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.

The frailty-driven predictive model for failure to rescue among patients who experienced a major complication following cervical decompression and fusion: an ACS-NSQIP analysis of 3,632 cases (2011-2020).

BACKGROUND CONTEXT: Preoperative risk stratification for patients considering cervical decompression and fusion (CDF) relies on established independent risk factors to predict the probability of complications and outcomes in order to help guide pre and perioperative decision-making. PURPOSE: This study aims to determine frailty's impact on failure to rescue (FTR), or when a mortality occurs within 30 days following a major complication. STUDY DESIGN/SETTING: Cross-sectional retrospective analysis of retrospective and nationally-representative data. PATIENT SAMPLE: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried for all CDF cases from 2011-2020. OUTCOME MEASURES: CDF patients who experienced a major complication were identified and FTR was calculated as death or hospice disposition within 30 days of a major complication. METHODS: Frailty was measured by the Risk Analysis Index-Revised (RAI-Rev). Baseline patient demographics and characteristics were compared for all FTR patients. 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 (ROC) curve analysis. RESULTS: There were 3632 CDF patients who suffered a major complication and 7.6% (277 patients) subsequently expired or dispositioned to hospice, the definition of FTR. Independent predictors of FTR were nonelective surgery, frailty, preoperative intubation, thrombosis or embolic complication, unplanned intubation, on ventilator for >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). CONCLUSION: Preoperative and postoperative risk factors, combined with frailty, yield a highly accurate predictive model for FTR in CDF patients. Our model may guide surgical management and/or prognostication regarding the likelihood of FTR after a major complication postoperatively with CDF patients. Future studies may determine the predictive ability of this model in other neurosurgical patient populations.

Frailty Is Associated With Decreased Survival in Adult Patients With Nonoperative and Operative Traumatic Subdural Hemorrhage: A Retrospective Cohort Study of 381,754 Patients.

Objective: We investigated frailty's impact on traumatic subdural hematoma (tSDH), examining its relationship with major complications, length of hospital stay (LOS), mortality, high level of care discharges, and survival probabilities following nonoperative and operative management. Background: Despite its frequency as a neurosurgical emergency, frailty's impact on tSDH remains underexplored. Frailty characterized by multisystem impairments significantly predicts poor outcomes, necessitating further investigation. Methods: A retrospective study examining tSDH patients ≥18 years and assigned an abbreviated injury scale score ≥3, and entered into ACS-TQIP between 2007 and 2020. We employed multivariable analyses for risk-adjusted associations of frailty and our outcomes, and Kaplan-Meier plots for survival probability. Results: Overall, 381,754 tSDH patients were identified by mFI-5 as robust-39.8%, normal-32.5%, frail-20.5%, and very frail-7.2%. There were 340,096 nonoperative and 41,658 operative patients. The median age was 70.0 (54.0-81.0) nonoperative, and 71.0 (57.0-80.0) operative cohorts. Cohorts were predominately male and White. Multivariable analyses showed a stepwise relationship with all outcomes P < 0.001; 7.1% nonoperative and 14.9% operative patients had an 20% to 46% increased risk of mortality, that is, nonoperative: very frail (HR: 1.20 [95% CI: 1.13-1.26]), and operative: very frail (HR: 1.46 [95% CI: 1.38-1.55]). There were precipitous reductions in survival probability across mFI-5 strata. Conclusion: Frailty was associated with major complications, LOS, mortality, and high level care discharges in a nationwide population of 381,754 patients. While timely surgery may be required for patients with tSDH, rapid deployment of point-of-care risk assessment for frailty creates an opportunity to equip physicians in allocating resources more precisely, possibly leading to better outcomes.

Causes and Predictors of Unplanned Readmission in Patients Undergoing Intracranial Tumor Resection: A Multicenter Analysis of 31,776 Patients.

BACKGROUND: Although unplanned readmission is a postoperative outcome metric associated with significant morbidity and financial burden, precise assessment tools for its prediction have not yet been developed. The Risk Analysis Index (RAI) could potentially be used to help improve the prediction of unplanned readmissions for patients undergoing intracranial tumor resection (ITR). In the present study, we evaluate the predictive accuracy of frailty on 30-day unplanned readmission after ITR using the RAI. METHODS: Data were obtained from the American College of Surgeons National Surgical Quality Improvement Program database. The baseline characteristics, preoperative clinical status, and outcomes were compared between patients with and without unplanned readmission. Frailty was calculated using the RAI. Univariate and multivariate logistic regression analyses were performed to identify independent associations between unplanned readmissions and patient characteristics. RESULTS: The unplanned readmission rate for this cohort (n = 31,776) was 10.8% (n = 3420). Of the 3420 readmitted patients, 958 required unplanned reoperation. Multiple characteristics were significantly different between the 2 groups, including age, body mass index, comorbidities, and RAI groups (P < 0.05). The common causes of unplanned readmission included infection (9.4%), seizures (6%), and pulmonary embolism (4%). The patient characteristics identified as reliable predictors of unplanned readmission included age, body mass index, functional status, diabetes, hypertension, hyponatremia, and the patient's RAI score (P < 0.05). Frail status, hyponatremia, leukocytosis, hypertension, and thrombocytosis were significant predictors of unplanned readmissions. CONCLUSIONS: The RAI is a reliable preoperative frailty index for predicting unplanned readmissions after ITR. Using the RAI could decrease unplanned readmissions by identifying high-risk patients and enabling future implementation of appropriate management guidelines.

Baseline Frailty and Discharge to Advanced Care Facilities in Patients Undergoing Lumbar Interbody Fusion for Lumbar Degenerative Disease: A Multicenter Registry Analysis of 7153 Patient Cases Comparing the Risk Analysis Index to the 5-Factor Modified Frailty Index.

OBJECTIVE: To evaluate the impact of frailty, as measured by the 5-factor modified Frailty Index (mFI-5) and the Risk Analysis Index (RAI), on advanced care facility discharge (FD) in patients who underwent lumbar fusion for lumbar degenerative spine disease. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (2012-2020) was queried for adults (≥18 years) undergoing lumbar fusion for lumbar degenerative disease. Descriptive statistics and univariate crosstabulation were used to assess baseline demographics, preoperative comorbidities, and postoperative outcomes. Receiver operating characteristic curve analysis was used to assess the discriminative threshold of the mFI-5 and RAI on FD within this population. RESULTS: The median patient age in this study cohort (N = 7153) was 56 years and FD occurred in 7.3% of cases. Receiver operating characteristic curve analysis demonstrated that both the mFI-5 and the RAI accurately predicted FD (C-statistics: mFI-5: 0.627; RAI: 0.746). DeLong's test found that the RAI had superior discrimination when compared to the mFI-5 (P < 0.0001). CONCLUSIONS: RAI is a reliable predictor of FD in lumbar degenerative disease patients who underwent lumbar interbody fusion and demonstrated superior discrimination compared to the mFI-5. Identification of patients at risk for FD may facilitate more precise risk stratification to enable better preoperative decision-making and help set more realistic expectations of care.

Preoperative Frailty Predicts Worse Outcomes after Microvascular Decompression for Trigeminal Neuralgia, Hemifacial Spasm, and Glossopharyngeal Neuralgia: A Multicenter Analysis of 1,473 Patients from a Prospective Surgical Registry.

