Clinical trial NCT06903481: Precision Sleep Medicine
Official title: Precision Sleep Medicine: Hardware and Software Innovations for the Combined Diagnosis and Treatment of Sleep Apnea at the Point-of-Care
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Obstructive Sleep Apnea
Keywords: Polysomnography (PSG) recordings
Lead sponsor: University Hospital, Basel, Switzerland
Sponsor class: OTHER
Collaborators: name: Rekonas GmbH
First posted: 2025-03-30
Enrollment: 1055
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Adults who underwent polysomnography recordings at the University Hospital Basel in 2023, as well as children and adolescents who underwent polysomnography recordings at the University Children's Hospital Basel between January 2022 and July 2024. All patients have signed the general consent of the university hospital (UBS), resp. The university children's hospital (UKBB).

Brief summary: This retrospective observational study aims to characterize the prevalence and clinical features of obstructive sleep apnea (OSA) phenotypes and develop a rater-independent algorithm for automated OSA phenotyping, improving diagnosis and personalized treatment.

Detailed description: 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.

Eligibility criteria: 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

Primary outcomes:
measure: Phenotype characterization
timeFrame: 2025
Secondary outcomes:
measure: Computer-aided phenotyping
timeFrame: 2025
Other outcomes:
Locations:
city: Basel
country: Switzerland
facility: University Children's Hospital Basel
state: Basel-Stadt
city: Basel
country: Switzerland
facility: University Hospital Basel
state: Basel-Stadt
Study officials:
affiliation: University Hospital, Basel, Switzerland
name: Matthias Herrmann, Dr. med.
role: PRINCIPAL_INVESTIGATOR
References: