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Clinical and Surgical Risk Factors for Wound Healing Disorders Following Non-Instrumented Lumbar Spine Surgery Using
Vitalij Zeiser1, David Nigl1, Lukas Kohlmaier1
1Department of Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria.
Abstract:
Background/Objectives: In this study, we aimed to identify clinical and laboratory factors associated with wound healing disorders (WHDs) in exclusively non-instrumented lumbar spine surgery using penalized regression analysis. Methods: A retrospective cohort study was conducted including 1269 adult patients undergoing non-instrumented lumbar spine surgery between 2015 and 2023. The primary outcome was postoperative WHD requiring medical or surgical intervention. Univariate logistic regression analysis was performed to identify candidate variables. Variable selection was conducted using least absolute shrinkage and selection operator (LASSO) regression, followed by Firth-corrected logistic regression. Model performance was assessed using receiver operating characteristic (ROC) curve analysis and calibration metrics. Results: WHD occurred in 34 patients (2.7%). Patients with WHD were significantly older and had longer operative durations (both p < 0.001), as well as significantly prolonged hospital stays (17.0 ± 9.9 vs. 8.0 ± 4.7 days, p < 0.001). In the final penalized model, age (OR 1.03, 95% CI: 1.00-1.07; p = 0.033) and operative duration (OR 1.01, 95% CI: 1.01-1.02; p < 0.001) were independently associated with WHD, while arterial hypertension showed a borderline association (OR 2.28, 95% CI: 0.96-6.04; p = 0.063). The model demonstrated moderate discriminative performance with an area under the curve (AUC) of 0.795 (95% CI: 0.72-0.87). Conclusions: Wound healing disorders following non-instrumented lumbar spine surgery are multifactorial. While several patient- and surgery-related variables were associated with wound healing disorders individually, only advanced age and longer operative duration remained independently associated with WHD after adjustment for multiple variables.