Laurence Weinberg, Dong Kyu Lee, Luke Fletcher, Bobby Ou Yang, Jadon Karp, Anoop N Koshy, Ranjan Guha, Hugh Slifirski, Michael R D'Silva, Rinaldo Bellomo, Leonid Churilov
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Multivariable logistic regression analysis was performed on a training cohort, followed by calibration on a validation cohort, followed by performance evaluation on a testing cohort. The discriminative accuracy was compared to that of the age-adjusted Charlson Comorbidity Index for each outcome. The primary outcome was the ability of the risk stratification tool to effectively classify patients into those who may or may not experience a postoperative complications or mortality within their index hospital stay.</p><p><strong>Results: </strong>A total of 3085 patients were enrolled. The GERIATRIC risk tool had good discriminative accuracy for any postoperative complication [area under the receiver operating characteristic curves (AUROC), 0.857; 95% CI = 0.824-0.890] and any severe postoperative complication (AUROC, 0.833; 95% CI = 0.793-0.874), and fair discriminative accuracy for in-hospital mortality (AUROC, 0.780; 95% CI = 0.668-0.893).</p><p><strong>Conclusions: </strong>Compared to the age-adjusted Charlson Comorbidity Index, The GERIATRIC risk tool was accurate in classifying patients into those who may or may not experience severe complications or die during their index admission. The tool can be used to assist perioperative clinicians with shared decision-making and short-term prognostication.</p>","PeriodicalId":72231,"journal":{"name":"Annals of surgery open : perspectives of surgical history, education, and clinical approaches","volume":"5 4","pages":"e524"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11661723/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Perioperative NonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) Risk Stratification Tool.\",\"authors\":\"Laurence Weinberg, Dong Kyu Lee, Luke Fletcher, Bobby Ou Yang, Jadon Karp, Anoop N Koshy, Ranjan Guha, Hugh Slifirski, Michael R D'Silva, Rinaldo Bellomo, Leonid Churilov\",\"doi\":\"10.1097/AS9.0000000000000524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To develop age-appropriate nonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) risk tool for classifying patients who may or may not develop postoperative complications or die within their index hospital admission.</p><p><strong>Background: </strong>There are no validated perioperative risk stratification tools for use in nonagenarian and centenarian patients-people aged 90 to 99 years and >100 years.</p><p><strong>Methods: </strong>In this retrospective observational study, nonagenarians and centenarians undergoing any surgical procedure were profiled. Surgery severity was stratified, and the incidence and grade of postoperative complications were recorded. Multivariable logistic regression analysis was performed on a training cohort, followed by calibration on a validation cohort, followed by performance evaluation on a testing cohort. The discriminative accuracy was compared to that of the age-adjusted Charlson Comorbidity Index for each outcome. The primary outcome was the ability of the risk stratification tool to effectively classify patients into those who may or may not experience a postoperative complications or mortality within their index hospital stay.</p><p><strong>Results: </strong>A total of 3085 patients were enrolled. The GERIATRIC risk tool had good discriminative accuracy for any postoperative complication [area under the receiver operating characteristic curves (AUROC), 0.857; 95% CI = 0.824-0.890] and any severe postoperative complication (AUROC, 0.833; 95% CI = 0.793-0.874), and fair discriminative accuracy for in-hospital mortality (AUROC, 0.780; 95% CI = 0.668-0.893).</p><p><strong>Conclusions: </strong>Compared to the age-adjusted Charlson Comorbidity Index, The GERIATRIC risk tool was accurate in classifying patients into those who may or may not experience severe complications or die during their index admission. 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引用次数: 0
摘要
目的:建立适合年龄的非90岁和百岁外科(GERIATRIC)风险评估工具,对可能或不可能发生术后并发症或在入院期间死亡的患者进行分类。背景:目前还没有经过验证的围手术期风险分层工具用于90 ~ 99岁和100 ~ 100岁的90 ~ 99岁和百岁患者。方法:在这项回顾性观察研究中,对接受任何外科手术的九十岁和百岁老人进行了分析。对手术严重程度进行分层,记录术后并发症的发生率和分级。对训练队列进行多变量logistic回归分析,对验证队列进行校正,对测试队列进行绩效评价。将每个结果的判别准确度与年龄校正的Charlson合并症指数进行比较。主要结果是风险分层工具有效地将患者分为在其指标住院期间可能发生或可能不发生术后并发症或死亡的患者的能力。结果:共纳入3085例患者。GERIATRIC风险工具对任何术后并发症具有良好的判别准确度[受试者工作特征曲线下面积(AUROC), 0.857;95% CI = 0.824-0.890]和任何严重的术后并发症(AUROC, 0.833;95% CI = 0.793-0.874),住院死亡率的判别准确度相当(AUROC, 0.780;95% ci = 0.668-0.893)。结论:与年龄调整的Charlson合并症指数相比,GERIATRIC风险工具在将患者分类为可能或不可能经历严重并发症或在入院期间死亡的患者方面是准确的。该工具可用于协助围手术期临床医生共同决策和短期预后。
The Perioperative NonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) Risk Stratification Tool.
Objective: To develop age-appropriate nonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) risk tool for classifying patients who may or may not develop postoperative complications or die within their index hospital admission.
Background: There are no validated perioperative risk stratification tools for use in nonagenarian and centenarian patients-people aged 90 to 99 years and >100 years.
Methods: In this retrospective observational study, nonagenarians and centenarians undergoing any surgical procedure were profiled. Surgery severity was stratified, and the incidence and grade of postoperative complications were recorded. Multivariable logistic regression analysis was performed on a training cohort, followed by calibration on a validation cohort, followed by performance evaluation on a testing cohort. The discriminative accuracy was compared to that of the age-adjusted Charlson Comorbidity Index for each outcome. The primary outcome was the ability of the risk stratification tool to effectively classify patients into those who may or may not experience a postoperative complications or mortality within their index hospital stay.
Results: A total of 3085 patients were enrolled. The GERIATRIC risk tool had good discriminative accuracy for any postoperative complication [area under the receiver operating characteristic curves (AUROC), 0.857; 95% CI = 0.824-0.890] and any severe postoperative complication (AUROC, 0.833; 95% CI = 0.793-0.874), and fair discriminative accuracy for in-hospital mortality (AUROC, 0.780; 95% CI = 0.668-0.893).
Conclusions: Compared to the age-adjusted Charlson Comorbidity Index, The GERIATRIC risk tool was accurate in classifying patients into those who may or may not experience severe complications or die during their index admission. The tool can be used to assist perioperative clinicians with shared decision-making and short-term prognostication.