The association of odds ratio product with respiratory and arousal measures in post-stroke patients.

Sleep Med

Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.

Published: March 2025

Study Objectives: Obstructive Sleep Apnea (OSA) affects up to 70 % of post-stroke patients, complicating recovery and rehabilitation. This study aimed to evaluate the utility of the Odds Ratio Product (ORP), a continuous EEG-derived metric of sleep depth, in predicting conventional respiratory and arousal measures in stroke patients. We hypothesized that ORP metrics will predict conventional measures in patients with a history of stroke or Transient ischemic attack (TIA).

Methods: A retrospective analysis was conducted on 113 stroke/TIA individuals who underwent in-laboratory polysomnography (PSG). ORP metrics, including ORP, ORP, ORP, and Wake Intrusion Indices (WIIs), were analyzed using multivariate linear regression models. Models were stratified by OSA status. Standardized coefficients were used to assess associations with the apnea-hypopnea index (AHI), respiratory disturbance index (RDI), and arousal indices.

Results: ORP metrics demonstrated statistically significant associations with conventional respiratory and arousal measures, with varying predictive strength across models. Specifically, ORP and WIIs exhibited strong predictive effects across all models. ORP significantly predicted respiratory and arousal measures in the overall sample and the OSA subgroup, but its predictive value diminished in the non-OSA subgroup. ORP was statistically significantly associated with respiratory and arousal measures; however, its associations with arousal measures were weaker in participants with OSA compared to those without OSA.

Conclusion: ORP metrics have the potential to refine OSA diagnoses and improve therapeutic strategies in post-stroke/TIA populations. Their integration into sleep assessments could facilitate early intervention and potentially optimize stroke recovery outcomes, addressing gaps in current evaluation methods.

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http://dx.doi.org/10.1016/j.sleep.2025.02.048DOI Listing

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