Farnoosh Nik-Ahd, Shoujun Zhao, W John Boscardin, Lufan Wang, Kenneth Covinsky, Anne M Suskind
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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 <i>P</i> values, were calculated to ensure the prognostic accuracy for postoperative complications.</p><p><strong>Results: </strong>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 <i>P</i> values, respectively, and high accuracy with low Brier scores. Calibration curves for each outcome demonstrated excellent model fit.</p><p><strong>Conclusions: </strong>This novel risk assessment tool may help guide surgical prognostication among this vulnerable population.</p>","PeriodicalId":17471,"journal":{"name":"Journal of Urology","volume":null,"pages":null},"PeriodicalIF":5.9000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343443/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of the UroARC Surgical Calculator: A Novel Risk Calculator for Older Adults Undergoing Surgery for Bladder Outlet Obstruction.\",\"authors\":\"Farnoosh Nik-Ahd, Shoujun Zhao, W John Boscardin, Lufan Wang, Kenneth Covinsky, Anne M Suskind\",\"doi\":\"10.1097/JU.0000000000003978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>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.</p><p><strong>Materials and methods: </strong>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 <i>P</i> values, were calculated to ensure the prognostic accuracy for postoperative complications.</p><p><strong>Results: </strong>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 <i>P</i> values, respectively, and high accuracy with low Brier scores. 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引用次数: 0
摘要
目的:膀胱出口梗阻(BOO)在老年人中很常见。许多接受手术治疗的老年人都有影响手术风险的其他弱点,包括体弱。以虚弱程度为基础来预测各种膀胱出口梗阻手术结果的临床工具将有助于帮助做出手术决策,但目前尚不存在:使用医疗保险 MedPAR、门诊病人和承保人文件对 2014 年至 2016 年期间接受 BOO 手术的医疗保险受益人进行识别和分析。创建了八个不同的 BOO 手术类别。使用基于索赔的虚弱指数(CFI)计算每位受益人的基线虚弱程度。将 CFI 中的所有 93 个变量和 Charlson 生病指数中的 17 个变量分别输入逐步逻辑回归模型,以确定对并发症最具预测性的变量。相似和重复的变量被合并成不同的类别。计算校准曲线和模型拟合测试,包括 C 统计量、Brier 评分和 Spiegelhalter P 值,以确保术后并发症预后的准确性:共确定了 212,543 名受益人。约42.5%的人属于前期体弱(0.15≤CFI<0.25),8.7%的人属于轻度体弱(0.25≤CFI<0.35),1.2%的人属于中度至重度体弱(CFI≥0.35)。通过逐步逻辑回归,13 个不同的预后变量类别被确定为最可靠的术后预后预测因子。大多数模型都表现出极佳的模型区分度和校准度,分别具有较高的 C 统计量和 Spiegelhalter P 值,以及较低的 Brier 分数和较高的准确度。每种结果的校准曲线都显示出了极佳的模型拟合度:这一新型风险评估工具可为这一弱势群体的手术预后提供指导。
Development of the UroARC Surgical Calculator: A Novel Risk Calculator for Older Adults Undergoing Surgery for Bladder Outlet Obstruction.
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.
期刊介绍:
The Official Journal of the American Urological Association (AUA), and the most widely read and highly cited journal in the field, The Journal of Urology® brings solid coverage of the clinically relevant content needed to stay at the forefront of the dynamic field of urology. This premier journal presents investigative studies on critical areas of research and practice, survey articles providing short condensations of the best and most important urology literature worldwide, and practice-oriented reports on significant clinical observations.