Development of the UroARC Surgical Calculator: A Novel Risk Calculator for Older Adults Undergoing Surgery for Bladder Outlet Obstruction.

Autor:	Nik-Ahd F; Department of Urology, University of California, San Francisco, San Francisco, California., Zhao S; Department of Urology, University of California, San Francisco, San Francisco, California., Boscardin WJ; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California., Wang L; Department of Urology, University of California, San Francisco, San Francisco, California., Covinsky K; Department of Geriatrics, University of California, San Francisco, San Francisco, California., Suskind AM; Department of Urology, University of California, San Francisco, San Francisco, California.
Jazyk:	angličtina
Zdroj:	The Journal of urology [J Urol] 2024 Sep; Vol. 212 (3), pp. 451-460. Date of Electronic Publication: 2024 Jun 26.
DOI:	10.1097/JU.0000000000003978
Abstrakt:	Purpose: Bladder outlet obstruction (BOO) is common in older adults. Many older adults who pursue surgery have additional vulnerabilities affecting surgical risk, including frailty. A clinical tool that builds on frailty to predict surgical outcomes for the spectrum of BOO procedures would be helpful to aid in surgical decision-making but does not currently exist. Materials and Methods: Medicare beneficiaries undergoing BOO surgery from 2014 to 2016 were identified and analyzed using the Medicare MedPAR, Outpatient, and Carrier files. Eight different BOO surgery categories were created. Baseline frailty was calculated for each beneficiary using the Claims-Based Frailty Index (CFI). All 93 variables in the CFI and the 17 variables in the Charlson Comorbidity Index were individually entered into stepwise logistic regression models to determine variables most highly predictive of complications. Similar and duplicative variables were combined into categories. Calibration curves and tests of model fit, including C statistics, Brier scores, and Spiegelhalter P values, were calculated to ensure the prognostic accuracy for postoperative complications. Results: In total, 212,543 beneficiaries were identified. Approximately 42.5% were prefrail (0.15 ≤ CFI < 0.25), 8.7% were mildly frail (0.25 ≤ CFI < 0.35), and 1.2% were moderately-to-severely frail (CFI ≥0.35). Using stepwise logistic regression, 13 distinct prognostic variable categories were identified as the most reliable predictors of postoperative outcomes. Most models demonstrated excellent model discrimination and calibration with high C statistic and Spiegelhalter P values, respectively, and high accuracy with low Brier scores. Calibration curves for each outcome demonstrated excellent model fit. Conclusions: This novel risk assessment tool may help guide surgical prognostication among this vulnerable population.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu