Abstract

This was a retrospective cohort study. The objective of this study was to assess the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator performance in patients undergoing surgery for metastatic spine disease. Patients with spinal metastases may require surgical intervention for cord compression or mechanical instability. The ACS-NSQIP calculator was developed to assist surgeons with estimating 30-day postoperative complications based on patient-specific risk factors and has been validated within several surgical patient populations. We included 148 consecutive patients at our institution who underwent surgery for metastatic spine disease between 2012 and 2022. Our outcomes were 30-day mortality, 30-day major complications, and length of hospital stay (LOS). Predicted risk, determined by the calculator, was compared with observed outcomes using receiver operating characteristic curves with area under the curve (AUC) and Wilcoxon signed-rank tests. Analyses were repeated using individual corpectomy and laminectomy Current Procedural Terminology (CPT) codes to determine procedure-specific accuracy. Based on the ACS-NSQIP calculator, there was good discrimination between observed and predicted 30-day mortality incidence overall (AUC=0.749), as well as in corpectomy cases (AUC=0.745) and laminectomy cases (AUC=0.788). Poor 30-day major complication discrimination was seen in all procedural cohorts, including overall (AUC=0.570), corpectomy (AUC=0.555), and laminectomy (AUC=0.623). The overall median observed LOS was similar to predicted LOS (9 vs. 8.5d, P =0.125). Observed and predicted LOS were also similar in corpectomy cases (8 vs. 9d; P =0.937) but not in laminectomy cases (10 vs. 7d, P =0.012). The ACS-NSQIP risk calculator was found to accurately predict 30-day postoperative mortality but not 30-day major complications. The calculator was also accurate in predicting LOS following corpectomy but not laminectomy. While this tool may be utilized to predict risk short-term mortality in this population, its clinical value for other outcomes is limited.

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