{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T16:14:33Z","timestamp":1784132073480,"version":"3.55.0"},"reference-count":26,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T00:00:00Z","timestamp":1728259200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Neurourology and Urodynamics"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Introduction<\/jats:title><jats:p>Surgeries for pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are commonly performed in older adults, many of whom are also frail. A surgical risk calculator for older adults undergoing POP\/SUI surgeries that incorporates frailty, a factor known to increase the risk of surgical complications, would be helpful for preoperative counseling but currently does not exist.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>Medicare Carrier, Outpatient, and MedPAR files were examined for beneficiaries undergoing POP and SUI surgery between 2014 and 2016. A total of 15 POP\/SUI categories were examined. The Claims\u2010Based Frailty Index (CFI), a validated measure of frailty in Medicare data, and Charlson Comorbidity Index were deconstructed into their individual variables, and individual variables were entered into stepwise logistic regression models to determine which variables were most highly predictive of 30\u2010day complications and 1\u2010year mortality. To verify the prognostic accuracy for each model for surgical complications of interest, calibration curves and tests of model fit, including C\u2010statistic, Brier scores, and Spiegelhalter <jats:italic>p<\/jats:italic> values, were determined.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In total, 108\u2009479 beneficiaries were included. Among these, 4.7% had CFI scores consistent with mild to severe frailty (CFI\u22650.25). A total of 13 prognostic variable categories were found to be most highly predictive of postoperative complications. Calibration curves for each outcome of interest showed models were well\u2010fit. Most models demonstrated high c\u2010statistic values (\u22650.7) and high Spiegelhalter <jats:italic>p<\/jats:italic> values (\u22650.9), indicating good model calibration and excellent discrimination, and low Brier scores (&lt;0.02), indicating high model accuracy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Urologic surgery for older Adults Risk Calculator serves as a novel surgical risk calculator that is readily accessible to both patients and clinicians that specifically factors in components of frailty. Furthermore, this calculator accounts for the heterogeneity of an aging population and can assist in individualized surgical decision\u2010making for these common procedures.<\/jats:p><\/jats:sec>","DOI":"10.1002\/nau.25573","type":"journal-article","created":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T07:39:25Z","timestamp":1728286765000},"page":"143-152","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["UroARC: A novel surgical risk calculator for older adults undergoing pelvic organ prolapse and stress urinary incontinence surgery"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4726-9894","authenticated-orcid":false,"given":"Farnoosh","family":"Nik\u2010Ahd","sequence":"first","affiliation":[{"name":"Department of Urology University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoujun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Urology University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lufan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Urology University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"W. John","family":"Boscardin","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenneth","family":"Covinsky","sequence":"additional","affiliation":[{"name":"Department of Geriatrics University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8437-3861","authenticated-orcid":false,"given":"Anne M.","family":"Suskind","sequence":"additional","affiliation":[{"name":"Department of Urology University of California San Francisco, San Francisco California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,10,7]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.300.11.1311"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.AOG.0000136100.10818.d8"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1067\/S0002-9378(03)00829-9"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0029-7844(97)00058-6"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1097\/GCO.0000000000000200"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1097\/JU.0000000000002441"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.urology.2022.06.031"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/glx229"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/gly197"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/gerona\/gly197"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9681(87)90171-8"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwq433"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/bju.13399"},{"issue":"4","key":"e_1_2_11_15_1","first-page":"579","article-title":"Best subset, forward stepwise or lasso? 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