Frailty Is Associated with In-Hospital Morbidity and Nonroutine Disposition in Brain Tumor Patients Undergoing Craniotomy

Frailty Predicts Failure to Rescue Following Malignant Brain Tumor Resection: A National Surgical Quality Improvement Program Analysis of 14,721 Patients/ (2012-2020)

OBJECTIVE

Failure to rescue (FTR) is defined as mortality within 30 days following a major complication. While FTR has been studied in various brain tumor resections, its predictors in malignant brain tumor resection (mBTR) remain unexplored. This study aims to identify FTR predictors in mBTR resection patients using a frailty-driven model.

METHODS

Patients undergoing craniotomy for mBTR were identified from the American College of Surgeons-National Surgical Quality Improvement Program database (2012-2020), with frailty measured by the Risk Analysis Index (RAI).

RESULTS

Of 14,721 mBTR patients, 1275 (8.66%) developed major postoperative complications and 166 (13.01%) experienced FTR. The cohort's median age was 59 years (interquartile range: 47-68). Multivariate analysis revealed nonelective surgery (odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.02-2.16, P < 0.05) as an independent risk factor for FTR. Frailty was a significant independent predictor of FTR with mBTR, with both frail (N = 110) and very frail (N = 22) patients having a 5.34-fold and 8.10-fold higher odds of FTR, respectively (P < 0.001). Expectedly, major postoperative complications were predictive of FTR, including unplanned intubation (OR: 2.56, CI: 1.66-3.95, P < 0.001), prolonged ventilation (OR: 2.00, CI: 1.37-3.14, P < 0.01), cardiac arrest (OR: 16.64, CI: 8.20-33.74, P < 0.001), and septic shock (OR: 2.08, CI: 1.10-3.91, P < 0.05). The RAI-driven frailty model demonstrated excellent discriminatory accuracy for predicting FTR patients undergoing mBTR (c-statistic: 0.82, 95% CI: 0.79-0.85).

CONCLUSIONS

Preoperative RAI-measured frailty, alongside nonelective surgery, and major postoperative complications were significant predictors of FTR in mBTR patients. Identifying mBTR patients at risk for FTR using frailty strata may aid in preoperative neurosurgical risk stratification to optimize patients prior to surgery.

Hospital frailty risk score predicts postoperative outcomes after endoscopic endonasal resection of non-functioning pituitary adenomas

PURPOSE

Frailty indices are invaluable resources in risk stratification and predicting high-value care outcomes for neurosurgical patients. The Hospital Frailty Risk Score (HFRS) is a recently developed and validated method for evaluating frailty; however, its implementation has yet to be assessed in patients with non-functioning pituitary adenomas undergoing endoscopic endonasal resection. In this study, we aimed to evaluate HFRS's predictive ability for high-value care outcomes, namely postoperative complications, length of stay (LOS), and hospital charges, and to compare it to other traditionally used frailty indices.

METHODS

A retrospective review of electronic medical records from 2017 to 2020. A total of 109 ICD-10 codes corresponding to various frailty-related conditions were used to identify the components of HFRS. These components were then used to calculate the HFRS for each patient, with higher scores indicative of elevated frailty. Standard multivariate logistic regression models were employed to explore the association between HFRS and high-value care outcomes. Model discrimination was assessed using the area under the ROC curves, and the DeLong test was used to compare AUCs.

RESULTS

A total of 172 patients were included, with a mean age of 57.27 ± 12.95 years and an average HFRS score of 3.65 ± 3.27. Among patients, 56% were male, 5.2% experience postoperative complications, 23.3% endured extended LOS, 25.0% incurred high hospital charges. In multivariate regression models, greater HFRS was significantly and independently associated with postoperative complications (OR = 1.51, P < 0.001), extended LOS (OR = 1.17, P = 0.006) and high hospital charges (OR = 1.18, P = 0.004). HFRS had the highest AUC compared to other frailty indices and was the most parsimonious model, with AUC values of 0.82, 0.64, and 0.63 for predicting complications, extended LOS, and higher charges, respectively.

CONCLUSION

Higher HFRS scores are significantly associated with postoperative complications, prolonged LOS, and high hospital charges for patients undergoing pituitary surgery.

Predictive Power of the Fried Phenotype in Assessing Postoperative Outcomes in Patients Undergoing Craniotomy for Tumor Resection

BACKGROUND AND OBJECTIVES

Compared with the modified Frailty Index-11 (mFI-11) frailty tool, reflective of patient comorbidities, the Fried phenotype weighs functional patient variables. This study examined using the Fried phenotype in predicting postoperative outcomes in craniotomy for patients with tumor.

METHODS

This retrospective cohort analysis included patients with Current Procedural Terminology codes for supratentorial/infratentorial tumor resections and preoperative frailty scores. Chart review collected the remaining variables for the primary outcome, length of stay (LOS), and secondary outcomes, discharge disposition and postoperative complications. Basic descriptive statistics summarized patient demographics, clinical parameters, and postoperative outcomes. χ 2 tests, t -tests, and ANOVA examined associations and mean differences. Logistic and Poisson regressions explored predictor-outcome relationships.

RESULTS

Over 7 years, these 153 patients underwent Fried assessments. The Fried score was biased toward females being more frail (nonfrail 38.0% female, prefrail 50.0% female and frail 65.6% female, P = .027) but not by age, body mass index, or tumor type. The mFI-11 was biased by age (nonfrail 67.8 years vs frail 72.3 years, P < .001) and body mass index (nonfrail 27.5 vs frail 30.8, P < .001) but not sex or tumor type. The Fried score was significantly correlated with increased LOS's (odds ratio [OR] = 5.92, 95% CI = 1.66-21.13, P < .001) but the mFI-11 was not (OR = 0.82, 95% CI = 0.35-1.93, P = .64). The Fried phenotype was significantly correlated with discharge disposition location ( P = .016), whereas the mFI-11 was not ( P = .749). The Fried score was significantly correlated with postoperative complications (OR = 1.36, 95% CI = 1.08-1.71, P = .01), whereas the mFI-11 was not (OR = 1.10, 95% CI = 0.86-1.41, P = .44).

