PurposeIn general, sleeping and activity patterns vary between individuals. This attribute, known as chronotype, may affect night shift performance. In the intensive care unit (ICR), night shift performance may impact patient safety. We have investigated the effect of chronotype and social demographics on sleepiness, fatigue, and night shift on the performance of nurses.MethodsThis was a prospective observational cohort study which assessed the performance of 96 ICU night shift nurses during the day and night shifts in a mixed medical–surgical ICU in the Netherlands. We determined chronotype and assessed sleeping behaviour for each nurse prior to starting shift work and before free days. The level of sleepiness and fatigue of nurses during the day and night shifts was determined, as was the effect of these conditions on psychomotor vigilance and mathematical problem-solving.ResultsThe majority of ICU nurses had a preference for early activity (morning chronotype). Compared to their counterparts (i.e. evening chronotypes), they were more likely to nap before commencing night shifts and more likely to have young children living at home. Despite increased sleepiness and fatigue during night shifts, no effect on psychomotor vigilance was observed during night shifts. Problem-solving accuracy remained high during night shifts, at the cost of productivity.ConclusionsMost of the ICU night shift nurses assessed here appeared to have adapted well to night shift work, despite the high percentage of morning chronotypes, possibly due to their 8-h shift duration. Parental responsibilities may, however, influence shift work tolerance.
Intensive-care-unit (ICU) patients exhibit disturbed sleeping patterns, often attributed to environmental noise, although the relative contribution of noise compared to other potentially disrupting factors is often debated. We therefore systematically reviewed studies of the effects of ICU noise on the quality of sleep to determine to what extent noise explains the observed sleep disruption, using the Cochrane Collaboration method for non-randomized studies. Searches in Scopus, PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library were conducted until May 2017. Twenty papers from 18 studies assessing sleep of adult patients and healthy volunteers in the ICU environment, whilst recording sound levels, were included and independently reviewed by two reviewers. We found that the numbers of arousals between the baseline and the ICU noise condition in healthy subjects differed significantly (mean difference 9.59; 95% confidence interval 2.48-16.70). However, there was considerable heterogeneity between studies (I 94%, P < 0.00001), and all studies suffered from a considerable risk of bias. The meta-analysis of results was hampered by widely varying definitions of sound parameters between studies and a general lack of detailed description of methods used. It is, therefore, currently impossible to quantify the extent to which noise contributes to sleep disruption among ICU patients, and thus, the potential benefit from noise reduction remains unclear. Regardless, the majority of the observed sleep disturbances remain unexplained. Future studies should, therefore, also focus on more intrinsic sleep-disrupting factors in the ICU environment.
IntroductionIntensive care unit (ICU) patients are known to experience severely disturbed sleep, with possible detrimental effects on short- and long- term outcomes. Investigation into the exact causes and effects of disturbed sleep has been hampered by cumbersome and time consuming methods of measuring and staging sleep. We introduce a novel method for ICU depth of sleep analysis, the ICU depth of sleep index (IDOS index), using single channel electroencephalography (EEG) and apply it to outpatient recordings. A proof of concept is shown in non-sedated ICU patients.MethodsPolysomnographic (PSG) recordings of five ICU patients and 15 healthy outpatients were analyzed using the IDOS index, based on the ratio between gamma and delta band power. Manual selection of thresholds was used to classify data as either wake, sleep or slow wave sleep (SWS). This classification was compared to visual sleep scoring by Rechtschaffen & Kales criteria in normal outpatient recordings and ICU recordings to illustrate face validity of the IDOS index.ResultsWhen reduced to two or three classes, the scoring of sleep by IDOS index and manual scoring show high agreement for normal sleep recordings. The obtained overall agreements, as quantified by the kappa coefficient, were 0.84 for sleep/wake classification and 0.82 for classification into three classes (wake, non-SWS and SWS). Sensitivity and specificity were highest for the wake state (93% and 93%, respectively) and lowest for SWS (82% and 76%, respectively). For ICU recordings, agreement was similar to agreement between visual scorers previously reported in literature.ConclusionsBesides the most satisfying visual resemblance with manually scored normal PSG recordings, the established face-validity of the IDOS index as an estimator of depth of sleep was excellent. This technique enables real-time, automated, single channel visualization of depth of sleep, facilitating the monitoring of sleep in the ICU.
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