Abstract
Infection is one of the important and frequent complications following implantable pulse generator and deep brain stimulation (DBS) electrode insertion. The goal of this study was to retrospectively evaluate and identify potential risk factors for DBS infections. From January 2015 to January 2021 in Qingdao municipal hospital (training cohort) and The First Affiliated Hospital of the University of Science and Technology of China (validation cohort), the authors enrolled patients with Parkinson disease who had undergone primary DBS placement or implantable pulse generator replacement. The cases were divided into infection or no-infection groups according to the 6-month follow-up. The authors used the logistic regression models to determine the association between the variables and DBS infection. Depending on the results of logistic regression, the authors established a nomogram. The calibration curves, receiver operating characteristic curve analysis, and decision curves were used to evaluate the reliability of the nomogram. There were 191 cases enrolled in the no-infection group and 20 cases in the infection group in the training cohort. The univariate logistic regression showed that BMI, blood glucose, and albumin were all significant predictors of infection after DBS surgery (OR 0.832 [p = 0.009], OR 1.735 [p < 0.001], and OR 0.823 [p = 0.001], respectively). In the crude, adjust I, and adjust II models, the three variables stated above were all considered to be significant predictors of infection after DBS surgery. The calibration curves in both training and validation cohorts showed that the predicted outcome fitted well to the observed outcome (p > 0.05). The decision curves showed that the nomogram had more benefits than the "All or None" scheme. The areas under the curve were 0.93 and 0.83 in the training and validation cohorts, respectively. The nomogram included BMI, blood glucose, and albumin, which were significant predictors of infection in patients with DBS surgery. The nomogram was reliable for clinical application.
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