CONCLUSION

The Fried phenotype more accurately correlates with postoperative outcomes including LOS, discharge disposition location, and complications than does the mFI-11 score. These findings can be used to guide preoperative planning, inform consent, and potentially identify patients who may benefit from functional optimization in the preoperative period to improve postoperative outcomes.

Utility of combining frailty and comorbid disease indices in predicting outcomes following craniotomy for adult primary brain tumors: A mixed-effects model analysis using the nationwide readmissions database

OBJECTIVE

The escalating healthcare expenditures in the United States, particularly in neurosurgery, necessitate effective tools for predicting patient outcomes and optimizing resource allocation. This study explores the utility of combining frailty and comorbidity indices, specifically the Johns Hopkins Adjusted Clinical Groups (JHACG) frailty index and the Elixhauser Comorbidity Index (ECI), in predicting hospital length of stay (LOS), non-routine discharge, and one-year readmission in patients undergoing craniotomy for benign and malignant primary brain tumors.

METHODS

Leveraging the Nationwide Readmissions Database (NRD) for 2016-2019, we analyzed data from 645 patients with benign and 30,991 with malignant tumors. Frailty, ECI, and frailty + ECI were assessed as predictors using generalized linear mixed-effects models. Receiver operating characteristic (ROC) curves evaluated predictive performance.

RESULTS

Patients in the benign tumor cohort had a mean LOS of 8.1 ± 15.1 days, and frailty + ECI outperformed frailty alone in predicting non-routine discharge (AUC 0.829 vs. 0.820, p = 0.035). The malignant tumor cohort patients had a mean LOS of 7.9 ± 9.1 days. In this cohort, frailty + ECI (AUC 0.821) outperformed both frailty (AUC 0.744, p < 0.0001) and ECI alone (AUC 0.809, p < 0.0001) in predicting hospital LOS. Frailty + ECI (AUC 0.831) also proved superior to frailty (AUC 0.809, p < 0.0001) and ECI alone (AUC 0.827, p < 0.0001) in predicting non-routine discharge location for patients with malignant tumors. All indices performed comparably to one another as a predictor of readmission in both cohorts.

CONCLUSION

This study highlights the synergistic predictive capacity of frailty + ECI, especially in malignant tumor cases, and further suggests that comorbid diseases may greatly influence perioperative outcomes more than frailty. Enhanced risk assessment could aid clinical decision-making, patient counseling, and resource allocation, ultimately optimizing patient outcomes.

Physical Health-Related Quality of Life and Postsurgical Outcomes in Brain Tumor Resection Patients

Background  Patient-reported outcome measures (PROMs) have gained traction in assessing patients' health around surgery. Among these, the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29) is a widely accepted tool for evaluating overall health, yet its applicability in cranial neurosurgery remains uncertain. Objective  This study aimed to evaluate the predictive value of preoperative PROMIS-29 scores for postoperative outcomes in patients undergoing brain tumor resection. Materials and Methods  We identified adult patients undergoing brain tumor resection at a single neurosurgical center between January 2018 and December 2021. We analyzed physical health (PH) summary scores to determine optimal thresholds for predicting length of stay (LOS), discharge disposition (DD), and 30-day readmission. Bivariate analyses were conducted to examine the distribution of PH scores based on patient characteristics. Multivariate logistic regression models were employed to assess the association between preoperative PH scores and short-term postoperative outcomes. Results  Among 157 patients (mean age 55.4 years, 58.0% female), 14.6% exhibited low PH summary scores. Additionally, 5.7% experienced prolonged LOS, 37.6% had nonroutine DDs, and 19.1% were readmitted within 30 days. Bivariate analyses indicated that patients with low PH summary scores, indicating poorer baseline PH, were more likely to have malignant tumors, nonelective admissions, and adverse outcomes. In multivariate analysis, low PH summary scores independently predicted increased odds of prolonged LOS (odds ratio [OR] = 6.09, p  = 0.003), nonroutine DD (OR = 4.25, p  = 0.020), and 30-day readmission (OR = 3.93, p  = 0.020). Conclusion  The PROMIS-29 PH summary score serves as a valuable predictor of short-term postoperative outcomes in brain tumor patients. Integrating this score into clinical practice can enhance the ability to anticipate meaningful postoperative results.

Impact of frailty on survival glioblastoma, IDH-wildtype patients

PURPOSE

Frailty increases the risk of mortality among patients. We studied the prognostic significance of frailty using the modified 5-item frailty index (5-mFI) in patients harboring a newly diagnosed supratentorial glioblastoma, IDH-wildtype.

METHODS

We retrospectively reviewed records of patients surgical treated at a single neurosurgical institution at the standard radiochemotherapy era (January 2006 - December 2021). Inclusion criteria were: age ≥ 18, newly diagnosed glioblastoma, IDH-wildtype, supratentorial location, available data to assess the 5-mFI index.

RESULTS

A total of 694 adult patients were included. The median overall survival was longer in the non-frail subgroup (5-mFI < 2, n = 538 patients; 14.3 months, 95%CI 12.5-16.0) than in the frail subgroup (5-mFI ≥ 2, n = 156 patients; 4.7 months, 95%CI 4.0-6.5 months; p < 0.001). 5-mFI ≥ 2 (adjusted Hazard Ratio (aHR) 1.31; 95%CI 1.07-1.61; p = 0.009) was an independent predictor of a shorter overall survival while age ≤ 60 years (aHR 0.78; 95%CI 0.66-0.93; p = 0.007), KPS score ≥ 70 (aHR 0.71; 95%CI 0.58-0.87; p = 0.001), unilateral location (aHR 0.67; 95%CI 0.52-0.87; p = 0.002), total removal (aHR 0.54; 95%CI 0.44-0.64; p < 0.0001), and standard radiochemotherapy protocol (aHR 0.32; 95%CI 0.26-0.38; p < 0.0001) were independent predictors of a longer overall survival. Frailty remained an independent predictor of overall survival within the subgroup of patients undergoing a first-line oncological treatment after surgery (n = 549) and within the subgroup of patients who benefited from a total removal plus adjuvant standard radiochemotherapy (n = 209).

