大型临床队列中与心房颤动发病相关的新型睡眠表型特征

IF 8 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS JACC. Clinical electrophysiology Pub Date : 2024-09-01 DOI:10.1016/j.jacep.2024.05.027
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引用次数: 0

摘要

背景:虽然睡眠障碍与心房颤动(房颤)有关,但生理改变和症状之间的相互作用仍不清楚。基于睡眠的表型可以解释这种复杂性,并转化为识别高危患者和治疗干预的可行方法:本研究假设症状的离散表型和基于多导睡眠图(PSG)的数据与房颤事件的关系有所不同:方法:对克利夫兰诊所患者(≥18 岁)在 2004 年 11 月 27 日至 2015 年 12 月 30 日期间接受 PSG 检查的 STARLIT(与患者特征相关的睡眠信号、测试和报告)登记数据进行了回顾性研究。通过对症状和基于 PSG 的睡眠呼吸障碍和睡眠结构测量进行潜类分析,确定了表型。表型被作为主要预测因素纳入了房颤事件的多变量调整 Cox 比例危险模型:在我们的队列中(N = 43,433 人,年龄 51.8 ± 14.5 岁,51.9% 为男性,74.9% 为白人),7.3%(n = 3,166 人)有基线房颤。在 7.6 ± 3.4 年的随访期间,8.9% 的患者(n = 3,595 例)发展为偶发性房颤。研究发现了五种表型。缺氧亚型(n = 3,245)的房颤发病率增加了 48%(HR:1.48;95% CI:1.34-1.64),呼吸暂停+唤醒亚型(n = 4,592)的房颤发病率增加了 22%(HR:1.22;95% CI:1.10-1.35),睡眠时间短+唤醒亚型(n = 4,592)的房颤发病率增加了 22%(HR:1.22;95% CI:1.10-1.35)。35),短睡眠+非快速眼动亚型(n = 6 126)与参照组长睡眠+快速眼动(n = 26 809)相比,房颤发生率增加了 11%(HR:1.11;95% CI:1.01-1.22)。低通气亚型(n = 2,661)与参照组没有差异(HR:0.89;95% CI:0.77-1.03):与之前支持缺氧作为房颤驱动因素和嗜睡表型的心脏风险的证据一致,这种症状和生理改变的组合说明了房颤发展的脆弱性,为增强我们对综合睡眠特异性症状和房性心律失常发生的生理风险的理解提供了潜在价值。
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Novel Sleep Phenotypic Profiles Associated With Incident Atrial Fibrillation in a Large Clinical Cohort

Background

While sleep disorders are implicated in atrial fibrillation (AF), the interplay of physiologic alterations and symptoms remains unclear. Sleep-based phenotypes can account for this complexity and translate to actionable approaches to identify at-risk patients and therapeutic interventions.

Objectives

This study hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF.

Methods

Data from the STARLIT (sleep Signals, Testing, And Reports LInked to patient Traits) registry on Cleveland Clinic patients (≥18 years of age) who underwent PSG from November 27, 2004, to December 30,2015, were retrospectively examined. Phenotypes were identified using latent class analysis of symptoms and PSG-based measures of sleep-disordered breathing and sleep architecture. Phenotypes were included as the primary predictor in a multivariable-adjusted Cox proportional hazard models for incident AF.

Results

In our cohort (N = 43,433, age 51.8 ± 14.5 years, 51.9% male, 74.9% White), 7.3% (n = 3,166) had baseline AF. Over a 7.6- ± 3.4-year follow-up period, 8.9% (n = 3,595) developed incident AF. Five phenotypes were identified. The hypoxia subtype (n = 3,245) had 48% increased incident AF (HR: 1.48; 95% CI: 1.34-1.64), the apneas + arousals subtype (n = 4,592) had 22% increased incident AF (HR: 1.22; 95% CI: 1.10-1.35), and the short sleep + nonrapid eye movement subtype (n = 6,126) had 11% increased incident AF (HR: 1.11; 95% CI: 1.01-1.22) compared with long sleep + rapid eye movement (n = 26,809), the reference group. The hypopneas subtype (n = 2,661) did not differ from reference (HR: 0.89; 95% CI: 0.77-1.03).

Conclusions

Consistent with prior evidence supporting hypoxia as an AF driver and cardiac risk of the sleepy phenotype, this constellation of symptoms and physiologic alterations illustrates vulnerability for AF development, providing potential value in enhancing our understanding of integrated sleep-specific symptoms and physiologic risk of atrial arrhythmogenesis.
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来源期刊
JACC. Clinical electrophysiology
JACC. Clinical electrophysiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
10.30
自引率
5.70%
发文量
250
期刊介绍: JACC: Clinical Electrophysiology is one of a family of specialist journals launched by the renowned Journal of the American College of Cardiology (JACC). It encompasses all aspects of the epidemiology, pathogenesis, diagnosis and treatment of cardiac arrhythmias. Submissions of original research and state-of-the-art reviews from cardiology, cardiovascular surgery, neurology, outcomes research, and related fields are encouraged. Experimental and preclinical work that directly relates to diagnostic or therapeutic interventions are also encouraged. In general, case reports will not be considered for publication.
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