心率及其从短期心电图记录中的可变性作为检测轻度认知障碍的潜在生物标志物
Anjo Xavier1, Sneha Noble1, Justin Joseph1
1Centre for Brain Research, Indian Institute of Science, Bengaluru, India.
American journal of Alzheimer's disease and other dementias
|December 17, 2024
概括
心率 (HR) 和心率变化 (HRV) 的变化可以检测轻度认知障碍 (MCI). 在MCI和健康个体之间观察到HRV指标的显著差异,机器学习模型实现了高精度.
科学领域:
- 心脏病学 心脏病学
- 神经学 神经学
- 生物医学工程 生物医学工程
背景情况:
- 由心率 (HR) 和心率变化 (HRV) 变化表明的自主功能障碍与神经退行有关.
- HR和HRV作为识别轻度认知障碍 (MCI) 的潜在生物标志物.
研究的目的:
- 调查HR和HRV作为MCI检测生物标志物的实用性在城市印度人口中.
- 分析特定的HRV参数及其与MCI诊断的相关性.
主要方法:
- 从297名城市印度参与者 (19.19%被诊断为MCI) 获得了心电图记录.
- 进行了R峰检测和对各种HRV指标的分析,包括NN间隔,SDNN和RMSSD.
- 使用机器学习分类器 (SVM,DA,NB) 评估基于HRV特征的分类准确性.
主要成果:
- 在MCI和非MCI组之间发现了平均NN间隔 (P=.0021),NN间隔的RMS (P=.0014),SDNN (P=.0192) 和RMSSD (P=.0206) 的显著差异.
- 机器学习模型,特别是使用RMS特征,在区分MCI和健康个体方面达到80.801%的高精度.
- 特定的HRV参数显示了区分认知状态的强大潜力.
结论:
- 心率 (HR) 和心率可变性 (HRV) 是早期MCI检测的有希望的非侵入性生物标志物.
- 这些发现支持将心血管自主功能评估纳入认知障碍的神经评估中.
- 进一步的研究可以完善这些生物标志物,以便在神经退行性疾病查中得到更广泛的临床应用.
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