The feasibility and reliability of actigraphy to monitor sleep in intensive care patients: an observational study

Abstract

Background Sleep amongst intensive care patients is reduced and highly fragmented which may adversely impact on recovery. The current challenge for Intensive Care clinicians is identifying feasible and accurate assessments of sleep that can be widely implemented. The objective of this study was to investigate the feasibility and reliability of a minimally invasive sleep monitoring technique compared to the gold standard, polysomnography, for sleep monitoring. Methods Prospective observational study employing a within subject design in adult patients admitted to an Intensive Care Unit. Sleep monitoring was undertaken amongst minimally sedated patients via concurrent polysomnography and actigraphy monitoring over a 24-h duration to assess agreement between the two methods; total sleep time and wake time. Results We recruited 80 patients who were mechanically ventilated (24%) and non-ventilated (76%) within the intensive care unit. Sleep was found to be highly fragmented, composed of numerous sleep bouts and characterized by abnormal sleep architecture. Actigraphy was found to have a moderate level of overall agreement in identifying sleep and wake states with polysomnography (69.4%; K = 0.386, p < 0.05) in an epoch by epoch analysis, with a moderate level of sensitivity (65.5%) and specificity (76.1%). Monitoring accuracy via actigraphy was improved amongst non-ventilated patients (specificity 83.7%; sensitivity 56.7%). Actigraphy was found to have a moderate correlation with polysomnography reported total sleep time (r = 0.359, p < 0.05) and wakefulness (r = 0.371, p < 0.05). Bland–Altman plots indicated that sleep was underestimated by actigraphy, with wakeful states overestimated. Conclusions Actigraphy was easy and safe to use, provided moderate level of agreement with polysomnography in distinguishing between sleep and wakeful states, and may be a reasonable alternative to measure sleep in intensive care patients. Clinical Trial Registration number ACTRN12615000945527 (Registered 9/9/2015).

Reduction of the Cycle Time in the Biopsies Diagnosis Through a Simulation Based on the Box Müller Algorithm

“…In subsequent studies, this analysis may be extended to cytologies and autopsies to reduce their waiting times. The results can be extrapolated to other health services ( 44 , 45 ).…”

Sleep assessment in critically ill adults: A systematic review and meta-analysis

“…Finally, we assessed associations between sleep characteristics and relevant health outcomes for ICU patients (delirium, length of ICU stay, length of mechanical ventilation, complications during ICU stay, and mortality). Whether tools were validated or not in the ICU population was based on the Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (PADIS) [1], the American Academy of Sleep Medicine [22], and a more recent study on actigraphy [154].…”

Rest-Activity Circadian Rhythm and Light Exposure Using Wrist Actigraphy in ICU Patients

“…It has been used to track circadian rest-activity cycles and to identify states of wakefulness and sleep [1]. A more recent study has found that ACTG have a moderate level of agreement with PSG in distinguishing between sleep and wakeful states which is more profound in non-ventilated patients [2]. Moreover, ACTG provides an objective physiological assessment via non-invasive use of motion accelerometers to detect multiplanar gross motor activity [2], indicating purposeful or nonpurposeful movement of patients.…”

“…A more recent study has found that ACTG have a moderate level of agreement with PSG in distinguishing between sleep and wakeful states which is more profound in non-ventilated patients [2]. Moreover, ACTG provides an objective physiological assessment via non-invasive use of motion accelerometers to detect multiplanar gross motor activity [2], indicating purposeful or nonpurposeful movement of patients. Especially, non parametric values (IS: intradaily stability; IV: interdaily variability; L5: least active 5-hour period; M10: most active 10-hour period; and RA: relative amplitude) can quantify circadian rest-activity rhythm providing an indication of circadian rhythmicity.…”

“…The relative amplitude (RA) of the rhythm, is the difference between M-10 and L-5 in the average 24-h pattern, normalized by their sum, ranging between >0 and <14. Higher RAs indicate a more robust 24 hour rest-activity rhythm, reflecting both relatively lower activity during the night and higher activity when awake [2]. Finally, IS provides an estimate of how closely the 24 hour rest-activity rhythm follows the 24 hour light-dark cycle (range: >0 and <1).…”