Poor sleep quality is associated with late noninvasive ventilation failure in patients with acute hypercapnic respiratory failure*:

Effect of Atypical Sleep EEG Patterns on Weaning From Prolonged Mechanical Ventilation

BACKGROUND

Approximately one-third of acute ICU patients display atypical sleep patterns that cannot be interpreted by using standard EEG criteria for sleep. Atypical sleep patterns have been associated with poor weaning outcomes in acute ICUs.

RESEARCH QUESTION

Do patients being weaned from prolonged mechanical ventilation experience atypical sleep EEG patterns, and are these patterns linked with weaning outcomes?

STUDY DESIGN AND METHODS

EEG power spectral analysis during wakefulness and overnight polysomnogram were performed on alert, nondelirious patients at a long-term acute care facility.

RESULTS

Forty-four patients had been ventilated for a median duration of 38 days at the time of the polysomnogram study. Eleven patients (25%) exhibited atypical sleep EEG. During wakefulness, relative EEG power spectral analysis revealed higher relative delta power in patients with atypical sleep than in patients with usual sleep (53% vs 41%; P < .001) and a higher slow-to-fast power ratio during wakefulness: 4.39 vs 2.17 (P < .001). Patients with atypical sleep displayed more subsyndromal delirium (36% vs 6%; P = .027) and less rapid eye movement sleep (4% vs 11% total sleep time; P < .02). Weaning failure was more common in the atypical sleep group than in the usual sleep group: 91% vs 45% (P = .013).

INTERPRETATION

This study provides the first evidence that patients in a long-term acute care facility being weaned from prolonged ventilation exhibit atypical sleep EEG patterns that are associated with weaning failure. Patients with atypical sleep EEG patterns had higher rates of subsyndromal delirium and slowing of the wakeful EEG, suggesting that these two findings represent a biological signal for brain dysfunction.

Effectiveness of sleep interventions to reduce delirium in critically ill patients: A systematic review and meta-analysis

PURPOSE

To analyze the effectiveness of sleep interventions in reducing the incidence and duration of delirium in the ICU.

MATERIALS AND METHODS

We searched the PubMed, Embase, CINAHL, Web of Science, Scopus, and Cochrane databases for relevant randomized controlled trials from inception to August 2022. Literature screening, data extraction, and quality assessment were performed independently by two investigators. Data from the included studies were analyzed using Stata and TSA software.

RESULTS

Fifteen randomized controlled trials were eligible. Meta-analysis showed that the sleep intervention was associated with a reduced incidence of delirium in the ICU (RR = 0.73, 95% CI = 0.58 to 0.93, p < 0.001) compared to the control group. The results of the trial sequence analysis further confirm that sleep interventions are effective in reducing the occurrence of delirium. Pooled data from the three dexmedetomidine trials showed significant differences in the incidence of ICU delirium between groups (RR = 0.43, 95% CI = 0.32 to 0.59, p < 0.001). The respective pooled results of other sleep interventions (e.g., light therapy, earplugs, melatonin, and multicomponent nonpharmacologic treatments) did not find a significant effect on reducing the incidence and duration of ICU delirium (p > 0.05).

CONCLUSIONS

The current evidence suggests that non-pharmacological sleep interventions are not effective in preventing delirium in ICU patients. However, limited by the number and quality of included studies, future well-designed multicenter randomized controlled trials are still needed to validate the results of this study.

Sleep Architecture Patterns in Critically Ill Patients and Survivors of Critical Illness: A Retrospective Study

Rationale: Sleep abnormalities are very frequent in critically ill patients during and after intensive care unit (ICU) stays. Their mechanisms are poorly understood. The odds ratio product (ORP) is a continuous metric (range, 0.0-2.5) of sleep depth measured in 3-second intervals and derived from the relationship of powers of different electroencephalographic frequencies to one another. When expressed as the percentage of epochs within 10 ORP deciles covering the entire ORP range, it provides information about the mechanism(s) of abnormal sleep. Objectives: To determine ORP architecture types in critically ill patients and survivors of critical illness who had previously undergone sleep studies. Methods: Nocturnal polysomnograms from 47 unsedated critically ill patients and 23 survivors of critical illness at hospital discharge were analyzed. Twelve critically ill patients were monitored also during the day, and 15 survivors underwent subsequent polysomnography 6 months after hospital discharge. In all polysomnograms, each 30-second epoch was characterized by the mean ORP of the 10 3-second epochs. The number of 30-second epochs with mean ORP within each of 10 ORP deciles covering the entire ORP range (0.0-2.5) was calculated and expressed as a percentage of total recording time. Thereafter, each polysomnogram was characterized using a two-digit ORP type, with the first digit (range, 1-3) reflecting increasing degrees of deep sleep (ORP < 0.5, deciles 1 and 2) and the second digit (range, 1-3) reflecting increasing degrees of full wakefulness (ORP > 2.25, decile 10). Results from patients were compared with those from 831 age- and gender-matched community dwellers free of sleep disorders. Results: In critically ill patients, types 1,1 and 1,2 (little deep sleep and little or average full wakefulness) dominated (46% of patients). In the community, these types are uncommon (<15%) and seen primarily in disorders that preclude progression to deep sleep (e.g., very severe obstructive sleep apnea). Next in frequency (22%) was type 1,3, consistent with hyperarousal. Day ORP sleep architecture was similar to night results. Survivors had similar patterns, with little improvement after 6 months. Conclusions: Sleep abnormalities in critically ill patients and survivors of critical illness result primarily from stimuli that preclude progression to deep sleep or from the presence of a hyperarousal state.

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.

Reinforcement Learning Model for Managing Noninvasive Ventilation Switching Policy

Noninvasive ventilation (NIV) has been recognized as a first-line treatment for respiratory failure in patients with chronic obstructive pulmonary disease (COPD) and hypercapnia respiratory failure, which can reduce mortality and burden of intubation. However, during the long-term NIV process, failure to respond to NIV may cause overtreatment or delayed intubation, which is associated with increased mortality or costs. Optimal strategies for switching regime in the course of NIV treatment remain to be explored.For the goal of reducing 28-day mortality of the patients undergoing NIV, Double Dueling Deep Q Network (D3QN) of offline-reinforcement learning algorithm was adopted to develop an optimal regime model for making treatment decisions of discontinuing ventilation, continuing NIV, or intubation. The model was trained and tested using the data from Multi-Parameter Intelligent Monitoring in Intensive Care III (MIMIC-III) and evaluated by the practical strategies. Furthermore, the applicability of the model in majority disease subgroups (Catalogued by International Classification of Diseases, ICD) was investigated. Compared with physician's strategies, the proposed model achieved a higher expected return score (4.25 vs. 2.68) and its recommended treatments reduced the expected mortality from 27.82% to 25.44% in all NIV cases. In particular, for these patients finally received intubation in practice, if the model also supported the regime, it would warn of switching to intubation 13.36 hours earlier than clinicians (8.64 vs. 22 hours after the NIV treatment), granting a 21.7% reduction in estimated mortality. In addition, the model was applicable across various disease groups with distinguished achievement in dealing with respiratory disorders. The proposed model is promising to dynamically provide personalized optimal NIV switching regime for patients undergoing NIV with the potential of improving treatment outcomes.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

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.

