Impact of obstructive sleep apnea on the obesity paradox in critically ill patients

This research by Bailly and others was published online in the Journal of Critical Care in December 2019
Objective:  Patients admitted to an intensive care unit (ICU) frequently suffer from multiple chronic diseases, including obstructive sleep apnea (OSA). Until recently OSA was not considered as a key determinant in an ICU patient’s prognosis. The objective of this study was to document the impact of OSA on the prognosis of ICU patients.
Methods:  Data were retrospectively collected concerning adult patients admitted to ICU at two university hospitals. In a nested study OSA status was checked using the hospital electronic medical records to identify exposed and unexposed cases. The following outcomes were considered: length of stay in the ICU, ICU mortality, in-hospital mortality, ventilator-associated pneumonia (VAP).
Results:  Out of 5146 patients included in the study, 289 had OSA at ICU admission (5.6%). After matching, the overall impact of OSA on length of ICU stay was not significant (p = .24). In a predefined subgroup analysis, there was a significant impact of OSA on the length of ICU stay for patients with BMI over 40 kg/m2 (IRR: 1.56 [1.05; 2.32], p = .03). OSA status had no impact on ICU or hospital mortality and VAP.
Conclusion:  In general, known OSA did not increase the ICU stay except for patients with both OSA and morbid obesity.
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Development and daily use of a numeric rating score to assess sleep quality in ICU patients

This publication by Rood and colleagues appeared online in Journal of Critical Care during April 2019.
Purpose:  Insufficient sleep burdens critically ill patients, optimizing sleep may enhance patient’s outcomes. Current assessment methods may unnecessary burden patients. Therefore, a single numeric rating score was validated for sleep assessment.
Materials and methods:  First, two cross-sectional measurements on two separate days, from cooperative patients from 19 centres assessed their sleep sufficiency, the numeric rating score (NRS) and the Richards Campbell Sleep Questionnaire (RCSQ). Assessments were compared using a Bland Altman plot. A NRS cut-off was determined using regression analysis. Second, daily sleep assessment was implemented and monitored single centre for a year.
Results:  Multicentre, 194 patients assessed sleep quality, of which 53% was rated as sufficient. Mean (±SD) difference between RCSQ and NRS-Sleep using Bland-Altman analysis was 0.25 (±1.21, 95% limits of agreement −2.12 to 2.62). The optimal cut-off was >5. Single centre, 1603 patients ranked 4532 ICU nights of sleep, of which 71% was sufficient; median NRS was 6 [IQR 5–7].
Conclusions:  A single numeric rating score for sleep is interchangeable for the RCSQ score for assessment of sleep quality. Optimal cut-off is >5. Use of a numeric rating score for sleep is a practical way to evaluate and monitor sleep as perceived by patients in daily ICU practice.
The full text of this article is available to subscribers via this link to the journal’s homepage.  The full text of articles from issues older than sixty days is available via this link to an archive of issues of Journal of Critical Care.  A Rotherham NHS Athens password is required.  Eligible staff can register for an Athens password via this link.  Please speak to the library staff for more details.

Sleep deprivation determinants as perceived by intensive care unit patients: Findings from a systematic review, meta-summary and meta-synthesis

This research by Mattiussi and others was published in “Intensive and Critical Care Nursing” during March 2019.
Objectives:  To summarise evidence on sleep deprivation and/or poor sleep determinants as experienced by intensive care unit patients.
Research methodology/design:  A systematic review of qualitative studies identified through PubMed, CINAHL and Scopus databases published in English up to 2018 was performed following PRISMA guidelines. The included studies were critically evaluated by using the Critical Appraisal Screening Programme tool. Study findings were then subjected to a meta-summary and a meta-synthesis.
Setting:  Intensive Care Units.
Main outcome measures:  Critically ill patients’ experiences of sleep deprivation.
Results:  Seven qualitative studies were included documenting the experience of 109 adult patients. A total of 12 codes emerged as causes of sleep deprivation and ‘feeling fear/concern’ was reported with the greatest frequency (71.4%) in the meta-summary. The 12 codes were categorised into three main themes influencing both directly and also interdependently the quality of sleep: (1) Experiencing complex interactions with the environment (nursing activities, frightening or disturbing sounds, acceptable sounds, time and space disorientation); (2) Undergoing intensive emotions and feelings (fear/concerns, state of abandon, inexplicable insomnia, inability to move, inability to talk) and (3) Receiving an appropriate standard of care (physical pain, feeling safe/unsafe).
Conclusions:  Despite the increased relevance of sleep deprivation and poor sleep quality, only a few studies have been performed to date aimed at identifying the factors involved in the phenomenon according to patient experience. The majority of determinants as identified from patients’ perspective are modifiable.
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Noise in the intensive care unit and its influence on sleep quality: a multicenter observational study in Dutch intensive care units

