Utility of Surgical Risk Calculators in Spine Surgery in Patients Aged Over 80 Years: Analysis of SpineSage and ACS NSQIP

Study Design Retrospective cohort study. Objective To validate the predictive accuracy of both the SpineSage and ACS-NSQIP surgical risk calculators in patients over the age of 80 years, undergoing spine surgery for any reason. Methods We included 210 consecutive patients treated with single-stage spine surgery at our institution between 2009 and 2019. The demographic details and preoperative characteristics of each patient were collected and reviewed for entry into both the SpineSage and ACS risk calculators. The estimated risk supplied by these calculators was compared to the observed rate of complications post-surgery. The main method of comparison was using receiver operating characteristic (ROC) curve analysis. Results Complications were identified in 51 patients (24%). Most patients underwent surgery for a degenerative cause (71%), with the majority of procedures performed on the lumbosacral spine (66%). Receiver operating characteristic (ROC) curves were calculated to compare the outcomes of each tool. Area under the curve (AUC) analysis showed similar predictive accuracy between SpineSage and ACS when predicting overall complications (0.688; P < .001 vs 0.634; P = .021). AUC analysis demonstrated that SpineSage had better predictive accuracy when estimating risk of major complications (0.778; P = .037 vs 0.675; P = .001). Conclusion For the prediction of risks associated with spine surgery in those aged >80 years, SpineSage appears to be preferable to the ACS-NSQIP surgical risk calculator in this single centre cohort, SpineSage was more accurate in predicting the risk of serious medical complications. The accuracy of both of these tools could still be improved upon.

Automated summary

This study validates the predictive accuracy of the SpineSage and ACS-NSQIP surgical risk calculators in patients over 80 years old undergoing spine surgery. SpineSage appears to be preferable to ACS-NSQIP in predicting overall complications and has better predictive accuracy in estimating the risk of major complications.