住院COVID-19患者的超短心率变化和短期死亡率之间的关系
Baoying Lin1, Lingdan Jin1, Lingjia Li1
1Department of Cardiology, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Cardiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.
超短心率变化 (US-HRV) 参数,特别是SDNN,与COVID-19患者的短期死亡率有关. 较低的SDNN水平表明风险更高,有助于早期识别高风险个体.
科学领域:
- 心脏病学 心脏病学
- 关键护理医学 关键护理医学
- 传染性疾病 传染性疾病
背景情况:
- COVID-19 构成重大威胁,需要准确的预后工具.
- 心率变化 (HRV) 反映了自主神经系统的功能,并已被探索为预后指标.
研究的目的:
- 评估住院COVID-19患者的超短心率变化 (US-HRV) 和短期死亡率之间的关联.
- 为早期识别高风险COVID-19患者开发预测模型.
主要方法:
- 一项对488名COVID-19患者进行的回顾性队列研究.
- 分析10秒心电图 (ECG) 数据,以计算US-HRV参数:正常到正常间隔的标准偏差 (SDNN) 和连续差异的平方根平均值 (rMSSD).
- 终点:短期死亡率 (住院或出院后1周内).
主要成果:
- 共有76名患者 (15.6%) 死亡.
- 在非幸存者组中观察到显著较低的SDNN和rMSSD值 (P < 0.001).
- SDNN表现出良好的预测性能 (AUC=0.761),美国-HRV参数组合显示AUC为0.774. 较低的SDNN水平与增加的死亡风险相关.
- 多变量分析确定SDNN是预后的独立预测因子 (OR=5.791,P=0.007).
- 开发的模型显示出强大的预测能力:1型AUC=0.866,2型AUC=0.914.
结论:
- 在住院COVID-19患者中,SDNN与短期死亡率显著相关.
- 美国-HRV参数,特别是SDNN,可以增强风险分层模型,以改善患者管理.
- 早期评估SDNN可能有助于识别需要更密切监测和干预的COVID-19患者.
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