This article by Simons and colleagues was published in the Critical Care October 2018 issue.
Background:  High noise levels in the intensive care unit (ICU) are a well-known problem. Little is known about the effect of noise on sleep quality in ICU patients. The study aim is to determine the effect of noise on subjective sleep quality.
Methods:  This was a multi-centre observational study in six Dutch ICUs. Noise recording equipment was installed in 2-4 rooms per ICU. Adult patients were eligible for the study 48 h after ICU admission and were followed up to maximum of five nights in the ICU. Exclusion criteria were presence of delirium and/or inability to be assessed for sleep quality. Sleep was evaluated using the Richards Campbell Sleep Questionnaire (range 0-100 mm). Noise recordings were used for analysis of various auditory parameters, including the number and duration of restorative periods. Hierarchical mixed model regression analysis was used to determine associations between noise and sleep.
Results:  In total, 64 patients (68% male), mean age 63.9 (± 11.7) years and mean Acute Physiology and Chronic Health Evaluation (APACHE) II score 21.1 (± 7.1) were included. Average sleep quality score was 56 ± 24 mm. The mean of the 24-h average sound pressure levels (LAeq, 24h) was 54.0 dBA (± 2.4). Mixed-effects regression analyses showed that background noise (β = - 0.51, p < 0.05) had a negative impact on sleep quality, whereas number of restorative periods (β = 0.53, p < 0.01) and female sex (β = 1.25, p < 0.01) were weakly but significantly correlated with sleep.
Conclusions:  Noise levels are negatively associated and restorative periods and female gender are positively associated with subjective sleep quality in ICU patients.
The full text of the article is available via this link.

Sleep in ICU: the role of environment

Boyko, Y. et al. Journal of Critical Care. Published online: 10 September 2016


Purpose: To determine if improving ICU environment would enhance sleep quality, assessed by polysomnography, in critically ill mechanically ventilated patients.

Materials and methods: Randomized controlled trial, cross-over design. The night intervention “Quiet routine” protocol was directed towards improving ICU environment between 10 pm and 6 am. Noise levels during control and intervention nights were recorded. Patients on mechanical ventilation and able to give consent were eligible for the study. We monitored sleep by PSG.2 sleep scoring criteria were insufficient for the assessment of polysomnograms. Modified classification for sleep scoring in critically ill patients, suggested by Watson, was used.

Results: Sound level analysis showed insignificant effect of the intervention on noise reduction (P = .3). The analysis of PSGs revealed that only 53% of the patients had identifiable characteristics of normal sleep, while 47% showed only pathologic patterns.

Conclusions: Characteristics of normal sleep were absent in many of the PSG recordings in these critically ill patients. We were not able to further reduce the already existing low noise levels in the ICU and did not find any association between the environmental intervention and the presence of normal sleep characteristics in the PSG.

Read the abstract here

The association of sleep quality, delirium, and sedation status with daily participation in physical therapy in the ICU

Kamdar, B.B. et al. Critical Care. Published online: 18 August 2016
Image source: Tim Ellis – Wellcome Images // CC BY-NC-ND 4.0

Background: Poor sleep is common in the ICU setting and may represent a modifiable risk factor for patient participation in ICU-based physical therapy (PT) interventions. This study evaluates the association of perceived sleep quality, delirium, sedation, and other clinically important patient and ICU factors with participation in physical therapy (PT) interventions.

Method: This was a secondary analysis of a prospective observational study of sleep in a single academic medical ICU (MICU). Perceived sleep quality was assessed using the Richards-Campbell Sleep Questionnaire (RCSQ) and delirium was assessed using the Confusion Assessment Method for the ICU (CAM-ICU). Other covariates included demographics, pre-hospitalization ambulation status, ICU admission diagnosis, daily mechanical ventilation status, and daily administration of benzodiazepines and opioids via bolus and continuous infusion. Associations with participation in PT interventions were assessed among patients eligible for PT using a multinomial Markov model with robust variance estimates.

Results: Overall, 327 consecutive MICU patients completed ≥1 assessment of perceived sleep quality. After adjusting for all covariates, daily assessment of perceived sleep quality was not associated with transitioning to participate in PT the following day (relative risk ratio [RRR] 1.02, 95 % CI 0.96–1.07, p = 0.55). However, the following factors had significant negative associations with participating in subsequent PT interventions: delirium (RRR 0.58, 95 % CI 0.41–0.76, p <0.001), opioid boluses (RRR 0.68, 95 % CI 0.47–0.99, p = 0.04), and continuous sedation infusions (RRR 0.58, 95 % CI 0.40–0.85, p = 0.01). Additionally, in patients with delirium, benzodiazepine boluses further reduced participation in subsequent PT interventions (RRR 0.25, 95 % CI 0.13–0.50, p <0.001).

Conclusions: Perceived sleep quality was not associated with participation in PT interventions the following day. However, continuous sedation infusions, opioid boluses, and delirium, particularly when occurring with administration of benzodiazepine boluses, were negatively associated with subsequent PT interventions and represent important modifiable factors for increasing participation in ICU-based PT interventions.

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Lighting, sleep and circadian rhythm: An intervention study in the intensive care unit

Engwall, Fridh, Johansson, Bergbom & Lindahl
Journal of Intensive and Critical Care Nursing
December 2015 Volume 31, Issue 6, Pages 325–335
Patients in an intensive care unit (ICU) may risk disruption of their circadian rhythm. In an intervention research project a cycled lighting system was set up in an ICU room to support patients’ circadian rhythm. Part I aimed to compare experiences of the lighting environment in two rooms with different lighting environments by lighting experiences questionnaire. The results indicated differences in advantage for the patients in the intervention room (n = 48), in perception of daytime brightness (p = 0.004). In nighttime, greater lighting variation (p = 0.005) was found in the ordinary room (n = 52). Part II aimed to describe experiences of lighting in the room equipped with the cycled lighting environment. Patients (n = 19) were interviewed and the results were presented in categories: “A dynamic lighting environment”, “Impact of lighting on patients’ sleep”, “The impact of lighting/lights on circadian rhythm” and “The lighting calms”. Most had experiences from sleep disorders and half had nightmares/sights and circadian rhythm disruption. Nearly all were pleased with the cycled lighting environment, which together with daylight supported their circadian rhythm. In night’s actual lighting levels helped patients and staff to connect which engendered feelings of calm.