Risk Analysis Index and 30-Day Mortality after Brain Tumor Resection: A Multicenter Frailty Analysis of 31,776 Patients from 2012 to 2020.

Introduction The aim of this study was to evaluate the discriminative accuracy of the preoperative Risk Analysis Index (RAI) frailty score for prediction of mortality or transition to hospice within 30 days of brain tumor resection (BTR) in a large multicenter, international, prospective database. Methods Records of BTR patients were extracted from the American College of Surgeons National Surgical Quality Improvement Program (2012-2020) database. The relationship between the RAI frailty scale and the primary end point (mortality or discharge to hospice within 30 days of surgery) was assessed using linear-by-linear proportional trend tests, logistic regression, and receiver operating characteristic (ROC) curve analysis (area under the curve as C-statistic). Results Patients with BTR ( N = 31,776) were stratified by RAI frailty tier: 16,800 robust (52.8%), 7,646 normal (24.1%), 6,593 frail (20.7%), and 737 severely frail (2.3%). The mortality/hospice rate was 2.5% ( n = 803) and was positively associated with increasing RAI tier: robust (0.9%), normal (3.3%), frail (4.6%), and severely frail (14.2%) ( p < 0.001). Isolated RAI was a robust discriminatory of primary end point in ROC curve analysis in the overall BTR cohort (C-statistic: 0.74; 95% confidence interval [CI]: 0.72-0.76) as well as the malignant (C-statistic: 0.74; 95% CI: 0. 67-0.80) and benign (C-statistic: 0.71; 95% CI: 0.70-0.73) tumor subsets (all p < 0.001). RAI score had statistically significantly better performance compared with the 5-factor modified frailty index and chronological age (both p < 0.0001). Conclusions RAI frailty score predicts 30-day mortality after BTR and may be translated to the bedside with a user-friendly calculator ( https://nsgyfrailtyoutcomeslab.shinyapps.io/braintumormortalityRAIcalc/ ). The findings hope to augment the informed consent and surgical decision-making process in this patient population and provide an example for future study designs.

Endoscopic and Nonendoscopic Approaches to Single-Level Lumbar Spine Decompression: Propensity Score-Matched Comparative Analysis and Frailty-Driven Predictive Model.

OBJECTIVE: The endoscopic spine surgery (ESS) approach is associated with high levels of patient satisfaction, shorter recovery time, and reduced complications. The present study reports multicenter, international data, comparing ESS and non-ESS approaches for singlelevel lumbar decompression, and proposes a frailty-driven predictive model for nonhome discharge (NHD) disposition. METHODS: Cases of ESS and non-ESS lumbar spine decompression were queried from the American College of Surgeons National Surgical Quality Improvement Program database (2017-2020). Propensity score matching was performed on baseline characteristics frailty score (measured by risk analysis index [RAI] and modified frailty index-5 [mFI-5]). The primary outcome of interest was NHD disposition. A predictive model was built using logistic regression with RAI as the primary driver. RESULTS: Single-level nonfusion spine lumbar decompression surgery was performed in 38,686 patients. Frailty, as measured by RAI, was a reliable predictor of NHD with excellent discriminatory accuracy in receiver operating characteristic (ROC) curve analysis: C-statistic: 0.80 (95% confidence interval [CI], 0.65-0.94) in ESS cohort, C-statistic: 0.75 (95% CI, 0.73-0.76) overall cohort. After propensity score matching, there was a reduction in total operative time (89 minutes vs. 103 minutes, p = 0.049) and hospital length of stay (LOS) (0.82 days vs. 1.37 days, p < 0.001) in patients treated endoscopically. In ROC curve analysis, the frailty-driven predictive model performed with excellent diagnostic accuracy for the primary outcome of NHD (C-statistic: 0.87; 95% CI, 0.85-0.88). CONCLUSION: After frailty-based propensity matching, ESS is associated with reduced operative time, shorter hospital LOS, and decreased NHD. The RAI frailty-driven model predicts NHD with excellent diagnostic accuracy and may be applied to preoperative decisionmaking with a user-friendly calculator: nsgyfrailtyoutcomeslab.shinyapps.io/lumbar_decompression_dischargedispo.

Frailty Measured by the Risk Analysis Index Predicts Nonhome Discharge and Mortality After Resection in Refractory Epilepsy: Analysis of 1236 Patients From a Prospective Surgical Registry, 2012 to 2020.

