The risk analysis index demonstrates exceptional discrimination in predicting frailty's impact on neurosurgical length of stay quality metrics.

BACKGROUND: Quality measures determine reimbursement rates and penalties in value-based payment models. Frailty impacts these quality metrics across surgical specialties. We compared the discriminatory thresholds for the risk analysis index (RAI), modified frailty index-5 (mFI-5) and increasing patient age for the outcomes of extended length of stay (LOS [eLOS]), prolonged LOS within 30 days (pLOS), and protracted LOS (LOS > 30). METHODS: Patients ≥18 years old who underwent neurosurgical procedures between 2012 and 2020 were queried from the ACS-NSQIP. We performed receiver operating characteristic analysis, and multivariable analyses to examine discriminatory thresholds and identify independent associations. RESULTS: There were 411,605 patients included, with a median age of 59 years (IQR, 48-69), 52.2% male patients, and a white majority 75.2%. For eLOS: RAI C-statistic 0.653 (95% CI: 0.652-0.655), versus mFI-5 C-statistic 0.552 (95% CI: 0.550-0.554) and increasing patient age C-statistic 0.573 (95% CI: 0.571-0.575). Similar trends were observed for pLOS- RAI: 0.718, mFI-5: 0.568, increasing patient age: 0.559, and for LOS>30- RAI: 0.714, mFI-5: 0.548, and increasing patient age: 0.506. Patients with major complications had eLOS 10.1%, pLOS 26.5%, and LOS >30 45.5%. RAI showed a larger effect for all three outcomes, and major complications in multivariable analyses. CONCLUSION: Increasing frailty was associated with three key quality metrics that is, eLOS, pLOS, LOS > 30 after neurosurgical procedures. The RAI demonstrated a higher discriminating threshold compared to both mFI-5 and increasing patient age. Preoperative frailty screening may improve quality metrics through risk mitigation strategies and better preoperative communication with patients and their families.

Frailty Predicts 30-day mortality following major complications in neurosurgery patients: The risk analysis index has superior discrimination compared to modified frailty index-5 and increasing patient age.

Background: Postoperative complications after cranial or spine surgery are prevalent, and frailty can be a key contributing patient factor. Therefore, we evaluated frailty's impact on 30-day mortality. We compared the discrimination for risk analysis index (RAI), modified frailty index-5 (mFI-5) and increasing patient age for predicting 30-day mortality. Methods: Patients with major complications following neurosurgery procedures between 2012- 2020 in the ACS-NSQIP database were included. We employed receiver operating characteristic (ROC) curve and examined discrimination thresholds for RAI, mFI-5, and increasing patient age for 30-day mortality. Independent relationships were examined using multivariable analysis. Results: There were 19,096 patients included in the study and in the ROC analysis for 30-day mortality, RAI showed superior discriminant validity threshold C-statistic 0.655 (95% CI: 0.644-0.666), compared to mFI-5 C-statistic 0.570 (95% CI 0.559-0.581), and increasing patient age C-statistic 0.607 (95% CI 0.595-0.619). When the patient population was divided into subsets based on the procedures type (spinal, cranial or other), spine procedures had the highest discriminant validity threshold for RAI (Cstatistic 0.717). Furthermore, there was a frailty risk tier dose response relationship with 30-day mortalityy (p<0.001). Conclusion: When a major complication arises after neurosurgical procedures, frail patients have a higher likelihood of dying within 30 days than their non-frail counterparts. The RAI demonstrated a higher discriminant validity threshold than mFI-5 and increasing patient age, making it a more clinically relevant tool for identifying and stratifying patients by frailty risk tiers. These findings highlight the importance of initiatives geared toward optimizing frail patients, to mitigate long-term disability.

The Weight of Frailty in Neurosurgery Patients: Analyzing the Combined Effect of Frailty and Body Mass Index on 30-Day Postoperative Mortality.