CONCLUSION

In newly diagnosed supratentorial glioblastoma, IDH-wildtype patients treated at the standard combined radiochemotherapy era, frailty, defined using a 5-mFI score ≥ 2 was an independent predictor of overall survival.

Frailty in intracranial meningioma resection: the risk analysis index demonstrates strong discrimination for predicting non-home discharge and in-hospital mortality

PURPOSE

Frailty is an independent risk factor for adverse postoperative outcomes following intracranial meningioma resection (IMR). The role of the Risk Analysis Index (RAI) in predicting postoperative outcomes following IMR is nascent but may inform preoperative patient selection and surgical planning.

METHODS

IMR patients from the Nationwide Inpatient Sample were identified using diagnostic and procedural codes (2019-2020). The relationship between preoperative RAI-measured frailty and primary outcomes (non-home discharge (NHD), in-hospital mortality) and secondary outcomes (extended length of stay (eLOS), complication rates) was assessed via multivariate analyses. The discriminatory accuracy of the RAI for primary outcomes was measured in area under the receiver operating characteristic (AUROC) curve analysis.

RESULTS

A total of 23,230 IMR patients (mean age = 59) were identified, with frailty statuses stratified by RAI score: 0-20 "robust" (R)(N = 10,665, 45.9%), 21-30 "normal" (N)(N = 8,895, 38.3%), 31-40 "frail" (F)(N = 2,605, 11.2%), and 41+ "very frail" (VF)(N = 1,065, 4.6%). Rates of NHD (R 11.5%, N 29.7%, F 60.8%, VF 61.5%), in-hospital mortality (R 0.5%, N 1.8%, F 3.8%, VF 7.0%), eLOS (R 13.2%, N 21.5%, F 40.9%, VF 46.0%), and complications (R 7.5%, N 11.6%, F 15.7%, VF 16.0%) significantly increased with increasing frailty thresholds (p < 0.001). The RAI demonstrated strong discrimination for NHD (C-statistic: 0.755) and in-hospital mortality (C-statistic: 0.754) in AUROC curve analysis.

CONCLUSION

Increasing RAI-measured frailty is significantly associated with increased complication rates, eLOS, NHD, and in-hospital mortality following IMR. The RAI demonstrates strong discrimination for predicting NHD and in-hospital mortality following IMR, and may aid in preoperative risk stratification.

Preoperative patient-reported physical health-related quality of life predicts short-term postoperative outcomes in brain tumor patients

BACKGROUND

Patient-reported outcome measures (PROMs) are increasingly used to assess patients' perioperative health. The PROM Information System 29 (PROMIS-29) is a well-validated global health assessment instrument for patient physical health, though its utility in cranial neurosurgery is unclear.

OBJECTIVE

To investigate the utility of preoperative PROMIS-29 physical health (PH) summary scores in predicting postoperative outcomes in brain tumor patients.

METHODS

Adult brain tumor patients undergoing resection at a single institution (January 2018-December 2021) were identified and prospectively received PROMIS-29 surveys during pre-operative visits. PH summary scores were constructed and optimum prediction thresholds for length of stay (LOS), discharge disposition (DD), and 30-day readmission were approximated by finding the Youden index of the associated receiver operating characteristic curves. Bivariate analyses were used to study the distribution of low (z-score≤-1) versus high (z-score>-1) PH scores according to baseline characteristics. Logistic regression models quantified the association between preoperative PH summary scores and post-operative outcomes.

RESULTS

A total of 157 brain tumor patients were identified (mean age 55.4±15.4 years; 58.0% female; mean PH score 45.5+10.5). Outcomes included prolonged LOS (24.8%), non-routine discharge disposition (37.6%), and 30-day readmission (19.1%). On bivariate analysis, patients with low PH scores were significantly more likely to be diagnosed with a high-grade tumor (69.6% vs 38.85%, p=0.010) and less likely to have elective surgery (34.8% vs 70.9%, p=0.002). Low PH score was associated with prolonged LOS (26.1% vs 22%, p<0.001), nonroutine discharge (73.9% vs 31.3%, p<0.001) and 30-day readmission (43.5% vs 14.9%, p=0.003). In multivariate analysis, low PH scores predicted greater LOS (odds ratio [OR]=6.09, p=0.003), nonroutine discharge (OR=4.25, p=0.020), and 30-day readmission (OR=3.93, p=0.020).

CONCLUSION

The PROMIS-29 PH summary score predicts short-term postoperative outcomes in brain tumor patients and may be incorporated into prospective clinical workflows.

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.

Impact of Frailty on Postoperative Outcomes in Extended Endonasal Skull Base Surgery for Suprasellar Pathologies

OBJECTIVE

Frailty metrics estimate a patient's ability to tolerate physiologic stress and there are limited frailty data in patients undergoing expanded endonasal approaches (EEA) for suprasellar pathologies. Elevated frailty metrics have been associated with increased perioperative complications in patients undergoing craniotomies. We sought to examine this potential relationship in EEA.

STUDY DESIGN

Retrospective cohort study.

SETTING

Two tertiary academic skull base centers.

METHODS

Cases of patients undergoing EEA for suprasellar pathologies were reviewed. Demographic, treatment, survival, and postoperative outcomes data were recorded. Frailty was calculated using validated indexes, including the American Society of Anesthesiologists (ASA) classification, the modified 5-item frailty index (mFI-5), and the Charlson comorbidity index (CCI). Primary outcomes included 30-day medical and surgical complications.

