Background: Sleep is increasingly recognized as a crucial component to rapid and successful rehabilitation, especially from traumatic brain injuries (TBIs). Assessment of longitudinal patterns of sleep in a hospital setting, however, are difficult and often the expertise or equipment to conduct such studies is not available. Actigraphy (wrist-worn accelerometry) has been used for many years as a simple proxy measurement of sleep patterns, but its use has not been thoroughly validated in individuals with TBI. Objective: To determine the validity of different sensitivity settings of actigraphy analysis to optimize its use as a proxy for recording sleep patterns in individuals with a TBI. Design: Comparison of actigraphy to criterion standard polysomnographic (PSG)-determination of sleep on a single overnight study. Setting: Six rehabilitation hospitals in the TBI Model System. Participants: Two hundred twenty-seven consecutive, medically stable individuals with a TBI. Interventions: Not applicable. Main Outcome Measure: Concordance between PSG- and actigraphy-determined sleep using different sensitivity threshold settings (low, medium, high, automated). Results: Bland-Altman plots revealed increasing error with increasing amounts of wake during the sleep episode. Precision-recall statistics indicate that with less sensitive actigraphy thresholds, episodes identified as “wake” are usually “wake,” but many true episodes of “wake” are missed. With more sensitive actigraphy thresholds, more episodes of “wake” are identified, but only some of these are true episodes of “wake.”. Conclusions: In hospitalized patients with TBI and poor sleep, actigraphy underestimates the level of sleep disruption and has poor concordance with PSG-determined sleep. Alternate methods of scoring sleep from actigraphy data are necessary in this population.
Bibliographical noteFunding Information:
The study authors would like to acknowledge the following staff for their efforts in recruitment and data collection: Danielle O'Connor, MPH (Tampa), Carlos Diaz-Sein, RPSGT (Tampa), Lancie Wharton, RPSGT (Tampa), Emily Noyes, MA (Tampa), Jacob Goodfleisch, BA (Ohio State), Dominic Sauer (Ohio State), Erica Wasmund (U Washington), Angela Philippus, MS (Craig Hospital), Jody Newman, MA, CCC-SLP (Craig Hospital), Emily Almeida, MS (Craig Hospital), Michael Makley, MD (Craig Hospital), Alan Weintraub, MD (Craig Hospital), Eric Spier, MD (Craig Hospital), Amber Lopez-Merfeld, MPH (Baylor Scott & White Rehabilitation), Lacy Hinkle (Baylor Scott & White Rehabilitation), Rosemary Dubiel, D.O. (Baylor Scott & White Rehabilitation), Terrie Jones, RN, RRT, RCP (Baylor Scott & White Rehabilitation), David L. Luterman, MD (Baylor Scott & White Rehabilitation), Devon Kratchman (Moss Rehabilitation Research Institute), Rachel Raucci (Moss Rehabilitation Research Institute), Julie Wilson (Moss Rehabilitation Research Institute), Kelly McLaughlin (Moss Rehabilitation Research Institute), Amber Leon (Moss Rehabilitation Research Institute), Brandice Coleman (Moss Rehabilitation Research Institute), Grace Loscalzo (Moss Rehabilitation Research Institute).
Research reported in this article was funded through a Patient‐Centered Outcomes Research Institute (PCORI) Award (CER‐1511‐33 005). This research was sponsored by VHA Central Office VA TBI Model Systems Program of Research; Subcontract from General Dynamics Information Technology (W91YTZ‐13‐C‐0015; HT0014‐19‐C‐0004) from the Defense and Veterans Brain Injury Center and National Institute on Disability, Independent Living, and Rehabilitation Research (NSDC Grant # 90DPTB00070, #90DP0084, 90DPTB0013‐01‐00, 90DPTB0008, 90DPT80004‐02). The statements presented in this publication are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient‐Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. Funding:
© 2020 American Academy of Physical Medicine and Rehabilitation. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.
- Comparative Study
- Validation Study