INTRODUCTION: Microvascular decompression (MVD) is an efficacious neurosurgical intervention for patients with medically intractable neurovascular compression syndromes. However, MVD may occasionally cause life-threatening or altering complications, particularly in patients unfit for surgical operations. Recent literature suggests a lack of association between chronological age and surgical outcomes for MVD. The Risk Analysis Index (RAI) is a validated frailty tool for surgical populations (both clinical and large database). The present study sought to evaluate the prognostic ability of frailty, as measured by RAI, to predict outcomes for patients undergoing MVD from a large multicenter surgical registry. METHODS: The American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) database (2011-2020) was queried using diagnosis/procedure codes for patients undergoing MVD procedures for trigeminal neuralgia (n = 1,211), hemifacial spasm (n = 236), or glossopharyngeal neuralgia (n = 26). The relationship between preoperative frailty (measured by RAI and 5-factor modified frailty index [mFI-5]) for primary endpoint of adverse discharge outcome (AD) was analyzed. AD was defined as discharge to a facility which was not home, hospice, or death within 30 days. Discriminatory accuracy for prediction of AD was assessed by computation of C-statistics (with 95% confidence interval) from receiver operating characteristic (ROC) curve analysis. RESULTS: Patients undergoing MVD (N = 1,473) were stratified by RAI frailty bins: 71% with RAI 0-20, 28% with RAI 21-30, and 1.2% with RAI 31+. Compared to RAI score 19 and below, RAI 20 and above had significantly higher rates of postoperative major complications (2.8% vs. 1.1%, p = 0.01), Clavien-Dindo grade IV complications (2.8% vs. 0.7%, p = 0.001), and AD (6.1% vs. 1.0%, p < 0.001). The rate of primary endpoint was 2.4% (N = 36) and was positively associated with increasing frailty tier: 1.5% in 0-20, 5.8% in 21-30, and 11.8% in 31+. RAI score demonstrated excellent discriminatory accuracy for primary endpoint in ROC analysis (C-statistic: 0.77, 95% CI: 0.74-0.79) and demonstrated superior discrimination compared to mFI-5 (C-statistic: 0.64, 95% CI: 0.61-0.66) (DeLong pairwise test, p = 0.003). CONCLUSIONS: This was the first study to link preoperative frailty to worse surgical outcomes after MVD surgery. RAI frailty score predicts AD after MVD with excellent discrimination and holds promise for preoperative counseling and risk stratification of surgical candidates. A risk assessment tool was developed and deployed with a user-friendly calculator: https://nsgyfrailtyoutcomeslab.shinyapps.io/microvascularDecompression.

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.

Thirty-day outcomes for suboccipital decompression in adults with Chiari malformation type I: a frailty-driven perspective from the American College of Surgeons National Surgical Quality Improvement Program.

OBJECTIVE: When indicated, patients with symptomatic Chiari malformation type I (CM-I) may benefit from suboccipital decompression (SOD). Although SOD is considered a lower-risk neurosurgical procedure, preoperative risk assessment and careful surgical patient selection remain critical. The objectives of the present study were twofold: 1) describe 30-day SOD outcomes for CM patients with attention to the impact of preoperative frailty and 2) design a predictive model for the primary endpoint of nonhome discharge (NHD). METHODS: There were 1015 CM-I patients who underwent SOD in the 2011-2020 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database, as specified by diagnostic and procedural codes (Current Procedural Terminology code 61343). Descriptive statistics were used to analyze total cohort baseline demographics, preoperative comorbidities, and postoperative outcomes within 30 days of surgery. Univariate cross-tabulation was used to compare baseline demographics and preoperative characteristics across the NHD and home discharge (HD) cohorts. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminative ability of the revised Risk Analysis Index (RAI-rev) on NHD. RESULTS: The study cohort had a median age of 36 years, and 80.6% of patients were female. Race distribution was categorized as White (69.9%), Black (16.6%), and other groups (13.6%). The most common preoperative comorbidities were active smoking (24.4%), hypertension (19.2%), and diabetes mellitus (4.7%). The primary outcome of NHD occurred in 4.6% of patients (n = 47). Increasing frailty (measured by the RAI-rev) was associated with a stepwise increase in the rate of NHD: 2.3% for RAI-rev scores 0-10, 5.8% for RAI-rev scores 11-15, 7.6% for RAI-rev scores 16-20, 18.2% for RAI-rev scores 21-25, and 77.8% for RAI-rev scores ≥ 26 (p < 0.001). Other preoperative factors associated with NHD included older age, nonelective surgery, diabetes, hypertension, and elevated creatinine (all p < 0.01). The other most common 30-day complications included unplanned readmission (9.3%), unplanned reoperation (5.3%), return to the operating room (5.8%), Clavien-Dindo grade IV (life-threatening) (1.5%), organ space surgical site infection (SSI) (1.5%), superficial SSI (1.4%), and reoperation for a CSF leak (1.1%). Surgical mortality (within 30 days) was extremely rare (1/1015, 0.1%). ROC curve analysis demonstrated that RAI-rev predicted NHD with significant discriminatory accuracy among CM-I patients who received SOD treatment (C-statistic 0.731, 95% CI 0.648-0.814). CONCLUSIONS: This decade-long analysis of a multicenter surgical registry provides internationally representative, modern rates of 30-day outcomes after suboccipital decompression (with or without duraplasty) for adult CM-I patients. Preoperative frailty assessment with the RAI-rev may help identify higher-risk surgical candidates.

