Respiratory event duration reveals novel phenotypes beyond the apnea-hypopnea index in obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a heterogeneous disorder characterized by recurrent upper airway collapse during sleep. Although the apnea-hypopnea index (AHI) remains the cornerstone of OSA diagnosis and severity assessment, it primarily reflects the frequency of respiratory events and may not adequately capture differences in respiratory event duration or the associated physiological burden. We aimed to identify novel OSA phenotypes by incorporating respiratory event duration into polysomnography-based cluster analysis.

METHODS: We retrospectively analyzed consecutive adult patients with OSA who underwent overnight polysomnography. Demographic, anthropometric, and polysomnographic characteristics were collected. Age, body mass index (BMI), neck circumference, AHI, lowest oxygen saturation (LowSpO₂), longest apnea duration (LAP), and longest hypopnea duration (LHP) were included in the clustering analysis. Hierarchical clustering using Ward's method was first performed to determine the optimal number of clusters, followed by K-means clustering to identify distinct OSA phenotypes.

RESULTS: Among 999 consecutive patients, 959 with complete clustering variables were included in the final analysis. Hierarchical clustering followed by K-means clustering identified four distinct OSA phenotypes. Cluster 1 represented a mild phenotype characterized by the lowest AHI, the shortest LAP, and preserved nocturnal oxygenation. Cluster 2 represented an obesity-associated severe phenotype with the highest BMI, the largest neck circumference, the highest AHI, and the greatest degree of nocturnal oxygen desaturation. Cluster 3 was characterized by markedly prolonged apnea duration despite only moderate AHI, whereas Cluster 4 exhibited the longest apnea and hypopnea durations accompanied by pronounced nocturnal hypoxemia. Significant differences were observed among the four phenotypes in demographic characteristics, obesity-related measures, disease severity, nocturnal oxygenation, and respiratory event duration (all P < 0.001). Importantly, respiratory event duration provided additional temporal characterization across phenotypes beyond conventional frequency-based severity assessment.

CONCLUSIONS: Respiratory event duration-enhanced clustering identified four exploratory OSA phenotypes with distinct temporal characteristics. These findings suggest that respiratory event duration may provide complementary information to conventional AHI-based severity assessment, while its clinical utility requires further validation.