Predictors of Nonroutine Discharge Disposition Among Patients with Parasagittal/Parafalcine Meningioma

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.

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.

Endoscopic Ipsilateral Interhemispheric Approach for Middle-Third Falcine Meningioma: A Case Report and Literature Review

Middle-third falcine meningiomas (FMs) are usually hidden deep under the eloquent cortex and abundant bridging veins, which represent the main hindrances to surgical access. The endoscopic approach has the advantages of wide visualization and free visual axis without areas of visual blindness, which allows for the resection of FMs with good visualization in a narrow space, especially in deep operations. Here, we report a case of a middle-third FM treated using the endoscopic ipsilateral interhemispheric approach. A 55-year-old female who had suffered a headache for 6 months without other remarkable symptoms was diagnosed with middle-third FM combined with imaging evaluation. According to the imaging performance and anatomical features, we scheduled the endoscopic ipsilateral interhemispheric approach to access and remove the tumor. Consequently, gross total tumor resection was achieved without surgery-related complications. After the surgery, the patient had an uneventful recovery and was discharged with no neurological deficit. During the 24-month follow-up, the patient's condition remained favorable, with no tumor recurrence. In our opinion, the endoscopic ipsilateral interhemispheric approach is a feasible surgical strategy for FMs, which deserves further exploration as a treatment option.

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.

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.

Predicting High-Value Care Outcomes After Surgery for Non-Skull Base Meningiomas

OBJECTIVE

A need exists to better understand the prognostic factors that influence high-value care outcomes after meningioma surgery. The goal of the present study was to develop predictive models to determine the patients at risk of experiencing an extended hospital length of stay (LOS), nonroutine discharge disposition, and/or a 90-day hospital readmission after non-skull base meningioma resection.

METHODS

In the present study, we analyzed the data from 396 patients who had undergone surgical resection of non-skull base meningiomas at a single institution between January 1, 2005 and December 31, 2020. The Mann-Whitney U test was used for bivariate analysis of the continuous variables and the Fisher exact test for bivariate analysis of the categorical variables. A multivariate analysis was conducted using logistic regression models.

RESULTS

Most patients had had a falcine or parasagittal meningioma (66.2%), with the remainder having convexity (31.8%) or intraventricular (2.0%) tumors. Nonelective surgery (P < 0.0001) and an increased tumor volume (P = 0.0022) were significantly associated with a LOS >4 days on multivariate analysis. The independent predictors of a nonroutine discharge disposition included male sex (P = 0.0090), nonmarried status (P = 0.024), nonelective surgery (P = 0.0067), tumor location within the parasagittal or intraventricular region (P = 0.0084), and an increased modified frailty index score (P = 0.039). Hospital readmission within 90 days was independently associated with nonprivate insurance (P = 0.010) and nonmarried status (P = 0.0081). Three models predicting for a prolonged LOS, nonroutine discharge disposition, and 90-day readmission were implemented in the form of an open-access, online calculator (available at: https://neurooncsurgery3.shinyapps.io/non_skull_base_meningiomas/).

CONCLUSIONS

After external validation, our open-access, online calculator could be useful for assessing the likelihood of adverse postoperative outcomes for patients undergoing surgery of non-skull base meningioma.

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.