建立和验证用于肝脑病变风险预测的诺莫格拉姆模型:回顾性分析
Chun Yao1, Liangjiang Huang1, Meng Wang2
1Guangxi University of Chinese Medicine, Nanning, 530001, Guangxi, People's Republic of China.
Scientific reports
|November 9, 2023
概括
一种新的诺莫格拉姆模型有效地预测了不补偿性肝硬化患者的肝脑病风险. 关键因素包括年龄,糖尿病,,血,有助于早期干预,以改善患者的治疗结果.
科学领域:
- 肝病学 肝病学是一种肝病学.
- 临床预测建模临床预测建模
- 胃肠病学 胃肠病学
背景情况:
- 肝脏脑病变 (HE) 对缺乏补偿的肝硬化患者构成重大风险.
- 准确的风险分层对于及时干预和改善患者管理至关重要.
- 现有的预测模型可能缺乏易用性或全面验证.
研究的目的:
- 开发和验证一种高质量,易于使用的脑图,用于预测肝脏脑病变风险.
- 确定与非补偿性肝硬化中HE发展相关的关键临床指标.
- 为了促进高风险患者的早期识别和干预.
主要方法:
- 分析了1178名患有不补偿性肝硬化症的患者队列.
- 单变量分析,LASSO回归和多因素分析确定了风险因素.
- 通过差异化,校准和决策曲线分析构建和验证了一个名ogram模型.
主要成果:
- 纳米图包括年龄,糖尿病,,自发性腹膜炎,氨酸酶和血液.
- 该模型表现出良好的歧视,AUC为0.738 (培训) 和0.667 (验证).
- 校准分析表明预测误差最小,决策曲线显示临床效用.
结论:
- 55岁以上的年龄,糖尿病,,自发性细菌性腹膜炎,异常的ALT和血液是HE的独立危险因素.
- 开发的诺莫图谱为预测非补偿性肝硬化病的HE风险提供了有效的工具.
- 这个模型可以帮助临床医生在早期风险识别和肝脏脑病变的管理.
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