ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2021
Sleep-wake parameters can be detected in patients with chronic stroke using a multisensor accelerometer: a validation study.
Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Sleep Quality, Circadian Rhythm Stability and Changes in Delirium State in Predicting Mortality Risk in Intensive Care Unit Patients: A Prospective Observational Study.Nursing in critical care · 2025Observational
- Weekend sedentary behaviour and cognition three months after stroke based on the exploratory analysis of the CANVAS study.Scientific reports · 2025Article
- Circadian Factors in Stroke: A Clinician's Perspective.Cardiology and therapy · 2023Review
- A comparison of agreement between actigraphy and polysomnography for assessing sleep during posttraumatic amnesia.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022Article
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Authors and funding
8 authors at 4 institutions in 2 countries.
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Abstract
STUDY
objectivesSleep-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.
methodsTwenty-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.
resultsTotal 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.
conclusionsThe 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.
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