Hengartner, Astrid C.

BACKGROUND AND OBJECTIVES: The Risk Analysis Index (RAI) is a comprehensive assessment of frailty for predicting neurosurgical outcomes. The aim of this study was to assess whether frailty, measured by a modified RAI (mRAI), was an independent predictor of adverse events (AEs), nonroutine discharge (NRD), and in-hospital mortality for patients with acute cervical spinal cord injuries (SCIs). METHODS: A retrospective cohort study was performed using the American College of Surgeons Trauma Quality Programs database. Adult patients with acute cervical SCI from 2016 to 2022 were stratified by mRAI score into 3 groups: Robust (mRAI 0-10), Frail (mRAI 11-20), and Very Frail (mRAI ≥21). Patient demographics, comorbidities, injury type, diagnostic and treatment modality, AEs, and in-hospital mortality were assessed. A multivariate logistic regression analysis was used to identify independent predictors of AEs, NRD, and in-hospital mortality. RESULTS: 71 048 patients were stratified by mRAI score: 59 796 Robust (84.2%), 9558 Frail (13.5%), and 1694 Very Frail (2.4%). The proportion of SCIs secondary to a fall (Robust: 44.1% vs Frail: 70.2% vs Very Frail: 82.3%; P < .001) and AEs (Robust: 21.5% vs Frail: 24.4% vs Very Frail: 25.0%; P < .001) significantly increased with frailty. Very Frail patients experienced higher NRDs (Robust: 72.3% vs Frail: 85.2% vs Very Frail: 91.0%; P < .001) and in-hospital mortality (Robust: 10.9% vs Frail: 18.3% vs Very Frail: 29.2%; P < .001). On multivariate regression analysis, both Frail (odds ratio [OR]: 1.42; 95% CI: 1.25-1.61; P < .001) and Very Frail (OR: 2.09; 95% CI: 1.46-2.99; P < .001) mRAI scores predicted NRD, but only Frail mRAI score (OR: 1.12; 95% CI: 1.05-1.21; P = .001) was significantly associated with AEs. In addition, Frail (OR: 1.50; 95% CI: 1.36-1.65; P < .001) and Very Frail (OR: 2.79; 95% CI: 2.36-3.29; P < .001) mRAI scores were independent predictors of in-hospital mortality. CONCLUSION: Our study suggests that mRAI may be used to assess morbidity and mortality in patients presenting with spinal cord injury.

Study Design Retrospective cohort study Objective The aim of this study was to determine the relative importance and predicative power of the Hospital Frailty Risk Score (HFRS) on unplanned 30-day readmission after surgical intervention for metastatic spinal column tumors. Methods All adult patients undergoing surgery for metastatic spinal column tumor were identified in the Nationwide Readmission Database from the years 2016 to 2018. Patients were categorized into 3 cohorts based on the criteria of the HFRS: Low(<5), Intermediate(5-14.9), and High(≥ 15). Random Forest (RF) classification was used to construct predictive models for 30-day patient readmission. Model performance was examined using the area under the receiver operating curve (AUC), and the Mean Decrease Gini (MDG) metric was used to quantify and rank features by relative importance. Results There were 4346 patients included. The proportion of patients who required any readmission were higher among the Intermediate and High frailty cohorts when compared to the Low frailty cohort ( Low:33.9% vs. Intermediate:39.3% vs. High:39.2%, P < .001). An RF classifier was trained to predict 30-day readmission on all features (AUC = .60) and architecturally equivalent model trained using only ten features with highest MDG (AUC = .59). Both models found frailty to have the highest importance in predicting risk of readmission. On multivariate regression analysis, Intermediate frailty [ OR:1.32, CI(1.06,1.64), P = .012] was found to be an independent predictor of unplanned 30-day readmission. Conclusion Our study utilizes machine learning approaches and predictive modeling to identify frailty as a significant risk-factor that contributes to unplanned 30-day readmission after spine surgery for metastatic spinal column metastases.

Study Design: Retrospective cohort study. Objective: The influence that race has on mortality rates in patients with spinal cord tumors is relatively unknown. The aim of this study was to investigate the influence of race on the outcomes of patients with primary malignant or nonmalignant tumors of the spinal cord or spinal meninges. Methods: The Surveillance, Epidemiology, and End Results (SEER) Registry was used to identify all patients with a code for primary malignant or nonmalignant tumor of the spinal cord (C72.0) or spinal meninges (C70.1) from 1973 through 2016. Racial groups (African-American/Black vs. White) were balanced using propensity-score (PS) matching using a non-parsimonious 1:1 nearest neighbor matching algorithm. Overall survival (OS) estimates were obtained using the Kaplan-Meier method and compared across non-PS-matched and PS-matched groups using log-rank tests. Associations of survival with clinical variables was assessed using doubly robust Cox proportional-hazards (CPH) regression analysis. Results: There were a total of 7,498 patients identified with 648 (6.8%) being African American. African-American patients with primary intradural spine tumors were more likely to die of all causes than were White patients in both the non-PS-matched [HR: 1.26, 95% CI: (1.04, 1.51), P = 0.01] and PS-matched cohorts [HR: 1.64, 95% CI: (1.28, 2.11), P < 0.0001]. On multivariate CPH regression analysis age at diagnosis [HR: 1.03, 95% CI: (1.02, 1.05), P < 0.0001], race [HR: 1.82, 95% CI: (1.22, 2.74), P = 0.004), and receipt of RT [HR: 2.62, 95% CI: (1.56, 4.37), P = 0.0002) were all significantly associated with all-cause mortality, when controlling for other demographic, tumor, and treatment variables. Conclusions: Our study provides population-based estimates of the prognosis for patients with primary malignant or nonmalignant tumors of the spinal cord or spinal meninges and suggests that race may impact all-cause mortality.