SP28. The Risk Analysis Index Has Superior Frailty Discrimination Than the Modified Frailty Index-5 for Predicting Poor Cranioplasty Outcomes

Abstract

PURPOSE: Cranioplasty is a common surgical procedure where autologous or synthetic materials are used to repair cranial defects and although considered simple and low-risk, it is surprisingly associated with significant morbidity and mortality. Although increased patient age has been shown to be a predictor of poor postoperative outcomes, no studies have evaluated frailty’s impact on cranioplasty outcomes. This study examined the association between frailty and cranioplasty by comparing effect sizes of the Risk Analysis Index-Administrative (RAI-A), Modified Frailty Index-5 (mFI-5), and increasing patient age on the primary outcome of 30-day mortality and secondary outcomes of non-home discharge rates and postoperative complications, as measured by the Clavien-Dindo (CD) complication classification system: (CD I: surgical site infection, CD II: postoperative bleeding or transfusion(s), CD IIIb: reoperation under general anesthesia, CD IV: sepsis, septic shock, pulmonary embolism, myocardial infraction, ventilator status, 30-day mortality). METHODS: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) was queried for all patients undergoing cranioplasty between 2012-2020. Data for baseline demographics, comorbidities, operative characteristics, and postoperative outcomes were evaluated. Statistical analysis was performed on IBM SPSS Statistics ver. 28.0 (IBM Co., Armonk, NY, USA). The discriminatory thresholds of RAI-A, mFI-5, and increasing patient age on 30-day mortality were evaluated using receiver operating characteristics (ROC) curve analysis. The area under the curve (AUC) is represented as a C-statistic with a 95% confidence interval (CI). Two distinct multivariable analyses were conducted for RAI-A and mFI-5 to measure the independent relationships between frailty and outcomes. Covariates controlled for included race, BMI, primary procedure, cranial defect size, and material type. Additionally, the mFI-5 model was age-adjusted, allowing for direct comparison of effect sizes between age and frailty. We excluded age from the model for RAI-A to prevent any collinearity, since age contributes to the total RAI-A score. RESULTS: There were 2,864 included study patients with a median age of 57 years (IQR, 44-67), and a higher proportion of patients were female (57.0%), and white (68.5%). The RAI-A demonstrated better predictive ability for 30-day mortality (C-Statistic: 0.741, 95% CI: 0.678-0.804) compared to mFI-5 (C-Statistic: 0.574, 95% CI: 0.489-0.659) and increasing patient age (C-Statistic: 0.671, 95% CI: 0.610-0.732). On multivariable analyses, RAI-A demonstrated superior independent associations with mortality, NHD, CDII, and CDIII when compared to mFI-5 and increasing patient age. (p<0.05). CONCLUSIONS: The RAI-A demonstrated superior discrimination than the mFI-5 and increasing patient age in predicting poor outcomes following cranioplasty. The high rates of operative morbidity (5.0-36.5%) and mortality (0.4-3.2%) after cranioplasty highlight the importance of being able to predict which patients are at increased risk for poor cranioplasty outcomes, so that shared decision making regarding the potential risk and benefits of treatment can occur. Multivariable Analyses for Postoperative Outcomes