天津医药 ›› 2025, Vol. 53 ›› Issue (7): 694-699.doi: 10.11958/20251117

• 临床研究 • 上一篇    下一篇

老年消化道出血患者不良预后的列线图预测模型的构建与验证

金吴娟1(), 倪刚1,(), 黄欣宇2, 王羊洋1   

  1. 1 安徽医科大学第三附属医院,合肥市第一人民医院老年科(邮编230041)
    2 安徽医科大学第三附属医院,合肥市第一人民医院输血科(邮编230041)
  • 收稿日期:2025-03-25 修回日期:2025-04-21 出版日期:2025-07-15 发布日期:2025-07-21
  • 通讯作者: E-mail:1205090027@qq.com
  • 作者简介:金吴娟(1991),女,主治医师,主要从事老年消化道疾病研究。E-mail:jinwujuan1501@126.com
  • 基金资助:
    安徽省高校健康智库咨政项目(2023szk001)

Construction and validation of nomogram prediction model for poor prognosis in elderly patients with gastrointestinal bleeding

JIN Wujuan1(), NI Gang1,(), HUANG Xinyu2, WANG Yangyang1   

  1. 1 Department of Geriatrics, the Third Affiliated Hospital of Anhui Medical University, the First People's Hospital of Hefei, Hefei 230041, China
    2 Department of Blood Transfusion, the Third Affiliated Hospital of Anhui Medical University, the First People's Hospital of Hefei, Hefei 230041, China
  • Received:2025-03-25 Revised:2025-04-21 Published:2025-07-15 Online:2025-07-21
  • Contact: E-mail:1205090027@qq.com

摘要:

目的 构建老年消化道出血患者出现不良预后的列线图预测模型并进行验证。方法 选取176例老年消化道出血患者作为研究对象,根据患者住院期间预后情况分为预后不良组(56例)和预后良好组(120例)。收集2组患者的临床资料,利用Lasso回归模型进行老年消化道出血患者发生不良预后的最佳变量筛选,将筛选的变量纳入多因素Logistic回归模型分析影响因素,并基于影响因素构建列线图,绘制受试者工作特征(ROC)曲线、临床校准曲线、决策分析曲线(DCA)验证列线图预测模型的临床实用性。结果 多因素Logistic回归分析显示,尿素氮(BUN;OR=2.766,95%CI:1.066~7.175)、休克指数(SI;OR=3.853,95%CI:1.028~14.446)水平高是影响老年消化道出血患者不良预后的独立危险因素(P<0.05),白蛋白(ALB;OR=0.100,95%CI:0.036~0.277)水平高是保护因素(P<0.05)。ROC曲线验证预测模型的曲线下面积为0.845(95%CI:0.786~0.904),校准曲线显示模型有较高的校准度,DCA显示模型具有明显的正向净收益。结论 基于老年消化道出血患者BUN、SI及ALB水平构建的患者不良预后的列线图预测模型具有较高的预测价值。

关键词: 预后, 列线图, 老年人, 消化道出血, 预测模型, 模型验证

Abstract:

Objective To construct and validate a nomogram prediction model for poor prognosis in elderly patients with gastrointestinal bleeding. Methods A total of 176 elderly patients with gastrointestinal bleeding were enrolled as the research objects. According to the prognosis during hospitalization, patients were divided into the poor prognosis group (56 cases) and the good prognosis group (120 cases). The clinical data of the two groups of patients were collected. The best variables of poor prognosis were screened by Lasso regression model, and the selected variables were included in the multivariate Logistic regression model to analyze the influencing factors. Nomogram was constructed based on the above influencing factors. Receiver operating characteristic (ROC) curve, clinical calibration curve and decision curve analysis (DCA) were drawn to validate clinical practicability of nomogram prediction model. Results Multivariate Logistic regression analysis showed that urea nitrogen (BUN, OR=2.766, 95%CI: 1.066-7.175) and high level of shock index (SI, OR=3.853, 95%CI: 1.028-14.446) were independent risk factors of poor prognosis in elderly patients with gastrointestinal bleeding (P<0.05), while high levels of albumin (ALB, OR=0.100, 95%CI: 0.036-0.277) were protective factors (P<0.05). ROC curve validated that the area under the curve of the prediction model was 0.845 (95%CI: 0.786-0.904). Calibration curve showed that the model had a relatively high degree of calibration. DCA showed that the model had a clear positive net benefit. Conclusion The nomogram prediction model constructed based on BUN, SI and ALB levels to predict the poor prognosis of elderly patients with gastrointestinal bleeding has a high predictive value.

Key words: prognosis, nomograms, aged, gastrointestinal bleeding, prediction model, model validation

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