Predictors of in-laboratory polysomnography attendance in a cohort of patients with stroke or TIA

Alex A MacDonald; Phavalan Rajendram; Maneesha Kamra; Brian J Murray; Penny A MacDonald; Mark I Boulos

doi:10.1016/j.sleep.2019.10.002

Predictors of in-laboratory polysomnography attendance in a cohort of patients with stroke or TIA

Sleep Med. 2020 Feb:66:159-164. doi: 10.1016/j.sleep.2019.10.002. Epub 2019 Oct 14.

Authors

Alex A MacDonald¹, Phavalan Rajendram², Maneesha Kamra³, Brian J Murray², Penny A MacDonald⁴, Mark I Boulos⁵

Affiliations

¹ Department of Psychiatry, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada; Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada.
² Department of Medicine, Division of Neurology, University of Toronto, Toronto, Canada; Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada.
³ Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada.
⁴ Brain and Mind Institute & Clinical Neurological Sciences, University of Western Ontario, London, Canada.
⁵ Department of Medicine, Division of Neurology, University of Toronto, Toronto, Canada; Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada. Electronic address: mark.boulos@sunnybrook.ca.

PMID: 31877507
DOI: 10.1016/j.sleep.2019.10.002

Abstract

Study objectives: After cerebrovascular events, obstructive sleep apnea (OSA) is associated with poor functional outcomes, an increased risk of recurrent stroke, and mortality. Although the significant under-diagnosis of OSA is likely multifactorial in nature, factors associated with attendance at in-laboratory polysomnography (iPSG) are poorly understood. We evaluated demographic, lifestyle, and clinical variables that predicted attendance at iPSG in a cohort of patients with stroke and transient ischemic attack (TIA) enrolled in a clinical research study.

Methods: Demographic, lifestyle, and clinical variables were summarized for the patients who did and did not attend iPSG. Multivariable binary logistic regression analyses were performed to examine four models that thematically aggregated predictors expected to relate to attendance. Further, t-tests for continuous variables, and chi-squared tests for categorical variables, were performed to uncover differences between the two groups.

Results: In the 122 participants included in our analyses, mean age was 66.6 ± 15.7 (64.8% males) with only 59.0% of participants attending iPSG. Only Model 1, which investigated the impact of demographic, lifestyle, and cognitive status, was significant (χ² = 35.31, p < 0.001). Among our variables, (1) younger age, (2) better cognition, (3) higher level of education, and (4) never-smoking status significantly predicted attendance at iPSG.

Conclusion: By understanding the relationship between variables that significantly predict attendance, we hope our results will translate into practices that promote iPSG attendance, which may help improve outcomes in the stroke/TIA population.

Clinical trials: SLEep APnea Screening Using Mobile Ambulatory Recorders After TIA/Stroke (SLEAP SMART) (NCT02454023); https://clinicaltrials.gov/ct2/show/NCT02454023.

Keywords: Obstructive sleep apnea; Polysomnography; Polysomnography attendance; Stroke; Transient ischemic attack.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Age Factors
Cohort Studies
Female
Humans
Ischemic Attack, Transient / complications*
Male
Middle Aged
Patients / statistics & numerical data*
Polysomnography*
Risk Factors
Stroke / complications*
Surveys and Questionnaires

Associated data

ClinicalTrials.gov/NCT02454023