BACKGROUND: Risk stratification of epilepsy surgery patients remains difficult. The Risk Analysis Index (RAI) is a frailty measurement that augments preoperative risk stratification. OBJECTIVE: To evaluate RAI's discriminative threshold for nonhome discharge disposition (NHD) and mortality (or discharge to hospice within 30 days of operation) in epilepsy surgery patients. METHODS: Patients were queried from the American College of Surgeons-National Surgical Quality Improvement Program database (2012-2020) using diagnosis/procedure codes. Linear-by-linear trend tests assessed RAI's relationship with NHD and mortality. Discriminatory accuracy was assessed by C-statistics (95% CI) in receiver operating characteristic curve analysis. RESULTS: Epilepsy resections (N = 1236) were grouped into temporal lobe (60.4%, N = 747) and nontemporal lobe (39.6%, N = 489) procedures. Patients were stratified by RAI tier: 76.5% robust (RAI 0-20), 16.2% normal (RAI 21-30), 6.6% frail (RAI 31-40), and 0.8% severely frail (RAI 41 and above). The NHD rate was 18.0% (N = 222) and positively associated with increasing RAI tier: 12.5% robust, 34.0% normal, 38.3% frail, and 50.0% severely frail ( P < .001). RAI had robust predictive discrimination for NHD in overall cohort (C-statistic 0.71), temporal lobe (C-statistic 0.70), and nontemporal lobe (C-statistic 0.71) cohorts. The mortality rate was 2.7% (N = 33) and significantly associated with RAI frailty: 1.1% robust, 8.0% normal, 6.2% frail, and 20.0% severely frail ( P < .001). RAI had excellent predictive discrimination for mortality in overall cohort (C-statistic 0.78), temporal lobe (C-statistic 0.80), and nontemporal lobe (C-statistic 0.74) cohorts. CONCLUSION: The RAI frailty score predicts mortality and NHD after epilepsy surgery. This is accomplished with a user-friendly calculator: https://nsgyfrailtyoutcomeslab.shinyapps.io/epilepsy/ .

Frailty measured by risk analysis index and adverse discharge outcomes after adult spine deformity surgery: analysis of 3104 patients from a prospective surgical registry (2011-2020).

BACKGROUND CONTEXT: Measurement of frailty with the Risk Analysis Index (RAI) has demonstrated improved outcome prediction compared to other frailty indices across the surgical literature. However, the generalizability and clinical utility of preoperative RAI scoring for prediction of postoperative morbidity after adult spinal deformity surgery is presently unknown. Thus, recent studies have called for an RAI analysis of spine deformity outcomes. PURPOSE: The present study sought to evaluate the discriminatory accuracy of preoperative frailty, as measured by RAI, for predicting postoperative morbidity among adult spine deformity surgery patients using data queried from a large prospective surgical registry representing over 700 hospitals from 49 US states and 11 countries. STUDY DESIGN/SETTING: Secondary analysis of a prospective surgical registry. PATIENT SAMPLE: American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011-2020). OUTCOME MEASURES: The primary endpoint was "adverse discharge outcome" (ADO) defined as discharge to a non-home, non-rehabilitation nursing/chronic care facility. METHODS: Adult spine deformity surgeries were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011-2020) using diagnosis and procedure codes. The relationship between increasing preoperative RAI frailty score and increasing rate of primary endpoint (ADO) was assessed with Cochran-Armitage linear trend tests. Discriminatory accuracy was tested by computation of concordance statistics (with 95% confidence interval [CI]) in receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 3104 patients underwent spine deformity surgery and were stratified by RAI score: 0-10: 22%, 11-15: 11%, 16-20: 29%, 21-25: 26%, 26-30: 8.0%, 31-35: 2.4%, and 36+: 1.4%. The rate of ADO was 14% (N=439/3094). The rate of ADO increased significantly with increasing RAI score (p<.0001). RAI demonstrated robust discriminatory accuracy for prediction of ADO in ROC analysis (C-statistic: 0.71, 95% CI: 0.69-0.74, p<.001). In pairwise comparison of ROC curves (DeLong test), RAI demonstrates superior discriminatory accuracy compared to the 5-factor modified frailty index (mFI-5; p<.001). CONCLUSION: Preoperative frailty, as measured by RAI, is a robust predictor of postoperative morbidity (measured by ADO) after adult spine deformity surgery. The frailty score may be translated directly to the bedside with a user-friendly risk calculator, deployed here: https://nsgyfrailtyoutcomeslab.shinyapps.io/spineDeformity.

A Predictive Model of Failure to Rescue After Thoracolumbar Fusion.

OBJECTIVE: Although failure to rescue (FTR) has been utilized as a quality-improvement metric in several surgical specialties, its current utilization in spine surgery is limited. Our study aims to identify the patient characteristics that are independent predictors of FTR among thoracolumbar fusion (TLF) patients. METHODS: Patients who underwent TLF were identified using relevant diagnostic and procedural codes from the National Surgical Quality Improvement Program (NSQIP) database from 2011-2020. Frailty was assessed using the risk analysis index (RAI). FTR was defined as death, within 30 days, following a major complication. Univariate and multivariable analyses were used to compare baseline characteristics and early postoperative sequelae across FTR and non-FTR cohorts. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminatory accuracy of the frailty-driven predictive model for FTR. RESULTS: The study cohort (N = 15,749) had a median age of 66 years (interquartile range, 15 years). Increasing frailty, as measured by the RAI, was associated with an increased likelihood of FTR: odds ratio (95% confidence interval [CI]) is RAI 21-25, 1.3 [0.8-2.2]; RAI 26-30, 4.0 [2.4-6.6]; RAI 31-35, 7.0 [3.8-12.7]; RAI 36-40, 10.0 [4.9-20.2]; RAI 41- 45, 21.5 [9.1-50.6]; RAI ≥ 46, 45.8 [14.8-141.5]. The frailty-driven predictive model for FTR demonstrated outstanding discriminatory accuracy (C-statistic = 0.92; CI, 0.89-0.95). CONCLUSION: Baseline frailty, as stratified by type of postoperative complication, predicts FTR with outstanding discriminatory accuracy in TLF patients. This frailty-driven model may inform patients and clinicians of FTR risk following TLF and help guide postoperative care after a major complication.