压力诱导的高血糖是急性胰腺炎中感染性胰腺缩的独立预测因素:机器学习驱动的预后模型
Xuchen Zhao1, Jiale Xu2, Congzhong Hu1
1Department of Biliary and Pancreatic Surgery, The Third Hospital of Shanxi Medical University (Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital), Taiyuan, Shanxi, People's Republic of China.
Journal of inflammation research
|November 19, 2025
概括
压力诱发的高血糖 (SHG) 显著恶化了急性胰腺炎 (AP) 患者的结果,导致更长的住院时间和感染胰腺缩 (IPN) 的风险增加. 一个新的预测模型有助于识别IPN高风险患者.
科学领域:
- 胃肠病学和肝病学
- 内分泌学 在内分泌学.
- 关键护理医学 关键护理医学
背景情况:
- 急性胰腺炎 (AP) 是一种严重的疾病,具有显著的发病率和死亡率.
- 压力诱导的高血糖 (SHG) 在AP中很常见,但其对结果的独立影响需要进一步澄清.
研究的目的:
- 调查SHG在急性胰腺炎 (AP) 中对临床结果的影响.
- 在AP患者中开发和验证感染胰腺亡 (IPN) 的临床预测模型.
主要方法:
- 从2017-2022年对1343名AP患者的回顾性分析.
- 倾向分数匹配 (PSM) 用于比较SHG和非SHG组之间的结果.
- 使用时间分裂队列的临床预测模型的开发和验证.
主要成果:
- 即使在PSM之后,SHG患者的住院时间也显著延长,ICU入院率更高,IPN率增加.
- 确定了IPN的七个独立预测因素:高脂血症,SHG,MCTSI,SIRS,PT%,LDL-C和周围胰腺溢液.
- 临床预测模型在验证队列中表现良好 (AUC=0.891).
结论:
- SHG是AP的独立不良预后因素,对临床结果产生不利影响.
- 开发的预测模型显示了有利的性能和临床实用性,用于识别AP患者的IPN风险.
- 创建了一个基于网络的计算器,以提高预测模型的临床实用性.
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