Time-Structured Detection of Pre-Event Cardiovascular Instability Using CPAP-Derived Cheyne–Stokes Breathing

Abstract Aims Continuous positive airway pressure (CPAP) telemonitoring provides daily respiratory metrics, including Cheyne–Stokes breathing percentage (CSB%), which may reflect ventilatory–circulatory instability. However, inter-individual variability limits the clinical applicability of fixed thresholds. We developed a time-structured detection architecture using CPAP telemonitoring time-series data and evaluated its ability to identify temporal patterns preceding cardiovascular and cerebrovascular events. Methods and results In this retrospective observational study, 1,265 patients with obstructive sleep apnoea undergoing CPAP telemonitoring were analysed. Daily CSB% values were smoothed using a 3-day moving average and evaluated relative to individualized dynamic baselines. The detection framework consisted of two complementary components: identification of sustained deviation from baseline and detection of abrupt pre-event surges. Central apnea predominance, assessed using the central apnea index, was incorporated as a hierarchical escalation layer. Among 25 adjudicated cardiovascular and cerebrovascular events in 20 patients (heart failure 11, atrial fibrillation 7, cerebrovascular accident 7), the architecture detected 23 events (92.0%) within the predefined D−28 window. Median lead time was 12.0 days (IQR 2.8–24.0). False-positive alerts were concentrated within a subset of individuals. Hierarchical filtering reduced alerts by 94.9% relative to the baseline signal layer while preserving event enrichment. Distinct temporal phenotypes, including trajectory-dominant and spike-dominant patterns, were observed across disease categories, consistent with disease-specific pre-event dynamics. Conclusion CPAP-derived CSB% may function as a time-structured digital biomarker reflecting evolving ventilatory–circulatory instability. A trajectory-based detection architecture may enable early identification of cardiovascular instability while maintaining operational feasibility in large-scale telemonitoring environments.

Authors

Institutions

Publication Details

Journal
European Heart Journal - Digital Health
Published
2026-07-01
DOI
https://doi.org/10.1093/ehjdh/ztag108
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Time-Structured Detection of Pre-Event Cardiovascular Instability Using CPAP-Derived Cheyne–Stokes Breathing

Yoko Takamatsu, Kimimasa Saito
European Heart Journal - Digital Health
Obstructive Sleep Apnea Research
article

Time-Structured Detection of Pre-Event Cardiovascular Instability Using CPAP-Derived Cheyne–Stokes Breathing

Yoko Takamatsu, Kimimasa Saito
article en

Abstract

Abstract Aims Continuous positive airway pressure (CPAP) telemonitoring provides daily respiratory metrics, including Cheyne–Stokes breathing percentage (CSB%), which may reflect ventilatory–circulatory instability. However, inter-individual variability limits the clinical applicability of fixed thresholds. We developed a time-structured detection architecture using CPAP telemonitoring time-series data and evaluated its ability to identify temporal patterns preceding cardiovascular and cerebrovascular events. Methods and results In this retrospective observational study, 1,265 patients with obstructive sleep apnoea undergoing CPAP telemonitoring were analysed. Daily CSB% values were smoothed using a 3-day moving average and evaluated relative to individualized dynamic baselines. The detection framework consisted of two complementary components: identification of sustained deviation from baseline and detection of abrupt pre-event surges. Central apnea predominance, assessed using the central apnea index, was incorporated as a hierarchical escalation layer. Among 25 adjudicated cardiovascular and cerebrovascular events in 20 patients (heart failure 11, atrial fibrillation 7, cerebrovascular accident 7), the architecture detected 23 events (92.0%) within the predefined D−28 window. Median lead time was 12.0 days (IQR 2.8–24.0). False-positive alerts were concentrated within a subset of individuals. Hierarchical filtering reduced alerts by 94.9% relative to the baseline signal layer while preserving event enrichment. Distinct temporal phenotypes, including trajectory-dominant and spike-dominant patterns, were observed across disease categories, consistent with disease-specific pre-event dynamics. Conclusion CPAP-derived CSB% may function as a time-structured digital biomarker reflecting evolving ventilatory–circulatory instability. A trajectory-based detection architecture may enable early identification of cardiovascular instability while maintaining operational feasibility in large-scale telemonitoring environments.

European Heart Journal - Digital Health
Unitika (Japan) (JP)
Good health and well-being
Openalex Percentile: Top 7%
Obstructive Sleep Apnea Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.