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/ .

Hospital-acquired infection following spinal tumor surgery: A frailty-driven pre-operative risk model.

BACKGROUND: Hospital-acquired infection (HAI) after spinal tumor resection surgery contributes to adverse patient outcomes and excess healthcare resource utilization. This study sought to develop a predictive model for HAI occurrence following surgery for spinal tumors. METHODS: The National Surgical Quality Improvement Program (NSQIP) 2015-2019 database was queried for spinal tumor resections. Baseline demographics and preoperative clinical characteristics, including frailty, were analyzed. Frailty was measured by modified frailty score 5 (mFI-5) and risk analysis index (RAI). Univariate and multivariable analyses were performed to identify independent risk factors for HAI occurrence. A logit-based predictive model for HAI occurrence was designed and discriminative power was assessed via receiver operating characteristic (ROC) analysis. RESULTS: Of 5883 patients undergoing spinal tumor surgery, HAI occurred in 574 (9.8 %). The HAI (vs. non-HAI) cohort was older and frailer with higher rates of preoperative functional dependence, chronic steroid use, chronic lung disease, coagulopathy, diabetes, hypertension, tobacco smoking, unintentional weight loss, and hypoalbuminemia (all P < 0.05). In multivariable analysis, independent predictors of HAI occurrence included severe frailty (mFI-5, OR: 2.3, 95 % CI: 1.1-5.2, P = 0.035), nonelective surgery (OR: 1.7, 95 % CI: 1.1-2.4, P = 0.007), and hypoalbuminemia (OR: 1.5, 95 % CI: 1.1-2.2, P = 0.027). A logistic regression model with frailty score alongside age, race, BMI, elective vs. non-elective surgery, and pre-operative labs have predicted HAI occurrence with a C-statistic of 0.68 (95 % CI: 0.64-0.72). CONCLUSIONS: HAI occurrence after spinal tumor surgery can be predicted by standardized frailty metrics, mFI-5 and RAI-rev, alongside routinely measured preoperative characteristics (demographics, comorbidities, pre-operative labs).

Frailty predicts worse outcomes for spine surgery patients with interhospital transfer status: Analysis of 295,875 patients from the National Surgical Quality Improvement Program (NSQIP) 2015-2019.

STUDY DESIGN: Retrospective analysis of a prospectively maintained database. OBJECTIVES: To evaluate the effects of interhospital transfer (IHT) status, age, and frailty on postoperative outcomes in patients who underwent spine surgery. METHODS: The National Surgical Quality Improvement Program (NSQIP) database was queried for patients who underwent spine surgeries from 2015 to 2019 (N = 295,875). Univariate and multivariable analyses were utilized to analyze the effect of IHT on postoperative outcomes and the contribution of baseline frailty status (mFI-5 score stratified into "pre-frail", "frail", and "severely frail") on outcomes in IHT patients. Effect sizes were summarized by odds ratio (OR) with associated 95% confidence intervals (95% CI). RESULTS: Of 295,875 patients in the study, 3.3% (N = 9666) were IHT status. On multivariable analysis, controlling for covariates, IHT status was significantly associated with greater likelihood of 30-day mortality (odds ratio [OR] = 9.3), major complications (OR=5.0), Clavien-Dindo (CD) grade IV complications (OR=7.0), unplanned readmission (OR=2.1), unplanned reoperation (OR=2.6), eLOS (OR=16.1), and discharge to non-home destination (OR=12.7) (all P < 0.001). Increasing frailty was significantly associated with poor outcomes in spine surgery patients with IHT status compared to chronological age. CONCLUSIONS: This study provides evidence that IHT status is associated with poor outcomes in spine surgery patients. Furthermore, increasing frailty more than increasing age was a robust predictor of poor outcomes among IHT spine surgical patients. Baseline frailty status, as measured by the mFI-5, may be utilized for preoperative risk stratification of patients with IHT status with anticipated spine surgery.

