整合ECG衍生特征与传统的CVD风险模型
Maryam Mahdavi1, Anoshirvan Kazemnejad2, Abbas Asosheh3
1Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Scientific reports
|November 7, 2025
概括
电心电图 (ECG) 功能改善了女性心血管疾病 (CVD) 风险预测,优于弗雷明汉风险评分 (FRS). 这增强了针对个性化的预防策略的早期检测.
科学领域:
- 心脏病学 心脏病学
- 预防医学 预防医学
- 生物医学信号处理
背景情况:
- 非传染性疾病 (NCD),特别是心血管疾病 (CVD),是全球主要的死亡原因.
- 伊朗面临高于平均水平的心血管疾病发病率和死亡率.
- 早期发现心血管疾病至关重要,因为它经常无症状地进展.
研究的目的:
- 评估心电图 (ECG) 信号特征对发生心血管疾病的预测能力.
- 将基于心电图的风险预测与弗雷明汉风险评分 (FRS) 进行比较.
- 评估在一个大队伍中对风险分层进行心电图信号处理.
主要方法:
- 在德黑兰脂质和葡萄糖研究 (TLGS) (2006-2008) 中,利用了4,637名成年人 (年龄≥40) 的心电图数据的信号处理.
- 随访参与者10年,以确定发生的心血管疾病 (冠心病或中风).
- 使用哈雷尔的C指数,NRI和IDI进行了重新校准的FRS模型与没有心电图特征的比较.
主要成果:
- 在10年内,483名参与者 (10.4%) 患有心血管疾病.
- 电图特征显著改善了女性心血管疾病风险预测 (C指数:0.84至0.85;NRI:55.7%;IDI:2.8%).
- 在男性中没有发现明显的改善;在中等风险的女性中,心电图模型的表现优于FRS.
结论:
- 整合ECG信号特征可以增强心血管疾病预测模型,特别是在女性身上.
- 基于心电图的风险分层显示了改善心血管疾病个性化预防策略的潜力.
- 需要进一步的研究来完善ECG工具的临床应用.
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