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

Sonora Andromeda Windermere; Kaitlyn Melnick; Sandra C Yan; Michelot Michel; Jonathan Munoz; Ghaidaa Ebrahim; Hayden Greene; Grace Hey; Muhammad Abdul Baker Chowdhury; Ashley P Ghiaseddin; Basma Mohammed; Maryam Rahman

doi:10.1227/neu.0000000000003231

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

Neurosurgery. 2024 Oct 17. doi: 10.1227/neu.0000000000003231. Online ahead of print.

Authors

Affiliations

¹ Lillian S. Wells Department of Neurosurgery, University of Florida, Gainesville, Florida, USA.
² Department of General Surgery, Virginia Commonwealth University, Richmond, Virginia, USA.
³ College of Medicine, University of Florida, Gainesville, Florida, USA.
⁴ Florida State University College of Medicine, Tallahassee, Florida, USA.
⁵ Department of Anesthesiology, Duke University, Durham, North Carolina, USA.

PMID: 39471075
DOI: 10.1227/neu.0000000000003231

Abstract

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. χ2 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.