Evidence map›Paper›PMID 38713325›Full record

ArticleJournal of neuro-oncology2024

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

Michael M Covell, Joanna M Roy, Nithin Gupta, Ahmed Sami Raihane, Kranti C Rumalla, Amanda Cyntia Lima Fonseca Rodrigues, Evan Courville, Christian A Bowers

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Article in Journal of neuro-oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Utility of Revised Risk Analysis Index as a Predictor of Mortality and Morbidity in Orthopaedic Trauma.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2025
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michael M CovellSchool of Medicine, Georgetown University, 3900 Reservoir Road, 20007, Washington, DC, USA.
Joanna M RoyBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA.
Nithin GuptaCampbell University School of Osteopathic Medicine, Lillington, NC, USA.
Ahmed Sami RaihaneBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA.
Kranti C RumallaBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA.
Amanda Cyntia Lima Fonseca RodriguesBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA.
Evan CourvilleBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA.
Christian A BowersBowers Neurosurgical Frailty and Outcomes Data Science Lab, 84070, Sandy, UT, USA. christianbowers4@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFrailty 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.

methodsIMR 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.

resultsA 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.

conclusionIncreasing 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.

Indexed as

FrailtyHospital MortalityMeningeal NeoplasmsMeningiomaPatient DischargeAdultAgedFemaleHumansMaleMiddle AgedNeurosurgical ProceduresPostoperative ComplicationsPrognosisRetrospective StudiesRisk AssessmentMeningiomaMeningioma ResectionNationwide Inpatient SampleNeurosurgeryRisk analysis index

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.