OBJECTIVE: There is a rising prevalence of overweight and obese persons in the US, and there is a paucity of information about the relationship between frailty and body mass index. Therefore, we examined discrimination thresholds and independent relationships of the risk analysis index (RAI), modified frailty index-5 (mFI-5), and increasing patient age in predicting 30-day postoperative mortality. METHODS: This retrospective American College of Surgeons National Surgical Quality Improvement Program analysis compared all overweight or obese adult patients who underwent neurosurgery procedures between 2012 and 2020. We compared discrimination using receiver operating characteristic curve analysis for RAI, mFI-5, and increasing patient age. Furthermore, multivariable analyses, as well as subgroup analyses by procedure type i.e., spine, skull base, and other (vascular and functional) were performed, and reported as odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: We included 315,725/412,909 (76.5%) neurosurgery patients, with a median age of 59 years (interquartile range: 48-68), predominately White 76.7% and male 54.3%. Receiver operating characteristic analysis for 30-day postoperative mortality demonstrated a higher discriminatory threshold for RAI (C-statistic: 0.790, 95%CI: 0.782-0.800) compared to mFI-5 (C-statistic: 0.692, 95%CI: 0.620-0.638) and increasing patient age (C-statistic: 0.659, 95%CI: 0.650-0.668). Multivariable analyses showed a dose-dependent association and a larger magnitude of effect by RAI: frail patients OR: 11.82 (95%CI: 10.57-13.24), and very frail patients OR: 31.19 (95%CI: 24.87-39.12). A similar trend was observed in all subgroup analyses i.e., spine, skull base, and other (vascular and functional) procedures (P ≤ 0.001). CONCLUSIONS: Increasing frailty was associated with a higher rate of 30-day postoperative mortality, with a dose-dependent effect. Furthermore, the RAI had a higher threshold for discrimination and larger effect sizes than mFI-5 and increasing patient age. These findings support RAI's use in preoperative assessments, as it has the potential to improve postoperative outcomes through targeted interventions.

Multiplicative effect of frailty and obesity on postoperative mortality following spine surgery: a deep dive into the frailty, obesity, and Clavien-Dindo dynamic.

BACKGROUND/OBJECTIVES: Obesity is a global health challenge that affects a large proportion of adults worldwide. Obesity and frailty pose considerable health risks due to their potential to interact and amplify one another's negative effects. Therefore, we sought to compare the discriminatory thresholds of the risk analysis index (RAI), 5-factor modified frailty index (m-FI-5) and patient age for the primary endpoint of postoperative mortality. SUBJECTS/METHODS: We included spine surgery patients ≥18 years old, from the American College of Surgeons National Quality Improvement program database from 2012-2020, that were classified as obese. We performed receiver operating characteristic curve analysis to compare the discrimination threshold of RAI, mFI-5, and patient age for postoperative mortality. Proportional hazards risk-adjusted regressions were performed, and Hazard ratios and corresponding 95% Confidence intervals (CI) are reported. RESULTS: Overall, there were 149 163 patients evaluated, and in the ROC analysis for postoperative mortality, RAI showed superior discrimination C-statistic 0.793 (95%CI: 0.773-0.813), compared to mFI-5 C-statistic 0.671 (95%CI 0.650-0.691), and patient age C-statistic 0.686 (95%CI 0.666-0.707). Risk-adjusted analyses were performed, and the RAI had a stepwise increasing effect size across frailty strata: typical patients HR 2.55 (95%CI 2.03-3.19), frail patients HR 3.48 (95%CI 2.49-4.86), and very frail patients HR 4.90 (95%CI 2.87-8.37). We found increasing postoperative mortality effect sizes within Clavein-Dindo complication strata, consistent across obesity categories, exponentially increasing with frailty, and multiplicatively enhanced within CD, frailty and obesity strata. CONCLUSION: In this study of 149 163 patients classified as obese and undergoing spine procedures in an international prospective surgical database, the RAI demonstrated superior discrimination compared to the mFI-5 and patient age in predicting postoperative mortality risk. The deleterious effects of frailty and obesity were synergistic as their combined effect predicted worse outcomes.

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.

The anatomy of the four streams of the prefrontal cortex. Preliminary evidence from a population based high definition tractography study.

The model of the four streams of the prefrontal cortex proposes 4 streams of information: motor through Brodmann area (BA) 8, emotion through BA 9, memory through BA 10, and emotional-related sensory through BA 11. Although there is a surge of functional data supporting these 4 streams within the PFC, the structural connectivity underlying these neural networks has not been fully clarified. Here we perform population-based high-definition tractography using an averaged template generated from data of 1,065 human healthy subjects acquired from the Human Connectome Project to further elucidate the structural organization of these regions. We report the structural connectivity of BA 8 with BA 6, BA 9 with the insula, BA 10 with the hippocampus, BA 11 with the temporal pole, and BA 11 with the amygdala. The 4 streams of the prefrontal cortex are subserved by a structural neural network encompassing fibers of the anterior part of the superior longitudinal fasciculus-I and II, corona radiata, cingulum, frontal aslant tract, and uncinate fasciculus. The identified neural network of the four streams of the PFC will allow the comprehensive analysis of these networks in normal and pathological brain function.

