Edward Litton1, Rosalind Elliott, Kelly Thompson, Nicola Watts, Ian Seppelt, Steven A R Webb. 1. 1Intensive Care Unit, St John of God Hospital, Subiaco, Perth, Western Australia, Australia. 2School of Medicine and Pharmacology, University of Western Australia, Crawley, Perth, Western Australia, Australia. 3Intensive Care Unit, Royal North Shore Hospital, St Leonards, Sydney, New South Wales, Australia. 4Critical Care and Trauma Division, The George Institute for Global Health, Sydney, New South Wales, Australia. 5Sydney Medical School-Nepean, University of Sydney, Sydney, New South Wales, Australia. 6St John of God Hospital, Subiaco, Perth, Western Australia, Australia. 7Monash University, Melbourne, Victoria, Australia.
Abstract
OBJECTIVES: To use clinically accessible tools to determine unit-level and individual patient factors associated with sound levels and sleep disruption in a range of representative ICUs. DESIGN: A cross-sectional, observational study. SETTING: Australian and New Zealand ICUs. PATIENTS: All patients 16 years or over occupying an ICU bed on one of two Point Prevalence study days in 2015. INTERVENTIONS: Ambient sound was measured for 1 minute using an application downloaded to a personal mobile device. Bedside nurses also recorded the total time and number of awakening for each patient overnight. MEASUREMENTS AND MAIN RESULTS: The study included 539 participants with sound level recorded using an application downloaded to a personal mobile device from 39 ICUs. Maximum and mean sound levels were 78 dB (SD, 9) and 62 dB (SD, 8), respectively. Maximum sound levels were higher in ICUs with a sleep policy or protocol compared with those without maximum sound levels 81 dB (95% CI, 79-83) versus 77 dB (95% CI, 77-78), mean difference 4 dB (95% CI, 0-2), p < 0.001. There was no significant difference in sound levels regardless of single room occupancy, mechanical ventilation status, or illness severity. Clinical nursing staff in all 39 ICUs were able to record sleep assessment in 15-minute intervals. The median time awake and number of prolonged disruptions were 3 hours (interquartile range, 1-4) and three (interquartile range, 2-5), respectively. CONCLUSIONS: Across a large number of ICUs, patients were exposed to high sound levels and substantial sleep disruption irrespective of factors including previous implementation of a sleep policy. Sound and sleep measurement using simple and accessible tools can facilitate future studies and could feasibly be implemented into clinical practice.
OBJECTIVES: To use clinically accessible tools to determine unit-level and individual patient factors associated with sound levels and sleep disruption in a range of representative ICUs. DESIGN: A cross-sectional, observational study. SETTING: Australian and New Zealand ICUs. PATIENTS: All patients 16 years or over occupying an ICU bed on one of two Point Prevalence study days in 2015. INTERVENTIONS: Ambient sound was measured for 1 minute using an application downloaded to a personal mobile device. Bedside nurses also recorded the total time and number of awakening for each patient overnight. MEASUREMENTS AND MAIN RESULTS: The study included 539 participants with sound level recorded using an application downloaded to a personal mobile device from 39 ICUs. Maximum and mean sound levels were 78 dB (SD, 9) and 62 dB (SD, 8), respectively. Maximum sound levels were higher in ICUs with a sleep policy or protocol compared with those without maximum sound levels 81 dB (95% CI, 79-83) versus 77 dB (95% CI, 77-78), mean difference 4 dB (95% CI, 0-2), p < 0.001. There was no significant difference in sound levels regardless of single room occupancy, mechanical ventilation status, or illness severity. Clinical nursing staff in all 39 ICUs were able to record sleep assessment in 15-minute intervals. The median time awake and number of prolonged disruptions were 3 hours (interquartile range, 1-4) and three (interquartile range, 2-5), respectively. CONCLUSIONS: Across a large number of ICUs, patients were exposed to high sound levels and substantial sleep disruption irrespective of factors including previous implementation of a sleep policy. Sound and sleep measurement using simple and accessible tools can facilitate future studies and could feasibly be implemented into clinical practice.
Authors: Bradley Wibrow; F Eduardo Martinez; Erina Myers; Andrew Chapman; Edward Litton; Kwok M Ho; Adrian Regli; David Hawkins; Andrew Ford; Frank M P van Haren; Simon Wyer; Joe McCaffrey; Alan Rashid; Erin Kelty; Kevin Murray; Matthew Anstey Journal: Intensive Care Med Date: 2022-02-27 Impact factor: 17.440
Authors: Lori J Delaney; Marian J Currie; Hsin-Chia Carol Huang; Edward Litton; Bradley Wibrow; Violeta Lopez; Frank Van Haren Journal: BMJ Open Date: 2018-01-21 Impact factor: 2.692