睡眠呼吸暂停在不同心血管疾病中的逐搏特征

文献信息

中文摘要

背景： 阻塞性睡眠呼吸暂停（OSA）与心血管疾病（CVD）密切相关，但不同的心血管表型可能对心电图衍生的RR间期动力学产生不同影响。既往研究表明，尺度依赖的去趋势波动分析（sDFA）可在广泛CVD状态下检测OSA，但这一关系在不同CVD亚型之间是否存在差异仍不清楚。
方法： 分析了睡眠心脏健康研究中具有心肌梗死（MI）、充血性心力衰竭（CHF）或心绞痛（ANG）病史的参与者的整夜多导睡眠图记录。排除同时患有其中一种以上疾病的参与者。OSA作为二分类结局进行分析，呼吸暂停低通气指数阈值为5次/小时。在每个亚组内使用年龄和体重指数进行倾向评分匹配。使用cHRV指标和二阶sDFA分析心电图衍生的RR间期动力学，并使用ROC-AUC评估判别能力。
结果： 匹配后的亚组包括112名MI参与者、18名CHF参与者和54名ANG参与者。在所有亚组中，sDFA的ROC-AUC值均高于cHRV指标。sDFA的最高ROC-AUC出现在ANG中（0.79），而MI中为0.66，CHF中为0.69。MI和ANG显示出大致相似的尺度依赖特征，而CHF似乎不同；然而，CHF分析的功效显著不足。
结论： 心电图衍生的sDFA特征在OSA判别中表现出亚型依赖性行为，在ANG中观察到最强性能。这些探索性发现提示，心血管表型可能影响OSA相关的RR间期动力学。二分类OSA分组可能掩盖与严重程度相关的差异，而排除患有多种心血管疾病的参与者限制了临床适用性。

英文摘要

BACKGROUND: Obstructive sleep apnea (OSA) is closely linked with cardiovascular disease (CVD), but different cardiovascular phenotypes may influence ECG-derived RR interval dynamics differently. Previous work has shown that scale-dependent detrended fluctuation analysis (sDFA) can detect OSA across broad CVD status, but it remains unclear whether this relationship differs between CVD subtypes.
METHODS: Overnight polysomnography recordings from the Sleep Heart Health Study were analyzed in participants with a history of myocardial infarction (MI), congestive heart failure (CHF), or angina pectoris (ANG). Participants with more than one of these conditions were excluded. OSA was analyzed as a binary outcome using an apnea-hypopnea index threshold of 5 events/h. Propensity score matching was performed within each subgroup using age and body mass index. ECG-derived RR interval dynamics were analyzed using cHRV metrics and second-order sDFA, with discrimination assessed using ROC-AUC.
RESULTS: The matched subgroups consisted of 112 participants with MI, 18 with CHF, and 54 with ANG. sDFA achieved higher ROC-AUC values than cHRV metrics in all subgroups. The highest sDFA ROC-AUC was observed in ANG (0.79), compared with 0.66 in MI and 0.69 in CHF. MI and ANG showed broadly similar scale-dependent profiles, whereas CHF appeared distinct; however, the CHF analysis was substantially underpowered.
CONCLUSION: ECG-derived sDFA features showed subtype-dependent behavior for OSA discrimination, with the strongest performance observed in ANG. These exploratory findings suggest that cardiovascular phenotype may influence OSA-related RR interval dynamics. Binary OSA grouping may mask severity-related differences, while exclusion of participants with multiple cardiovascular conditions limits clinical applicability.