Precision Sleep Medicine

Obstructive sleep apnea (OSA) is characterized by repeated upper airway blockages during sleep, but it presents with a range of phenotypic variations, each with potentially distinct clinical implications. Current clinical definitions are not always precise, making it difficult to clearly classify patients with overlapping features. This phenotypic overlap poses challenges for understanding the true prevalence of "pure" versus "mixed" OSA phenotypes and their respective clinical implications.

To comprehensively characterize the prevalence and clinical features of distinct OSA phenotypes in a large, diverse patient population, this retrospective study analyzes polysomnography (PSG) data from two publicly available National Sleep Research Resource datasets. The findings are then compared to datasets from the University Hospital Basel and University Children's Hospital Basel to assess generalizability.

Furthermore, the study employs computer-aided analysis of PSG data to develop rater-independent algorithms for objective and automated OSA phenotyping. These advancements aim to improve understanding of OSA heterogeneity, facilitating more precise diagnoses and personalized treatment strategies.

Inclusion criteria

• age 19 years and older (data from University Hospital Basel (USB))
• age 18 years or younger (data from University Children's Hospital Basel (UKBB))
• Epworth Sleepiness Scale (ESS) score available (USB only)
• Diagnosis available (e.g. Obstructive sleep apnea (OSA), Central Sleep Apnea (CSA), Cheyne Stokes Breathing (CSR), ...)
• signed written general consent

Exclusion criteria

• history of treatment of sleep apnea
• tracheostomy
• current home oxygen therapy
• decline to sign the written general consent, or absence of written general consent