Effects of dexmedetomidine on postoperative sleep quality: a systematic review and meta-analysis of randomized controlled trials

STUDY OBJECTIVES

To assess the effect of dexmedetomidine (DEX) on postoperative sleep quality using polysomnography (PSG) to identify possible interventions for postoperative sleep disturbances.

METHODS

An electronic search of PubMed/MEDLINE, EMBASE, Cochrane Library and Web of Science was conducted from database inception to November 20, 2022. Randomized controlled trials (RCTs) on the effect of DEX administration on postoperative sleep quality using PSG or its derivatives were included. No language restrictions were applied. The sleep efficiency index (SEI), arousal index (AI), percentages of stage N1, N2 and N3 of non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep were measured in our meta-analysis.

RESULTS

Five studies, involving 381 participants were included. Administration of DEX significantly improved SEI, lowered AI, decreased the duration of stage N1 sleep and increased the duration of stage N2 sleep compared to placebo groups. There were no significant differences in the duration of stage N3 sleep and REM sleep. DEX administration lowered the postoperative Visual Analogue Scale (VAS) score and improved the Ramsay sedation score with no adverse effect on postoperative delirium (POD). However, high heterogeneity was observed in most of the primary and secondary outcomes.

CONCLUSIONS

Our study provides support for the perioperative administration of DEX to improve postoperative sleep quality. The optimal dosage and overall effect of DEX on postoperative sleep quality require further investigation using large-scale randomized controlled trials.

An Automated Algorithm for Determining Sleep Using Single-Channel Electroencephalography to Detect Delirium: A Prospective Observational Study in Intensive Care Units

The relationship between polysomnography-based objective sleep and delirium in the intensive care unit (ICU) is inconsistent across studies, suggesting limitations in manually determining the sleep stage of critically ill patients. We objectively measured 24-h sleep using a single-channel electroencephalogram (SleepScope [SS]) and an under-mattress sleep monitor (Nemuri SCAN [NSCAN]), both of which have independent algorithms that automatically determine sleep and wakefulness. Eighteen patients (median age, 68 years) admitted to the ICU after valvular surgery or coronary artery bypass grafting were included, and their sleep time was measured one day after extubation. The median total sleep times (TSTs) measured by SS (TST-SS) and NSCAN were 548 (48−1050) and 1024 (462−1257) min, respectively. Two patients with delirium during the 24-h sleep measurement had very short TST-SS of 48 and 125 min, and the percentage of daytime sleep accounted for >80% in both SS and NSCAN. This preliminary case series showed marked sleep deprivation and increased rates of daytime sleeping in ICU patients with delirium. Although data accuracy from under-mattress sleep monitors is contentious, automated algorithmic sleep/wakefulness determination using a single-channel electroencephalogram may be useful in detecting delirium in ICU patients and could even be superior to polysomnography.

Effect of low-dose dexmedetomidine on sleep quality in postoperative patients with mechanical ventilation in the intensive care unit: A pilot randomized trial

Background

Sleep disturbances are prevalent in patients requiring invasive mechanical ventilation in the intensive care unit (ICU) and are associated with worse outcomes. Sedative-dose dexmedetomidine may improve sleep quality in this patient population but is associated with adverse events. Herein, we tested the effect of low-dose dexmedetomidine infusion on nighttime sleep quality in postoperative ICU patients with invasive ventilation.

Methods

In this pilot randomized trial, 80 adult patients who were admitted to the ICU after non-cardiac surgery and required invasive mechanical ventilation were randomized to receive either low-dose dexmedetomidine (0.1 to 0.2 μg/kg/h, n = 40) or placebo (n = 40) for up to 72 h. The primary endpoint was overall subjective sleep quality measured using the Richards–Campbell Sleep Questionnaire (score ranges from 0 to 100, with a higher score indicating better quality) in the night of surgery. Secondary outcomes included sleep structure parameters monitored with polysomnography from 9:00 PM on the day of surgery to the next 6:00 AM.

Results

All 80 patients were included in the intention-to-treat analysis. The overall subjective sleep quality was median 52 (interquartile 20, 66) with placebo vs. 61 (27, 79) with dexmedetomidine, and the difference was not statistically significant (median difference 8; 95% CI: −2, 22; P = 0.120). Among 68 patients included in sleep structure analysis, those in the dexmedetomidine group tended to have longer total sleep time [median difference 54 min (95% CI: −4, 120); P = 0.061], higher sleep efficiency [median difference 10.0% (95% CI: −0.8%, 22.3%); P = 0.060], lower percentage of stage N1 sleep [median difference −3.9% (95% CI: −11.8%, 0.5%); P = 0.090], higher percentage of stage N3 sleep [median difference 0.0% (95% CI: 0.0%, 0.4%); P = 0.057], and lower arousal index [median difference −0.9 (95% CI −2.2, 0.1); P = 0.091] but not statistically significant. There were no differences between the two groups regarding the incidence of adverse events.

Conclusion

Among patients admitted to the ICU after surgery with intubation and mechanical ventilation, low-dose dexmedetomidine infusion did not significantly improve the sleep quality pattern, although there were trends of improvement. Our findings support the conduct of a large randomized trial to investigate the effect of low-dose dexmedetomidine in this patient population.

Clinical trial registration

ClinicalTrial.gov, identifier: NCT03335527.

Factors Associated with and Prognosis Impact of Perceived Sleep Quality and Estimated Quantity in Patients Receiving Non-Invasive Ventilation for Acute Respiratory Failure

Background. The objectives of this study were (1) to determine factors associated with impaired sleep and (2) to evaluate the relationship between impaired sleep and the outcome. Methods. Secondary analysis of a prospective observational cohort study in 54 intensive care units in France and Belgium. Sleep quality was quantified by the patients with a semi-quantitative scale. Results. Among the 389 patients included, 40% reported poor sleep during the first night in the ICU and the median (interquartile) total sleep time was 4 h (2−5). Factors independently associated with poor sleep quality were the SOFA score (odds ratio [OR] 0.90, p = 0.037), anxiety (OR 0.43, p = 0.001) and the presence of air leaks (OR 0.52, p = 0.013). Factors independently associated with short-estimated sleep duration (<4 h) were the SOFA score (1.13, p = 0.005), dyspnea on admission (1.13, p = 0.031) and the presence of air leaks (1.92, p = 0.008). Non-invasive ventilation failure was independently associated with poor sleep quality (OR 3.02, p = 0.021) and short sleep duration (OR 0.77, p = 0.001). Sleep quality and duration were not associated with an increase in mortality or length of stay. Conclusions. The sleep of patients with ARF requiring NIV is impaired and is associated with a high rate of NIV failure.

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.

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.

