Ye BaoLong, Xie JunFeng, Xi KeXing, Huang ZhiShun, Liao YanNian, Chen ZiWen, Ji Wu
Department of Gastrointestinal and Hernia Surgery, Ganzhou Hospital-Nanfang Hospital, Southern Medical University, Ganzhou, China.
Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Front Oncol. 2024 Feb 5;13:1309724. doi: 10.3389/fonc.2023.1309724. eCollection 2023.
Several surgical risk models are widely utilized in general surgery to predict postoperative morbidity. However, no studies have been undertaken to examine the predictive efficacy of these models in biliary tract cancer patients, and other perioperative variables can also influence morbidity. As a result, the study's goal was to examine these models alone, as well as risk models combined with disease-specific factors, in predicting severe complications.
A retrospective study of 129 patients was carried out. Data on demographics, surgery, and outcomes were gathered. These model equations were used to determine the morbidity risks. Severe morbidity was defined as the complication comprehensive index ≥ 40.
Severe morbidity was observed in 25% (32/129) patients. Multivariate analysis demonstrated that four parameters [comprehensive risk score ≥1, T stage, albumin decrease value, and international normalized ratio (INR)] had a significant influence on the probability of major complications. The area under the curve (AUC) of combining the four parameters was assessed as having strong predictive value and was superior to the Estimation of Physiologic Ability and Surgical Stress System (E-PASS) alone (the AUC value was 0.858 0.724, p = 0.0375). The AUC for the modified E-PASS (mE-PASS) and Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM) in patients over the age of 70 was classified as no predictive value (p = 0.217 and p = 0.063, respectively).
The mE-PASS and POSSUM models are ineffective in predicting postoperative morbidity in patients above the age of 70. In biliary tract cancer (BTC) patients undergoing radical operation, a combination of E-PASS and perioperative parameters generates a reasonable prediction value for severe complications.
几种手术风险模型在普通外科中被广泛用于预测术后发病率。然而，尚未有研究探讨这些模型在胆道癌患者中的预测效果，并且其他围手术期变量也会影响发病率。因此，本研究的目的是单独检验这些模型以及结合疾病特异性因素的风险模型在预测严重并发症方面的效果。
对129例患者进行了回顾性研究。收集了人口统计学、手术和结局数据。使用这些模型方程来确定发病风险。严重发病被定义为并发症综合指数≥40。
25%（32/129）的患者出现严重发病。多变量分析表明，四个参数[综合风险评分≥1、T分期、白蛋白降低值和国际标准化比值（INR）]对主要并发症的发生概率有显著影响。评估四个参数组合的曲线下面积（AUC）具有较强的预测价值，且优于单独的生理能力和手术应激系统估计（E-PASS）（AUC值为0.858对0.724，p = 0.0375）。70岁以上患者的改良E-PASS（mE-PASS）和用于死亡率和发病率枚举的生理和手术严重程度评分（POSSUM）的AUC被分类为无预测价值（分别为p = 0.217和p = 0.063）。
mE-PASS和POSSUM模型在预测70岁以上患者的术后发病率方面无效。在接受根治性手术的胆道癌（BTC）患者中，E-PASS和围手术期参数的组合对严重并发症产生了合理的预测价值。
