Projects per year
Study Objectives: Sleep-wake dysfunction is bidirectionally associated with the pathogenesis and evolution of stroke. Longitudinal and prospective measurement of sleep after chronic stroke remains poorly characterized because of a lack of validated objective and ambulatory sleep measurement tools in neurological populations. This study aimed to validate a multisensor sleep monitor, the SenseWear Armband (SWA), in patients with ischemic stroke and control patients using at-home polysomnography. Methods: Twenty-eight radiologically confirmed patients with ischemic stroke (aged 69.61 ± 7.35 years; mean = 4.1 years poststroke) and 16 control patients (aged 73.75 ± 7.10 years) underwent overnight at-home polysomnography in tandem with the SWA. Lin's concordance correlation coefficient and reduced major axis regressions were employed to assess concordance of SWA vs polysomnography-measured total sleep time, sleep efficiency, sleep onset latency, and wake after sleep onset. Subsequently, data were converted to 30-second epochs to match at-home polysomnography. Epoch-by-epoch agreement between SWA and at-home polysomnography was estimated using crude agreement, Cohen's kappa, sensitivity, and specificity. Results: Total sleep time was the most robustly quantified sleep-wake variable (concordance correlation coefficient = 0.49). The SWA performed poorest for sleep measures requiring discrimination of wakefulness (sleep onset latency; concordance correlation coefficient = 0.16). The sensitivity of the SWA was high (95.90%) for patients with stroke and for control patients (95.70%). The specificity of the SWA was fair-moderate for patients with stroke (40.45%) and moderate for control patients (45.60%). Epoch-by-epoch agreement rate was fair (78%) in patients with stroke and fair (74%) in controls. Conclusions: The SWA shows promise as an ambulatory tool to estimate macro parameters of sleep-wake; however, agreement at an epoch level is only moderate-fair. Use of the SWA warrants caution when it is used as a diagnostic tool or in populations with significant sleep-wake fragmentation.
|Number of pages||9|
|Journal||Journal of Clinical Sleep Medicine|
|Publication status||Published - 1 Feb 2021|
- Behavioral sleep medicine
- Sleep/wake physiology
Effects of Poor Sleep on Alzheimer’s Disease Pathogenesis: Extending the Glymphatic Flow Hypothesis
Pase, M., Lim, Y. Y., Naughton, M. & Buckley, R.
National Health and Medical Research Council (NHMRC) (Australia)
4/05/20 → 31/12/24
Uncovering vascular contributions to neurodegenerative disease and dementia
4/05/20 → 31/12/22
Contributions of sleep to preclinical and clinical Alzheimer's disease
Himali , J. J. & Pase, M.
1/04/20 → 28/02/23