Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Clin Chim Acta. 2022 Sep 1;534:57-64. doi: 10.1016/j.cca.2022.07.003. Epub 2022 Jul 11.
The aim of this retrospective study is to develop and validate a predictive nomogram for predicting the risk of post-operative abdominal infection (PAI) in patients undergoing pancreaticoduodenectomy (PD).
A total of 360 patients who underwent PD were enrolled into this research and randomly divided into the development and validation group. The clinical data of patients were statistically compared and the nomogram was constructed based on the results of multivariate logistic regression analysis and stepwise (stepAIC) selection. The nomogram was internally and crossly validated by the development and validation cohort. The discriminatory ability of the nomogram was estimated by AUC (Area Under the receiver operating characteristic Curve), calibration curve and decision curve analysis.
After PD, post-operative abdominal infection occurred in 33.89% (n = 122) of patients. The nomogram showed that preoperative biliary drainage and C-reactive protein (CRP), direct bilirubin (DB), alkaline phosphatase (AKP) levels on the 3rd postoperative day (POD3) were independent prognostic factors for abdominal infection after PD. The internal and cross validation of Receiver Operating Characteristic (ROC) curve was statistically significant (AUC = 0.723 and 0.786, respectively). The calibration curves showed good agreement between nomogram predictions and actual observations. The decision curves showed that the nomogram was of great clinical value.
A nomogram based on perioperative risk factors such as preoperative biliary drainage, CRP, DB and AKP could simply and accurately predict the risk degree of PAI in patients undergoing PD.
本回顾性研究旨在开发和验证一种预测模型，用于预测接受胰十二指肠切除术（PD）的患者术后腹部感染（PAI）的风险。
本研究共纳入 360 例接受 PD 的患者，并将其随机分为开发和验证组。对患者的临床数据进行统计学比较，并基于多变量逻辑回归分析和逐步（stepAIC）选择的结果构建预测模型。通过开发和验证队列对预测模型进行内部和交叉验证。通过 AUC（接受者操作特征曲线下的面积）、校准曲线和决策曲线分析评估预测模型的区分能力。
PD 术后，有 33.89%（n=122）的患者发生术后腹部感染。预测模型显示，术前胆道引流和术后第 3 天（POD3）的 C 反应蛋白（CRP）、直接胆红素（DB）和碱性磷酸酶（AKP）水平是 PD 后腹部感染的独立预后因素。ROC 曲线的内部和交叉验证具有统计学意义（AUC 分别为 0.723 和 0.786）。校准曲线显示预测模型与实际观察结果具有良好的一致性。决策曲线表明预测模型具有重要的临床价值。
基于术前胆道引流、CRP、DB 和 AKP 等围手术期危险因素的预测模型，可以简单、准确地预测接受 PD 的患者发生 PAI 的风险程度。
