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P112 Under-mattress sleep monitoring to predict readmission risk after COPD exacerbation

BACKGROUND: Recurrent hospitalisation for COPD exacerbations is a major contributor to disease burden and healthcare costs. This study aims to establish if post-discharge sleep or vital sign parameters are predictive of hospital readmissions after COPD exacerbations. METHODS: Patients admitted with...

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Detalles Bibliográficos
Autores principales: Proctor, S, Molloy, W, Chai-Coetzer, C, Catcheside, P, Adams, R, Mukherjee, S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109303/
http://dx.doi.org/10.1093/sleepadvances/zpab014.155
Descripción
Sumario:BACKGROUND: Recurrent hospitalisation for COPD exacerbations is a major contributor to disease burden and healthcare costs. This study aims to establish if post-discharge sleep or vital sign parameters are predictive of hospital readmissions after COPD exacerbations. METHODS: Patients admitted with a COPD exacerbation were recruited from November 2019 until May 2021. Sleep parameters were assessed for at least one night in hospital and 10 nights post-discharge using an under-mattress device (EarlySense). Analysis on data from the first 26 participants were conducted using independent sample Mann-Whitney U tests comparing device-estimated sleep parameters between participants admitted versus not readmitted at one- and three-months post-discharge. PROGRESS TO DATE: Thirty-four participants have consented. In the 26 participants completing the study to date, all-cause hospital readmission rates at one- and three-months were 26% and 65% respectively. Participants readmitted versus not readmitted at one-month had lower percentage of time in light sleep (43 ± 12% vs 58 ± 12%, p=0.029) and lower estimated AHI (5.6 ± 1.9 vs 17 ± 11 /hr, p=0.042). There were no differences at three-months. INTENDED OUTCOME AND IMPACT: Data from the full cohort will be used to assess heart rate and respiratory rate across each night and stage of sleep which could reveal clinically useful methods in the emerging field of ambulatory sleep monitoring. The feasibility and challenges of using ambulatory monitoring devices in patients with chronic respiratory disease will be reported. This study will guide future work that could potentially improve ambulatory monitoring through user-friendly and clinically feasible devices.