator built, which is available through the website: https://wang-cdutcm.shinyapps.io/DynNomapp/.ConclusionsThe present study developed an infection risk model for EVD patients, which is freely accessible and may serve as a simple decision tool in the clinic.