PDF(Pubmed)
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：
风险评估是困难的，但将为外科医生和大型肝胆手术的患者提供有价值的数据。理想的风险计算器应该通过高效，及时,和准确的风险分层。美国外科医生学会国家外科质量改善计划（ACS-NSQIP）手术风险计算器（SRC）和朴茨茅斯生理和手术严重程度评分（P-POSSUM）是手术风险分层工具用于评估术后发病率。在这项研究中,从一家三级大学医院接受大型肝胆手术的300例患者的术前数据从电子病历中回顾性收集，并输入ACS-SRC和P-POSSUM系统。并据此计算和记录所产生的风险评分.ACS-NSQIP-M1（C统计量=0.725）和M2（C统计量=0.791）模型显示出比P-POSSUM-M1（C统计量=0.672）模型更好的发病率辨别能力。P-POSSUM-M2（C-statistics=0.806）模型在发病率方面比其他模型显示出更好的分化成功率。ACS-NSQIP-M1（C统计量=0.888）和M2（C统计量=0.956）模型显示出比P-POSSUM-M1（C统计量=0.776）模型更好的死亡率判别。P-POSSUM-M2(C-statistics=0.948)模型显示出比ACS-NSQIP-M1和P-POSSUM-M1模型更好的死亡率分化成功率。在大型肝胆手术中使用ACS-SRC和P-POSSUM计算器可提供定量数据，以评估外科医生和患者的风险。将这些计算器集成到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，发病率的P-POSSUM-M2模型和死亡率的ACS-NSQIP-M2模型表现出优异的总体表现。
