Sleep-wake parameters can be detected in patients with chronic stroke using a multisensor accelerometer: a validation study

Elie Gottlieb; Leonid Churilov; Emilio Werden; Thomas Churchward; Matthew P Pase; Natalia Egorova; Mark E Howard; Amy Brodtmann

doi:10.5664/jcsm.8812

Sleep-wake parameters can be detected in patients with chronic stroke using a multisensor accelerometer: a validation study

J Clin Sleep Med. 2021 Feb 1;17(2):167-175. doi: 10.5664/jcsm.8812.

Authors

Elie Gottlieb^{1

2}, Leonid Churilov², Emilio Werden^{1

2}, Thomas Churchward^{3

4}, Matthew P Pase^{5

6}, Natalia Egorova^{1

7}, Mark E Howard^{2

3

4

8}, Amy Brodtmann^{1

2

8}

Affiliations

¹ The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
² University of Melbourne, Melbourne, Victoria, Australia.
³ Institute for Breathing and Sleep, Melbourne, Victoria, Australia.
⁴ Austin Health, Heidelberg, Victoria, Australia.
⁵ Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria, Australia.
⁶ Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.
⁷ Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia.
⁸ Co-senior authors.

Abstract

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.

Keywords: accelerometer; aging; behavioral sleep medicine; instrumentation; scoring; sleep/wake physiology; stroke; validation.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Actigraphy*
Humans
Polysomnography
Prospective Studies
Sleep
Stroke* / complications

Grants and funding

R01 AG062531/AG/NIA NIH HHS/United States