Actigraphy to Evaluate Sleep in the Intensive Care Unit. A Systematic Review

Nighttime sleep and daytime sleepiness patterns among left ventricular assist device patients

Despite the high prevalence of sleep disturbance in the heart failure population, information about its consequence on daytime function in patients with left-ventricular assist devices (LVADs) is limited. This study examined the nighttime and daytime sleep patterns and changes from pre-implant to 6 months post-implant. This study included 32 LVAD patients. Demographics, nighttime and daytime sleep variables were collected pre-implant and at 1, 3, and 6 months post-implant. Wrist actigraphy and self-report questionnaires measured objective and subjective sleep, respectively. Objective nighttime sleep data were sleep efficiency (SE), sleep latency (SL), total sleep time (TST), wake after sleep onset (WASO), and sleep fragmentation (SF). Objective daytime sleep data were nap times. Self-reported Subjective Sleep Quality Scale (SSQS) and Stanford Sleepiness Scale (SSS) were subjective measures. Increased SF and WASO scores and decreased TST and SE scores were found pre-LVAD implant, indicative of poor sleep quality. TST, SE, naptime and SSQS scores were higher at 3 and 6 months post-implant compared to baseline. Decreases in TST and SF scores were observed at 3 and 6 months post-implant along with increases in SSS scores. Increasing SSS scores and decreasing overall scores from pre- and up to 6 months post-implant suggest improvement in daytime function. This study provides information on sleep-daytime function in the LVAD patient population. Improvements in daytime sleepiness do not imply "good" sleep quality, consistent with the extant knowledge in LVAD literature. Future investigations should elucidate the mechanism by which sleep-daytime function influences quality of life.

Analysis of the factors influencing of sleep quality in intensive care unit awake patients based on a structural equation model: A cross-sectional study

OBJECTIVE

The objective of this study was to construct and validate a structural equation model (SEM) to identify factors associated with sleep quality in awake patients in the intensive care unit (ICU) and to assist in the development of clinical intervention strategies.

RESEARCH METHODS/SETTING

In this cross-sectional study, 200 awake patients who were cared for in the ICU of a tertiary hospital in China were surveyed via several self-report questionnaires and wearable actigraphy sleep monitoring devices. Based on the collected data, structural equation modelling analysis was performed using SPSS and AMOS statistical analysis software. The study is reported using the STROBE checklist.

RESULTS

The fit indices of the SEM were acceptable: χ2/df = 1.676 (p < .001) and RMSEA = .058 (p < 0.080). Anxiety/depression had a direct negative effect on the sleep quality of awake patients cared for in the ICU (β = -.440, p < .001). In addition, disease-freeness progress had an indirect negative effect on the sleep quality of awake patients cared for in the ICU (β = -.142, p < .001). Analgesics had an indirect negative effect on the sleep quality of awake patients cared for in the ICU through pain and sedatives (β = -.082, p < .001). Sedation had a direct positive effect on the sleep quality of conscious patients cared for in the ICU (β = .493; p < .001).

CONCLUSION

The results of the SEM showed that the sleep quality of awake patients cared for in the ICU is mainly affected by psychological and disease-related factors, especially anxiety, depression and pain, so we can improve the sleep quality of patients through psychological intervention and drug intervention.

Feasibility and Acceptability of Using Wireless Limited Polysomnography to Capture Sleep Before, During, and After Hospitalization for Patients With Planned Cardiothoracic Surgery

BACKGROUND

Sleep disruption, a common symptom among patients requiring cardiovascular surgery, is a potential risk factor for the development of postoperative delirium. Postoperative delirium is a disorder of acute disturbances in cognition associated with prolonged hospitalization, cognitive decline, and mortality.

OBJECTIVE

The aim of this study was to evaluate the feasibility and acceptability of using polysomnography (PSG) to capture sleep in patients with scheduled cardiothoracic surgery.

METHODS

Wireless limited PSG assessed sleep at baseline (presurgery at home), postoperatively in the intensive care unit, and at home post hospital discharge. Primary outcomes were quality and completeness of PSG signals, and acceptability by participants and nursing staff.

RESULTS

Among 15 patients, PSG data were of high quality, and mean percentage of unscorable data was 5.5% ± 11.1%, 3.7% ± 5.4%, and 3.7% ± 8.4% for baseline, intensive care unit, and posthospitalization measurements, respectively. Nurses and patients found the PSG monitor acceptable.

CONCLUSIONS

Wireless, limited PSG to capture sleep across the surgical continuum was feasible, and data were of high quality. Authors of future studies will evaluate associations of sleep indices and development of postoperative delirium in this high-risk population.

A systematic review of the performance of actigraphy in measuring sleep stages

The accuracy of actigraphy for sleep staging is assumed to be poor, but examination is limited. This systematic review aimed to assess the performance of actigraphy in sleep stage classification of adults. A systematic search was performed using MEDLINE, Web of Science, Google Scholar, and Embase databases. We identified eight studies that compared sleep architecture estimates between wrist-worn actigraphy and polysomnography. Large heterogeneity was found with respect to how sleep stages were grouped, and the choice of metrics used to evaluate performance. Quantitative synthesis was not possible, so we performed a narrative synthesis of the literature. From the limited number of studies, we found that actigraphy-based sleep staging had some ability to classify different sleep stages compared with polysomnography.

Rest-activity patterns associated with delirium in patients with intracerebral hemorrhage

BACKGROUND

Delirium is an acute cognitive disturbance frequently characterized by abnormal psychomotor activity and sleep-wake cycle disruption. However, the degree to which delirium affects activity patterns in the acute period after stroke is unclear. We aimed to examine these patterns in a cohort of patients with intracerebral hemorrhage (ICH).

METHODS

We enrolled 40 patients with intracerebral hemorrhage (ICH) who had daily DSM-5-based delirium assessments. Continuous activity measurements were captured using bilateral wrist actigraphs throughout each patient's admission. Activity data were collected in 1-min intervals, with "rest" defined as periods with zero activity. We compared differences in activity based on delirium status across multiple time intervals using multivariable models adjusted for age, ICH severity, and mechanical ventilation.

RESULTS

There were 279 days of actigraphy monitoring, of which 199 (71%) were rated as days with delirium. In multivariable analyses, delirium was associated with 98.4 (95% CI 10.4-186.4) fewer daily minutes of rest, including 5.3% (95% CI -0.1-10.1%) fewer minutes during daytime periods (06:00-21:59) and 10.2% (95% CI 1.9-18.4%) fewer minutes during nocturnal periods (22:00-5:59), with higher levels of activity across multiple individual hourly intervals (18:00-21:00, 23:00-03:00, and 04:00-08:00). These differences were even more pronounced in hyperactive or mixed delirium, although even hypoactive delirium was associated with more activity during multiple time periods.

CONCLUSIONS

Post-stroke delirium is associated with less rest and higher overall levels of activity, especially during nocturnal periods.

Diagnostic Value of the Bispectral Index to Assess Sleep Quality after Elective Surgery in Intensive Care Unit

Purpose

Monitoring and improving sleep quality may help recovery from major illness. Polysomnography is a gold standard for measuring sleep quality, but routine use is not practical. The goal of this study is to investigate the diagnostic accuracy of an alternative monitor, the Bispectral Index (BIS), for evaluating the quality of sleep-in postoperative patients in the intensive care unit (ICU).

Study design

An observational study.

Materials and methods

Patients admitted to postoperative ICU after elective major noncardiac surgery were monitored with both BIS and PSG during the first night. The temporally synchronized data from both monitors were obtained for measurement of the association. Clinical outcomes were compared between patients with different postoperative sleep quality.

Results

Thirty-three patients were enrolled in this study. For determining the average BIS index associated with good postoperative sleep quality, receiver operating characteristics (ROC) curve was generated. Area under the ROC curve (AUC) was 0.65. The cutoff with best discriminability was 75 with a sensitivity of 68% and a specificity of 56%. Compared with those with good and poor postoperative sleep quality, there were no differences in main postoperative outcomes including duration of mechanical ventilation and ICU stay. Although the quality of sleep after surgery of all subjects with postoperative delirium was poor, the incidence of delirium between the groups did not significantly differ (0% vs 10.3%; p = 0.184).

Conclusion

The monitoring of BIS is a viable tool for evaluating sleep quality in mechanically ventilated patients in the postoperative ICU with acceptable precision.

Trial registration

www.clinicaltrials.in.th, TCTR20200310005.

How to cite this article

Sirilaksanamanon P, Thawitsri T, Charuluxananan S, Chirakalwasan N. Diagnostic Value of the Bispectral Index to Assess Sleep Quality after Elective Surgery in Intensive Care Unit. Indian J Crit Care Med 2023;27(11):795-800.

