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胆汁性胰腺炎患者肿瘤标志物升高的临床意义

Clinical significance of elevated tumor markers in patients with biliary pancreatitis.

作者信息

Han He, Li Zhiyuan, Li Yunfan, Zhang Liwen, Chen Jixiang, Fan Xin

机构信息

Department of General Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.

Department of Respiratory, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.

出版信息

Front Med (Lausanne). 2025 Jun 4;12:1486963. doi: 10.3389/fmed.2025.1486963. eCollection 2025.

Abstract

OBJECTIVE

This study explores the clinical significance of elevated tumor markers in patients with biliary pancreatitis. It aims to develop a machine learning-based clinical prediction model to facilitate early intervention and improve outcomes in acute biliary pancreatitis (ABP).

METHODS

We collected data from patients admitted with biliary pancreatitis to the Department of General Surgery at Jiangsu University Hospital from January 1, 2016, to December 31, 2023. We recorded general patient information.

RESULTS

Markers including Carbohydrate Antigen (CA) 50, CA19-9, CA125, CA724, CA242, ferritin, leukocyte count, high-sensitivity C-reactive protein (HS-CRP), total bilirubin, direct bilirubin, alanine aminotransferase, and aspartate aminotransferase were significantly higher in the severe acute pancreatitis (SAP) and moderately severe acute pancreatitis (MSAP) groups compared to the mild acute pancreatitis (MAP) group ( < 0.05). Univariate logistic regression analysis identified white blood cell count, HS-CRP, CA50, CA19-9, CA125, urinary amylase, total bilirubin, aspartate aminotransferase, and hospitalization duration as risk factors for progression to MSAP or SAP. Multivariate logistic regression analysis confirmed hospitalization duration as an independent risk factor.

CONCLUSION

Elevated tumor markers have clinical significance in biliary pancreatitis. We propose a clinical prediction model based on machine learning to screen variables and guide treatment adjustments for MAP.

摘要

目的

本研究探讨胆道胰腺炎患者肿瘤标志物升高的临床意义。旨在开发一种基于机器学习的临床预测模型,以促进早期干预并改善急性胆源性胰腺炎(ABP)的治疗结果。

方法

我们收集了2016年1月1日至2023年12月31日期间在江苏大学附属医院普通外科收治的胆道胰腺炎患者的数据。我们记录了患者的一般信息。

结果

与轻度急性胰腺炎(MAP)组相比,重度急性胰腺炎(SAP)组和中度重度急性胰腺炎(MSAP)组中的糖类抗原(CA)50、CA19-9、CA125、CA724、CA242、铁蛋白、白细胞计数、高敏C反应蛋白(HS-CRP)、总胆红素、直接胆红素、丙氨酸转氨酶和天冬氨酸转氨酶等标志物显著更高(<0.05)。单因素逻辑回归分析确定白细胞计数、HS-CRP、CA50、CA19-9、CA125、尿淀粉酶、总胆红素、天冬氨酸转氨酶和住院时间是进展为MSAP或SAP的危险因素。多因素逻辑回归分析确认住院时间是独立危险因素。

结论

肿瘤标志物升高在胆道胰腺炎中具有临床意义。我们提出了一种基于机器学习的临床预测模型,以筛选变量并指导对MAP的治疗调整。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/890c/12174463/44882b3bf6a9/fmed-12-1486963-g001.jpg

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