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Association of Patient Frailty With Vestibular Schwannoma Resection Outcomes and Machine Learning Development of a Vestibular Schwannoma Risk Stratification Score.
Tang, Oliver Y; Bajaj, Ankush I; Zhao, Kevin; Rivera Perla, Krissia M; Ying, Yu-Lan Mary; Jyung, Robert W; Liu, James K.
Afiliação
  • Tang OY; Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
  • Bajaj AI; Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
  • Zhao K; Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey, Newark, New Jersey, USA.
  • Rivera Perla KM; Department of Neurological Surgery, New Jersey Medical School, Newark, New Jersey, USA.
  • Ying YM; Saint Barnabas Medical Center, RWJBarnabas Health, Livingston, New Jersey, USA.
  • Jyung RW; Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
  • Liu JK; Department of Plastic Surgery, Johns Hopkins University, Baltimore, Maryland, USA.
Neurosurgery ; 91(2): 312-321, 2022 08 01.
Article em En | MEDLINE | ID: mdl-35411872
ABSTRACT

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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neuroma Acústico / Fragilidade Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Middle aged Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neuroma Acústico / Fragilidade Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Middle aged Idioma: En Ano de publicação: 2022 Tipo de documento: Article