Sleep and critical illness: a review

Critical illness and stays in the Intensive Care Unit (ICU) have significant impact on sleep. Poor sleep is common in this setting, can persist beyond acute critical illness, and is associated with increased morbidity and mortality. In the past 5 years, intensive care clinical practice guidelines have directed more focus on sleep and circadian disruption, spurring new initiatives to study and improve sleep complications in the critically ill. The global SARS-COV-2 (COVID-19) pandemic and dramatic spikes in patients requiring ICU level care also brought augmented levels of sleep disruption, the understanding of which continues to evolve. This review aims to summarize existing literature on sleep and critical illness and briefly discuss future directions in the field.

Delirium detection using wearable sensors and machine learning in patients with intracerebral hemorrhage

Objective

Delirium is associated with worse outcomes in patients with stroke and neurocritical illness, but delirium detection in these patients can be challenging with existing screening tools. To address this gap, we aimed to develop and evaluate machine learning models that detect episodes of post-stroke delirium based on data from wearable activity monitors in conjunction with stroke-related clinical features.

Design

Prospective observational cohort study.

Setting

Neurocritical Care and Stroke Units at an academic medical center.

Patients

We recruited 39 patients with moderate-to-severe acute intracerebral hemorrhage (ICH) and hemiparesis over a 1-year period [mean (SD) age 71.3 (12.20), 54% male, median (IQR) initial NIH Stroke Scale 14.5 (6), median (IQR) ICH score 2 (1)].

Measurements and main results

Each patient received daily assessments for delirium by an attending neurologist, while activity data were recorded throughout each patient's hospitalization using wrist-worn actigraph devices (on both paretic and non-paretic arms). We compared the predictive accuracy of Random Forest, SVM and XGBoost machine learning methods in classifying daily delirium status using clinical information alone and combined with actigraph data. Among our study cohort, 85% of patients (n = 33) had at least one delirium episode, while 71% of monitoring days (n = 209) were rated as days with delirium. Clinical information alone had a low accuracy in detecting delirium on a day-to-day basis [accuracy mean (SD) 62% (18%), F1 score mean (SD) 50% (17%)]. Prediction performance improved significantly (p < 0.001) with the addition of actigraph data [accuracy mean (SD) 74% (10%), F1 score 65% (10%)]. Among actigraphy features, night-time actigraph data were especially relevant for classification accuracy.

Conclusions

We found that actigraphy in conjunction with machine learning models improves clinical detection of delirium in patients with stroke, thus paving the way to make actigraph-assisted predictions clinically actionable.

Sleep during and following critical illness: A narrative review

Sleep is a complex process influenced by biological and environmental factors. Disturbances of sleep quantity and quality occur frequently in the critically ill and remain prevalent in survivors for at least 12 mo. Sleep disturbances are associated with adverse outcomes across multiple organ systems but are most strongly linked to delirium and cognitive impairment. This review will outline the predisposing and precipitating factors for sleep disturbance, categorised into patient, environmental and treatment-related factors. The objective and subjective methodologies used to quantify sleep during critical illness will be reviewed. While polysomnography remains the gold-standard, its use in the critical care setting still presents many barriers. Other methodologies are needed to better understand the pathophysiology, epidemiology and treatment of sleep disturbance in this population. Subjective outcome measures, including the Richards-Campbell Sleep Questionnaire, are still required for trials involving a greater number of patients and provide valuable insight into patients’ experiences of disturbed sleep. Finally, sleep optimisation strategies are reviewed, including intervention bundles, ambient noise and light reduction, quiet time, and the use of ear plugs and eye masks. While drugs to improve sleep are frequently prescribed to patients in the ICU, evidence supporting their effectiveness is lacking.

Improve sleep in critically ill patients: Study protocol for a randomized controlled trial for a multi-component intervention of environment control in the ICU

INTRODUCTION

In critically ill patients, sleep and circadian rhythms are greatly altered. These disturbances have been associated with adverse consequences, including increased mortality. Factors associated with the ICU environment, such as exposure to inadequate light and noise levels during the day and night or inflexible schedules of daily care activities, have been described as playing an essential role in sleep disturbances. The main objective of this study is to evaluate the impact of the use of a multifaceted environmental control intervention in the ICU on the quantity and quality of sleep, delirium, and post-intensive care neuropsychological impairment in critically ill patients.

METHODS

This is a prospective, parallel-group, randomized trial in 56 critically ill patients once they are starting to recover from their acute illness. Patients will be randomized to receive a multifaceted intervention of environmental control in the ICU (dynamic light therapy, auditory masking, and rationalization of ICU nocturnal patient care activities) or standard care. The protocol will be applied from enrollment until ICU discharge. Baseline parameters, light and noise levels, polysomnography and actigraphy, daily oscillation of plasma concentrations of Melatonin and Cortisol, and questionnaires for the qualitative evaluation of sleep, will be assessed during the study. In addition, all patients will undergo standardized follow-up before hospital discharge and at 6 months to evaluate neuropsychological impairment.

DISCUSSION

This study is the first randomized clinical trial in critically ill patients to evaluate the effect of a multicomponent, non-pharmacological environmental control intervention on sleep improvement in ICU patients. The results will provide data about the potential synergistic effects of a combined multi-component environmental intervention in ICU on outcomes in the ICU and long term, and the mechanism of action.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT. Registered on January 10, 2023. Last updated on 24 Jan 2023.

Society of Anesthesia and Sleep Medicine Position Paper on Patient Sleep During Hospitalization

This article addresses the issue of patient sleep during hospitalization, which the Society of Anesthesia and Sleep Medicine believes merits wider consideration by health authorities than it has received to date. Adequate sleep is fundamental to health and well-being, and insufficiencies in its duration, quality, or timing have adverse effects that are acutely evident. These include cardiovascular dysfunction, impaired ventilatory function, cognitive impairment, increased pain perception, psychomotor disturbance (including increased fall risk), psychological disturbance (including anxiety and depression), metabolic dysfunction (including increased insulin resistance and catabolic propensity), and immune dysfunction and proinflammatory effects (increasing infection risk and pain generation). All these changes negatively impact health status and are counterproductive to recovery from illness and operation. Hospitalization challenges sleep in a variety of ways. These challenges include environmental factors such as noise, bright light, and overnight awakenings for observations, interventions, and transfers; physiological factors such as pain, dyspnea, bowel or urinary dysfunction, or discomfort from therapeutic devices; psychological factors such as stress and anxiety; care-related factors including medications or medication withdrawal; and preexisting sleep disorders that may not be recognized or adequately managed. Many of these challenges appear readily addressable. The key to doing so is to give sleep greater priority, with attention directed at ensuring that patients' sleep needs are recognized and met, both within the hospital and beyond. Requirements include staff education, creation of protocols to enhance the prospect of sleep needs being addressed, and improvement in hospital design to mitigate environmental disturbances. Hospitals and health care providers have a duty to provide, to the greatest extent possible, appropriate preconditions for healing. Accumulating evidence suggests that these preconditions include adequate patient sleep duration and quality. The Society of Anesthesia and Sleep Medicine calls for systematic changes in the approach of hospital leadership and staff to this issue. Measures required include incorporation of optimization of patient sleep into the objectives of perioperative and general patient care guidelines. These steps should be complemented by further research into the impact of hospitalization on sleep, the effects of poor sleep on health outcomes after hospitalization, and assessment of interventions to improve it.

Subjective sleep assessment compared to polysomnography in mechanically ventilated critically ill ICU patients

Sleep deprivation is expected in the intensive care unit (ICU) and is associated with delirium and increased mortality. Polysomnography (PSG) is the gold standard for sleep assessment, but practical issues limit the method. Hence, many ICUs worldwide use subjective sleep assessment (SSA) for sleep monitoring, but the agreement between SSA and PSG is unknown. The hypothesis was that the level of agreement between SSA and PSG was low and that total sleep time (TST) assessed with SSA would be overestimated compared to PSG in this existing cohort database. In this sub-analysis, 30 consecutive study participants underwent 15-h PSG recordings during two consecutive nights. The attending nurse performed an hourly subjective observer rating of sleep quantity during both nights, and the agreement between SSA and PSG was determined along with mean TST. Primary outcome: The level of agreement between SSA and PSG determined by Bland-Altman analysis. Secondary outcome: (1) The overall mean TST estimated by SSA compared to PSG in all study participants enrolled in the main study during both study nights, (2) TST for all study participants evaluated hourly during both study nights, (3) TST assessed with SSA compared to PSG in study participants sedated with dexmedetomidine during the second night and for study participants treated with placebo or non-sedation the first and second nights. The level of agreement between SSA and PSG was low. Mean TST estimated by SSA during the time interval 4.00 p.m. to 7.00 a.m. was 481 min (428;534, 95% CI) vs. PSG at 437 min (386;488, 95% CI) (p = .05). When sedated with dexmedetomidine, TST estimated using SSA was 650 min (571;729, 95% CI) versus PSG which was 588 min (531;645, 95% CI) (p = 0.56). For participants treated with placebo or non-sedation TST estimated with SSA was 397 min (343;450, 95% CI) versus PSG at 362 min (302;422, 95% CI) versus (p = 0.17). In mechanically ventilated critically ill ICU patients, the level of agreement between SSA and PSG was low, and there was a significant overestimation of mean TST. SSA should only be used under awareness that it is imprecise and overestimates TST.