Evaluation of Sleep Architecture using 24-hour Polysomnography in Patients Recovering from Critical Illness in an Intensive Care Unit and High Dependency Unit: a Longitudinal, Prospective, and Observational Study

Background and objective

The sleep architecture of critically ill patients being treated in Intensive Care Units (ICU) and High Dependency Units (HDU) is frequently unsettled and inadequate both qualitatively and quantitatively. The study aimed to investigate and elucidate factors influencing sleep architecture and quality in ICU and HDU in a limited resource setting with financial constraints, lacking human resources and technology for routine monitoring of noise, light and sleep promotion strategies in ICU.

Methods

The study was longitudinal, prospective, hospital-based, analytic, and observational. Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS) pre hospitalisation scores were recorded. Patients underwent 24-hour polysomnography (PSG) with the simultaneous monitoring of noise and light in their environments. Patients stabilised in ICU were transferred to HDU, where the 24-hour PSG with the simultaneous monitoring of noise and light in their environments was repeated. Following PSG, the Richards-Campbell Sleep Questionnaire (RCSQ) was employed to rate patients’ sleep in both the ICU and HDU.

Results

Of 46 screened patients, 26 patients were treated in the ICU and then transferred to the HDU. The mean (SD) of the study population’s mean (SD) age was 35.96 (11.6) years with a predominantly male population (53.2% (n=14)). The mean (SD) of the ISI and ESS scores were 6.88 (2.58) and 4.92 (1.99), respectively. The comparative analysis of PSG data recording from the ICU and HDU showed a statistically significant reduction in N1, N2 and an increase in N3 stages of sleep (p<0.05). Mean (SD) of RCSQ in the ICU and the HDU were 54.65 (7.70) and 60.19 (10.85) (p-value = 0.04) respectively. The disease severity (APACHE II) has a weak correlation with the arousal index but failed to reach statistical significance (coeff= 0.347, p= 0.083).

Conclusion

Sleep in ICU is disturbed and persisting during the recovery period in critically ill. However, during recovery, sleep architecture shows signs of restoration.

Effect of enterally administered sleep-promoting medication on the intravenous sedative dose and its safety and cost profile in mechanically ventilated patients: A retrospective cohort study

BACKGROUND

The clinical effect of enteral administration of sleep-promoting medication (SPM) in mechanically ventilated patients remains unclear. This study aimed to investigate the relationship between enteral SPM administration and the intravenous sedative dose and examine the safety and cost of enteral SPM administration.

METHODS

This single-center retrospective cohort study was conducted in a Japanese tertiary hospital intensive care unit (ICU). The exposure was enteral SPM administration during mechanical ventilation. The outcome was the average daily propofol dose per body weight administered as a continuous sedative during mechanical ventilation. Patients were divided into three groups based on the timing of SPM administration at ICU admission: "administration within 48 hours (early administration [EA])," "administration after 48 hours (late administration [LA])," and "no administration (NA)." We used multiple linear regression models.

RESULTS

Of 123 included patients, 37, 50, and 36 patients were assigned to the EA, LA, and NA groups, respectively. The average daily propofol dose per body weight was significantly lower in the EA group than in the LA and NA groups (β -5.13 [95% confidence interval (CI) -8.93 to -1.33] and β -4.51 [95% CI -8.59 to -0.43], respectively). Regarding safety, enteral SPM administration did not increase adverse events, including self-extubation. The total cost of neuroactive drugs tended to be lower in the EA group than in the LA and NA groups.

CONCLUSIONS

Early enteral SPM administration reduced the average daily propofol dose per body weight without increasing adverse events.

Dynamic prediction of late noninvasive ventilation failure in intensive care unit using a time adaptive machine model

BACKGROUND

Noninvasive ventilation (NIV) failure is strongly associated with poor prognosis. Nowadays, plenty of mature studies have been proposed to predict early NIV failure (within 48 hours of NIV), however, the prediction for late NIV failure (after 48 hours of NIV) lacks sufficient research. Late NIV failure delays intubation resulting in the increasing mortality of the patients. Therefore, it is of great significance to expeditiously predict the late NIV failure. In order to dynamically predict late NIV failure, we proposed a Time Updated Light Gradient Boosting Machine (TULightGBM) model.

MATERIAL AND METHODS

In this work, 5653 patients undergoing NIV over 48 hours were extracted from the database of Medical Information Mart for Intensive Care Ⅲ (MIMIC-Ⅲ) for model construction. The TULightGBM model consists of a series of sub-models which learn clinical information from updating data within 48 hours of NIV and integrates the outputs of the sub-models by the dynamic attention mechanism to predict late NIV failure. The performance of the proposed TULightGBM model was assessed by comparison with common models of logistic regression (LR), random forest (RF), LightGBM, eXtreme gradient boosting (XGBoost), artificial neural network (ANN), and long short-term memory (LSTM).

RESULTS

The TULightGBM model yielded prediction results at 8, 16, 24, 36, and 48 hours after the start of the NIV with dynamic AUC values of 0.8323, 0.8435, 0.8576, 0.8886, and 0.9123, respectively. Furthermore, the sensitivity, specificity, and accuracy of the TULightGBM model were 0.8207, 0.8164, and 0.8184, respectively. The proposed model achieved superior performance over other tested models.

CONCLUSIONS

The TULightGBM model is able to dynamically predict the late NIV failure with high accuracy and offer potential decision support for clinical practice.

Non-pharmacological sleep interventions for adult patients in intensive care Units: A systematic review

OBJECTIVES

To synthesize and evaluate current non-pharmacological sleep interventions for critically ill adult patients in intensive care units and provide recommendations for future studies of non-pharmacological means of improving this population's sleep quality.

RESEARCH METHODOLOGY/DESIGN

The literature search was conducted following PRISMA guidelines. Seven databases CINAHL, PsycINFO, Embase, Medline, Cochrane Library, Web of Science, and Scopus and three keywords, sleep, intervention and intensive care unit were employed. All possible combinations of the keywords and similar words were considered. Included studies were primary studies, involved adult intensive care unit patients, focused on non-pharmacological sleep interventions, measured subjective and/or objective sleep quality and were published in English between January 2010 and September 2020.

RESULTS

The 20 included studies examined different types of non-pharmacological sleep interventions involving use of earplugs, an eye mask, white noise, music, aromatherapy, massage, acupressure, light intensity, a sleep hygiene protocol, quiet time and minimization of nursing care. Of 18 studies employing an experimental design, most reported that non-pharmacological interventions improved sleep quality. All these interventions involved environmental factors or complementary relaxation strategies.

CONCLUSIONS

Non-pharmacological sleep interventions can have a positive influence on sleep quality in critically ill patients, but more research is needed to determine their effectiveness.

Effects of Sedatives on Sleep Architecture Measured With Odds Ratio Product in Critically Ill Patients

Supplemental Digital Content is available in the text.

OBJECTIVES:

Evaluation of sleep quality in critically ill patients is difficult using conventional scoring criteria. The aim of this study was to examine sleep in critically ill patients with and without light sedation using the odds ratio product, a validated continuous metric of sleep depth (0 = deep sleep; 2.5 = full wakefulness) that does not rely on the features needed for conventional staging.

