Nomogram clinical prediction model for severe perioperative complications of hepatic resection for hepatolithiasis based on the albumin-bilirubin score
10.19405/j.cnki.issn1000–1492. 2026.03.025
- VernacularTitle:基于白蛋白-胆红素评分的肝胆管结石病肝切除围手术期严重并发症的列线图临床预测模型
- Author:
Ming CAO
1
;
Haoran SUN
1
;
Zhangliu JIN
1
;
Bin ZHANG
1
;
Lei WANG
1
Author Information
1. Department of General Surgery， The Second Affiliated Hospital of Anhui Medical University， Hefei 230601
- Publication Type:Journal Article
- Keywords:
ALBI score;
hepatolithiasis;
hepatic resection;
perioperative management;
complications;
nomogram
- From:
Acta Universitatis Medicinalis Anhui
2026;61(3):569-575
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo develop and validate a nomogram based on the albumin-bilirubin （ALBI） score for predicting the risk of severe perioperative complications in patients undergoing hepatectomy for hepatolithiasis. MethodsA retrospective analysis was conducted on the clinical data of 163 hepatolithiasis patients who underwent hepatectomy. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for severe perioperative complications. A nomogram prediction model was constructed and its performance was evaluated. ResultsAmong the 163 patients， 66 and 97 were classified into the low-grade and high-grade ALBI groups， respectively. Significant intergroup differences were observed in gender， total bilirubin， albumin levels， and the incidence of severe complications （P0.05）. Severe complications occurred in 40 patients. Independent risk factors included age 60 years （OR=5.49， P0.001）， high-grade ALBI （OR=8.30， P0.001）， history of biliary surgery （OR=2.60， P=0.035）， hepatectomy （segmentectomy）≥3 （OR=2.75， P=0.028）， and open surgical approach （OR=4.00， P=0.009）. A nomogram for predicting severe perioperative complications was successfully established. Internal validation showed that the model had an area under the ROC curve （AUC） of 0.865， which outperformed traditional single predictors. The calibration curve closely aligned with the ideal curve， with a mean absolute error （MAE） of 0.027. Decision curve analysis （DCA） demonstrated a net clinical benefit when the threshold probability exceeded 10%， superior to that of traditional predictors. ConclusionThe ALBI score-based nomogram is successfully developed and validated to predict the risk of severe perioperative complications in hepatolithiasis patients undergoing hepatectomy. The model demonstrated favorable predictive performance and high clinical utility， serving as an effective tool for both preoperative risk assessment and postoperative risk stratification.