Actigraphy-based sleep and activity measurements in intensive care unit patients randomized to ramelteon or placebo for delirium prevention

Patients in the ICU often sleep poorly for various reasons, which may predispose to delirium. We previously conducted a clinical trial in which we tested the efficacy of ramelteon, a melatonin-receptor agonist used to treat insomnia, versus placebo, in preventing ICU delirium in patients who underwent elective pulmonary thromboendarterectomy (PTE) surgery. Here we examine sleep, activity, and circadian patterns, measured with actigraphy, to understand changes in these metrics with our intervention and in those with and without delirium. Participants wore wrist actigraphy devices while recovering post-operatively in the ICU. For sleep analysis, we extracted total sleep time and sleep fragmentation metrics over the 22:00 to 06:00 period nightly, and daytime nap duration from the daytime period (0:600 to 22:00) for each participant. For activity analyses, we extracted the following metrics: total daytime activity count (AC), maximum daytime AC, total nighttime AC, and maximum nighttime AC. Next, we performed a nonparametric circadian analysis on ACs over each 24-h day and extracted the following: interdaily stability (IS), intra-daily variability (IV), relative amplitude (RA), and low and high periods of activity (L5 and M10) as well as their start times. These metrics were compared between patients who received ramelteon versus placebo, and between patients who became delirious versus those who did not develop delirium. We additionally made comparisons between groups for daytime and nighttime light levels. No differences in sleep, activity, circadian metrics or light levels were found between drug groups. Delirious patients, when compared to those who were never delirious, had a lower IS (0.35 ± 0.16 vs. 0.47 ± 0.23; P = 0.006). Otherewise, no differences in IV, L5, M10, or RA were found between groups. L5 and M10 activity values increased significantly over the post-extubation for the whole cohort. No differences were found for daytime or nighttime light levels between groups. Overall, ramelteon did not impact sleep or circadian metrics in this cohort. Consistent with clinical experience, delirious patients had less inter-daily stability in their rest-activity rhythms. These data suggest that actigraphy might have value for individual assessment of sleep in the ICU, and for determining and detecting the impact of interventions directed at improving sleep and circadian activity rhythms in the ICU.Trial registration: REGISTERED at CLINICALTRIALS.GOV: NCT02691013. Registered on February 24, 2016 by principal investigator, Dr. Robert L. Owens.

Automation of classification of sleep stages and estimation of sleep efficiency using actigraphy

Introduction

Sleep is a fundamental and essential physiological process for recovering physiological function. Sleep disturbance or deprivation has been known to be a causative factor of various physiological and psychological disorders. Therefore, sleep evaluation is vital for diagnosing or monitoring those disorders. Although PSG (polysomnography) has been the gold standard for assessing sleep quality and classifying sleep stages, PSG has various limitations for common uses. In substitution for PSG, there has been vigorous research using actigraphy.

Methods

For classifying sleep stages automatically, we propose machine learning models with HRV (heart rate variability)-related features and acceleration features, which were processed from the actigraphy (Maxim band) data. Those classification results were transformed into a binary classification for estimating sleep efficiency. With 30 subjects, we conducted PSG, and they slept overnight with wrist-type actigraphy. We assessed the performance of four proposed machine learning models.

Results

With HRV-related and raw features of actigraphy, Cohen's kappa was 0.974 (p < 0.001) for classifying sleep stages into five stages: wake (W), REM (Rapid Eye Movement) (R), Sleep N1 (Non-Rapid Eye Movement Stage 1, S1), Sleep N2 (Non-Rapid Eye Movement Stage 2, S2), Sleep N3 (Non-Rapid Eye Movement Stage 3, S3). In addition, our machine learning model for the estimation of sleep efficiency showed an accuracy of 0.86.

Discussion

Our model demonstrated that automated sleep classification results could perfectly match the PSG results. Since models with acceleration features showed modest performance in differentiating some sleep stages, further research on acceleration features must be done. In addition, the sleep efficiency model demonstrated modest results. However, an investigation into the effects of HRV-derived and acceleration features is required.

Sedation/agitation monitoring using a wearable device for ventilated children

BACKGROUND

Developing continuous and labor-saving sedation/agitation monitoring methods in ventilated children is important to avoid undesirable events such as unplanned extubation. The existing scales are often challenging to use. We therefore aimed to evaluate the feasibility of sedation/agitation monitoring using a wearable device with a built-in accelerometer for ventilated children.

METHODS

This prospective observational pilot study included children aged 15 years or less, admitted to the pediatric intensive care unit on mechanical ventilation after cardiac catheterization between December 2021 and April 2022. The wearable device with a built-in accelerometer was attached to either of the upper limbs, and accelerations due to upper limb movements were measured for 2 h after admission or until extubation, whichever was earliest. Accelerations were measured at 0.02 s intervals, with the mean acceleration calculated for each 1 min interval. The State Behavioral Scale (SBS) was completed at 1 min intervals, with the SBS score (-1, 0, 1, or 2) compared with the mean acceleration.

RESULTS

The study included 20 children with a median age of 12 months. The mean accelerations and SBS scores were positively correlated (Kendall's τ, 0.22; p < 0.001), with an increase in the median (interquartile range) acceleration from an SBS score of -1 through 2, as follows: SBS -1, 0.200 (0.151-0.232) m/s2 ; SBS 0, 0.202 (0.190-0.235) m/s2 ; SBS, 1, 0.312 (0.236-0.427) m/s2 ; SBS 2, 0.455 (0.332-0.517) m/s2 . No adverse events were observed.

CONCLUSIONS

This study showed that continuous, labor-saving sedation/agitation monitoring of ventilated children was feasible using a wearable device with a built-in accelerometer.

Sleep staging in the ICU with heart rate variability and breathing signals. An exploratory cross-sectional study using deep neural networks

Introduction: To measure sleep in the intensive care unit (ICU), full polysomnography is impractical, while activity monitoring and subjective assessments are severely confounded. However, sleep is an intensely networked state, and reflected in numerous signals. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods Methods: We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in age and sex-matched sleep laboratory patients Results: We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p < 0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients Conclusion: The cardiovascular and respiratory networks encode sleep state information, which, together with artificial intelligence methods, can be utilized to measure sleep state in the ICU.

Sleep cycle in children with severe acute bronchopneumonia during mechanical ventilation at different depths of sedation

BACKGROUND

To investigate the characteristics of sleep cycle in children with severe acute bronchopneumonia treated with invasive mechanical ventilation at different sedation depths.

METHODS

We included 35 pediatric patients with severe acute bronchopneumonia treated using mechanical ventilation in Pediatric Intensive Care Unit of Shengjing Hospital of China Medical University. They were divided into deep sedation group (n = 21; ramsay score 5-6) and light sedation group (n = 14; ramsay score3-4) based on sedation depth achieved during mechanical ventilation. Long-term video electroencephalography (EEG) monitoring was performed within the first 24 h after starting mechanical ventilation and after weaning from mechanical ventilation and discontinuing sedatives and analgesics. The results were analyzed and compared with those of normal children to analyze changes in sleep cycle characteristics at different sedation depths and mechanical ventilation stages.

RESULTS

There were 29 cases altered sleep architecture. The deep sedation group had a significantly higher incidence of sleep architecture altered, total sleep duration, and non-rapid eye movement sleep-1 (NREM-1) loss incidence than the light sedation group. Moreover, the deep sedation group had a significantly lower awakening number and rapid eye movement sleep (REM) percentage than the light sedation group. The sleep cycle returned to normal in 27 (77%) patients without NREM-1 or REM sleep loss.

CONCLUSIONS

Deep sedation during mechanical ventilation allows longer total sleep duration, fewer awakenings, and an increased deep sleep proportion, but sleep architecture is severely altered. After weaning from mechanical ventilation and sedative discontinuation, lightly sedated children exhibit better sleep recovery.