DESIGN:

Retrospective study.

SETTINGS:

A 16-bed medical-surgical ICU.

PATIENTS:

Twenty-three mechanically ventilated patients who had previously undergone two nocturnal sleep studies, one without and one with sedation (propofol, n = 12; dexmedetomidine, n = 11).

INTERVENTIONS:

None.

MEASUREMENTS AND MAIN RESULTS:

Sleep architecture was evaluated with odds ratio product analysis by the distribution of 30-second epochs with different odds ratio product values. Electroencephalogram spectral patterns and frequency of wake intrusions (3-s odds ratio product > 1.75) were measured at different odds ratio product levels. Thirty-seven normal sleepers were used as controls. Compared with normal sleepers, unsedated critically ill patients spent little time in stable sleep (percent odds ratio product < 1.0: 31% vs 63%; p < 0.001), whereas most of the time were either in stage wake (odds ratio product > 1.75) or in a transitional state (odds ratio product 1.0–1.75), characterized by frequent wake intrusions. Propofol and dexmedetomidine had comparable effects on sleep. Sedation resulted in significant shift in odds ratio product distribution toward normal; percent odds ratio product less than 1.0 increased by 54% (p = 0.006), and percent odds ratio product greater than 1.75 decreased by 48% (p = 0.013). In six patients (26%), sedation failed to improve sleep.

CONCLUSIONS:

In stable critically ill unsedated patients, sleep quality is poor with frequent wake intrusions and little stable sleep. Light sedation with propofol or dexmedetomidine resulted in a shift in sleep architecture toward normal in most, but not all, patients.

The central nervous system during lung injury and mechanical ventilation: a narrative review

Mechanical ventilation induces a number of systemic responses for which the brain plays an essential role. During the last decade, substantial evidence has emerged showing that the brain modifies pulmonary responses to physical and biological stimuli by various mechanisms, including the modulation of neuroinflammatory reflexes and the onset of abnormal breathing patterns. Afferent signals and circulating factors from injured peripheral tissues, including the lung, can induce neuronal reprogramming, potentially contributing to neurocognitive dysfunction and psychological alterations seen in critically ill patients. These impairments are ubiquitous in the presence of positive pressure ventilation. This narrative review summarises current evidence of lung-brain crosstalk in patients receiving mechanical ventilation and describes the clinical implications of this crosstalk. Further, it proposes directions for future research ranging from identifying mechanisms of multiorgan failure to mitigating long-term sequelae after critical illness.

A Systematic Review of Risk Factors for Sleep Disruption in Critically Ill Adults

OBJECTIVES

Numerous risk factors for sleep disruption in critically ill adults have been described. We performed a systematic review of all risk factors associated with sleep disruption in the ICU setting.

DATA SOURCES

PubMed, EMBASE, CINAHL, Web of Science, Cochrane Central Register for Controlled Trials, and Cochrane Database of Systematic Reviews.

STUDY SELECTION

English-language studies of any design published between 1990 and April 2018 that evaluated sleep in greater than or equal to 10 critically ill adults (> 18 yr old) and investigated greater than or equal to 1 potential risk factor for sleep disruption during ICU stay. We assessed study quality using Newcastle-Ottawa Scale or Cochrane Risk of Bias tool.

DATA EXTRACTION

We abstracted all data independently and in duplicate. Potential ICU sleep disruption risk factors were categorized into three categories based on how data were reported: 1) patient-reported reasons for sleep disruption, 2) patient-reported ratings of potential factors affecting sleep quality, and 3) studies reporting a statistical or temporal association between potential risk factors and disrupted sleep.

DATA SYNTHESIS

Of 5,148 citations, we included 62 studies. Pain, discomfort, anxiety/fear, noise, light, and ICU care-related activities are the most common and widely studied patient-reported factors causing sleep disruption. Patients rated noise and light as the most sleep-disruptive factors. Higher number of comorbidities, poor home sleep quality, home sleep aid use, and delirium were factors associated with sleep disruption identified in available studies.

CONCLUSIONS

This systematic review summarizes all premorbid, illness-related, and ICU-related factors associated with sleep disruption in the ICU. These findings will inform sleep promotion efforts in the ICU and guide further research in this field.

Incidence, characteristics, and outcomes of delirium in patients with noninvasive ventilation: a prospective observational study

Background

Factors that may increase the risk for delirium and the firm knowledge around mechanism for delirium in noninvasive ventilation (NIV) patients is lacking. We investigated the incidence, characteristics, and outcomes of delirium in NIV patients.

Methods

A prospective observational study was performed in an intensive care unit (ICU) of a teaching hospital. Patients in whom NIV was used as a first-line intervention were enrolled. During NIV intervention, delirium was screened using the Confusion Assessment Method for the ICU each day. The association between delirium and poor outcomes (e.g., NIV failure, ICU and hospital mortality) was investigated using forward stepwise multivariate logistic regression analyses.

Results

We enrolled 1083 patients. Of these, 196 patients (18.1%) experienced delirium during NIV intervention. Patients with delirium had higher NIV failure rates (37.8% vs. 21.0%, p < 0.01), higher ICU mortality (33.2% vs. 14.3%, p < 0.01), and higher hospital mortality (37.2% vs. 17.0%, p < 0.01) than subjects without delirium. They also had a longer duration of NIV (median 6.3 vs. 3.7 days, p < 0.01), and stayed longer in the ICU (median 9.0 vs. 6.0 days, p < 0.01) and the hospital (median 14.5 vs. 11.0 days, p < 0.01). These results were confirmed in COPD and non-COPD cohorts. According to subtype, compared to hyperactive delirium patients, hypoactive and mixed delirium patients spent more days and many more days on NIV (median 3.4 vs. 6.5 vs. 10.1 days, p < 0.01). Similar outcomes were found for length of stay in the ICU and hospital. However, NIV failure, ICU mortality, and hospital mortality did not differ among the three subtypes.

Conclusions

Delirium is associated with increases in poor outcomes (NIV failure, ICU mortality, and hospital mortality) and the use of medical resources (duration of NIV, and lengths of stay in the ICU and hospital). Regarding subtype, hypoactive and mixed delirium are associated with higher, and much higher, consumption of medical resources, respectively, compared to hyperactive delirium.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01517-3.

The prevalence and impact of pre-existing sleep disorder diagnoses and objective sleep parameters in patients hospitalized for COVID-19

STUDY OBJECTIVES

Obstructive sleep apnea and other sleep disorders overlap with comorbidities associated with poor outcomes related to severe acute respiratory syndrome coronavirus 2 infection. However, the prevalence of obstructive sleep apnea among patients hospitalized for COVID-19 and relationship to outcomes is poorly characterized, and the relevance of other sleep disorders remains unknown. The objective of this study was to identify the prevalence of pre-existing sleep disorders and association with outcomes related to severe COVID-19 illness.

