Sleep medicine · 2026
Heterogeneity in CPAP titration across unsupervised polysomnographic phenotypes of Obstructive Sleep Apnea: a retrospective study.
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Fang Ruichen, Yang Hangyi, Li Shuangyan, Cheng Yihong, Xu Yan, Wang Yuling, Jiang Jinnong, Zhang Bin
Аннотация
OBJECTIVE: The efficacy of CPAP therapy depends on optimal titration. However, pre-titration sleep assessment is limited to the AHI, which overlooks the substantial heterogeneity of OSA. Therefore, this study applied cluster analysis to describe PSG-based OSA phenotypes and investigate their CPAP titration characteristics, aiming to inform more individualized titration strategies.
METHODS: This was a retrospective analysis of patients newly diagnosed with OSA by PSG who subsequently underwent CPAP titration. Subjects were classified using two-step cluster analysis, with PSG parameters and demographic characteristics as clustering features. Study outcomes included titrated CPAP level, titration grade, and changes in sleep parameters from baseline to the titration night across clusters. Between-cluster differences were assessed using chi-square and Kruskal-Wallis tests, and sleep parameters changes were evaluated with a linear mixed-effects model (LMM).
RESULTS: 758 subjects were categorized into four phenotypic clusters: 1. REM-related, non-mixed OSA (18.9%); 2. Male, non-REM-related, mixed OSA (10.9%); 3. Male, non-REM-related, non-mixed OSA (57.7%); 4. Female, non-REM-related OSA (12.5%). Among the four clusters, Cluster 2 exhibited the highest titrated pressure and titration complexity, while Cluster 1 showed the lowest (p ≤ 0.001). The LMM, adjusted for baseline PSG parameters, revealed differences in the acute changes in sleep parameters during titration across the four clusters, with Cluster 2 showing the most pronounced acute improvements (p < 0.001).
CONCLUSIONS: Beyond the AHI, PSG can provide additional phenotyping information that is associated with distinct CPAP titration characteristics, which may help inform individualized titration strategies.
METHODS: This was a retrospective analysis of patients newly diagnosed with OSA by PSG who subsequently underwent CPAP titration. Subjects were classified using two-step cluster analysis, with PSG parameters and demographic characteristics as clustering features. Study outcomes included titrated CPAP level, titration grade, and changes in sleep parameters from baseline to the titration night across clusters. Between-cluster differences were assessed using chi-square and Kruskal-Wallis tests, and sleep parameters changes were evaluated with a linear mixed-effects model (LMM).
RESULTS: 758 subjects were categorized into four phenotypic clusters: 1. REM-related, non-mixed OSA (18.9%); 2. Male, non-REM-related, mixed OSA (10.9%); 3. Male, non-REM-related, non-mixed OSA (57.7%); 4. Female, non-REM-related OSA (12.5%). Among the four clusters, Cluster 2 exhibited the highest titrated pressure and titration complexity, while Cluster 1 showed the lowest (p ≤ 0.001). The LMM, adjusted for baseline PSG parameters, revealed differences in the acute changes in sleep parameters during titration across the four clusters, with Cluster 2 showing the most pronounced acute improvements (p < 0.001).
CONCLUSIONS: Beyond the AHI, PSG can provide additional phenotyping information that is associated with distinct CPAP titration characteristics, which may help inform individualized titration strategies.