RESULTS

A total of 88 patients were included, with 59 (67%) female patients and a mean age of 54 ± 15 years. The most common pathologies included 53 meningiomas (60.2%) and 21 craniopharyngiomas (23.9%). Most patients were ASA class 3 (54.5%) with mean mFI-5 0.82 ± 1.01 and CCI 4.18 ± 2.42. There was no association between increased frailty and 30-day medical or surgical outcomes (including postoperative cerebrospinal fluid leak), prolonged length of hospital stay, or mortality (all P > .05). Higher mFI-5 was associated with an increased risk for 30-day readmission (odds ratio: 2.35, 95% confidence Interval: 1.10-5.64, P = .04).

CONCLUSION

Despite the patient population being notably frail, we only identified an increased risk for 30-day readmission and observed no links with deteriorating surgical, medical, or mortality outcomes. This implies that conventional frailty metrics may not effectively align with EEA outcomes.

Frailty is a Predictor of Increased Readmissions and Increased Postoperative Complications After Elective Treatment of Unruptured Aneurysms

INTRODUCTION

Frailty is a state of decreased physiologic reserve associated with adverse treatment outcomes across surgical specialties. We sought to determine whether frailty affected patient outcomes after elective treatment (open microsurgical clipping or endovascular therapy [EVT]) of unruptured cerebral aneurysms (UCAs).

METHODS

The National Readmissions Database was queried from 2010 to 2014 to identify patients who had a known UCA and underwent elective clipping or EVT. Frailty was assessed using the Johns Hopkins Adjusted Clinical Groups frailty indicator tool. Multivariable exact logistic regression analyses were conducted to assess the associations between frailty and the primary outcome variables of 30- and 90-day readmissions, complications, length of stay (LOS), and patient disposition.

RESULTS

Of 18,483 patients who underwent elective treatment for UCAs, 358 (1.9%) met the criteria for frailty. After adjusting for patient- and hospital-based factors, frailty (30-day: odds ratio [OR], 1.55; 95% confidence interval [CI], 1.11-2.17; P = 0.01; 90-day: OR, 1.47; 95% CI, 1.05-2.06; P = 0.02) and clipping versus EVT (30-day: OR, 2.12; 95% CI, 1.85-2.43; P < 0.000; 90-day: OR, 1.80; 95% CI, 1.59-2.03; P < 0.0001) were associated with increased readmission rates. Furthermore, frailty was associated with an increased rate of complications (surgical: OR, 2.91; 95% CI, 2.27-3.72; P < 0.0001; neurological: OR, 3.04; 95% CI, 2.43-3.81; P < 0.0001; major: OR, 2.75; 95% CI, 1.96-3.84; P < 0.0001), increased LOSs (incidence rate ratio, 3.08; 95% CI, 2.59-3.66; P < 0.0001), and an increased rate of nonroutine disposition (OR, 3.94; 95% CI, 2.91-5.34; P < 0.0001).

CONCLUSIONS

Frailty was associated with an increased likelihood of 30- and 90-day readmissions after elective treatment of UCAs. Frailty was notably associated with several postoperative complications, longer LOSs, and nonroutine disposition in the treatment of UCAs.

Strategies to Assess and Manage Frailty among Patients Diagnosed with Primary Malignant Brain Tumors

OPINION STATEMENT

Frailty refers to a biologic process that results in reduced physiologic and functional reserve. Patients diagnosed with primary malignant brain tumors experience high symptom burden from tumor and tumor-directed treatments that, coupled with previous comorbidities, may contribute to frailty. Within the primary malignant brain tumor population, frailty is known to associate with mortality, higher healthcare utilization, and increased risk of postoperative complications. As such, methods to assess and manage frailty are paramount. However, there is currently no clear consensus on how to best assess and manage frailty throughout the entirety of the disease trajectory. Given the association between frailty and health outcomes, more research is needed to determine best practice protocols for the assessment and management of frailty among patients diagnosed with primary malignant brain tumors.

Trends in frailty in brain tumor care during the COVID-19 pandemic in a nationwide hospital network in Germany

PURPOSE

Among brain tumor patients, frailty is associated with poor outcomes. The COVID-19 pandemic has led to increased frailty in the general population. To date, evidence on changes in frailty among brain tumor patients during the pandemic is lacking. We aimed to compare frailty among brain tumor patients in Germany during the COVID-19 pandemic to the pre-pandemic era and to assess potential effects on brain tumor care.

METHODS

In this retrospective observational study, we compared frailty among brain tumor patients hospitalized during the COVID-19 pandemic in years 2020 through 2022 to pre-pandemic years 2016 through 2019 based on administrative data from a nationwide network of 78 hospitals in Germany. Using the Hospital Frailty Risk Score (HFRS), frailty was categorized as low, intermediate, or high. We examined changes in frailty, patient demographics, the burden of comorbidity, rates of surgery, and mortality rates for different frailty groups during the pandemic and compared them to pre-pandemic levels.

RESULTS

Of the 20,005 included hospitalizations for brain tumors, 7979 were during the pandemic (mean age 60.0 years (± 18.4); females: 49.8%), and 12,026 in the pre-pandemic period (mean age: 59.0 years [± 18.4]; females: 49.2%). Average daily admissions decreased from 8.2 (± 5.1) during pre-pandemic years to 7.3 (± 4.5) during the pandemic (p < 0.01). The overall median HFRS decreased from 3.1 (IQR: 0.9-7.3) during the pre-pandemic years to 2.6 (IQR: 0.3-6.8) during the pandemic (p < 0.01). At the same time, the Elixhauser Comorbidity Index (ECI) decreased from 17.0 (± 12.4) to 16.1 (± 12.0; p < 0.01), but to a larger degree among high compared to low frailty cases (by 1.8 vs. 0.3 points; p = 0.04). In the entire cohort, the mean length of stay was significantly shorter in the pandemic period (9.5 days [± 10.7]) compared with pre-pandemic levels (10.2 days [± 11.8]; p < 0.01) with similar differences in the three frailty groups. Rates of brain tumor resection increased from 29.9% in pre-pandemic years to 36.6% during the pandemic (p < 0.001) without differences between frailty levels. Rates of in-hospital mortality did not change during the pandemic (6.1% vs. 6.7%, p = 0.07), and there was no interaction with frailty.