METHODS

Patients with severe acute respiratory syndrome coronavirus 2 infection admitted to the University of Michigan Hospital System were included. Electronic medical records were queried for sleep disorders diagnostic codes. Data were extracted from polysomnography and home sleep testing in a subgroup with previous diagnostic testing at our center. Logistic regression was used to examine the association of sleep disorders with mechanical ventilation requirement, treatment with vasopressors, and death and Cox proportional hazards regression for time to discharge.

RESULTS

Among n = 572 adult patients hospitalized for COVID-19, 113 (19.8%) patients had obstructive sleep apnea, 4 patients had central sleep apnea (0.7%), 5 had hypoventilation (0.9%), 63 had insomnia (11.0%), and 22 had restless legs syndrome or periodic limb movements disorder (3.9%). After adjusting for age, sex, body mass index, and race, no significant relationship was apparent between sleep disorders diagnoses or indices of sleep-disordered breathing severity and outcomes.

CONCLUSIONS

This is the first study to determine the prevalence of obstructive sleep apnea and other sleep disorders in a well-characterized cohort of patients hospitalized for COVID-19. Once hospitalized, a significant contribution of sleep disorders to outcomes was not identified. Therefore, future evaluations should focus on earlier outcomes, such as infection or clinical manifestations after exposure to severe acute respiratory syndrome coronavirus 2.

Role of sleep on respiratory failure after extubation in the ICU

Background

Sleep had never been assessed immediately after extubation in patients still in the ICU. However, sleep deprivation may alter respiratory function and may promote respiratory failure. We hypothesized that sleep alterations after extubation could be associated with an increased risk of post-extubation respiratory failure and reintubation. We conducted a prospective observational cohort study performed at the medical ICU of the university hospital of Poitiers in France. Patients at high-risk of extubation failure (> 65 years, with any underlying cardiac or lung disease, or intubated > 7 days) were included. Patients intubated less than 24 h, with central nervous or psychiatric disorders, continuous sedation, neuroleptic medication, or uncooperative were excluded. Sleep was assessed by complete polysomnography just following extubation including the night. The main objective was to compare sleep between patients who developed post-extubation respiratory failure or required reintubation and the others.

Results

Over a 3-year period, 52 patients had complete polysomnography among whom 12 (23%) developed post-extubation respiratory failure and 8 (15%) required reintubation. Among them, 10 (19%) had atypical sleep, 15 (29%) had no deep sleep, and 33 (63%) had no rapid eye movement (REM) sleep. Total sleep time was 3.2 h in median [interquartile range, 2.0–4.4] in patients who developed post-extubation respiratory failure vs. 2.0 [1.1–3.8] in those who were successfully extubated (p = 0.34). Total sleep time, and durations of deep and REM sleep stages did not differ between patients who required reintubation and the others. Reintubation rates were 21% (7/33) in patients with no REM sleep and 5% (1/19) in patients with REM sleep (difference, − 16% [95% CI − 33% to 6%]; p = 0.23).

Conclusions

Sleep assessment by polysomnography after extubation showed a dramatically low total, deep and REM sleep time. Sleep did not differ between patients who were successfully extubated and those who developed post-extubation respiratory failure or required reintubation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00863-z.

Impact of a sleep promotion protocol on off-pump coronary artery bypass graft patients

BACKGROUND

Sleep abnormalities frequently occur in intensive care unit (ICU) patients, and the consequences of sleep abnormalities in patients who undergo off-pump coronary artery bypass graft (OPCABG) surgery are particularly significant. Although many interventions have been reported to improve sleep, few sleep promotion protocols have been designed specifically for patients in cardiac ICUs.

AIMS AND OBJECTIVES

This study aimed to explore the effects of an evidence-based sleep promotion protocol on patients who underwent OPCABG in a cardiac ICU.

DESIGN

A quasi-experimental study was conducted in a comprehensive hospital in Shandong province of China.

METHODS

Overall, 67 participants were recruited (37 in the control group and 30 in the intervention group). An evidence-based sleep promotion protocol was developed by a 10-member interprofessional collaborative team and then applied. Sound levels, light intensity, and the number of nocturnal interventions were compared between groups. The Chinese version of the Richards-Campbell Sleep Questionnaire (RCSQ) was used to compare intergroup sleep status on two consecutive postoperative nights.

RESULTS

No significant differences were found for demographics or disease severity between the groups. In the intervention group, sound levels and light intensity were significantly lower at various times, and nocturnal interventions were significantly less frequent over the two consecutive nights. RCSQ scores were significantly higher in the intervention group for both nights.

CONCLUSIONS

The sleep promotion protocol reduced sound levels, night-time light intensity, the number of nocturnal interventions, and improved sleep among OPCABG patients in a cardiac ICU.

RELEVANCE TO CLINICAL PRACTICE

Evidence-based practice can help to promote good quality of care, improve patient outcomes, and advance nursing in clinical settings.

Short-term physical health effects of sleep disruptions attributed to the acute hospital environment: a systematic review

The sleep disruption experienced by patients admitted to hospital may have a negative effect on health but the nature and magnitude of the effect has not been conclusively outlined. The review was designed to examine the impact of sleep disruption associated with being a hospital inpatient, on short-term physical health outcomes in adult patients. Searches comprised journal databases, gray literature sources, and backward and forward citation searching. Two reviewers independently screened the records. Original studies of adult hospitalized patients' sleep were included if physical outcomes were also measured. Interventional studies were excluded. The methodological quality was assessed independently by 2 reviewers using CASP checklists. Sleep assessment measures and results, physical outcomes and contextual data were extracted. Results were synthesized according to frequently reported outcomes: delirium, pain intensity, physical strength, and respiratory function. A meta-analysis was not performed; studies were heterogeneous and reporting was limited. Of 9919 retrieved records, 26 published studies were included (published: 2001-2020). Risk of bias was moderately high. Confounding factors were poorly reported. Total sleep time was either normal or reduced. Sleep was disrupted: arousal indices were high (mean: 0 5-21/h); slow wave sleep proportions were limited. Subjective sleep quality was poor. The association between sleep reduction or disruption and short-term health outcomes was negative, mixed or equivocal and included increased delirium, higher pain intensity, poorer strength, and adverse respiratory function. The impact of sleep disruption on outcomes for hospitalized patients is not well defined.

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.

Risk Factors Associated with Late Failure of Noninvasive Ventilation in Patients with Chronic Obstructive Pulmonary Disease

Background

Risk factors for noninvasive ventilation (NIV) failure after initial success are not fully clear in patients with acute exacerbation of chronic obstructive pulmonary disease (COPD).

Methods

Patients who received NIV beyond 48 h due to acute exacerbation of COPD were enrolled. However, we excluded those whose pH was higher than 7.35 or PaCO₂ was less than 45 mmHg which was measured before NIV. Late failure of NIV was defined as patients required intubation or died during NIV after initial success.

