• Hideaki Nakayama, Mina Kobayashi, Satoru Tsuiki, Mariko Yanagihara, and Yuichi Inoue.
• Department of Respiratory Medicine, Tokyo Medical University, 6-7-1Nishi-shinjuku, Shinjuku-ku, Tokyo, 160-0023, Japan. hidenaka@tokyo-med.ac.jp.
• Sleep Breath. 2019 Dec 1; 23 (4): 1087-1094.

PurposeThe upper airway (UA) anatomical collapsibility, UA muscle responsiveness, breathing control, and/or arousability are important contributing factors for obstructive sleep apnea (OSA). Differences in clinical manifestations of OSA are believed to reflect interactions among these factors. We aimed to classify OSA patients into subgroups based on polysomnographic (PSG) variables using cluster analysis and assess each subgroup's characteristics.MethodsMen with moderate or severe OSA and without any concomitant heart or psychosomatic disease were recruited. A hierarchical cluster analysis was performed using variables including fraction of apnea, respiratory event duration, minimum oxygen saturation, arousal rate before termination, and frequency of respiratory events in the supine position. The impact of sleep stages or body position on PSG variables was also evaluated in each cluster.ResultsA total of 210 men (mean age, 50.0 years, mean body mass index, 27.4 kg/m2) were studied. The three subgroups that emerged from the analysis were defined as follows: cluster 1 (high fraction of apnea and severe desaturation (20%)), cluster 2 (high fraction of apnea and long event duration (31%)), and cluster 3 (low fraction of apnea (49%)). There were differences in the body mass index and apnea type between the three clusters. Sleep stages and/or body position affected PSG variables in each cluster.ConclusionsPatients with OSA could be divided into three distinct subgroups based on PSG variables. This clustering may be used for assessing the pathophysiology of OSA to tailor individual treatment other than continuous positive airway pressure therapy.

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