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评估 ACS 手术风险计算器与 P-POSSUM 在预测重大肝胆手术死亡率和发病率方面的有效性:一项观察性研究。

Assessing the effectiveness of ACS surgical risk calculator versus P-POSSUM in predicting mortality and morbidity for major hepatobiliary surgery: An observational study.

机构信息

Department of General Surgery, Istanbul University Cerrahpasa - Cerrahpasa School of Medicine, Istanbul, Turkey.

Department of General Surgery, Izmir University of Economics, School of Medicine, Izmir, Turkey.

出版信息

Medicine (Baltimore). 2024 Jul 12;103(28):e38973. doi: 10.1097/MD.0000000000038973.

Abstract

Risk assessment is difficult yet would provide valuable data for both the surgeons and the patients in major hepatobiliary surgeries. An ideal risk calculator should improve workflow through efficient, timely, and accurate risk stratification. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator (SRC) and Portsmouth Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (P-POSSUM) are surgical risk stratification tools used to assess postoperative morbidity. In this study, preoperative data from 300 patients undergoing major hepatobiliary surgeries performed at a single tertiary university hospital were retrospectively collected from electronic patient records and entered into the ACS-SRC and P-POSSUM systems, and the resulting risk scores were calculated and recorded accordingly. The ACS-NSQIP-M1 (C-statistics = 0.725) and M2 (C-statistics = 0.791) models showed better morbidity discrimination ability than P-POSSUM-M1 (C-statistics = 0.672) model. The P-POSSUM-M2 (C-statistics = 0.806) model showed better differentiation success in morbidity than other models. The ACS-NSQIP-M1 (C-statistics = 0.888) and M2 (C-statistics = 0.956) models showed better mortality discrimination than P-POSSUM-M1 (C-statistics = 0.776) model. The P-POSSUM-M2 (C-statistics = 0.948) model showed better mortality differentiation success than the ACS-NSQIP-M1 and P-POSSUM-M1 models. The use of ACS-SRC and P-POSSUM calculators for major hepatobiliary surgeries offers quantitative data to assess risks for both the surgeon and the patient. Integrating these calculators into preoperative evaluation practices can enhance decision-making processes for patients. The results of the statistical analyses indicated that the P-POSSUM-M2 model for morbidity and the ACS-NSQIP-M2 model for mortality exhibited superior overall performance.

摘要

风险评估虽然困难,但可为重大肝胆外科手术的外科医生和患者提供有价值的数据。理想的风险计算器应通过高效、及时和准确的风险分层来改善工作流程。美国外科医师学院国家外科质量改进计划 (ACS-NSQIP) 外科风险计算器 (SRC) 和朴茨茅斯生理和手术严重程度评分用于死亡率和发病率计数 (P-POSSUM) 是用于评估术后发病率的外科风险分层工具。在这项研究中,从一家三级大学医院进行的 300 例重大肝胆外科手术的电子病历中回顾性收集了术前数据,并输入到 ACS-SRC 和 P-POSSUM 系统中,相应地计算并记录了得出的风险评分。ACS-NSQIP-M1(C 统计量=0.725)和 M2(C 统计量=0.791)模型在预测发病率方面比 P-POSSUM-M1(C 统计量=0.672)模型具有更好的区分能力。P-POSSUM-M2(C 统计量=0.806)模型在预测发病率方面的区分成功率优于其他模型。ACS-NSQIP-M1(C 统计量=0.888)和 M2(C 统计量=0.956)模型在预测死亡率方面比 P-POSSUM-M1(C 统计量=0.776)模型具有更好的区分能力。P-POSSUM-M2(C 统计量=0.948)模型在预测死亡率方面的区分成功率优于 ACS-NSQIP-M1 和 P-POSSUM-M1 模型。使用 ACS-SRC 和 P-POSSUM 计算器对重大肝胆外科手术进行风险评估可为外科医生和患者提供定量数据。将这些计算器纳入术前评估实践中可以增强患者的决策过程。统计分析结果表明,P-POSSUM-M2 模型在预测发病率方面和 ACS-NSQIP-M2 模型在预测死亡率方面表现出更好的整体性能。

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