Diagnostic, Obstructive Apnea, Sleep Apnea Syndrome (OSAS)
Conditions
Keywords
Home Sleep Apnea Testing
Brief summary
Obstructive sleep apnea (OSA) is usually diagnosed from a single night of home sleep apnea testing using the apnea-hypopnea index (AHI). However, the AHI varies substantially from night to night, undermining diagnostic accuracy, and shows only modest correlation with symptoms. This variability further limits its usefulness for predicting cardiovascular and other complications. Besides the traditional AHI, more robust physiological markers are needed. Several emerging physiological metrics - hypoxic burden, ventilatory burden, heart rate variability, autonomic arousals, and the pulse wave amplitude drop index - capture the physiological impact of OSA more comprehensively and demonstrate stronger associations with cardiovascular risk. Despite this promise, their night-to-night variability has not been studied. A systematic evaluation of both established and novel OSA metrics across nights is essential to identify reliable, stable parameters suitable for clinical routine. This improves diagnostic precision beyond what traditional metrics can provide, enhances patient selection, reduces costs and patient harm, and may improve treatment outcomes.
Interventions
None listed
Sponsors
Insel Gruppe AG, University Hospital Bern
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients with suspected or diagnosed sleep-disordered breathing, irrespective of disease severity, as defined by the indications for home sleep apnea testing in the German guidelines \[15\] * No active treatment during sleep recordings or within preceding two weeks (e.g., mandibular advancement devices, positive airway pressure therapy) * Written informed consent obtained
Exclusion criteria
* Age \<18 years * Known or suspected neurological sleep disorder (e.g., narcolepsy, parasomnia) * Known or suspected psychiatric sleep disorder * Known or suspected central and complex sleep apnea * Participants who are unable to perform sleep measurements reliably * Insufficient knowledge of the project language (German) * Inability to give consent * Shift workers (with shift work \<2 weeks before testing)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Night-to-night variability of apnea-hypopnea index (events per hour of sleep) over 4 nights | 4 nights of respiratory polygraphy | The variability of the apnea-hypopnea index (events per hour of sleep) over 4 nights will be quantified using linear mixed-effects models, accounting for confounding variables. |
| Night-to-night variability of oxygen desaturation index (events per hour of sleep) over 10 nights | 4 nights of respiratory polygraphy and 10 nights of oxymetry | The variability will be quantified using linear mixed-effects models, accounting for confounding variables. |
| Night-to-night variability of hypoxic burden (minute x percent per hour of sleep) over 10 nights | 4 nights of respiratory polygraphy and 10 nights of oxymetry | The variability will be quantified using linear mixed-effects models, accounting for confounding variables. |
| Night-to-night variability of ventilatory burden over 4 nights | 4 nights of respiratory polygraphy | The variability will be quantified using linear mixed-effects models, accounting for confounding variables. Ventilatory burden will be calculated according to Parekh et al. |
| Night-to-night variability of heart rate variability over 10 nights | 4 nights of respiratory polygraphy and 10 nights of oxymetry | The variability will be quantified using linear mixed-effects models, accounting for confounding variables. |
| Night-to-night variability of pulse wave amplitude drops (events per hour) over 10 nights | 4 nights of respiratory polygraphy and 10 nights of oxymetry | The variability will be quantified using linear mixed-effects models, accounting for confounding variables. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Identification of factors contributing to and explaining variability | 4 nights of respiratory polygraphy and 10 nights of oxymetry | Each influencing factor will be evaluated on its potential to explain the observed variability in the objective physiological parameters listed above. Each factor will be included individually as a fixed effect in the mixed-effects model and tested for significance. The following factors will be analyzed: * Age (years) * Body mass index (kg(m2) * Gender * Upper airway anatomy (tonsil size) * Mean OSA severity over all nights (of the respective parameter) * Sleep position (supine time as a percent of sleep time) * Alcohol consumption (number of drinks) * Caffeine intake (number of cups) * Nicotine use (number of packages) * Sleep Medication (free text) * Subjective sleep quality (visual analog scale, VAS, 0 to 10 points) * Snoring intensity (VAS, 0 to 10 points) * Daytime sleepiness on a VAS of the subsequent day (0 to 10 points) * Daytime sleepiness on the Epworth Sleepiness Scale of the subsequent day (0 to 24 points) * Respiratory symptoms such as infection (VAS) * Allergy symptoms |
| Correlation between physiological parameters from sleep testing and patient-reported outcome measures (PROMs) | 4 nights of respiratory polygraphy and 10 nights of oxymetry | Associations between physiological metrics and PROMs will be assessed using mixed-effects models, analogously to the analysis of influencing factors above and correlation analysis (Spearman's rank coefficient). Patient-reported symptoms for correlation analyses: * Sleep quality on a VAS (0 to 10 points) * Snoring intensity on a VAS (0 to 10 points) * Daytime sleepiness on a VAS (0 to 10 points) * Epworth Sleepiness Scale (0 to 24 points) |
Countries
Switzerland
Outcome results
None listed