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通过一种新的生物标志物增强模型,改善代谢性肝病中的心血管风险预测
Lars Hegstrom1, Yestle Kim2, Pete Vu2
1Nference, Cambridge, Massachusetts, USA.
一种新的LIVER-ASCVD+模型改善了在患有代谢功能障碍相关的性肝病 (MASLD) 和代谢功能障碍相关的性肝炎 (MASH) 患者的心血管风险预测. 该模型整合了肝脏生物标志物,为这些高风险人群提供了比现有工具更好的准确性.
科学领域:
- 心脏病学 心脏病学
- 肝病学 肝病学是一种肝病学.
- 流行病学 流行病学
背景情况:
- 代谢功能障碍相关的性肝病 (MASLD) 和代谢功能障碍相关的性肝炎 (MASH) 正在成为全球越来越严重的健康问题.
- 目前的心血管疾病 (CVD) 风险模型不充分预测MASLD/MASH患者的事件.
研究的目的:
- 开发和验证一种新的回归模型,LIVER-ASCVD+,用于在MASLD/MASH患者中增强心血管疾病风险预测.
- 为了提高准确性,将传统的心血管风险因素与肝脏生物标志物相结合.
主要方法:
- 一项追溯的队列研究,包括9185名经活检确认的MASH患者.
- 对比LIVER-ASCVD+模型与ASCVD风险估计器Plus的性能.
- 卡普兰-梅尔生存分析和倾向匹配的对照队伍.
主要成果:
- LIVER-ASCVD+对心肌梗塞/中风 (AUC:0.68) 和死亡率 (AUC:0.63) 的预测准确度优于ASCVD风险估计器Plus (AUC:0.63和0.54).
- 该模型有效地将患者分为不同的风险类别,结果有显著差异.
- 卡普兰-梅尔分析证实了该模型增强的预测能力.
结论:
- 整合肝脏生物标志物显著改善了MASLD/MASH患者心血管疾病风险预测.
- LIVER-ASCVD+模型为临床决策和改善患者结果提供了一个有前途的工具.
- 建议对LIVER-ASCVD+模型进行进一步验证.
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