CONCLUSION

Even though our findings are limited in that the HFRS is validated only for patients ≥ 75 years of age, our study among patients of all ages hospitalized for brain tumors in Germany suggests a marked decrease in levels of frailty and in the burden of comorbidities during the COVID-19 pandemic.

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.

Frailty and postoperative outcomes in brain tumor patients: a systematic review subdivided by tumor etiology

PURPOSE

Frailty has gained prominence in neurosurgical oncology, with more studies exploring its relationship to postoperative outcomes in brain tumor patients. As this body of literature continues to grow, concisely reviewing recent developments in the field is necessary. Here we provide a systematic review of frailty in brain tumor patients subdivided by tumor type, incorporating both modern frailty indices and traditional Karnofsky Performance Status (KPS) metrics.

METHODS

Systematic literature review was performed using PRISMA guidelines. PubMed and Google Scholar were queried for articles related to frailty, KPS, and brain tumor outcomes. Only articles describing novel associations between frailty or KPS and primary intracranial tumors were included.

RESULTS

After exclusion criteria, systematic review yielded 52 publications. Amongst malignant lesions, 16 studies focused on glioblastoma. Amongst benign tumors, 13 focused on meningiomas, and 6 focused on vestibular schwannomas. Seventeen studies grouped all brain tumor patients together. Seven studies incorporated both frailty indices and KPS into their analyses. Studies correlated frailty with various postoperative outcomes, including complications and mortality.

CONCLUSION

Our review identified several patterns of overall postsurgical outcomes reporting for patients with brain tumors and frailty. To date, reviews of frailty in patients with brain tumors have been largely limited to certain frailty indices, analyzing all patients together regardless of lesion etiology. Although this technique is beneficial in providing a general overview of frailty's use for brain tumor patients, given each tumor pathology has its own unique etiology, this combined approach potentially neglects key nuances governing frailty's use and prognostic value.

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 predicts hospital acquired infections after brain tumor resection: Analysis of 27,947 patients' data from a prospective multicenter surgical registry

BACKGROUND

Hospital acquired infections (HAIs) present a significant source of economic burden in the United States. The role of frailty as a predictor of HAIs has not been illustrated among patients undergoing craniotomy for brain tumor resection (BTR).

METHODS

The American College of Surgery National Surgical Quality Improvement Program (ACS-NSQIP) database was queried from 2015 to 2019 to identify patients who underwent craniotomy for BTR. Patients were categorized as pre-frail, frail and severely frail using the 5-factor Modified Frailty Index (mFI-5). Demographics, clinical and laboratory parameters, and HAIs were assessed. A multivariate logistic regression model was created to predict the occurrence of HAIs using these variables.

RESULTS

A total of 27,947 patients were assessed. 1772 (6.3 %) of these patients developed an HAI after surgery. Severely frail patients were more likely to develop an HAI in comparison to pre-frail patients (OR = 2.48, 95 % CI = 1.65-3.74, p < 0.001 vs. OR = 1.43, 95 % CI = 1.18-1.72, p < 0.001). Ventilator dependence was the strongest predictor of developing an HAI (OR = 2.96, 95 % CI = 1.86-4.71, p < 0.001).

CONCLUSION

Baseline frailty, by virtue of its ability to predict HAIs, should be utilized in adopting measures to reduce the incidence of HAIs.

Is surgical resection predict overall survival in frail patients with glioblastoma, IDH-wildtype?

PURPOSE

We assessed the impact of frailty on surgical outcomes, survival, and functional dependency in elderly patients harboring a glioblastoma, isocitrate dehydrogenase (IDH)-wildtype.

METHODS

We retrospectively reviewed records of old and frail patients surgical treated at a single neurosurgical institution between January 2018 to May 2021. Inclusion criteria were: (1) neuropathological diagnosis of glioblastoma, IDH-wildtype; (2) patient≥65years at the time of surgery; (3) available data to assess the frailty index according to the 5-modified Frailty Index (5-mFI).

RESULTS

A total of 47 patients were included. The 5-mFI was at 0 in 11 cases (23.4%), at 1 in 30 cases (63.8%), at 2 in two cases (4.2%), at 3 in two cases (4.2%), and at 4 in two cases (4.2%). A gross total resection was performed in 26 patients (55.3%), a subtotal resection was performed in 13 patients (27.6%), and a biopsy was performed in 8 patients (17.1%). The rate of 30-day postoperative complications was higher in the biopsy subgroup and in the 5-mFI=4 subgroup. Gross total resection and age≤70years were independent predictors of a longer overall survival. Sex, 5-mFI, postoperative complications, and preoperative Karnofsky Performance Status score did not influence overall survival and functional dependency.

CONCLUSION

In patients≥65years harboring a glioblastoma, IDH-wildtype, gross total resection remains an independent predictor of longer survival and good postoperative functional recovery. The frailty, assessed by the 5-mFI score, does not influence surgery and outcomes in this dataset. Further confirmatory analyses are required.