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.

Preoperative risk model for perioperative stroke after intracranial tumor resection: ACS NSQIP analysis of 30,951 cases.

OBJECTIVE: Perioperative and/or postoperative cerebrovascular accidents (PCVAs) after intracranial tumor resection (ITR) are serious complications with devastating effects on quality of life and survival. Here, the authors retrospectively analyzed a prospectively maintained, multicenter surgical registry to design a risk model for PCVA after ITR to support efforts in neurosurgical personalized medicine to risk stratify patients and potentially mitigate poor outcomes. METHODS: The National Surgical Quality Improvement Program database was queried for ITR cases (2015-2019, n = 30,951). Patients with and without PCVAs were compared on baseline demographics, preoperative clinical characteristics, and outcomes. Frailty (physiological reserve for surgery) was measured by the Revised Risk Analysis Index (RAI-rev). Logistic regression analysis was performed to identify independent associations between preoperative covariates and PCVA occurrence. The ITR-PCVA risk model was generated based on logit effect sizes and assessed in area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: The rate of PCVA was 1.7% (n = 532). Patients with PCVAs, on average, were older and frailer, and had increased rates of nonelective surgery, interhospital transfer status, diabetes, hypertension, unintentional weight loss, and elevated BUN. PCVA was associated with higher rates of postoperative reintubation, infection, thromboembolic events, prolonged length of stay, readmission, reoperation, nonhome discharge destination, and 30-day mortality (all p < 0.001). In multivariable analysis, predictors of PCVAs included RAI "frail" category (OR 1.7, 95% CI 1.2-2.4; p = 0.006), Black (vs White) race (OR 1.5, 95% CI 1.1-2.1; p = 0.009), nonelective surgery (OR 1.4, 95% CI 1.1-1.7; p = 0.003), diabetes mellitus (OR 1.5, 95% CI 1.1-1.9; p = 0.002), hypertension (OR 1.4, 95% CI 1.1-1.7; p = 0.006), and preoperative elevated blood urea nitrogen (OR 1.4, 95% CI 1.1-1.8; p = 0.014). The ITR-PCVA predictive model was proposed from the resultant multivariable analysis and performed with a modest C-statistic in AUROC analysis of 0.64 (95% CI 0.61-0.66). Multicollinearity diagnostics did not detect any correlation between RAI-rev parameters and other covariates (variance inflation factor = 1). CONCLUSIONS: The current study proposes a novel preoperative risk model for PCVA in patients undergoing ITR. Patients with poor physiological reserve (measured by frailty), multiple comorbidities, abnormal preoperative laboratory values, and those admitted under high acuity were at highest risk. The ITR-PCVA risk model may support patient-centered counseling striving to respect goals of care and maximize quality of life. Future prospective studies are warranted to validate the ITR-PCVA risk model and evaluate its utility as a bedside clinical tool.

Preoperative frailty measured by risk analysis index predicts complications and poor discharge outcomes after Brain Tumor Resection in a large multi-center analysis.

