DCM-PROGRESS:在非缺血性扩张性心肌病患者中预测末期心力衰竭
A F Schmidt1,2,3,4, P Leinveber5, R Panovsky6,7
1Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands.
medRxiv : the preprint server for health sciences
|September 25, 2023
概括
我们开发了一种新模型来预测扩张性心肌病 (DCM) 患者末期心力衰竭 (HF) 的5年风险. 这种经过验证的工具可以改善患者监测和临床决策,以获得更好的结果.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 预测分析是一种预测分析.
背景情况:
- 非缺血性扩张性心肌病 (DCM) 患者面临着末期心力衰竭 (HF) 的显著风险.
- 准确的风险预测对于及时干预和个性化患者管理至关重要.
- 目前的风险分层工具可能需要对DCM特定群体进行增强.
研究的目的:
- 开发和验证一个预测模型,用于DCM患者5年末期HF风险的预测模型.
- 为DCM患者提供个性化的监测和管理策略.
主要方法:
- 使用293名荷兰DCM患者的数据开发了一种拉索回归模型.
- 对来自捷克共和国的235名DCM患者的队列进行了外部验证.
- 预测因素包括临床,心电图,心声和生化参数;最终阶段的HF被定义为死亡,移植或心室辅助器件植入.
主要成果:
- 纳入NYHA类,心率,缩血压,身高,R轴和TAPSE的拉索模型实现了高的区分性能 (导出时的c-统计值为0.85,验证时为0.75).
- 该模型与MAGGIC得分 (c-统计值0.69) 相比,显示出更高的歧视性.
- 无论是MAGGIC得分还是DCM-PROGRESS模型,都显示出风险略高估值,但其他方面都得到了良好的校准.
结论:
- 在DCM患者中成功开发了一种已验证的,高度歧视性的末期HF风险预测模型.
- 该DCM-PROGRESS模型显示了显著提高临床决策和患者监测策略的潜力.
- 国际验证表明在各种临床环境中具有广泛的适用性.
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