Results

We enrolled 291 patients in this study. Of them, 48 (16%) patients experienced late NIV failure (45 received intubation and 3 died during NIV). The median time from initiation of NIV to intubation was 4.8 days (IQR: 3.4–8.1). Compared with the data collected at initiation of NIV, the heart rate, respiratory rate, pH, and PaCO₂ significantly improved after 1–2 h of NIV both in the NIV success and late failure of NIV groups. Nosocomial pneumonia (odds ratio (OR) = 75, 95% confidence interval (CI): 11–537), heart rate at initiation of NIV (1.04, 1.01–1.06 beat per min), and pH at 1–2 h of NIV (2.06, 1.41–3.00 per decrease of 0.05 from 7.35) were independent risk factors for late failure of NIV. In addition, the Glasgow coma scale (OR = 0.50, 95% CI: 0.34–0.73 per one unit increase) and PaO₂/FiO₂ (0.992, 0.986–0.998 per one unit increase) were independent protective factors for late failure of NIV. In addition, patients with late failure of NIV had longer ICU stay (median 9.5 vs. 6.6 days) and higher hospital mortality (92% vs. 3%) compared with those with NIV success.

Conclusions

Nosocomial pneumonia; heart rate at initiation of NIV; and consciousness, acidosis, and oxygenation at 1–2 h of NIV were associated with late failure of NIV in patients with COPD exacerbation. And, late failure of NIV was associated with increased hospital mortality.

Non-pharmacological interventions to reduce the incidence and duration of delirium in critically ill patients: A systematic review and network meta-analysis

OBJECTIVE

To compare non-pharmacological interventions in their ability to prevent delirium in critically ill patients, and find the optimal regimen for treatment.

METHODS

Literature searches were conducted using PubMed, Embase, CINAHL, and Cochrane Library databases until the end of June 2019. We estimated the risk ratios (RRs) for the incidence of delirium and in-hospital mortality and found the mean difference (MD) for delirium duration and the length of ICU stay. The probabilities of interventions were ranked based on clinical outcomes. The study was registered on PROSPERO (CRD42020160757).

RESULTS

Twenty-six eligible studies were included in the network meta-analysis. Studies were grouped into seven intervention types: physical environment intervention (PEI), sedation reducing (SR), family participation (FP), exercise program (EP), cerebral hemodynamics improving (CHI), multi-component studies (MLT) and usual care (UC). In term of reducing the incidence of delirium, the two most effective interventions were FP (risk ratio (RR) 0.19, 95% confidence interval (CI) 0.08 to 0.44; surface under the cumulative ranking curve (SUCRA) = 94%) and MLT (RR 0.43, 95% CI 0.30 to 0.57; SUCRA = 68%) compared with observation. Although all interventions demonstrated nonsignificant efficacy in regards to delirium duration and the length of the patient's stay in the ICU, MLT (SUCRA = 78.6% and 71.2%, respectively) was found to be the most effective intervention strategy. In addition, EP (SUCRA = 97.2%) facilitated a significant reduction in hospital mortality, followed in efficacy by MLT (SUCRA = 73.2%), CHI (SUCRA = 35.8%), PEI (SUCRA = 34.8%), and SR (SUCRA = 31.8%).

CONCLUSIONS

Multi-component strategies are overall the optimal intervention techniques for preventing delirium and reducing ICU length of stay in critically ill patients by way of utilizing several interventions simultaneously. Additionally, family participation as a method of patient-centered care resulted in better outcomes for reducing the incidence of delirium.

Assessing delirium with nursing care instruments: Evaluation of the cognitive and associated domains

OBJECTIVE

Nursing instruments have the potential for daily screening of delirium; however, they have not yet been evaluated. Therefore, after assessing the functional domains of the electronic Patient Assessment - Acute Care (ePA-AC), this study evaluates the cognitive and associated domains.

METHODS

In this prospective cohort study in the intensive care unit, 277 patients were assessed and 118 patients were delirious. The impacts of delirium on the cognitive domains, consciousness and cognition, communication and interaction, in addition to respiration, pain, and wounds were determined with simple logistic regressions and their respective odds ratios (ORs).

RESULTS

Delirium was associated with substantial impairment throughout the evaluated domains. Delirious patients were somnolent (OR 6), their orientation (OR 8.2-10.6) and ability to acquire knowledge (OR 5.5-11.6) were substantially impaired, they lost the competence to manage daily routines (OR 8.2-22.4), and their attention was compromised (OR 12.8). In addition, these patients received psychotropics (OR 3.8), were visually impaired (OR 1.8), unable to communicate their needs (OR 5.6-7.6), displayed reduced self-initiated activities (OR 6.5-6.9) and challenging behaviors (OR 6.2), as well as sleep-wake disturbances (OR 2.2-5), Furthermore, delirium was associated with mechanical ventilation, abdominal/thoracic injuries or operations (OR 4.2-4.4), and sensory perception impairment (OR 3.9-5.8).

SIGNIFICANCE OF RESULTS

Delirium caused substantial impairment in cognitive and associated domains. In addition to the previously described functional impairments, these findings will aid the implementation of nursing instruments in delirium screening.

Steroid-Induced Sleep Disturbance and Delirium: A Focused Review for Critically Ill Patients

OBJECTIVE

Insomnia and delirium have gained much attention since the publication of recent guidelines for the management in critically ill adults. Neurologic effects such as sleep disturbance, psychosis, and delirium are commonly cited adverse effects (AEs) of corticosteroids. Steroid use is considered a modifiable risk factor in intensive care unit patients; however, reported mechanisms are often lacking. This focused review will specifically evaluate the effects of steroids on sleep deprivation, psychosis, delirium, and what is known about these effects in a critically ill population.

OBSERVATIONS

The medical literature proposes 3 pathways primarily responsible for neurocognitive AEs of steroids: behavior changes through modification of the hypothalamic-pituitary-adrenal axis, changes in natural sleep-wake cycles, and hyperarousal caused by modification in neuroinhibitory pathways. Initial search fields produced 285 articles. Case reports, reviews, letters, and articles pertaining to primary care or palliative populations were excluded, leaving 8 relevant articles for inclusion.

CONCLUSIONS

Although steroid therapy often cannot be altered in the critically ill population, research showed that steroid overuse is common in intensive care units. Minimizing dosage and duration are important ways clinicians can mitigate AEs.