PURPOSE: To evaluate the independent effect of frailty, as measured by the Risk Analysis Index-Administrative (RAI-A) for postoperative complications and discharge outcomes following brain tumor resection (BTR) in a large multi-center analysis. METHODS: Patients undergoing BTR were queried from the National Surgical Quality Improvement Program (NSIQP) for the years 2015 to 2019. Multivariable logistic regression was performed to evaluate the independent associations between frailty tools (age, 5-factor modified frailty score [mFI-5], and RAI-A) on postoperative complications and discharge outcomes. RESULTS: We identified 30,951 patients who underwent craniotomy for BTR; the median age of our study sample was 59 (IQR 47-68) years old and 47.8% of patients were male. Overall, increasing RAI-A score, in an overall stepwise fashion, was associated with increasing risk of adverse outcomes including in-hospital mortality, non-routine discharge, major complications, Clavien-Dindo Grade IV complication, and extended length of stay. Multivariable regression analysis (adjusting for age, sex, BMI, non-elective surgery status, race, and ethnicity) demonstrated that RAI-A was an independent predictor for worse BTR outcomes. The RAI-A tiers 41-45 (1.2% cohort) and > 45 (0.3% cohort) were ~ 4 (Odds Ratio [OR]: 4.3, 95% CI: 2.1-8.9) and ~ 9 (OR: 9.5, 95% CI: 3.9-22.9) times more likely to have in-hospital mortality compared to RAI-A 0-20 (34% cohort). CONCLUSIONS AND RELEVANCE: Increasing preoperative frailty as measured by the RAI-A score is independently associated with increased risk of complications and adverse discharge outcomes after BTR. The RAI-A may help providers present better preoperative risk assessment for patients and families weighing the risks and benefits of potential BTR.

Worse cranial neurosurgical outcomes predicted by increasing frailty in patients with interhospital transfer status: Analysis of 47,736 patients from the National Surgical Quality Improvement Program (NSQIP) 2015-2019.

INTRODUCTION: With limited healthcare resources and risks associated with unwarranted interhospital transfers (IHT), it is important to select patients most likely to have improved outcomes with IHT. The present study analyzed the effect of IHT and frailty on postoperative outcomes in a large database of patients who underwent cranial neurosurgical operations. METHODS: The National Surgical Quality Improvement Program (NSQIP) database was queried for patients who underwent cranial neurosurgical procedures (2015-2019, N = 47,736). Baseline demographics, clinical characteristics, and outcome variables were compared between IHT and n-IHT patients. Univariate and multivariable analyses analyzed the effect of IHT status on postoperative outcomes and the utility of frailty (modified frailty index-5 [mFI-5] stratified into "pre-frail, "frail", and "severely frail") as a preoperative risk factor. Effect sizes from regression analyses were presented as odds ratio (OR) with associated 95% confidence intervals (95% CI). RESULTS: Of 47,736 patients with cranial neurosurgical operations, 9612 (20.1%) were IHT. Patients with IHT were older, frailer, with a higher rate of functional dependence. In multivariable analysis adjusted for baseline covariates, IHT status was independent associated with 30-day mortality (OR: 2.0, 95% CI: 1.2-3.6), major complication (OR: 1.5, 95% CI: 1.1-2.1), extended hospital length of stay (eLOS) (OR: 3.8, 95% CI: 3.6-4.1), and non-routine discharge disposition (OR: 2.4, 95% CI: 1.8-3.2) (all p < 0.05). Within the IHT cohort, increasing frailty ("pre-frail", "frail", "severely frail") was independently associated with increasing odds of 30-day mortality (OR: 1.4, 1.9, 3.9), major complication (OR: 1.4, 1.9, 3.3), unplanned readmission (OR: 1.1, 1.4, 2.1), reoperation (OR: 1.3, 1.5, 1.9), eLOS (OR: 1.2, 1.3, 1.5), and non-routine discharge (OR: 1.4, 1.9, 4.4) (all p < 0.05). All levels of frailty were more strongly associated with postoperative outcomes than chronological age. CONCLUSIONS: This novel analysis suggests that patients transferred for cranial neurosurgery operations are significantly more likely to have worse postoperative health outcomes. Furthermore, the analysis suggests that frailty (as measured by mFI-5) is a powerful independent predictor of outcomes in transferred cranial neurosurgery patients. The findings support the use of frailty scoring in the pre-transfer and preoperative setting for patient counseling and risk stratification.