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

  • Albert Q. Schmidt
  • , Salome von Euw
  • , Joanna M. Roy
  • , Georgios P. Skandalakis
  • , Syed Faraz Kazim
  • , Meic H. Schmidt
  • , Christian A. Bowers

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Article number107724
JournalClinical Neurology and Neurosurgery
Volume229
DOIs
StatePublished - Jun 2023
Externally publishedYes

Keywords

  • Brain tumors
  • Frailty
  • Modified frailty index (mFI-5)
  • National Surgical Quality Improvement Program (NSQIP)
  • Surgical outcomes

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