May 10, 2026SLEEP
0484 The Effect of Statistical Analysis Method on the Trend of Obstructive Sleep Apnea-Induced Heart Rate Change: The Multi-Ethnic Study of Atherosclerosis
Key result
Quartile and max-min metrics yield up to ~8x larger HR changes during OSA than the mean.
- n=2,035
Why the study?
Although OSA-induced heart rate changes are widely studied as noninvasive biomarkers, the lack of standardized analysis methods has led to inconsistent findings, requiring evaluation of how analysis choices affect observed changes.
How do different statistical analysis choices influence the observed heart rate changes induced by obstructive sleep apnea?
Population
2,035 participants with validated OSA annotations in the Multi-Ethnic Study of Atherosclerosis Sleep Ancillary Study
Comparison
Different HR metrics, analysis window durations, OSA segmentations, and OSA episode definitions
Design
Cross-sectional analysis of polysomnography data
Authors
Discussion
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Implication
Warrants caution with mean HR metrics in OSA; leaves open optimal method for quantifying autonomic responses and CV risk.
Key Points
- This study aims to understand how different statistical analysis methods affect heart rate changes during obstructive sleep apnea events.
- Analyzed polysomnography data from 2,035 participants in the Multi-Ethnic Study of Atherosclerosis.
- Evaluated heart rate changes using various metrics (mean, quartile, max-min) across different analysis windows and segmentations.
- Investigated pre-, intra-, and post-OSA period HR changes with defined episode structures.
- Quartile and max-min metrics showed HR changes about 5 times and 8 times larger than the mean metric, respectively.
- 10–15s analysis windows produced HR changes 25–85% larger than those calculated with a 5s window.
- Combining pre- and intra-OSA periods affected HR changes with notable variations depending on the analysis method used.
Study Design
Type
Observational (n=2,035)
Structured PICO
How do different statistical analysis choices influence the observed heart rate changes induced by obstructive sleep apnea?
P
Population
2,035 participants with validated obstructive sleep apnea (OSA) annotations in the Multi-Ethnic Study of Atherosclerosis Sleep Ancillary Study
I
Intervention
Various statistical analysis methods for quantifying ECG-derived heart rate changes (including HR metrics, analysis window durations, OSA segmentations, and OSA episode definitions)
O
Outcome
ECG-derived heart rate changes in pre-, intra-, and post-OSA eventssurrogate
Statistical analysis choices, such as HR metrics and window durations, significantly influence the quantification of OSA-induced heart rate changes, highlighting the need for standardized methodologies.
Cite This Study
Zhou et al. (2026) conducted an observational in Obstructive sleep apnea (OSA) (n=2,035). Various statistical analysis methods (metrics, window durations, segmentations) was evaluated on ECG-derived heart rate (HR) changes in pre-, intra-, and post-OSA events. Statistical analysis choices significantly influenced observed heart rate changes during obstructive sleep apnea, with quartile and max-min metrics producing 5 to 8 times larger changes than the mean.