Andexanet alfa therapy showed No increased rate of thromboembolic events in spontaneous intracranial hemorrhage patients: A multicenter electronic health record study.

•Intracranial hemorrhage accounts for two out of every three major intracranial hemorrhages.•Systemic anticoagulation is routinely prescribed for prevention of cerebrovascular accidents.•The FDA approved Andexanet alfa to treat life-threatening bleeding.•Andexanet alfa relationship to outcomes requires further investigation.

The 5-item modified frailty index predicts spinal osteotomy outcomes better than age in adult spinal deformity patients: an ACS - NSQIP analysis.

PURPOSE: To evaluate the utility of 5-Item Modified Frailty Index (mFI-5) as compared to chronological age in predicting outcomes of spinal osteotomy in Adult Spinal Deformity (ASD) patients. METHODS: Using Current Procedural and Terminology (CPT) codes, the American College of Surgeons National Surgery Quality Improvement Program (ACS-NSQIP) database was queried for adult patients undergoing spinal osteotomy from 2015 to 2019. Multivariate regression analysis was performed to evaluate the effect of baseline frailty status, measured by mFI-5 score, and chronological age on postoperative outcomes. Receiver-operating characteristic (ROC) curve analysis was performed to analyze the discriminative performance of age versus mFI-5. RESULTS: A total of 1,789 spinal osteotomy patients (median age 62 years) were included in the analysis. Among the patients assessed, 38.5% (n = 689) were pre-frail, 14.6% frail (n = 262), and 2.2% (n = 39) severely frail using the mFI-5. Based on the multivariate analysis, increasing frailty tier was associated with worsening outcomes, and higher odds ratios (OR) for poor outcomes were found for increasing frailty tiers as compared to age. Severe frailty was associated with the worst outcomes, e.g., unplanned readmission (OR 9.618, [95% CI 4.054-22.818], p < 0.001) and major complications (OR 5.172, [95% CI 2.271-11.783], p < 0.001). In the ROC curve analysis, mFI-5 score (AUC 0.838) demonstrated superior discriminative performance than age (AUC 0.601) for mortality. CONCLUSIONS: The mFI5 frailty score was found to be a better predictor than age of worse postoperative outcomes in ASD patients. Incorporating frailty in preoperative risk stratification is recommended in ASD surgery.

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.

Clinically predictive baseline labs for post-operative outcomes of brain tumors using NSQIP database.

PURPOSE: This study was performed to assess the effect of baseline Preoperative Laboratory Values (PLV) on post-operative Brain Tumor Resection (BTR) outcomes in a large national registry. METHODS: We extracted data from the National Surgical Quality Improvement Program (NSQIP) database for BTR patients 2015-2019 (n = 3 0,951). Uni- and multivariate analyses were performed for PLV and key surgical outcomes. RESULTS: The most significant PLV predictors of 30-day mortality after BTR included hypernatremia (odds ratio, OR 4.184, 95% CI, 2.384-7.343, p < 0.001), high serum creatinine (OR 2.244, 95% CI 1.502-3.352, p < 0.001), thrombocytopenia (OR 1.997, 95% CI 1.438, 2.772, p < 0.001), and leukocytosis (OR 1.635, 95% CI 1.264, 2.116, p < 0.001). The most significant predictors of Clavien IV complications were increased INR (OR 2.653, 95% CI 1.444, 4.875, p < 0.01), thrombocytopenia (OR 1.514, 95% CI 1.280, 1.792, p < 0.001), hypoalbuminemia (OR 1.480, 95% CI 1.274, 1.719, p < 0.001), and leukocytosis (OR 1.467, 95% CI 1.306, 1.647, p < 0.001). The most robust predictors of eLOS were increased INR (OR 1.941, 95% CI 1.231, 3.060, p < 0.01) and hypoalbuminemia (OR 1.993, 95% CI 1.823, 2.179, p < 0.001), and those for non-routine discharge included increased INR (OR 1.897, 95% CI 1.196, 3.008, p < 0.01) and hypernatremia (OR 1.565, 95% CI 1.217, 2.012, p < 0.001). CONCLUSIONS: Several PLV independently predicted worse outcomes in BTR patients. Baseline labs should be routinely used for the pre-operative risk stratification of these patients.

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/ .

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.

Association of baseline frailty and age with postoperative outcomes in metastatic brain tumor patients.