A comprehensive analysis of the triad of frailty, aging, and obesity in spine surgery: the risk analysis index predicted 30-day mortality with superior discrimination.

BACKGROUND CONTEXT: The United States has experienced substantial shifts in its population dynamics due to an aging population and increasing obesity rates. Nonetheless, there is limited data about the interplay between the triad of frailty, aging, and obesity. PURPOSE: To investigate discriminative thresholds and independent associations of the Risk Analysis Index (RAI), Modified Frailty Index-5 (mFI-5), and greater patient age. STUDY DESIGN: An observational retrospective cohort study. PATIENT SAMPLE: We analyzed 49,754 spine surgery patients from the American College of Surgeons National Surgical Quality Improvement Program database from 2012 to 2020. OUTCOME MEASURE: A total of 30-day postoperative mortality. METHODS: Using receiver operating characteristic (ROC) and multivariable (odds ratios [OR] and 95% confidence intervals [CI]) analyses, we compared the discriminative thresholds and independent associations of RAI, mFI-5, and greater patient age in elderly obese patients who underwent spine surgery. RESULTS: There were 49,754 spine surgery patients, with a median age of 71 years (IQR: 68-75), largely white (82.6%) and male (51.9%). The ROC analysis for 30-day postoperative mortality demonstrated superior discrimination for RAI (C-statistic 0.779, 95%CI 0.54-0.805) compared to mFI-5 (C-statistic 0.623, 95% CI 0.594-0.651) and greater patient age (C-statistic 0.627, 95% CI 0.598-0.656). Multivariable analyses revealed a dose-dependent association and a larger effect magnitude for RAI: frail patients OR: 19.52 (95% CI 18.29-20.82) and very frail patients OR: 65.81 (95% CI 62.32-69.50). A similar trend was observed in the interaction evaluating RAI-age-obesity (p<.001). CONCLUSION: Our study highlights a strong association between frailty and 30-day postoperative mortality in elderly obese spine patients, revealing a dose-dependent relationship. The RAI has superior discrimination than the mFI-5 and greater patient age in predicting 30-day postoperative mortality after spine surgery. Using the RAI in preoperative assessments may improve outcomes and help healthcare providers effectively communicate accurate surgical risks and potential benefits, set realistic recovery expectations, and enhances patient satisfaction.

Prospective application of the risk analysis index to measure preoperative frailty in spinal tumor surgery: A single center outcomes analysis.

Introduction: Surgeons are frequently faced with challenging clinical dilemmas evaluating whether the benefits of surgery outweigh the substantial risks routinely encountered with spinal tumor surgery. The Clinical Risk Analysis Index (RAI-C) is a robust frailty tool administered via a patient-friendly questionnaire that strives to augment preoperative risk stratification. The objective of the study was to prospectively measure frailty with RAI-C and track postoperative outcomes after spinal tumor surgery. Methods: Patients surgically treated for spinal tumors were followed prospectively from 7/2020-7/2022 at a single tertiary center. RAI-C was ascertained during preoperative visits and verified by the provider. The RAI-C scores were assessed in relation to postoperative functional status (measured by modified Rankin Scale score [mRS]) at the last follow-up visit. Results: Of 39 patients, 47% were robust (RAI 0-20), 26% normal (21-30), 16% frail (31-40), and 11% severely frail (RAI 41+).). Pathology included primary (59%) and metastatic (41%) tumors with corresponding mRS>2 rates of 17% and 38%, respectively. Tumors were classified as extradural (49%), intradural extramedullary (46%), or intradural intramedullary (5.4%) with mRS>2 rates of 28%, 24%, and 50%, respectively. RAI-C had a positive association with mRS>2 â€‹at follow-up: 16% for robust, 20% for normal, 43% for frail, and 67% for severely frail. The two deaths in the series had the highest RAI-C scores (45 and 46) and were patients with metastatic cancer. The RAI-C was a robust and diagnostically accurate predictor of mRS>2 in receiver operating characteristic curve analysis (C-statistic: 0.70, 95 CI: 0.49-0.90). Conclusions: The findings exemplify the clinical utility of RAI-C frailty scoring for prediction of outcomes after spinal tumor surgery and it has potential to help in the surgical decision-making process as well as surgical consent. As a preliminary case series, the authors intend to provide additional data with a larger sample size and longer follow-up duration in a future study.

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).