在酒精相关的肝病中,急性-慢性肝衰竭的基于机器学习的风险因素
Linhui Hu1, Hao Cheng1, Jing Pan1
1Department of Infectious Disease, Peking University First Hospital, Beijing, People's Republic of China.
Annals of medicine
|January 30, 2026
概括
在与酒精相关的肝病 (ALD) 中,急性至慢性肝衰竭 (ACLF) 的早期发现至关重要. 使用总 bilirubin,叶酸,维生素 B12 和前热血素时间差的新模型准确地预测了 ACLF 风险.
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
- 生物化学 生物化学
背景情况:
- 酒精相关性肝病 (ALD) 带来了重大的临床挑战,急性至慢性肝衰竭 (ACLF) 导致高早期死亡率.
- 早期识别患有ACLF风险的患者对于改善ALD的结果至关重要.
研究的目的:
- 开发和验证ALD患者中ACLF的预测模型.
- 确定早期ACLF风险分层的关键临床指标.
主要方法:
- 对210名ALD患者 (2000-2024) 的回顾性观察研究.
- 用 LASSO 调节后勤回归 (LR) 进行预测器选择.
- 使用十倍交叉验证和AUC进行模型验证;用Shapley值评估特征重要性.
主要成果:
- 确定了四种ACLF的独立预测因素:总胆红素 (TBIL),叶酸,维生素B12 (VitB12),和前列血时间差 (ΔPT).
- 开发的LR模型显示出出色的预测准确性,AUC为0.970.
结论:
- 开发了一个结合LR和机器学习的强大的临床预测模型.
- 结核酸,叶酸,VitB12和ΔPT是早期ALD患者ACLF风险分层的关键预后标志物.
- 基于该模型的及时干预可以减少ACLF发病率.
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