Hypnogram-derived structured data reveal differences in sleep stage transition characteristics between high and low...

Area of Science:

• Sleep Medicine
• Neuroscience
• Pulmonology

Background:

• Arousal threshold (ArTH) is linked to sleep stability and disease severity in OSA.
• Conventional polysomnography (PSG) metrics do not fully capture dynamic sleep stage transitions.
• The impact of varying ArTH phenotypes on sleep architecture and transition dynamics is not well understood.

Purpose of the Study:

• To investigate how different arousal threshold (ArTH) phenotypes affect sleep architecture and transition dynamics in patients with Obstructive Sleep Apnea (OSA).
• To analyze sleep stage sequences and transition patterns using hypnogram-based analysis.

Main Methods:

• Retrospective analysis of 1792 OSA patients stratified by arousal threshold.
• Conversion of hypnograms into structured sleep-stage sequences using Python.
• Propensity score matching for age, gender, and BMI, followed by survival analysis, Poisson regression, and multistate Cox/semi-Markov models to evaluate group differences in stage persistence and transition dynamics.

Main Results:

• The High ArTH group (n=580) exhibited longer durations of N1, N2, and REM sleep, and a lower percentage of N3 sleep compared to the Low ArTH group (n=580).
• Transition analyses revealed unstable N2 sleep with frequent NREM oscillations (e.g., N1↔N2), reduced progression to N3 sleep, and lower probability of transitioning from NREM to wake states in the High ArTH group.
• These findings indicate impaired sleep stability in patients with a high arousal threshold.

Conclusions:

• Patients with a high arousal threshold (ArTH) demonstrate unstable N2 sleep.
• Frequent NREM oscillations and reduced deep sleep progression are characteristic of high ArTH phenotypes.
• These sleep disturbances are particularly pronounced in moderate to severe OSA cases.