Frailty as a predictor of neurosurgical outcomes in brain tumor patients: A systematic review and meta-analysis

BACKGROUND

Patients with frailty are at a high risk of poor health outcomes, and frailty has been explored as a predictor of adverse events, such as perioperative complications, readmissions, falls, disability, and mortality in the neurosurgical literature. However, the precise relationship between frailty and neurosurgical outcomes in patients with brain tumor has not been established, and thus evidence-based advancements in neurosurgical management. The objectives of this study are to describe existing evidence and conduct the first systematic review and meta-analysis of the relationship between frailty and neurosurgical outcomes among brain tumor patients.

METHODS

Seven English databases and four Chinese databases were searched to identify neurosurgical outcomes and the prevalence of frailty among patients with a brain tumor, with no restrictions on the publication period. According to the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis and the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines, two independent reviewers employed the Newcastle-Ottawa scale in cohort studies and JBI Critical Appraisal Checklist for Cross-sectional Studies to evaluate the methodological quality of each study. Then random-effects or fixed-effects meta-analysis was used in combining odds ratio (OR) or hazard ratio (RR) for the categorical data and continuous data of neurosurgical outcomes. The primary outcomes are mortality and postoperative complications, and secondary outcomes include readmission, discharge disposition, length of stay (LOS), and hospitalization costs.

RESULTS

A total of 13 papers were included in the systematic review, and the prevalence of frailty ranged from 1.48 to 57%. Frailty was significantly associated with increased risk of mortality (OR = 1.63; CI = 1.33-1.98; p < 0.001), postoperative complications (OR = 1.48; CI = 1.40-1.55; p < 0.001; I ² = 33%), nonroutine discharge disposition to a facility other than home (OR = 1.72; CI = 1.41-2.11; p < 0.001), prolonged LOS (OR = 1.25; CI = 1.09-1.43; p = 0.001), and high hospitalization costs among brain tumor patients. However, frailty was not independently associated with readmission (OR = 0.99; CI = 0.96-1.03; p = 0.74).

CONCLUSION

Frailty is an independent predictor of mortality, postoperative complications, nonroutine discharge disposition, LOS, and hospitalization costs among brain tumor patients. In addition, frailty plays a significant potential role in risk stratification, preoperative shared decision making, and perioperative management.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021248424.

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.

Frailty in Patients Undergoing Surgery for Brain Tumors: A Systematic Review of the Literature

BACKGROUND

Emerging literature suggests that frailty may be an important driver of postoperative outcomes in patients undergoing surgery for brain tumors. We systematically reviewed the literature on frailty in patients with brain tumor with respect to 3 questions: What methods of frailty assessment have been applied to patients with brain tumor? What thresholds have been defined to distinguish between different levels of frailty? What clinical outcomes does frailty predict in patients with brain tumor?

METHODS

A literature search was conducted using PubMed, Embase, The Cochrane Library, Web of Science, Scopus, and ClinicalTrials.gov. Included studies were specific to patients with brain tumor, used a validated instrument to assess frailty, and measured the impact of frailty on postoperative outcomes.

RESULTS

Of 753 citations, 21 studies met our inclusion criteria. Frailty instruments were studied, in order of frequency reported, including the 5-factor modified frailty index, 11-factor modified frailty index, Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator, and Hopkins Frailty Score. Multiple different conventions and thresholds were reported for distinguishing the levels of frailty. Clinical outcomes associated with frailty included mortality, survival, complications, length of stay, charges, costs, discharge disposition, readmissions, and operative time.

CONCLUSIONS

Frailty is an increasingly popular concept in patients with brain tumor that is associated with important clinical outcomes. However, the extant literature is largely comprised of retrospective studies with heterogeneous definitions of frailty, thresholds for defining levels of frailty, and patient populations. Further work is needed to understand best practices in assessing frailty in patients with brain tumor and applying these concepts to clinical practice.

Advanced frailty assessment tool predicts successful awake craniotomy in a 92-year-old patient: A case report

Background:

The awake craniotomy (AC) procedure allows for safe and maximal resection of brain tumors from highly eloquent regions. However, geriatric patients are often viewed as poor candidates for AC due to age and medical comorbidities. Frailty assessments gauge physiological reserve for surgery and are valuable tools for preoperative decision-making. Here, we present a novel case illustrating how frailty scoring enabled an elderly but otherwise healthy female to undergo successful AC for tumor resection.

Case Description:

A 92-year-old right-handed female with history of hypertension and basal cell skin cancer presented with a 1-month history of progressive aphasia and was found to have a ring-enhancing left frontoparietal mass abutting the rolandic cortex concerning for malignant neoplasm. Frailty scoring with the recalibrated risk analysis index (RAI-C) tool revealed a score of 30 (of 81) indicating low surgical risk. The patient and family were counseled appropriately that, despite advanced chronological age, a low frailty score predicts favorable surgical outcomes. The patient underwent left-sided AC for resection of tumor and experienced immediate improvement of speech intraoperatively. After surgery, the patient was neurologically intact and had an unremarkable postoperative course with significant improvements from preoperatively baseline at follow-up.

Conclusion:

To the best of our knowledge, this case represents the oldest patient to undergo successful AC for brain tumor resection. Nonfrail patients over 90 years of age with the proper indications may tolerate cranial surgery. Frailty scoring is a powerful tool for preoperative risk assessment in the geriatric neurosurgery population.

Utility of hospital frailty risk score for predicting postoperative outcomes in craniopharyngioma

OVERVIEW

Frailty is an age-associated decline in functional status leading to increased vulnerability to otherwise innocuous stressors. In neurosurgical patients, frailty has been associated with postoperative complications, increased mortality, longer hospitalization, and increased care costs for a variety of conditions. This study seeks to determine the association between frailty and postoperative outcomes in patients undergoing surgery for craniopharyngioma.

METHODS

The Nationwide Inpatient Sample (NIS) database was queried for patients diagnosed with craniopharyngioma who underwent surgery via either craniotomy or transsphenoidal approach. Comorbid diagnoses were used to calculate the Hospital Frailty Risk Score (HFRS) and assign patients to low (< 5), intermediate (5-15), or high-risk (> 15) categories. Logistic regression was completed to determine whether the HFRS category was predictive of mortality, postoperative complication, extended hospitalization, or increased hospital costs compared to age.

