Abstract

INTRODUCTION: Cervical decompression & fusion (CDF) outcome prognostication relies on preoperative risk factors to predict complications and outcomes in order to help guide pre- and perioperative decision-making. METHODS: CDF cases were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database 2011-2020. Patients who underwent CDF and experienced a major complication were identified. Within this cohort, FTR was calculated as death or hospice within 30 days of a major complication. Frailty was measured by the Risk Analysis Index-Revised (RAI-Rev). Demographics and baseline characteristics of patients were compared by FTR. Significant factors were assessed by univariate and multivariable regression for the development of a frailty-driven predictive model for FTR. The discriminative ability of the predictive model was assessed using a receiving operating characteristic curve analysis. RESULTS: There were 3,632 patients who suffered a major complication from CDF, and 7.6% (277 patients) experienced FTR. Independent predictors of FTR were non-elective surgery, frailty status, preoperative intubation, thrombosis or embolism complication, unplanned intubation, prolonged ventilator use (>48 hours), cardiac arrest, and septic shock. Frailty, and a combination of preoperative and postoperative risk factors in a predictive model for FTR achieved outstanding discriminatory accuracy (C-statistic = 0.901, CI: 0.883-0.919). CONCLUSIONS: Preoperative and postoperative risk factors yield a highly accurate predictive model for FTR in CDF patients. Our model may guide surgical management and/or prognostication following the development of a major complication. Future studies may determine the predictive ability of this model in other neurosurgical patient populations. Our predictive model may be deployed by-the-beside here: https://nsgyfrailtyoutcomeslab.shinyapps.io/FailureToRescueCervicalFusion/

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