BACKGROUND: The impact of baseline frailty status versus that of chronological age on surgical outcomes of metastatic brain tumor patients remains largely unknown. The present study aimed to evaluate this relationship for preoperative risk stratification using a large national database. METHODS: The National Surgical Quality Improvement Program database was queried to extract data of metastatic brain tumor patients who underwent surgery between 2015 and 2019 (n=5,943). Univariate and multivariate analyses were performed to assess the effect of age and modified frailty index-5 (mFI-5) on mortality, major complications, unplanned readmission and reoperation, extended length of stay (eLOS), and non-home discharge. RESULTS: Both univariate and multivariate analyses demonstrated that frailty status was significantly predictive of 30-day mortality, major complications, eLOS, and non-home discharge. Although increasing age was also a significant predictor of eLOS and discharge to non-home destination, effect sizes were smaller compared with frailty. CONCLUSIONS: The present study, based on analysis of data from a large national registry, shows that frailty, when compared with age, is a superior predictor of postoperative outcomes in metastatic brain tumor patients. A future prospective study, namely a randomized controlled trial, would be beneficial in helping to corroborate the findings of this retrospective study.

Perioperative Risk Stratification Model for Readmission after Panniculectomy.

BACKGROUND: Readmission is an important metric for surgical quality of care. This study aimed to develop a validated risk model that reliably predicts readmission after panniculectomy using the American College of Surgeons National Surgical Quality Improvement Program database. METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was queried to identify all patients who had undergone panniculectomy from 2005 to 2018. The outcome of interest was 30-day readmission. The cohort was divided randomly into 70 percent development and 30 percent validation groups. Independent predictors of 30-day readmission were identified using multivariable logistic regression on the development group. The predictors were weighted according to beta coefficients to generate an integer-based clinical risk score predictive of readmission, which was validated against the validation group. RESULTS: For the model selection, 22 variables were identified based on criteria of p < 0.05 percent and complete data availability. Variables included in the development model included inpatient surgery, hypertension, obesity, functional dependence, chronic obstructive pulmonary disease, wound class greater than or equal to 3, American Society of Anesthesiologists class greater than 3, and liposuction. Receiver operating characteristic curve analysis of the validation group rendered an area under the curve of 0.710, which demonstrates the accuracy of this prediction model. The predicted incidence within each risk stratum was statistically similar to the observed incidence in the validation group ( p < 0.01), further highlighting the accuracy of the model. CONCLUSIONS: The authors present a validated risk stratification model for readmission following panniculectomy. Prospective studies are needed to determine whether the implementation of the authors' clinical risk score optimizes safety and reduces readmission rates. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

Worse Pituitary Adenoma Surgical Outcomes Predicted by Increasing Frailty, Not Age.

PURPOSE: Increasing patient age has been associated with worse outcomes after pituitary adenoma resection in previous studies, but the prognostic value of frailty compared with advancing age on pituitary adenoma resection outcomes has not been clearly evaluated. METHODS: The National Surgical Quality Improvement Program from 2015 to 2019 was queried for data for patients aged >18 years who underwent pituitary adenoma resection (n = 1454 identified patients). Univariate and multivariate analyses of age and frailty (5-factor modified frailty index [mFI-5]) were performed on 30-day mortality, major complications, extended length of stay (eLOS), discharge destination, and readmission and reoperation. The receiver operating characteristic curve analysis was performed to compare effect of age and mFI-5. RESULTS: On univariate analysis, increasing frailty was significantly associated with greater risk of unplanned readmission (frail: odds ratio [OR], 1.9; 95% confidence interval [CI], 1.2-3.2; severely frail: OR, 6.9; 95% CI, 2.4-19.8) and a major complication (frail: OR, 3.6; 95% CI, 2.1-6.1). Severe frailty was also associated with nonhome discharge (OR, 10.6; 95% CI, 3.2-35.8) and eLOS (OR, 4.5; 95% CI, 1.5-13.4). Increasing age was not associated with any of these outcome measures. Multivariate analysis also demonstrated similar trends. In receiver operating characteristic curve analysis, the mFI-5 score showed higher discrimination for major complications compared with age (area under the curve: 0.624 vs. 0.503; P < 0.001). CONCLUSION: Increasing frailty, and not advancing age, was an independent predictor for major complications, unplanned readmissions, eLOS, and nonhome discharge after pituitary adenoma resection, suggesting frailty to be superior to age in preoperative risk stratification in this patient population.

Association of baseline frailty status and age with outcomes in patients undergoing intracranial meningioma surgery: Results of a nationwide analysis of 5818 patients from the National Surgical Quality Improvement Program (NSQIP) 2015-2019.

