Journal of electrocardiology · 2026
Beat-to-beat signatures of sleep apnea across cardiovascular diseases.
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Niemi Topi, Huovinen Mila, Räsänen Esa
Аннотация
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.
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.