Genetic variant rs3750625 in the 3'UTR of ADRA2A affects the sleep quality of patients in the ICU by promoting miR‑34a binding to ADRA2A

Poor sleep is very common in patients in the ICU and hence, sleep quality is considered an important aspect of intensive care; however, the underlying mechanisms of poor sleep in patients in the ICU remain unknown. In this study, we aimed to explore the role of rs3750625, which is located in the 3'UTR of adrenoceptor alpha 2A (ADRA2A), in sleep quality. For this purpose, luciferase assay was conducted to investigate the association between miR‑34a and ADRA2A, and the effect of rs3750625 on the binding affinity between miR‑34a and ADRA2A was examined. RT‑qPCR and western blot analysis were carried out to examine the regulatory association between miR‑34a and ADRA2A. The differences in sleep time and efficiency were compared between groups carrying the AC and CC genotypes of rs3750625, respectively. According to the results from an online search, miR‑34a could directly bind to the 3'UTR of ADRA2A, and such binding was confirmed by the observation that miR‑34a inhibited the luciferase activity of major or minor ADRA2A 3'UTR in a dose‑dependent manner in HCN‑1A and U251 cells. In addition, the ADRA2A protein and mRNA levels in the HCN‑1A and U251 cells were evidently decreased following transfection with miR‑34a precursors. Notably, patients in the AC group exhibited a similar level of miR‑34a mRNA expression compared with patients in the CC group; however, the ADRA2A mRNA and protein levels in the CC group were significantly increased in comparison with those in the AC group. In addition, the sleep time and sleep efficiency in the CC group were much higher than those in the AC group. Furthermore, the mean arterial pressure (MAP) values in both the AC and CC groups remained stable from 22:00 to 08:00, and the respiratory rates in both groups were quite similar. However, the heart rate of patients in the CC group was much lower than that of patients in the AC group. On the whole, the findings of this study suggest that the genetic variant rs3750625 in the 3'UTR of ADRA2A affects the sleep quality of patients in the ICU by promoting the binding of miR‑34a to ADRA2A, and hence it may serve as a novel biomarker for the prediction of the sleep quality of patients in the ICU.

Atypical Sleep and Postoperative Delirium in the Cardiothoracic Surgical Intensive Care Unit: A Pilot Prospective Study

PURPOSE

Postoperative delirium (POD) is a very common and serious neurological complication in patients admitted to the cardiothoracic surgical intensive care unit (CSICU). We aimed to identify a novel potential sleep-based marker for POD and investigate the relevance between atypical sleep and POD.

PATIENTS AND METHODS

This was a prospective, observational study of patients admitted to the CSICU between December 2019 and February 2020 at our center. Sleep characteristics from 21:00 on postoperative day 1 to 07:00 on postoperative day 2 were assessed using polysomnography (PSG). POD from the end of PSG monitoring until postoperative day 5 was evaluated using the Confusion Assessment Method for the Intensive Care Unit.

RESULTS

This analysis included 20 patients admitted to the CSICU. The incidence of atypical sleep was 45.0%. Compared to patients without delirium, those with delirium had less delta power, less percentage REM sleep, and a higher proportion of atypical sleep and REM sleep loss (P < 0.05).

CONCLUSION

The presence of atypical sleep and the absence of REM sleep were associated with POD in patients admitted to the CSICU.

Sleep and Delirium in Adults Who Are Critically Ill: A Contemporary Review

Sleep is important to health and well-being, and studies in healthy adults have demonstrated that sleep deprivation impacts respiratory, immune, and cognitive function. Historically, because of the nature of critical illness, sleep has not been considered a priority for patient care in the ICU. More recently, research has demonstrated that sleep is markedly abnormal in patients who are critically ill. In addition, there is often disruption of circadian rhythms. Delirium is a syndrome of acute alteration in mental status that occurs in the setting of contributing factors such as serious illness, medication, and drug or alcohol intoxication or withdrawal. Delirium is a frequent occurrence in critical illness, and research has demonstrated several adverse outcomes associated with delirium including persistent cognitive impairment and increased mortality. Sleep deprivation and delirium share many common symptoms. The similarity in symptoms between sleep disruption and delirium have prompted experts to draw links between the two and question both the relationship and its direction. In addition, the inclusion of sleep disturbance to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition in its constellation of symptoms used in diagnosing delirium has increased awareness of the link between sleep and delirium. This paper will review the literature on sleep in critical illness and the potential mechanisms and pathways that may connect sleep and delirium.

Early prediction of noninvasive ventilation failure in COPD patients: derivation, internal validation, and external validation of a simple risk score

Background

Early identification of noninvasive ventilation (NIV) failure is a promising strategy for reducing mortality in chronic obstructive pulmonary disease (COPD) patients. However, a risk-scoring system is lacking.

Methods

To develop a scale to predict NIV failure, 500 COPD patients were enrolled in a derivation cohort. Heart rate, acidosis (assessed by pH), consciousness (assessed by Glasgow coma score), oxygenation, and respiratory rate (HACOR) were entered into the scoring system. Another two groups of 323 and 395 patients were enrolled to internally and externally validate the scale, respectively. NIV failure was defined as intubation or death during NIV.

Results

Using HACOR score collected at 1–2 h of NIV to predict NIV failure, the area under the receiver operating characteristic curves (AUC) was 0.90, 0.89, and 0.71 for the derivation, internal-validation, and external-validation cohorts, respectively. For the prediction of early NIV failure in these three cohorts, the AUC was 0.91, 0.96, and 0.83, respectively. In all patients with HACOR score > 5, the NIV failure rate was 50.2%. In these patients, early intubation (< 48 h) was associated with decreased hospital mortality (unadjusted odds ratio = 0.15, 95% confidence interval 0.05–0.39, p < 0.01).

Conclusions

HACOR scores exhibited good predictive power for NIV failure in COPD patients, particularly for the prediction of early NIV failure (< 48 h). In high-risk patients, early intubation was associated with decreased hospital mortality.

Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU

OBJECTIVE

To update and expand the 2013 Clinical Practice Guidelines for the Management of Pain, Agitation, and Delirium in Adult Patients in the ICU.

DESIGN

Thirty-two international experts, four methodologists, and four critical illness survivors met virtually at least monthly. All section groups gathered face-to-face at annual Society of Critical Care Medicine congresses; virtual connections included those unable to attend. A formal conflict of interest policy was developed a priori and enforced throughout the process. Teleconferences and electronic discussions among subgroups and whole panel were part of the guidelines' development. A general content review was completed face-to-face by all panel members in January 2017.

METHODS

Content experts, methodologists, and ICU survivors were represented in each of the five sections of the guidelines: Pain, Agitation/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption). Each section created Population, Intervention, Comparison, and Outcome, and nonactionable, descriptive questions based on perceived clinical relevance. The guideline group then voted their ranking, and patients prioritized their importance. For each Population, Intervention, Comparison, and Outcome question, sections searched the best available evidence, determined its quality, and formulated recommendations as "strong," "conditional," or "good" practice statements based on Grading of Recommendations Assessment, Development and Evaluation principles. In addition, evidence gaps and clinical caveats were explicitly identified.

RESULTS

The Pain, Agitation/Sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption) panel issued 37 recommendations (three strong and 34 conditional), two good practice statements, and 32 ungraded, nonactionable statements. Three questions from the patient-centered prioritized question list remained without recommendation.

CONCLUSIONS

We found substantial agreement among a large, interdisciplinary cohort of international experts regarding evidence supporting recommendations, and the remaining literature gaps in the assessment, prevention, and treatment of Pain, Agitation/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption) in critically ill adults. Highlighting this evidence and the research needs will improve Pain, Agitation/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption) management and provide the foundation for improved outcomes and science in this vulnerable population.