Circadian rest-activity misalignment in critically ill medical intensive care unit patients

Circadian alignment of rest-activity rhythms is an essential biological process that may be vulnerable to misalignment in critically ill patients. We evaluated circadian rest-activity rhythms in critically ill patients and their association with baseline (e.g. age) and clinical (e.g. mechanical ventilation status) variables, along with intensive care unit light-dark cycles. Using wrist actigraphy, we collected 48-hr activity and light exposure data from critically ill patients in a tertiary care medical intensive care unit. We evaluated circadian rest-activity rhythms using COSINOR and non-parametric circadian rhythm analysis models, and stratified these data across baseline and clinical variables. We used linear regression to evaluate the association of circadian rest-activity and light-dark exposure rhythms. In COSINOR and non-parametric circadian rhythm analysis analyses, the 34 medical intensive care unit patients completing 48-hr actigraphy recordings exhibited mean MESOR (mean activity levels of a fitted curve) and amplitudes of 0.50 ± 0.32 and 0.20 ± 0.19 movements per 30-s epoch, with high interdaily variability. Patients who were older, mechanically ventilated, sedated, restrained and with higher organ failure scores tended to exhibit greater circadian rest-activity misalignment, with three of 34 (9%) patients exhibiting no circadian rhythmicity. Circadian light-dark exposure misalignment was observed as well and was associated with rest-activity misalignment (p = 0.03). Critically ill patients in our MICU experienced profound circadian rest-activity misalignment, with mostly weak or absent rhythms, along with circadian light-dark exposure misalignment. Potentially modifiable factors contributing to rest-activity misalignment (i.e. mechanical ventilation, restraints, low daytime light levels) highlight possible targets for future improvement efforts.

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

PURPOSE

To systematically review sleep evaluation, characterize sleep disruption, and explore effects of sleepdisruption on outcomes in adult ICU patients.

MATERIALS AND METHODS

We systematically searched databases from May 1969 to June 2021 (PROSPERO protocol number: CRD42020175581). Prospective and retrospective studies were included studying sleep in critically ill adults, excluding patients with sleep or psychiatric disorders. Meta-regression methods were applied when feasible.

RESULTS

132 studies (8797 patients) were included. Fifteen sleep assessment methods were identified, with only two validated. Patients had significant sleep disruption, with low sleep time, and low proportion of restorative rapid eye movement (REM). Sedation was associated with higher sleep efficiency and sleep time. Surgical versus medical patients had lower sleep quality. Patients on ventilation had a higher amount of light sleep. Meta-regression only suggested an association between total sleep time and occurrence of delirium (p < 0.001, 15 studies, 519 patients). Scarce data precluded further analyses. Sleep characterized with polysomnography (PSG) correlated well with actigraphy and Richards Campbell Sleep Questionnaire (RCSQ).

CONCLUSIONS

Sleep in critically ill patients is severely disturbed, and actigraphy and RCSQ seem reliable alternatives to PSG. Future studies should evaluate impact of sleep disruption on outcomes.

Effects of nonpharmacological interventions on sleep improvement and delirium prevention in critically ill patients: A systematic review and meta-analysis

OBJECTIVE

Sleep disturbance and delirium are common problems experienced by critically ill patients in the intensive care unit (ICU). These interrelated issues increase the length of stay in the ICU but might also negatively affect long-term health outcomes. The objective of this study was to identify the nonpharmacological interventions provided to improve sleep or prevent delirium in ICU patients or both and integrate their effect sizes.

REVIEW METHODS

This study was a registered systematic review and meta-analysis. We searched MEDLINE, CINAHL, EMBASE, Web of Science, and Cochrane Library from their inception until December 2021. We included randomised controlled trials and nonrandomised controlled trials-(RCT) that provided nonpharmacological interventions and reported sleep or delirium as outcome variables. Studies not published in English or whose full text was not available were excluded. The quality of the evidence was assessed with version 2 of the Cochrane risk-of-bias tool for RCTs and the Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I).

RESULTS

The systematic review included 118 studies, and the meta-analysis included 100 studies. Overall nonpharmacological interventions had significant effects on subjective sleep quality (standardised mean difference = 0.30, 95% confidence interval [CI] = 0.05 to 0.56), delirium incidence (odds ratio = 0.62, 95% CI = 0.53 to 0.73), and delirium duration (standardised mean difference = -0.68, 95% CI = -0.93 to -0.43). In individual interventions, aromatherapy, music, and massage effectively improved sleep. Exercise, family participation, information giving, cognitive stimulation, bright light therapy, architectural intervention, and bundles/protocols effectively reduced delirium. Light/noise blocking was the only intervention that ensured both sleep improvement and delirium prevention.

CONCLUSIONS

Our results suggest nonpharmacological interventions improve sleep and prevent delirium in ICU patients. We recommend that ICU nurses use nonpharmacological interventions that promote person-environment compatibility in their clinical practice. The results of our review can guide nurses in adopting interventions related to sleep and delirium.

PROSPERO REFERENCE NUMBER

CRD42021230815.

Efforts to improve sleep quality in a medical intensive care unit: effect of a protocol of non-pharmacological interventions

PURPOSE

This study aimed to evaluate the effect of a protocol of nonpharmacological interventions to improve sleep quality in the intensive care unit (ICU). Due to its close relationship with sleep quality, the effects of the same interventions on noise levels and delirium rates were also evaluated in this study.

METHODS

This pretest-posttest design with a control group was carried out in a medical ICU over 8 months. Data were collected using Acute Physiology and Chronic Health Evaluation II, the Glasgow Coma Scale, the Richmond Agitation-Sedation Scale, the Richards-Campbell Sleep Questionnaire (RCSQ), the Confusion Assessment Method for the Intensive Care Unit, and noise measurement devices. In the first phase of the study, patients receiving standard care in the ICU were followed. After the first stage, a training session was held for nurses to raise awareness and information. Then, the sleep-promoting protocol created by the researchers was applied. The ambient noise level was measured continuously.

RESULTS

A total of 78 patients with a mean age of 70.0 ± 13.2 years were followed in the ICU for an average of 7.3 ± 3.8 days. With protocol implementation, the ambient noise level in the ICU was reduced from 70.9 ± 3.8 dB(A) to 62.7 ± 3.5 dB(A) (p < 0.01); the RCSQ scores of the patients increased from 48.3 ± 1.4 to 62.1 ± 1.8 (p < 0.01). Although statistically nonsignificant, efforts to improve sleep quality also reduced the development of delirium by 15%.

CONCLUSION

It is possible to improve sleep quality and reduce noise levels in an ICU with a protocol consisting of multicomponent nonpharmacological interventions.

Adding Insult to Injury: Sleep Deficiency in Hospitalized Patients

Sleep deficiency is a common problem in the hospital setting. Contributing factors include preexisting medical conditions, illness severity, the hospital environment, and treatment-related effects. Hospitalized patients are particularly vulnerable to the negative health effects of sleep deficiency that impact multiple organ systems. Objective sleep measurement is difficult to achieve in the hospital setting, posing a barrier to linking improvements in hospital outcomes with sleep promotion protocols. Key next steps in hospital sleep promotion include improvement in sleep measurement techniques and harmonization of study protocols and outcomes to strengthen existing evidence and facilitate data interpretation across studies.

Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field.

Noise Levels and Sleep in a Surgical ICU

Sleep is disturbed in critically ill patients and is a frequently overlooked complication. The aim of our study is to evaluate the impact of sound levels in our surgical ICU on our patients’ sleep on the first night of admission. The study was performed in a tertiary care university hospital, in a 12-bed surgical ICU. Over a 6-week period, a total of 148 adult, non-intubated and non-sedated patients completed the study. During this six-week period, sound levels were continuously measured using a type II sound level meter. Sleep quality was evaluated using the Richards–Campbell Sleep Questionnaire (RCSQ), which was completed both by patients and nurses on the first morning after admission. A non-significant correlation was found between night sound levels and sleep quality in the overall sample (r = −1.83, 95% CI; −4.54 to 0.88, p = 0.19). After multivariable analysis, a correlation was found between higher sound levels at night and lower RCSQ evaluations (r = −3.92, 95% CI; −7.57 to −0.27, p = 0.04). We found a significant correlation between lower sound levels at night and a better quality of sleep in our patients; for each 1 dBA increase in LAFeq sound levels at night, patients scored 3.92 points lower on the sleep questionnaire.

Usefulness of Aerobic Exercise for Home Blood Pressure Control in Patients with Diabetes: Randomized Crossover Trial

Hypertension usually coexists with diabetes mellitus and significantly increases the risk of macrovascular complications. Blood pressure measured at home, especially nocturnal blood pressure, is particularly important because it is more strongly associated with target organ damage than clinical blood pressure measurements. Regular moderate aerobic exercise has been shown to have anti-hypertensive effects. This study aimed to investigate the effects of aerobic exercise on home blood pressure in patients with diabetes. This randomized crossover trial was based on outpatient treatment at a university hospital. In this randomized crossover trial, 124 patients with type 2 diabetes were randomly assigned to two groups over 56 days: an exercise preceding group (exercise intervention for 28 days and then no exercise intervention for the following 28 days) and an exercise lagging group (no exercise intervention for 28 days and then exercise intervention for the following 28 days). The associations between the nocturnal blood pressure and exercise intervention were assessed accordingly. A decrease in blood pressure was observed in the morning and evening, at 2 a.m. and 3 a.m. after exercise intervention; however, there was no significant difference between groups. Moderate exercise was not effective in lowering nocturnal blood pressure in this study.