PURPOSE: The objective of this study was to compare the effect of frailty, as measured by the 5-factor modified frailty index (mFI-5), with that of age on postoperative outcomes of patients undergoing surgery for intracranial meningiomas, using data from a large national registry. METHODS: The National Surgical Quality Improvement Program (NSQIP) database (2015-2019) was queried to analyze data from patients undergoing intracranial meningioma resection (N = 5,818). Univariate and multivariate analyses of age and mFI-5 score were performed for 30-day mortality, major complications, unplanned reoperation, unplanned readmission, extended hospital length of stay (eLOS), and discharge to a non-home destination. RESULTS: Both univariate and multivariate analyses (adjusted for sex, body mass index, transfer status, smoking, and operative time) demonstrated that mFI-5 and age were significant predictors of adverse postoperative outcomes in patients with intracranial meningioma. However, based on odds ratios (OR) and effect sizes, increasing frailty tiers were better predictors than age of adverse outcomes. Severely frail patients showed highest effects sizes for all postoperative outcome variables [OR 11.17 (95% CI 3.45-36.19), p<0.001 for mortality; OR 4.15 (95% CI 2.46-6.99), p<0.001 for major complications; OR 4.37 (95% CI 2.68-7.12), p<0.001 for unplanned readmission; OR 2.31 (95% CI 1.17-4.55), p<0.001 for unplanned reoperation; OR 4.28 (95% CI 2.74-6.68), p<0.001 for eLOS; and OR 9.34 (95% CI 6.03-14.47, p<0.001) for discharge other than home. CONCLUSION: In this national database study, baseline frailty status was a better independent predictor for worse postoperative outcomes than age in patients with intracranial meningioma.

Risk Analysis Index and Its Recalibrated Version Predict Postoperative Outcomes Better Than 5-Factor Modified Frailty Index in Traumatic Spinal Injury.

OBJECTIVE: To assess the discriminative ability of the Risk Analysis Index-administrative (RAI-A) and its recalibrated version (RAI-Rev), compared to the 5-factor modified frailty index (mFI-5), in predicting postoperative outcomes in patients undergoing surgical intervention for traumatic spine injuries (TSIs). METHODS: The Current Procedural Terminology (CPT) and International Classification of Disease-9 (ICD-9) and ICD-10 codes were used to identify patients ≥ 18 years who underwent surgical intervention for TSI from National Surgical Quality Improvement Program (ACS-NSQIP) database 2015-2019 (n = 6,571). Multivariate analysis and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the comparative discriminative ability of RAI-Rev, RAI-A, and mFI-5 for 30-day postoperative outcomes. RESULTS: Multivariate regression analysis showed that with all 3 frailty scores, increasing frailty tiers resulted in worse postoperative outcomes, and patients identified as frail and severely frail using RAI-Rev and RAI-A had the highest odds of poor outcomes. In the ROC curve/C-statistics analysis for prediction of 30-day mortality and morbidity, both RAI-Rev and RAI-A outperformed mFI-5, and for many outcomes, RAI-Rev showed better discriminative performance compared to RAI-A, including mortality (p = 0.0043, DeLong test), extended length of stay (p = 0.0042), readmission (p < 0.0001), reoperation (p = 0.0175), and nonhome discharge (p < 0.0001). CONCLUSION: Both RAI-Rev and RAI-A performed better than mFI-5, and RAI-Rev was superior to RAI-A in predicting postoperative mortality and morbidity in TSI patients. RAI-based frailty indices can be used in preoperative risk assessment of spinal trauma patients.

Modified Frailty Index (mFI) predicts 30-day complications after microsurgical breast reconstruction.

Frailty lacks a universal definition. The modified Frailty Index (mFI) using patient comorbidities can be used to measure frailty. We hypothesized that mFI predicts 30-day complications after microsurgical breast reconstruction. American College of Surgeons' (ACS) National Surgical Quality Improvement Project (NSQIP) was investigated to identify patients undergoing microsurgical breast reconstruction between 2005-2014 using Current Procedure Terminology (CPT) code, 19364. We used mFI as a measure of frailty. The patients were assigned a frailty score based on the number of preoperative comorbid conditions as defined by the mFI. Other risk indices used include age, BMI, wound class, ASA class. Stratification was performed in ascending order for each. The outcome measure was aggregate 30-day complications. Regression analysis was performed followed by Receptor Operating Characteristic (ROC) curve to determine the accuracy of each risk index in predicting 30-day complications. Of the 3237 patients 24% experienced complications. Univariate logistic regression analysis found odds ratio of complications for frailty score 1 = 22.1 (CI = 17.9-27.3, p < 0.01), and 2 = 28 (CI = 18.3-43, p < 0.01) compared to frailty score = 0. ROC curve demonstrated mFI with the highest concordance score (c-score = 0.816). Multivariable logistic regression found frailty as the strongest independent predictor of 30-day aggregate complications adjusted OR = 22.24, CI = 17.77-27.82, p < 0.01 when compared to other risk indices. The modified Frailty Index is a simple, reliable, and objective tool that can be used to predict postoperative complications after microsurgical breast reconstruction. The application of this tool can help microsurgeons preoperatively identify patients who are at high risk.Abbreviations: ACS: American College of Surgeons; ASA: American Society of Anesthesiologists; BMI: body mass index; CHF: congestive heart failure; CPT: current procedural terminology; COPD: chronic obstructive pulmonary disease; CVA: cerebrovascular accident; DM: diabetes mellitus; IRB: institutional review board; mfi: modified frailty index; MI: myocardial infarction; NSQIP: national surgical quality improvement program; PVD: peripheral vascular disease; ROC: receptor operating characteristic; TIA: transient ischemic attach.