• Jessica Ryvlin, Seung Woo Kim, Rafael De la Garza Ramos, Mousa Hamad, Ariel Stock, Edwin Owolo, Mitchell S Fourman, Ananth Eleswarapu, Yaroslav Gelfand, Saikiran Murthy, and Reza Yassari.
• Department of Neurological Surgery, Montefiore Medical Center Albert Einstein College of Medicine, Bronx, New York, New York, USA. Electronic address: Jessica.Ryvlin@einsteinmed.edu.
• World Neurosurg. 2024 May 1; 185: e351e356e351-e356.

Study DesignThis was a single-institutional retrospective cohort study.ObjectiveWound infections are common following spine metastasis surgery and can result in unplanned reoperations. A recent study published an online wound complication risk calculator but has not yet undergone external validation. Our aim was to evaluate the accuracy of this risk calculator in predicting 30-day wound infections and 30-day wound reoperations using our operative spine metastasis population.MethodsAn internal operative database was used to identify patients between 2012 and 2022. The primary outcomes were 1) any surgical site infection and 2) wound-related revision surgery within 30 days following surgery. Patient details were manually collected from electronic medical records and entered into the calculator to determine predicted complication risk percentages. Predicted risks were compared to observed outcomes using receiver operator characteristic (ROC) curves with areas under the curve (AUC).ResultsA total of 153 patients were included. The observed 30-day postoperative wound infection incidence was 5% while the predicted wound infection incidence was 6%. In ROC analysis, good discrimination was found for the wound infection model (AUC = 0.737; P = 0.024). The observed wound reoperation rate was 5% and the predicted wound reoperation rate was 6%. ROC analysis demonstrated poor discrimination for wound reoperations (AUC = 0.559; P = 0.597).ConclusionsThe online wound-related risk calculator was found to accurately predict wound infections but not wound reoperations within our metastatic spine surgery cohort. We suggest that the model may be clinically useful despite underlying population differences, but further work must be done to generate and validate accurate prediction tools.Copyright © 2024 Elsevier Inc. All rights reserved.

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