Sleep and Actigraphy Research Trends: A Bibliometric and Keyword Network Analysis From 2004 to 2020

Background and Objective As sleep is a predictor of quality of life, studying sleep health and measurement is important. Actigraphy as a physiologic measure based on monitoring an individual’s movement has also been increasing in use as it has several advantages over traditional self-reports. This study aimed to report the research trends of sleep and actigraphy using a bibliometric and keyword analysis.Methods Using topic search queries, this study collected data from 3955 publications published between 2004 and 2020 and listed in the Web of Science Core Collection. A text-mining unstructured data analysis was performed using author keywords and a bibliographic analysis.Results Studies on sleep and actigraphy have been actively conducted in the fields of neurosciences and neurology but not in other fields. A gradual increase in publication and the steep increase in citations related to this topic occurring during the period considered. By clustering the author keywords, the analysis revealed five clusters: 1) monitoring physical activity and blood pressure, 2) measuring sleep quality, 3) insomnia and cognitive behavioral therapy for adolescents and children, 4) disorders and circadian rhythms, and 5) shift work. The leading research cluster has changed over the time.Conclusions With the increase in the number of studies and citations on sleep and actigraphy over the past 16 years, the trend of sleep and actigraphy studies have shifted from a focus on sleeprelated psychiatric disorders to a focus on cognitive behavioral therapy for children and adolescents and, more recently, the measurement of sleep quality.

Manual Annotation of Time in Bed Using Free-Living Recordings of Accelerometry Data

With the emergence of machine learning for the classification of sleep and other human behaviors from accelerometer data, the need for correctly annotated data is higher than ever. We present and evaluate a novel method for the manual annotation of in-bed periods in accelerometer data using the open-source software Audacity^®, and we compare the method to the EEG-based sleep monitoring device Zmachine^® Insight+ and self-reported sleep diaries. For evaluating the manual annotation method, we calculated the inter- and intra-rater agreement and agreement with Zmachine and sleep diaries using interclass correlation coefficients and Bland–Altman analysis. Our results showed excellent inter- and intra-rater agreement and excellent agreement with Zmachine and sleep diaries. The Bland–Altman limits of agreement were generally around ±30 min for the comparison between the manual annotation and the Zmachine timestamps for the in-bed period. Moreover, the mean bias was minuscule. We conclude that the manual annotation method presented is a viable option for annotating in-bed periods in accelerometer data, which will further qualify datasets without labeling or sleep records.

Actigraphy in mechanically ventilated pediatric ICU patients: comparison to PSG and evaluation of behavioral circadian rhythmicity

Sleep disruption is common in pediatric intensive care unit (PICU) patients, but measuring sleep in this population is challenging. We aimed to evaluate the utility of actigraphy for estimating circadian rhythmicity in mechanically ventilated PICU patients and its accuracy for measuring sleep by comparing it to polysomnogram (PSG). We conducted a single-center prospective observational study of children 6 months - 17 years of age receiving mechanical ventilation and standard, protocolized sedation for acute respiratory failure, excluding children with acute or historical neurologic injury. We enrolled 16 children and monitored them with up to 14 days of actigraphy and 24 hours of simultaneous limited (10 channel) PSG. Daily actigraphy-based activity profiles demonstrated that patients had a high level of nighttime activity (30-41% of total activity), suggesting disrupted circadian activity cycles. Among n = 12 patients with sufficient actigraphy and PSG data overlap, actigraphy-based sleep estimation showed poor agreement with PSG-identified sleep states, with good sensitivity (94%) but poor specificity (28%), low accuracy (70%,) and low agreement (Cohen's kappa = 0.2, 95% CI = 0.08-0.31). Using univariate linear regression, we identified that Cornell Assessment of Pediatric Delirium scores were associated with accuracy of actigraphy but that other clinical factors including sedative medication doses, activity levels, and restraint use were not. In this population, actigraphy did not reliably discern between sleep and wake states. However, in select patients, actigraphy was able to distinguish diurnal variation in activity patterns, and therefore may be useful for evaluating patients' response to circadian-oriented interventions.

Sleep-wake rhythms determined by actigraphy during in-hospital stay following discharge from an intensive care unit

BACKGROUND

Sleep and circadian disturbances play a major role in recovery after critical illness. Ample research has shown sleep to be disturbed during the stay at the intensive care unit (ICU); however, the trajectory of sleep after ICU discharge is sparsely described. The current study aimed to describe the development of the sleep-wake rhythm in subjects discharged from ICU to a hospital ward.

METHODS

Following discharge from the ICU to a general hospital ward, the participants were monitored with an ActiGraph for sleep assessment for 7 days or until hospital discharge or death. Data were analysed for day-to-day change with t-tests and for the whole period with repeated measures analysis.

RESULTS

For the 38 included patients, repeated measures analysis showed no significant improvement in total sleep time and wake time. However, for secondary outcomes, improvements for wake after sleep onset (P = .02) and reduction in the number of naps (P = .03) both in the day-to-day and overall trend analysis were observed.

CONCLUSION

The duration of sleep and wake time did not improve during ward stay. However, sleep became less fragmented and naps during the day declined. Due to the small sample size further, larger trials are needed.

Daytime activity and sleep are associated with motor function in older intensive care unit survivors

BACKGROUND

Hospitalized older intensive care unit (ICU) survivors are often inactive and experience sleep disturbances.

OBJECTIVE

We explored associations between post-ICU activity, sleep/rest, and motor function among hospitalized older ICU survivors.

METHODS

We enrolled 30 older ICU survivors, ages 65 and older, within 24-48 h of ICU discharge. Actigraphy measured post-ICU activity and sleep/rest. Selected measures from the National Institutes of Health Toolbox Motor Battery assessed grip strength and dexterity. Multivariate regression examined associations between post-ICU activity, sleep/rest, and motor function, adjusting for covariates.

RESULTS

Lower daytime activity (β = 0.258, p = .035) and greater daytime sleep/rest (β = -0.295, p = .022) were associated with worse grip strength. Lower daytime activity (β = -0.376, p = .037) and greater daytime sleep/rest (β = 0.409, p = .026) were associated with worse dexterity.

CONCLUSION

Post-ICU inactivity and prolonged rest periods are associated with worse motor function in hospitalized older ICU survivors.

Characterisation of ICU sleep by a commercially available activity tracker and its agreement with patient-perceived sleep quality

Background

A low-cost, quantitative method to evaluate sleep in the intensive care unit (ICU) that is both feasible for routine clinical practice and reliable does not yet exist. We characterised nocturnal ICU sleep using a commercially available activity tracker and evaluated agreement between tracker-derived sleep data and patient-perceived sleep quality.

Patients and methods

A prospective cohort study was performed in a 40-bed ICU at a community teaching hospital. An activity tracker (Fitbit Charge 2) was applied for up to 7 ICU days in English-speaking adults with an anticipated ICU stay ≥2 days and without mechanical ventilation, sleep apnoea, delirium, continuous sedation, contact isolation or recent anaesthesia. The Richards-Campbell Sleep Questionnaire (RCSQ) was administered each morning by a trained investigator.

Results

Available activity tracker-derived data for each ICU study night (20:00–09:00) (total sleep time (TST), number of awakenings (#AW), and time spent light sleep, deep sleep and rapid eye movement (REM) sleep) were downloaded and analysed. Across the 232 evaluated nights (76 patients), TST and RCSQ data were available for 232 (100%), #AW data for 180 (78%) and sleep stage data for 73 (31%). Agreement between TST (349±168 min) and RCSQ Score was moderate and significant (r=0.34; 95% CI 0.18 to 0.48). Agreement between #AW (median (IQR), 4 (2–9)) and RCSQ Score was negative and non-significant (r=−0.01; 95% CI −0.19 to 0.14). Agreement between time (min) spent in light (259 (182 to 328)), deep (43±29), and REM (47 (28–72)) sleep and RCSQ Score was moderate but non-significant (light (r=0.44, 95% CI −0.05 to 0.36); deep sleep (r=0.44, 95% CI −0.11 to 0.15) and REM sleep (r=0.44; 95% CI −0.21 to 0.21)).

Conclusions

A Fitbit Charge 2 when applied to non-intubated adults in an ICU consistently collects TST data but not #AW or sleep stage data at night. The TST moderately correlates with patient-perceived sleep quality; a correlation between either #AW or sleep stages and sleep quality was not found.

Stress-Induced Behavioral Quiescence and Abnormal Rest-Activity Rhythms During Critical Illness

OBJECTIVES

To characterize acute alterations of circadian and ultradian rest-activity rhythms in critically ill patients and their association with brain dysfunction, systemic multiple organ dysfunction, and melatonin rhythms.