RESULTS

Increased frailty score was predictive of increased length of stay, increased hospital costs, and non-home discharge in binary logistic regression with good discrimination on the ROC curve compared to age at admission. HFRS risk categories were significantly predictive of the development of any complication, with 100% of high-risk patients developing a complication compared to 76% of intermediate-risk and 63% of low-risk patients. HFRS risk categories were also predictive of the extended length of stay (71%, 49%, and 11% for high-, intermediate-, and low-risk, respectively) and non-home discharge (86%, 56%, and 17%). Regression analysis was unable to be performed for mortality due to the low number of deaths in the study group.

CONCLUSION

In patients undergoing any surgery for craniopharyngioma, frailty is predictive of increased hospital length of stay and overall care costs. HFRS failed to independently predict mortality because the incidence of mortality is too low in this population to analyze. The HFRS is a valuable tool to identify post-operative outcomes following surgery for craniopharyngioma.

Novel Predictive Models for High-Value Care Outcomes Following Glioblastoma Resection

BACKGROUND

Treating patients with glioblastoma (GBM) requires extensive medical infrastructure. Individualized risk assessment for extended length of stay (LOS), nonroutine discharge disposition, and increased total hospital charges is critical to optimize delivery of care. Our study sought to develop predictive models identifying independent risk factors for these outcomes.

METHODS

We retrospectively reviewed patients undergoing GBM resection at our institution between January 2017 and September 2020. Extended LOS and elevated hospital charges were defined as values in the upper quartile of the cohort. Nonroutine discharge was defined as any disposition other than to home. Multivariate models for each outcome included covariates demonstrating P ≤ 0.10 on bivariate analysis.

RESULTS

We identified 265 patients undergoing GBM resection, with an average age of 58.2 years. 24.5% of patients experienced extended LOS, 22.6% underwent nonroutine discharge, and 24.9% incurred elevated total hospital charges. Decreasing Karnofsky Performance Status (KPS) (P = 0.004), increasing modified 5-factor frailty (mFI-5) index (P = 0.012), lower surgeon experience (P = 0.005), emergent surgery (P < 0.0001), and larger tumor volume (P < 0.0001) predicted extended LOS. Independent predictors of nonroutine discharge included older age (P = 0.02), decreasing KPS (P < 0.0001), and emergent surgery (P = 0.048). Nonprivate insurance (P = 0.011), decreasing KPS (P = 0.029), emergent surgery (P < 0.0001), and larger tumor volume (P = 0.004) predicted elevated hospital charges. These models were incorporated into an open-access online calculator (https://neurooncsurgery3.shinyapps.io/gbm_calculator/).

CONCLUSIONS

Several factors were independent predictors for at least 1 high-value care outcome, with lower KPS and emergent admission associated with each outcome. These models and our calculator may help clinicians provide individualized postoperative risk assessment to glioblastoma patients.

The role of frailty in the clinical management of neurofibromatosis type 1: a mixed-effects modeling study using the Nationwide Readmissions Database

OBJECTIVE

Frailty embodies a state of increased medical vulnerability that is most often secondary to age-associated decline. Recent literature has highlighted the role of frailty and its association with significantly higher rates of morbidity and mortality in patients with CNS neoplasms. There is a paucity of research regarding the effects of frailty as it relates to neurocutaneous disorders, namely, neurofibromatosis type 1 (NF1). In this study, the authors evaluated the role of frailty in patients with NF1 and compared its predictive usefulness against the Elixhauser Comorbidity Index (ECI).

METHODS

Publicly available 2016–2017 data from the Nationwide Readmissions Database was used to identify patients with a diagnosis of NF1 who underwent neurosurgical resection of an intracranial tumor. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups frailty-defining indicator. ECI scores were collected in patients for quantitative measurement of comorbidities. Propensity score matching was performed for age, sex, ECI, insurance type, and median income by zip code, which yielded 60 frail and 60 nonfrail patients. Receiver operating characteristic (ROC) curves were created for complications, including mortality, nonroutine discharge, financial costs, length of stay (LOS), and readmissions while using comorbidity indices as predictor values. The area under the curve (AUC) of each ROC served as a proxy for model performance.

RESULTS

After propensity matching of the groups, frail patients had an increased mean ± SD hospital cost ($85,441.67 ± $59,201.09) compared with nonfrail patients ($49,321.77 ± $50,705.80) (p = 0.010). Similar trends were also found in LOS between frail (23.1 ± 14.2 days) and nonfrail (10.7 ± 10.5 days) patients (p = 0.0020). For each complication of interest, ROC curves revealed that frailty scores, ECI scores, and a combination of frailty+ECI were similarly accurate predictors of variables (p > 0.05). Frailty+ECI (AUC 0.929) outperformed using only ECI for the variable of increased LOS (AUC 0.833) (p = 0.013). When considering 1-year readmission, frailty (AUC 0.642) was outperformed by both models using ECI (AUC 0.725, p = 0.039) and frailty+ECI (AUC 0.734, p = 0.038).

CONCLUSIONS

These findings suggest that frailty and ECI are useful in predicting key complications, including mortality, nonroutine discharge, readmission, LOS, and higher costs in NF1 patients undergoing intracranial tumor resection. Consideration of a patient’s frailty status is pertinent to guide appropriate inpatient management as well as resource allocation and discharge planning.

Association of Patient Frailty With Vestibular Schwannoma Resection Outcomes and Machine Learning Development of a Vestibular Schwannoma Risk Stratification Score

BACKGROUND

Patient frailty is predictive of higher neurosurgical morbidity and mortality. However, existing frailty measures are hindered by lack of specificity to neurosurgery.

