全球电异质性的潜在特征:西班牙裔社区健康研究/拉丁裔研究。

IF 3.9 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS European heart journal. Digital health Pub Date : 2024-07-08 eCollection Date: 2024-09-01 DOI:10.1093/ehjdh/ztae048
Larisa G Tereshchenko, Kazi T Haq, Stacey J Howell, Evan C Mitchell, Jesús Martínez, Jessica Hyde, Genesis Briceno, Jose Pena, Edvinas Pocius, Akram Khan, Elsayed Z Soliman, João A C Lima, Samir R Kapadia, Anita D Misra-Hebert, Michael W Kattan, Mayank M Kansal, Martha L Daviglus, Robert Kaplan
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引用次数: 0

摘要

目的:尽管中风、肥胖和糖尿病在不同种族/族裔中发病率最高,但矛盾的是,西班牙裔/拉美裔人群心房颤动和明尼苏达代码定义的主要心电图异常的发病率却最低。我们的目标是在西班牙裔社区健康研究/拉美裔研究(HCHS/SOL)人群中使用潜在特征分析,以深入了解流行病学的差异:我们对 HCHS/SOL 的基线访问进行了横断面分析。全局电异质性(GEH)以空间 QRS-T 角(QRSTa)、空间心室阶差方位角(SVGaz)、抬高(SVGel)、幅度(SVGmag)和绝对 QRST 积分总和(SAIQRST)进行测量。统计分析采用分层两阶段区域概率样本设计。我们对年龄、性别、种族背景、教育程度、高血压、糖尿病、吸烟、血脂异常、肥胖、慢性肾病、体力活动、饮食质量、平均 RR'间隔、中位数节拍类型和心血管疾病(CVD)进行了调整,拟合了一个多变量潜特征广义结构方程模型,以深入了解 GEH 特征。在 15 684 名参与者(年龄 41 岁;53% 为女性;6% 已知有心血管疾病)中,17% 的人有可能出现异常 GEH 曲线(QRSTa 80 ± 27°、SVGaz -4 ± 21°、SVGel 72 ± 12°、SVGmag 45 ± 12 mVms 和 SAIQRST 120 ± 23 mVms)。对于 QRSTa 较窄(40.0 ± 10.2°)和 SVG 较大(SVGmag 108.3 ± 22.6 mVms;SAIQRST 203.4 ± 39.1 mVms)的参试者,有 23% 的概率属于 1 级,有 60% 的概率属于 2 级中间水平:西班牙裔/拉美裔人群中有很大一部分人(17%)的GEH图谱发生改变的几率增加,很可能是异常的,而83%的人群对有害风险因素的暴露具有抵抗力。
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Latent profiles of global electrical heterogeneity: the Hispanic Community Health Study/Study of Latinos.

Aims: Despite the highest prevalence of stroke, obesity, and diabetes across races/ethnicities, paradoxically, Hispanic/Latino populations have the lowest prevalence of atrial fibrillation and major Minnesota code-defined ECG abnormalities. We aimed to use Latent Profile Analysis in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) population to obtain insight into epidemiological discrepancies.

Methods and results: We conducted a cross-sectional analysis of baseline HCHS/SOL visit. Global electrical heterogeneity (GEH) was measured as spatial QRS-T angle (QRSTa), spatial ventricular gradient azimuth (SVGaz), elevation (SVGel), magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). Statistical analysis accounted for the stratified two-stage area probability sample design. We fitted a multivariate latent profile generalized structural equation model adjusted for age, sex, ethnic background, education, hypertension, diabetes, smoking, dyslipidaemia, obesity, chronic kidney disease, physical activity, diet quality, average RR' interval, median beat type, and cardiovascular disease (CVD) to gain insight into the GEH profiles. Among 15 684 participants (age 41 years; 53% females; 6% known CVD), 17% had an increased probability of likely abnormal GEH profile (QRSTa 80 ± 27°, SVGaz -4 ± 21°, SVGel 72 ± 12°, SVGmag 45 ± 12 mVms, and SAIQRST 120 ± 23 mVms). There was a 23% probability for a participant of being in Class 1 with a narrow QRSTa (40.0 ± 10.2°) and large SVG (SVGmag 108.3 ± 22.6 mVms; SAIQRST 203.4 ± 39.1 mVms) and a 60% probability of being in intermediate Class 2.

Conclusion: A substantial proportion (17%) in the Hispanic/Latino population had an increased probability of altered, likely abnormal GEH profile, whereas 83% of the population was resilient to harmful risk factors exposures.

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