DESIGN

Prospective study observing a cohort for 48 hours beginning within the first day of ICU admission.

SETTING

ICUs within an academic medical center.

PATIENTS

Patients presenting from the community with acute onset of either intracerebral hemorrhage or sepsis as representative neurologic and systemic critical illnesses. Healthy control patients were studied in the community, during hospital bedrest, and during sleep deprivation.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Circadian and ultradian characteristics of rest-activity patterns were measured by wrist actigraphy, severity of neurologic and systemic illness by Glasgow Coma Scale and Sequential Organ Failure Assessment, and central circadian rhythm by melatonin profile. We studied 112 critically ill patients, including 53 with sepsis and 59 with intracerebral hemorrhage, along with 53 control participants. Total daily activity was markedly reduced and rest-activity rhythmicity was undetectable, neither of which was replicated by hospital bedrest in healthy controls. Circadian rest-activity rhythm fragmentation and attenuation and ultradian disorganization was associated with Glasgow Coma Scale and Sequential Organ Failure Assessment in adjusted models. Rest-activity rhythms showed no detectable phase coherence with melatonin rhythms.

CONCLUSIONS

Critically ill patients rapidly enter a state of behavioral quiescence proportionate to their illness severity with concomitant disturbance of circadian and ultradian rest-activity rhythms and loss of phase coherence with the melatonin rhythm. Quiescence characteristics in rest-activity rhythms were not different in patients with and without delirium, suggesting them to be distinct phenomena. Animal models of severe physiologic stress have shown that specific neural pathway separate from the sleep-wake regulatory pathway induce behavioral quiescence and rest-activity arrhythmia, and facilitate recovery of cellular homeostasis. Whether quiescence is a conserved protective response pathway in humans is not yet understood.

Sleep in Aneurysmal Subarachnoid Hemorrhage Patients During Critical and Acute Care

BACKGROUND

Nurses caring for intensive care patients diagnosed with an aneurysmal subarachnoid hemorrhage (aSAH) conduct frequent neurological assessments and vital signs over an extended period during which patients are at risk of vasospasm. The frequency of assessments can negatively impact sleep, resulting in altered thought processes and mood, including delirium. There are 2 types of sleep during the night: non-rapid eye movement (non-REM) sleep and REM sleep (also called stage R). Non-REM sleep is subdivided into 3 stages: stage N1, stage N2, and stage N3. These 4 stages of sleep are referred to as sleep architecture.

OBJECTIVE

The aim of this study was to explore patterns of sleep in patients with aSAH over time during hospitalization.

METHODS

Sleep data of stages and cycles were collected with use of a Fitbit activity tracker in this pilot, exploratory research study. Demographic data included age and gender. Six English-speaking patients, diagnosed with an aneurysmal SAH, confirmed by diagnostic angiogram, were followed in neuro-intensive care unit (ICU), neuro-step-down, neuroscience unit, and inpatient rehabilitation.

RESULTS

There were a total of 226 sleep events. A sleep event encompassed a recorded start and end time on a single date. Each event included several sleep cycles. Each sleep cycle consisted of wakefulness, light sleep, deep sleep, and REM sleep. In 79 sleep events, light and deep sleep did add up to more than 4 hours; only 38 sleep events indicated more than 90 minutes of REM/night; 61 events showed the cycle of light-deep-light-REM cycles; 80 events showed 3 to 5 REM periods/night; and only 46 events demonstrated that the early-morning REM cycle was the longest. The average number of REM cycles increased from ICU (n = 4.6) to rehabilitation (n = 6.5). The percentage of days with sleep cycles also increased from ICU to rehabilitation (42 to 64).

DISCUSSION

"Normal" sleep patterns are disrupted in aSAH patients throughout their hospitalization. Data in this study revealed that the patients do sleep; however, it is rarely organized. Patients were not always able to progress through the expected sleep cycle of light to deep to light to REM. Hospitalized aSAH patients do engage in REM sleep, but its pattern is abnormal. Staff should strategize on minimizing interruptions, clustering care, and minimizing sounds. Nurses should advocate for the frequency of assessments and vital signs based on hospital/unit policy and individual patient needs.

Sleep and Activity Patterns Are Altered During Early Critical Illness in Mechanically Ventilated Adults

BACKGROUND

Mechanically ventilated (MV) patients in the intensive care unit (ICU) often experience disturbed sleep and profound inactivity.

OBJECTIVES

The aim of this study was to report 5 consecutive days' descriptive analyses on sleep efficiency (SE), total sleep time (TST), daytime activity ratio (DAR), and hourly activity counts among critically ill MV adults from 9 ICUs across 2 hospitals.

METHODS

A secondary analysis was undertaken from our parent National Institutes of Health-funded randomized controlled trial (NIH R01 NR016702). Subjects included 31 critically ill patients from multiple ICUs. Wrist actigraphy estimated SE and TST. Mean DAR, an indicator of altered sleep-wake cycles, was calculated. Continuous 24-hour activity counts over 5 consecutive days were summarized. Descriptive analyses were used.

RESULTS

A total of 31 subjects with complete actigraphy data were included. Mean age was 59.6 (SD, 17.3) years; 41.9% were male; 83.9% were White, and 67.7% were Hispanic/Latino; and the mean APACHE III (Acute Physiology and Chronic Health Evaluation III) severity of illness score was 74.5 (SD, 25.5). The mean nighttime SE and TST over the 5-day ICU period were 83.1% (SD, 16.14%) and 6.6 (SD, 1.3) hours, respectively. The mean DAR over the 5-day ICU period was 66.5% (SD, 19.2%). The DAR surpassed 80% on only 17.5% of subject days. The majority of subjects' activity level was low, falling below 1000 activity counts per hour.

CONCLUSION

Our study revealed poor rest-activity cycle consolidation among critically ill MV patients during the early ICU period. Future interventional studies should promote quality sleep at nighttime and promote mobilization during the daytime.

Assessment and Monitoring of Sleep in the Intensive Care Unit

Sleep affects physiologic and psychological recovery throughout critical illness. Patients often describe poor sleep as a major source of distress while hospitalized in an intensive care unit. The intensive care unit environment poses unique challenges for sleep assessment and monitoring. The purpose of this literature review is to discuss methods of assessment and monitoring of sleep within the intensive care unit setting. The advantages and disadvantages of physiologic monitoring of sleep (eg, polysomnography, bispectral index, and actigraphy) are compared with those of subjective measures of sleep quality (eg, validated patient-oriented sleep questionnaires, and informal nursing assessments).

The Impact of Earplugs and Eye Masks on Sleep Quality in Surgical ICU Patients at Risk for Frequent Awakenings

OBJECTIVES

Sleep disturbances may contribute to the development of delirium, prolonged ICU stay, and increased mortality. There is conflicting data on the effectiveness of earplugs and eye masks for sleep promotion in the ICU. This study evaluates the impact of earplugs and eye masks on sleep quality in postoperative surgical ICU patients at risk for frequent awakenings.

DESIGN

Prospective randomized controlled trial.

SETTING

Surgical ICU within the University of Texas Southwestern Medical Center.

PATIENTS

Adult, female patients admitted to the surgical ICU requiring hourly postoperative assessments following breast free flap surgery between February 2018 and October 2019.

INTERVENTIONS

Patients were randomized into an intervention group or a control group. The intervention group received earplugs and eye masks in addition to standard postoperative care, whereas the control group received standard postoperative care.

MEASUREMENTS AND MAIN RESULTS

The primary outcome was overall sleep quality assessed via the Richards-Campbell Sleep Questionnaire. Secondary outcomes of patient satisfaction and rates of ICU delirium were assessed with a modified version of the Family Satisfaction in the ICU survey and the Confusion Assessment Method for the ICU. After a planned interim analysis, the study was stopped early because prespecified criteria for significance were attained. Compared with the control group's average Richards-Campbell Sleep Questionnaire total score of 47.3 (95% CI, 40.8-53.8), the intervention group's average Richards-Campbell Sleep Questionnaire total score was significantly higher at 64.5 (95% CI, 58.3-70.7; p = 0.0007). There were no significant between-group differences for Confusion Assessment Method for the ICU scores or modified Family Satisfaction in the ICU survey scores.

CONCLUSIONS

These results suggest that earplugs and eye masks are effective in improving sleep quality in ICU patients undergoing frequent assessments. The results strengthen the evidence for nonpharmacologic sleep-promoting adjuncts in the ICU.

The Effect of a Quality Improvement Intervention on Sleep and Delirium in Critically Ill Patients in a Surgical ICU

BACKGROUND

Delirium is a deleterious condition affecting up to 60% of patients in the surgical ICU (SICU). Few SICU-focused delirium interventions have been implemented, including those addressing sleep-wake disruption, a modifiable delirium risk factor common in critically ill patients.