OBJECTIVE

To analyze the association between 3 risk stratification scores and outcomes for nationwide vestibular schwannoma (VS) resection admissions and develop a custom VS risk stratification score.

METHODS

We identified all VS resection admissions in the National Inpatient Sample (2002-2017). Three risk stratification scores were analyzed: modified Frailty Index-5, modified Frailty Index-11(mFI-11), and Charlson Comorbidity Index (CCI). Survey-weighted multivariate regression evaluated associations between frailty and inpatient outcomes, adjusting for patient demographics, hospital characteristics, and disease severity. Subsequently, we used k-fold cross validation and Akaike Information Criterion-based model selection to create a custom risk stratification score.

RESULTS

We analyzed 32 465 VS resection admissions. High frailty, as identified by the mFI-11 (odds ratio [OR] = 1.27, P = .021) and CCI (OR = 1.72, P < .001), predicted higher odds of perioperative complications. All 3 scores were also associated with lower routine discharge rates and elevated length of stay (LOS) and costs (all P < .05). Our custom VS-5 score (https://skullbaseresearch.shinyapps.io/vs-5_calculator/) featured 5 variables (age ≥60 years, hydrocephalus, preoperative cranial nerve palsies, diabetes mellitus, and hypertension) and was predictive of higher mortality (OR = 6.40, P = .001), decreased routine hospital discharge (OR = 0.28, P < .001), and elevated complications (OR = 1.59, P < .001), LOS (+48%, P < .001), and costs (+23%, P = .001). The VS-5 outperformed the modified Frailty Index-5, mFI-11, and CCI in predicting routine discharge (all P < .001), including in a pseudoprospective cohort (2018-2019) of 3885 admissions.

CONCLUSION

Patient frailty predicted poorer inpatient outcomes after VS surgery. Our custom VS-5 score outperformed earlier risk stratification scores.

Comparative associations of baseline frailty status and age with postoperative mortality and duration of hospital stay following metastatic brain tumor resection

Metastatic brain tumors are the most common intracranial neoplasms diagnosed in the United States. Although baseline frailty status has been validated as a robust predictor of morbidity and mortality across various surgical disciplines, evidence within cranial neurosurgical oncology is limited. Adult metastatic brain tumor patients treated with resection were identified in the National Inpatient Sample during the period of 2015-2018. Frailty was quantified using the 11-point modified frailty index (mFI-11) and its association with clinical endpoints was evaluated through complex samples multivariable logistic regression and receiver operating characteristic (ROC) curve analyses. Among 13,650 metastatic brain tumor patients identified (mean age 62.8 years), 26.8% (n = 3665) were robust (mFI = 0), 31.4% (n = 4660) were pre-frail (mFI = 1), 23.2% (n = 3165) were frail (mFI = 2), and 15.8% (n = 2160) were severely frail (mFI ≥ 3). On univariable assessment, these cohorts stratified by increasing frailty were significantly associated with postoperative complications (13.6%, 15.9%, 23.9%, 26.4%; p < 0.001), mortality (1.2%, 1.4%, 2.7%, 3.2%; p = 0.028), and extended length of stay (eLOS) (15.7%, 22.5%, 28.9%, 37.7%; p < 0.001). Following multivariable logistic regression analysis, frailty (by mFI-11) was independently associated with postoperative mortality (aOR 1.34, 95% CI 1.08, 1.65) and eLOS (aOR 1.26, 95% CI 1.17, 1.37), while increasing age was not associated with these endpoints. ROC curve analysis demonstrated superior discrimination of frailty (by mFI-11) in comparison with age for both mortality (AUC 0.61 vs. 0.58) and eLOS (AUC 0.61 vs. 0.53). Further statistical assessment through propensity score adjustment and decision tree analysis confirmed and extended the findings of the primary analytical models. Frailty may be a more robust predictor of postoperative outcomes in comparison with age following metastatic brain tumor resection.

Association of baseline frailty status and age with postoperative morbidity and mortality following intracranial meningioma resection

PURPOSE

Although numerous studies have established advanced patient age as a risk factor for poor outcomes following intracranial meningioma resection, large-scale evaluation of frailty for preoperative risk assessment has yet to be examined.

METHODS

Weighted discharge data from the National Inpatient Sample were queried for adult patients undergoing benign intracranial meningioma resection from 2015 to 2018. Complex samples multivariable logistic regression models and receiver operating characteristic curve analysis were performed to evaluate adjusted associations and discrimination of frailty, quantified using the 11-factor modified frailty index (mFI), for clinical endpoints.

RESULTS

Among 20,250 patients identified (mean age 60.6 years), 35.4% (n = 7170) were robust (mFI = 0), 34.5% (n = 6985) pre-frail (mFI = 1), 20.1% (n = 4075) frail (mFI = 2), and 10.0% (n = 2020) severely frail (mFI ≥ 3). On univariable analysis, these sub-cohorts stratified by increasing frailty were significantly associated with the development of Clavien-Dindo grade IV (life-threatening) complications (inclusive of those resulting in mortality) (1.3% vs. 3.1% vs. 6.5% vs. 9.4%, p < 0.001) and extended length of stay (eLOS) (15.4% vs. 22.5% vs. 29.3% vs. 37.4%, p < 0.001). Following multivariable analysis, increasing frailty (aOR 1.40, 95% CI 1.17, 1.68, p < 0.001) and age (aOR 1.20, 95% CI 1.05, 1.38, p = 0.009) were both independently associated with development of life-threatening complications or mortality, whereas increasing frailty (aOR 1.20, 95% CI 1.10, 1.32, p < 0.001), but not age, was associated with eLOS. Frailty (by mFI-11) achieved superior discrimination in comparison to age for both endpoints (AUC 0.69 and 0.61, respectively).

CONCLUSION

Frailty may be more accurate than advanced patient age alone for prognostication of adverse events and outcomes following intracranial meningioma resection.