137 Risk Modeling Predicts Complication Rates for Spinal Surgery. Issue Volume 61:Issue CN Supp. 1(2014)Supplement (1st August 2014)

• Record Type: Journal Article
• Authors: Kimmell, Kristopher T.; Vates, G. Edward; Jahromi, Babak S.
• Is Part Of: Neurosurgery. Volume 61:Issue CN Supp. 1(2014)Supplement
• Page Start: 204
• Page End: 204
• Publication Date: 2014-08-01
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1227/01.neu.0000452411.61076.85
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: INTRODUCTION: In the current era of quality reporting and pay for performance, neurosurgeons must develop models to identify patients at high risk of complications. We sought to identify risk factors for complications in spine surgery and develop a score predictive of complications. METHODS: We examined spinal surgeries from the American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) database. 22 430 cases were identified based on current procedural terminology. RESULTS: The overall complication rate for the cohort was 9.9%. The most common complications were postoperative bleeding requiring transfusion (4.1%), non-wound infections (3.1%), and wound-related infections (2.2%). Multivariate regression analysis identified 20 factors associated with complications. Assigning 1 point for the presence of each factor, a risk model was developed. The range of scores for the cohort was 0 to 13 with a median score of 4. Complication rates for a risk score of 0 to 4 was 3.7% and for scores 5 to 13 was 18.5%. The risk model robustly predicted complication rates, with a complication rate of 1.2% for a score of 0 (n = 412, 1.8% of total) and 63.6% and 100% for scores of 12 and 13 (n = 22 patients, 0.1% of total cohort), respectively ( P < .001). The risk score also correlated strongly with total length of stay, mortality, and total work relative value units (wRVU) for the case. CONCLUSION: Patient-specific risk factors including comorbidities are strongly associated with surgical complications, length of stay, cost of care, and mortality in spine surgery, and can be used to develop risk models that are highly predictive of complications.