RESEARCH QUESTION

What is the effect on delirium and sleep quality of a multicomponent nonpharmacologic intervention aimed at improving sleep-wake disruption in patients in the SICU setting?

STUDY DESIGN AND METHODS

Using a staggered pre-post design, we implemented a quality improvement intervention in two SICUs (general surgery or trauma and cardiovascular) in an academic medical center. After a preintervention (baseline) period, a multicomponent unit-wide nighttime (ie, efforts to minimize unnecessary sound and light, provision of earplugs and eye masks) and daytime (ie, raising blinds, promotion of physical activity) intervention bundle was implemented. A daily checklist was used to prompt staff to complete intervention bundle elements. Delirium was evaluated twice daily using the Confusion Assessment Method for the Intensive Care Unit. Patient sleep quality ratings were evaluated daily using the Richards-Campbell Sleep Questionnaire (RCSQ).

RESULTS

Six hundred forty-six SICU admissions (332 baseline, 314 intervention) were analyzed. Median age was 61 years (interquartile range, 49-70 years); 35% of the cohort were women and 83% were White. During the intervention period, patients experienced fewer days of delirium (proportion ± SD of ICU days, 15 ± 27%) as compared with the preintervention period (20 ± 31%; P = .022), with an adjusted pre-post decrease of 4.9% (95% CI, 0.5%-9.2%; P = .03). Overall RCSQ-perceived sleep quality ratings did not change, but the RCSQ noise subscore increased (9.5% [95% CI, 1.1%-17.5%; P = .02).

INTERPRETATION

Our multicomponent intervention was associated with a significant reduction in the proportion of days patients experienced delirium, reinforcing the feasibility and effectiveness of a nonpharmacologic sleep-wake bundle to reduce delirium in critically ill patients in the SICU.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT03313115; URL: www.clinicaltrials.gov.

Nighttime Sleep Duration Is Associated With Length of Stay Outcomes Among Older Adult Survivors of Critical Illness

BACKGROUND

Older adults who required mechanical ventilation while in an intensive care unit (ICU) require adequate sleep throughout recovery from critical illness. Poor post-ICU sleep quality may contribute to worsening impairments in physical, cognitive, or psychological status after critical illness, known as post-ICU syndrome. Previous research has evaluated post-ICU sleep with qualitative or mixed methods (eg, interviews, questionnaires). We proposed measurement of sleep with actigraphy. We hypothesized that nighttime sleep is associated with length of stay (LOS).

OBJECTIVES

The aims of this study were to describe sleep quality of previously mechanically ventilated older adults recently transferred out of ICU and explore relationships between sleep duration and LOS outcomes.

METHODS

We enrolled 30 older adults, 65 years and older, within 24 to 48 hours after ICU discharge. We collected actigraphy data on post-ICU sleep duration (total sleep time [TST]) and sleep fragmentation (wake time after sleep onset) over 2 consecutive nights. We explored associations between TST and LOS (in days) outcomes using multivariate regression.

RESULTS

Subjects' mean TST was 7.55 ± 2.52 hours, and mean wake time after sleep onset was 2.26 ± 0.17 hours. In exploratory regression analyses, longer ICU LOS (β = 0.543, P < .001) and longer length of mechanical ventilation (β = 0.420, P = .028) were associated with greater post-ICU TST, after adjusting for potential confounding factors. Total sleep time was prospectively associated with total hospital LOS (β = 0.535, P < .001).

DISCUSSION

Older ICU survivors demonstrate greater sleep duration and worse sleep fragmentation. Poor sleep may contribute to longer LOS, secondary to post-ICU syndrome and sequelae. We recommend nursing interventions to promote sleep consolidation throughout transitions of care in the acute post-ICU recovery period.

Daytime-to-Nighttime Sleep Ratios and Cognitive Impairment in Older Intensive Care Unit Survivors

BACKGROUND

Sleep duration and proportion of daytime versus nighttime sleep may affect cognitive function in older patients in the transition out of the intensive care unit.

OBJECTIVE

To explore the relationship between the daytime-to-nighttime sleep ratio and cognitive impairment in older intensive care unit survivors.

METHODS

The study enrolled 30 older adults within 24 to 48 hours after intensive care unit discharge. All participants were functionally independent before admission and underwent mechanical ventilation in the intensive care unit. Actigraphy was used to estimate daytime (6 AM to 9:59 PM) and nighttime (10 PM to 5:59 AM) total sleep duration. Daytime-to-nighttime sleep ratios were calculated by dividing the proportion of daytime sleep by the proportion of nighttime sleep. The National Institutes of Health Toolbox Cognition Battery Dimensional Change Card Sort Test (DCCST) was used to assess cognition. Associations between sleep and cognition were explored using multivariate regression after adjusting for covariates.

RESULTS

The mean (SD) daytime sleep duration was 7.55 (4.30) hours (range, 0.16-14.21 hours), and the mean (SD) nighttime sleep duration was 4.99 (1.95) hours (range, 0.36-7.21 hours). The mean (SD) daytime-to-nighttime sleep ratio was 0.71 (0.30) (range, 0.03-1.10). Greater daytime sleep duration (β = -0.351, P = .008) and higher daytime-to-nighttime sleep ratios (β = -0.373, P = .008) were negatively associated with DCCST scores.

CONCLUSIONS

The daytime-to-nighttime sleep ratio was abnormally high in the study population, revealing an altered sleep/wake cycle. Higher daytime-to-nighttime sleep ratios were associated with worse cognition, suggesting that proportionally greater daytime sleep may predict cognitive impairment.

Sleep quality assessment in intensive care: actigraphy vs. Richards-Campbell sleep questionnaire

Introduction

It has been repeatedly shown that sleep of intensive care unit (ICU) patients is fragmented and its architecture is impaired. As sleep disorders have numerous negative effects on the organism, there have been efforts to implement sleep-promoting strategies into practice. When comparing the effectiveness of such measures, sleep quality assessment itself is a considerable problem.

Objective

The study aimed to assess the quality and quantity of night sleep in ICU patients simultaneously with actigraphy (ACT) and the Richards-Campbell Sleep Questionnaire (RCSQ). The secondary goals were to test the performance and effectiveness of the above methods and to verify correlations between selected RCSQ items and actigraph parameters.

Methods

A single-center prospective observational study (20 patients staying in a Interdisciplinary Intensive Care Unit). The quality of sleep was assessed using a Czech version of the RCSQ and ACT. The obtained data were analyzed and their dependence or correlations were verified by selected statistical tests.

Results

The mean RCSQ score was 47.6 (SD 24.4). The worst results were found for sleep latency (44.4; SD 31.2); the best results were for sleep quality (50.2; SD 29.4). The mean sleep effciency measured with ACT reached 86.6% (SD 9.2); the mean number of awakenings per night was 17.1 (SD 8.5). The RCSQ total parameter with a cutoff of 50 (RCSQ total = 50 good sleep / RCSQ total < 50 poor sleep) was shown to be suitable for discrimination of subjectively perceived sleep quality in ICU patients. However, the study failed to show statistically significant relations between subjectively perceived sleep quality (RCSQ) and ACT measurements.

Conclusion

The RCSQ appears to be a suitable instrument for assessing night sleep quality in ICU patients. On the other hand, the study showed a very low level of agreement between subjective sleep quality assessment and objective ACT measurements. The main drawback of ACT is low reliability of obtained data. Further research is needed to determine its role in sleep quality assessment in the ICU setting.

Impact of Sleep Deprivation in the Neurological Intensive Care Unit: A Narrative Review

Sleep is fundamental for everyday functioning, yet it is often negatively impacted in critically ill patients by the intensive care setting. With a focus on the neurological intensive care unit (NeuroICU), this narrative review summarizes methods of measuring sleep and addresses common causes of sleep disturbance in the hospital including environmental, pharmacological, and patient-related factors. The effects of sleep deprivation on the cardiovascular, pulmonary, immune, endocrine, and neuropsychological systems are discussed, with a focus on short-term deprivation in critically ill populations. Where evidence is lacking in the literature, long-term sleep deprivation studies and the effects of sleep deprivation in healthy individuals are also referenced. Lastly, strategies for the promotion of sleep in the NeuroICU are presented.

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

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).