Respiratory Failure, Noninvasive Ventilation, and Symptom Burden: An Observational Study

BACKGROUND

Noninvasive ventilation (NIV) is commonly used to manage acute respiratory failure due to decompensated cardiorespiratory disease. We describe symptom burden in this population.

MEASURES

Fifty consecutive, consenting, English-speaking, cognitively intact patients, admitted to wards other than the intensive care unit in a tertiary teaching hospital and treated with NIV for hypercapnic respiratory failure, were recruited. The 14-item Condensed Memorial Symptom Assessment Scale was used to assess physical and psychological symptoms within 36 hours of commencing NIV. Breathlessness (using Borg score), pain location and intensity using a numerical rating scale, and four symptoms potentially prevalent in patients undergoing NIV (cough, sputum, gastric bloating, and dry eyes) were also assessed.

OUTCOMES

Patients reported a median of 10 symptoms (IQR 9-13). A median of five symptoms (IQR 3-7) were rated as severe. Breathlessness was the most prevalent and most distressing symptom, with participants reporting a mean maximum Borg score of 7.55 over the 24 hours before admission. Dry mouth, lack of energy, cough, sputum, difficulty sleeping, and psychological symptoms were prevalent. Pain, when reported, was of moderate intensity and contributed to distress.

CONCLUSIONS/LESSONS LEARNED

This study describes the patient-reported symptoms occurring during an episode of acute respiratory failure. Understanding the symptom profile of patients in this setting may allow clinicians to target symptom relief while simultaneously managing respiratory failure, enhancing care.

Association between death and loss of stage N2 sleep features among critically Ill patients with delirium

PURPOSE

Critically ill patients experience significant sleep disruption. In this study of ICU patients with delirium, we evaluated associations between the loss of stage N2 features (K-complexes, sleep spindles), grade of encephalopathy based on electroencephalography (EEG), and intensive care unit (ICU) outcomes. We hypothesized that loss of stage N2 features is associated with more severe grades of encephalopathy and worse ICU outcomes including death.

MATERIALS AND METHODS

This was an observational cohort study of 93 medical ICU patients without primary acute brain injury who underwent continuous EEG. Type and severity of critical illness, sedative-hypnotic use, length of stay, modified Rankin Scale at hospital discharge, and death during hospitalization were abstracted from the medical record. EEG was evaluated for grade of encephalopathy and sleep features.

RESULTS

Patients without K-complexes or without sleep spindles had more severe encephalopathy and higher odds of death. The odds ratio for patients without K-complexes was 18.8 (p = .046). The odds ratio for patients without sleep spindles was 6.3 (p = .036).

CONCLUSIONS

Loss of stage N2 features is common and associated with more severe encephalopathy and higher odds of death. The absence of either Stage N2 feature, K complexes or sleep spindles, may have important prognostic value.

Non-circadian signals in the intensive care unit: Point prevalence morning, noon and night

BACKGROUND

Intensive care unit (ICU) sleep disturbance is severe and potentially related to abnormal light and sound exposure.

OBJECTIVES

To assess the prevalence of measures of light and sound disturbance in ICU patient rooms, and whether these could be modified by a sleep-promotion intervention.

METHODS

This observational study with a before and after design for a quality improvement initiative surveyed environmental factors in ICU rooms at 01:00 08:00, and 12:00. Surveys assessed light usage, television usage, window shade position, and room door/curtain position. Factors were compared before and after an ICU sleep-promotion intervention.

RESULTS

990 (pre-intervention) and 819 (post-intervention) occupied rooms were surveyed. Pre-intervention, the prevalence of night-time factors included: bright lights on (21%), television on (46%), and room door open (94%). Post-intervention, more rooms had all lights off at night (41% v 50%, p = 0.04), and fewer rooms had open door curtains (57% v 42%, p = 0.001) and window shades (78% v 62%, p = 0.002).

CONCLUSIONS

Disruptive environmental factors are common in the ICU. Some factors improve with sleep-promotion interventions.

The effects of mechanical ventilation on the quality of sleep of hospitalised patients in the Intensive Care Unit

Aim

To examine the effects of mechanical ventilation on the quality of sleep in patients in the intensive care unit (ICU) using recent and relevant literature.

Methods

To verify the examined objective, the results of the analysis of available original scientific works have been used including defined inclusion/exclusion criteria and search strategy. Appropriate works found were analysed further. The applied methodology was in line with the general principles of Evidence-Based Medicine. The following literary databases were used: CINAHL, Medline and gray literature: Google Scholar.

Results

A total of 91 trials were found. Eleven of these relevant to the follow-up analysis were selected: all trials were carried out under real ICU conditions and the total of 192 patients were included in the review. There is an agreement within all trials that sleep in patients requiring mechanical ventilation is disturbed. Most reviewed trials have shown that mechanical ventilation is probably not the main factor causing sleep disturbances, but an appropriate ventilation strategy can significantly help to improve its quality by reducing the frequency of the patient-ventilator asynchrony.

Conclusion

Based on the analysis, it appears that an appropriate ventilation mode setting can have a beneficial effect on the quality of sleep in ICU patients.

How should we monitor patients with acute respiratory failure treated with noninvasive ventilation?

Noninvasive ventilation (NIV) is currently one of the most commonly used support methods in hypoxaemic and hypercapnic acute respiratory failure (ARF). With advancing technology and increasing experience, not only are indications for NIV getting broader, but more severe patients are treated with NIV. Depending on disease type and clinical status, NIV can be applied both in the general ward and in high-dependency/intensive care unit settings with different environmental opportunities. However, it is important to remember that patients with ARF are always very fragile with possible high mortality risk. The delay in recognition of unresponsiveness to NIV, progression of respiratory failure or new-onset complications may result in devastating and fatal outcomes. Therefore, it is crucial to understand that timely action taken according to monitoring variables is one of the key elements for NIV success. The purpose of this review is to outline basic and advanced monitoring techniques for NIV during an ARF episode.

Impact of sleep alterations on weaning duration in mechanically ventilated patients: a prospective study

Sleep is markedly altered in intensive care unit (ICU) patients and may alter respiratory performance. Our objective was to assess the impact of sleep alterations on weaning duration.

We conducted a prospective physiological study at a French teaching hospital. ICU patients intubated for at least 24 h and difficult to wean were included. Complete polysomnography (PSG) was performed after the first spontaneous breathing trial failure. Presence of atypical sleep, duration of sleep stages, particularly rapid eye movement (REM) sleep, and electroencephalogram (EEG) reactivity at eyes opening were assessed by a neurologist.

20 out of 45 patients studied (44%) had atypical sleep that could not be classified according to the standard criteria. Duration of weaning between PSG and extubation was significantly longer in patients with atypical sleep (median (interquartile range) 5 (2–8) versus 2 (1–2) days; p=0.001) and in those with no REM sleep compared with the others. Using multivariate logistic regression analysis, atypical sleep remained independently associated with prolonged weaning (>48 h after PSG). Altered EEG reactivity at eyes opening was a good predictor of atypical sleep.

Our results suggest for the first time that brain dysfunction may have an influence on the ability to breathe spontaneously.