天津医药 ›› 2026, Vol. 54 ›› Issue (1): 35-40.doi: 10.11958/20251377

• 临床研究 • 上一篇    下一篇

胆总管结石并发急性胆源性胰腺炎的危险因素及预测模型的构建

楚兴(), 刘磊, 杨华, 陈宏()   

  1. 汉中市中心医院肝胆胰脾外科(邮编723000)
  • 收稿日期:2025-04-02 修回日期:2025-06-27 出版日期:2026-01-15 发布日期:2026-01-19
  • 通讯作者: E-mail:chenhonggandan@163.com
  • 作者简介:楚兴(1992),男,主治医师,主要从事肝胆胰肿瘤的诊断及治疗方面研究。E-mail:Cx75672@163.com
  • 基金资助:
    陕西省科技计划项目(2021JM1021)

Risk factors and prediction model construction for acute biliary pancreatitis complicated with common bile duct stones

CHU Xing(), LIU Lei, YANG Hua, CHEN Hong()   

  1. Department of Hepatobiliary Surgery, Hanzhong Central Hospital, Hanzhong 723000, China
  • Received:2025-04-02 Revised:2025-06-27 Published:2026-01-15 Online:2026-01-19
  • Contact: E-mail:chenhonggandan@163.com

摘要:

目的 分析胆总管结石(CBDS)并发急性胆源性胰腺炎(ABP)的危险因素并构建预测模型。方法 纳入并发ABP的CBDS患者105例为ABP组,另纳入未并发ABP的CBDS患者105例为非ABP组。收集所有CBDS患者临床资料,通过多因素非条件Logistic回归分析CBDS并发ABP的危险因素,并据此构建CBDS并发ABP的列线图预测模型,H-L检验预测模型的拟合度;受试者工作特征(ROC)曲线分析预测模型的预测价值,C-index分析预测模型的区分能力,校准曲线分析预测模型的准确性,决策曲线分析预测模型的临床效益。结果 Logistic回归分析显示,年龄高、糖尿病、结石直径大、胆总管直径大、中性粒细胞/淋巴细胞比值(NLR)高、血淀粉酶(AMS)高、C反应蛋白(CRP)高为CBDS并发ABP的独立危险因素(P<0.05)。基于影响CBDS并发ABP的危险因素构建列线图预测模型,该预测模型H-L检验P>0.05。ROC曲线显示,该预测模型预测CBDS并发ABP的曲线下面积为0.884,C-index为0.884,校准曲线显示模型预测概率趋势接近理想曲线,决策曲线显示预测模型净收益范围较大。结论 基于CBDS并发ABP的危险因素构建的列线图预测模型具有良好的预测能效。

关键词: 胆总管结石病, 胰腺炎, 危险因素, 列线图, 急性胆源性胰腺炎

Abstract:

Objective To analyze the risk factors and construct prediction model for acute biliary pancreatitis (ABP) complicated by common bile duct stones (CBDS). Methods A total of 105 patients with CBDS complicated by ABP were included as the ABP group, and another 105 CBDS patients without ABP were included as the non-ABP group. Clinical data of all patients were collected. Multivariate unconditional Logistic regression was used to identify the risk factors for CBDS complicated by ABP, and a nomogram predictive model was developed accordingly. The H-L test was used to evaluate the fit degree of the model. The predictive value was assessed by the receiver operating characteristic (ROC) curve. C-index analysis was used to predict the discriminatory ability of the model. Calibration curve was used to analyze and predict the accuracy of the model. The decision curve was used to analyze clinical benefits of the model. Results Logistic regression analysis showed that older age, diabetes, larger stone diameter, larger common bile duct diameter, higher neutrophil-to-lymphocyte ratio (NLR), elevated serum amylase (AMS) and higher C-reactive protein (CRP) levels were independent risk factors for CBDS complicated by ABP (P<0.05). A nomogram predictive model was constructed based on these factors, and the H-L test showed good model fit (P > 0.05). The ROC curve indicated an area under the curve (AUC) of 0.884, and the C-index was 0.884. The calibration curve demonstrated that the predicted probabilities were close to the ideal line, and the decision curve showed a wide range of net benefit. Conclusion The nomogram predictive model based on the identified risk factors for CBDS complicated by ABP shows good predictive performance. Keywords: common bile duct stones; pancreatitis; risk factors; nomogram; acute biliary pancreatitis

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