Family automated voice reorientation (FAVoR) intervention for mechanically ventilated patients in the intensive care unit: Study protocol for a randomized controlled trial

Delirium in the intensive care unit (ICU) affects up to 80% of critically ill, mechanically ventilated (MV) adults. Delirium is associated with substantial negative outcomes, including increased hospital complications and long-term effects on cognition and health status in ICU survivors. The purpose of this randomized controlled trial is to test the effectiveness of a Family Automated Voice Reorientation (FAVoR) intervention on delirium among critically ill MV patients. The FAVoR intervention uses scripted audio messages, which are recorded by the patient's family and played at hourly intervals during daytime hours. This ongoing orientation to the ICU environment through recorded messages in a voice familiar to the patient may enable the patient to more accurately interpret the environment and thus reduce risk of delirium. The study's primary aim is to test the effect of the FAVoR intervention on delirium in critically ill MV adults in the ICU. The secondary aims are to explore: (1) if the effect of FAVoR on delirium is mediated by sleep, (2) if selected biobehavioral factors moderate the effects of FAVoR on delirium, and (3) the effects of FAVoR on short-term and long-term outcomes, including cognition and health status. Subjects (n = 178) are randomly assigned to the intervention or control group within 48 h of initial ICU admission and intubation. The intervention group receives FAVoR over a 5-day period, while the control group receives usual care. Delirium-free days, sleep and activity, cognition, patient-reported health status and sleep quality, and data regarding iatrogenic/environmental and biobehavioral factors are collected.

Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study

Background

Understanding the social mechanisms of the circadian rhythms of activity represents a major issue in better managing the mechanisms of age-related diseases occurring over time in the elderly population. The automated analysis of call detail records (CDRs) provided by modern phone technologies can help meet such an objective. At this stage, however, whether and how the circadian rhythms of telephone call activity can be automatically and properly modeled in the elderly population remains to be established.

Objective

Our goal for this study is to address whether and how the circadian rhythms of social activity observed through telephone calls could be automatically modeled in older adults.

Methods

We analyzed a 12-month data set of outgoing telephone CDRs of 26 adults older than 65 years of age. We designed a statistical learning modeling approach adapted for exploratory analysis. First, Gaussian mixture models (GMMs) were calculated to automatically model each participant’s circadian rhythm of telephone call activity. Second, k-means clustering was used for grouping participants into distinct groups depending on the characteristics of their personal GMMs.

Results

The results showed the existence of specific structures of telephone call activity in the daily social activity of older adults. At the individual level, GMMs allowed the identification of personal habits, such as morningness-eveningness for making calls. At the population level, k-means clustering allowed the structuring of these individual habits into specific morningness or eveningness clusters.

Conclusions

These findings support the potential of phone technologies and statistical learning approaches to automatically provide personalized and precise information on the social rhythms of telephone call activity of older individuals. Futures studies could integrate such digital insights with other sources of data to complete assessments of the circadian rhythms of activity in elderly populations.

Novel statistical approach for assessing the persistence of the circadian rhythms of social activity from telephone call detail records in older adults

How circadian rhythms of activity manifest themselves in social life of humans remains one of the most intriguing questions in chronobiology and a major issue for personalized medicine. Over the past years, substantial advances have been made in understanding the personal nature and the robustness—i.e. the persistence—of the circadian rhythms of social activity by the analysis of phone use. At this stage however, the consistency of such advances as their statistical validity remains unclear. The present paper has been specifically designed to address this issue. To this end, we propose a novel statistical procedure for the measurement of the circadian rhythms of social activity which is particularly well-suited for the existing framework of persistence analysis. Furthermore, we illustrate how this procedure works concretely by assessing the persistence of the circadian rhythms of telephone call activity from a 12-month call detail records (CDRs) dataset of adults over than 65 years. The results show the ability of our approach for assessing persistence with a statistical significance. In the field of CDRs analysis, this novel statistical approach can be used for completing the existing methods used to analyze the persistence of the circadian rhythms of a social nature. More importantly, it provides an opportunity to open up the analysis of CDRs for various domains of application in personalized medicine requiring access to statistical significance such as health care monitoring.

Sleep Quality Associated With Motor Function Among Older Adult Survivors of Critical Illness

BACKGROUND

Poor sleep is associated with worse motor function in older adults. Sleep may affect motor function specifically among older adults recovering from critical illness after transfer out of an intensive care unit (ICU).

OBJECTIVES

Describe motor function (grip strength) of older ICU survivors and explore relationships between sleep and ICU-acquired weakness in the early post-ICU transition period.

METHODS

We enrolled 30 older adults who were functionally independent prior to hospitalization, mechanically ventilated while in ICU, and within 24-48 hours post-ICU discharge. Handgrip dynamometry assessed post-ICU motor function (fully corrected T score on the National Institutes of Health Motor Battery Grip Strength Test). Actigraphy estimated post-ICU sleep duration (total sleep time [TST]) and fragmentation (wake after sleep onset) over two consecutive nights from 22:00 p.m. to 06:00 a.m.. We identified differences in grip strength by history of obstructive sleep apnea (OSA) using independent-samples t tests. We examined associations between sleep duration and grip strength using exploratory multivariate regression analyses, after adjustment for clinically relevant covariates.

RESULTS

Grip strength among this cohort of older ICU survivors was almost 2 SDs below the norm for healthy older adults, indicating considerable ICU-acquired weakness. Grip strength was lower among subjects with history of OSA than those without OSA. Greater TST was associated with worse grip strength, after adjusting for history of OSA and Pittsburgh Sleep Quality Index global score. Moreover, among the subset of male subjects (n = 19), greater TST was significantly and negatively associated with grip strength, after adjusting for Acute Physiology, Age, and Chronic Health Evaluation III score, and Pittsburgh Sleep Quality Index global score.

DISCUSSION

Sleep promotion may be a potentially modifiable risk factor to mitigate ICU-acquired weakness in older ICU survivors. We propose that improving sleep throughout recovery from critical illness may indirectly promote better outcomes, as poor grip strength is linked to longer length of hospital stay, higher acuity of discharge disposition, and worsened functional decline in older adults.

Sleep Architecture in Mechanically Ventilated Pediatric ICU Patients Receiving Goal-Directed, Dexmedetomidine- and Opioid-based Sedation

This single-center prospective observational study aimed to evaluate sleep architecture in mechanically ventilated pediatric intensive care unit (PICU) patients receiving protocolized light sedation. We enrolled 18 children, 6 months to 17 years of age, receiving mechanical ventilation and standard, protocolized sedation for acute respiratory failure, and monitored them with 24 hours of limited (10 channels) polysomnogram (PSG). The PSG was scored by a sleep technician and reviewed by a pediatric sleep medicine physician. Sixteen children had adequate PSG data for sleep stage scoring. All received continuous opioid infusions, 15 (94%) received dexmedetomidine, and 7 (44%) received intermittent benzodiazepines. Total sleep time was above the age-matched normal reference range (median 867 vs. 641 minutes, p = 0.002), attributable to increased stage N1 and N2 sleep. Diurnal variation was absent, with a median of 47% of sleep occurring during night-time hours. Rapid eye movement (REM) sleep was observed as absent in most patients (n = 12, 75%). Sleep was substantially disrupted, with more awakenings per hour than normal for age (median 2.2 vs. 1.1, p = 0.008), resulting in a median average sleep period duration (sleep before awakening) of only 25 minutes (interquartile range [IQR]: 14–36) versus normal 72 minutes (IQR: 65–86, p = 0.001). Higher ketamine and propofol doses were associated with increased sleep disruption. Children receiving targeted, opioid-, and dexmedetomidine-based sedation to facilitate mechanical ventilation for acute respiratory failure have substantial sleep disruption and abnormal sleep architecture, achieving little to no REM sleep. Dexmedetomidine-based sedation does not ensure quality sleep in this population.

The Association between Sleep Duration and Quality with Readmissions: An Exploratory Pilot-Study among Cardiology Inpatients

Background: Readmissions within 30 days of discharge are prominent among patients with cardiovascular disease. Post hospital syndrome hypothesizes that sleep disturbance during the index admission contributes to an acquired transient vulnerability, leading to increased risk of readmission. This study evaluated the association of in-hospital sleep (a) duration and (b) quality with 30-day all-cause unplanned readmission. Methods: This prospective observational cohort study included patients admitted to the coronary care unit of a South Australian hospital between 2016–2018. Study participants were invited to wear an ActiGraph GT3X+ for the duration of their admission and for two weeks post-discharge. Validated sleep and quality of life questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), were administered. Readmission status and questionnaires were assessed at 30 days post-discharge via patient telephone interview and a review of hospital records. Results: The final cohort consisted of 75 patients (readmitted: n = 15, non-readmitted: n = 60), of which 72% were male with a mean age 66.9 ± 13.1 years. Total sleep time (TST), both in hospital (6.9 ± 1.3 vs. 6.8 ± 2.9 h, p = 0.96) and post-discharge (7.4 ± 1.3 h vs. 8.9 ± 12.6 h, p = 0.76), was similar in all patients. Patient’s perception of sleep, reflected by PSQI scores, was poorer in readmitted patients (9.13 ± 3.6 vs. 6.4 ± 4.1, p = 0.02). Conclusions: Although an association between total sleep time and 30-day readmission was not found, patients who reported poorer sleep quality were more likely to be readmitted within 30 days. This study also highlighted the importance of improving sleep, both in and out of the hospital, to improve the outcomes of cardiology inpatients.