Sound level intensity severely disrupts sleep in ventilated ICU patients throughout a 24-h period: a preliminary 24-h study of sleep stages and associated sound levels

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.

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.

Optimizing Sleep and Circadian Health in the NeuroICU

Purpose of Review

This article introduces fundamental concepts in circadian biology and the neuroscience of sleep, reviews recent studies characterizing circadian rhythm and sleep disruption among critically ill patients and potentially links to functional outcomes, and draws upon existing literature to propose therapeutic strategies to mitigate those harms. Particular attention is given to patients with critical neurologic conditions and the unique environment of the neuro-intensive care unit.

Recent Findings

Circadian rhythm disruption is widespread among critically ill patients and sleep time is reduced and abnormally fragmented. There is a strong association between the degree of arousal suppression observed at the bedside and the extent of circadian disruption at the system (e.g., melatonin concentration rhythms) and cellular levels (e.g., core clock gene transcription rhythms). There is a paucity of electrographically normal sleep, and rest-activity rhythms are severely disturbed. Common care interventions such as neurochecks introduce unique disruptions in neurologic patients. There are no pharmacologic interventions proven to normalize circadian rhythms or restore physiologically normal sleep. Instead, interventions are focused on reducing pharmacologic and environmental factors that perpetuate disruption.

Summary

The intensive care environment introduces numerous potent disruptors to sleep and circadian rhythms. Direct neurologic injury and neuro-monitoring practices likely compound those factors to further derange circadian and sleep functions. In the absence of direct interventions to induce normalized rhythms and sleep, current therapy depends upon normalizing external stimuli.

Sleep Spindles and K-Complexes Are Favorable Prognostic Biomarkers in Critically Ill Patients

SUMMARY

In this narrative review, we summarize recent research on the prognostic significance of biomarkers of sleep in continuous EEG and polysomnographic recordings in intensive care unit patients. Recent studies show the EEG biosignatures of non-rapid eye movement 2 sleep (sleep spindles and K-complexes) on continuous EEG in critically ill patients better predict functional outcomes and mortality than the ictal-interictal continuum patterns. Emergence of more complex and better organized sleep architecture has been shown to parallel neurocognitive recovery and correlate with functional outcomes in traumatic brain injury and strokes. Particularly interesting are studies which suggest intravenous dexmedetomidine may induce a more biomimetic non-rapid eye movement sleep state than intravenous propofol, potentially providing more restorative sleep and lessening delirium. Protocols to improve intensive care unit sleep and neurophysiological studies evaluating the effect of these on sleep and sleep architecture are here reviewed.

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.

Newborn Incubators Do Not Protect from High Noise Levels in the Neonatal Intensive Care Unit and Are Relevant Noise Sources by Themselves

BACKGROUND

While meaningful sound exposure has been shown to be important for newborn development, an excess of noise can delay the proper development of the auditory cortex.

AIM

The aim of this study was to assess the acoustic environment of a preterm baby in an incubator on a newborn intensive care unit (NICU).

METHODS

An empty but running incubator (Giraffe Omnibed, GE Healthcare) was used to evaluate the incubator frequency response with 60 measurements. In addition, a full day and night period outside and inside the incubator at the NICU of the University Hospital Zurich was acoustically analyzed.

RESULTS

The fan construction inside the incubator generates noise in the frequency range of 1.3-1.5 kHz with a weighted sound pressure level (SPL) of 40.5 dB(A). The construction of the incubator narrows the transmitted frequency spectrum of sound entering the incubator to lower frequencies, but it does not attenuate transient noises such as alarms or opening and closing of cabinet doors substantially. Alarms, as generated by the monitors, the incubator, and additional devices, still pass to the newborn.

CONCLUSIONS

The incubator does protect only insufficiently from noise coming from the NICUThe transmitted frequency spectrum is changed, limiting the impact of NICU noise on the neonate, but also limiting the neonate's perception of voices. The incubator, in particular its fan, as well as alarms from patient monitors are major sources of noise. Further optimizations with regard to the sound exposure in the NICU, as well as studies on the role of the incubator as a source and modulator, are needed to meet the preterm infants' multi-sensory needs.

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.

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.

Viability and validity of the bispectral index to measure sleep in patients in the intensive care unit

Objective

To investigate the viability of the bispectral index in the sleep evaluation of critically ill patients and to quantify the associations of sleep parameters measured by this index with the Richards-Campbell Sleep Questionnaire and environmental noise.

Methods

This was a cross-sectional observational study that evaluated critically ill adults with diseases of low or moderate severity. The following were measured: total sleep volume and time, deep sleep volume and time, continuous sleep volume and time, sleep onset latency, and environmental sound pressure level. The subjective perception of sleep was evaluated with the Richards-Campbell Sleep Questionnaire the morning after each night of observation.

Results

Patients had a low total sleep time (234 minutes), a predominance of superficial sleep stages, and little deep sleep (1.7 minutes). The total, deep, and continuous sleep volumes were 3,679, 9.4, and 3,143 (bispectral index units × minutes), respectively. The sleep latency was 94 minutes. The mean score of the Richards-Campbell Sleep Questionnaire was 57.9. Total sleep volume, total sleep time, and continuous sleep volume were weakly correlated with the Richards-Campbell Sleep Questionnaire depth of sleep domain score, overall sleep quality domain score, and total score. Total volume, total time, and continuous volume were moderately correlated with the occurrence of awakenings domain score.

Conclusion

The bispectral index is an instrument with limited viability to monitor the sleep of lucid patients and patients with low to moderate disease severity in the intensive care unit. Patients with higher total sleep volume, total sleep time, and continuous sleep volume had better overall sleep perception.

Circadian Hygiene in the ICU Environment (CHIE) study

Objective: To investigate the environment and care in the intensive care unit (ICU) and its relationship to patient circadian temperature disruption. Design: 30-day, prospective period prevalence study. Setting: 27-bed tertiary ICU. Participants: Patients expected to remain in the ICU for at least 24 hours. Main outcome measures: Temperature, relative humidity, light and sound intensity in the ICU; nursing interventions (using the Therapeutic Intervention Scoring System-28); and core body temperature of ICU patients. Results: Of 28 patients surveyed, 20 (71%) were mechanically ventilated. Median (interquartile range [IQR]) light intensity peaked at 07:00 at 165 (12-1218) lux with a trough at 23:00 of 15 (12-51) lux and was consistently < 100 lux between 21:00 and 06:00. Peak median (IQR) sound intensity was at 07:00 (62.55 [57.87-68.03] dB) while 58.84 (54.81-64.71) dB at 02:00. Ambient temperature and humidity varied with median (IQR) peaks of 23.11°C (22.74-23.31°C) at 16:00 and 44.07% (32.76-51.08%) at 11:00 and median troughs of 22.37°C (21.79-22.88°C) at 05:00 and 39.95% (31.53-47.95%) at 14:00, respectively. Disturbances to sleep during the night occurred due to care activities including linen changes (15 patients, 54%) and bathing (13, 46%). On the day before and the day of the study, 13 patients (47%) and 10 patients (36%), respectively, had a circadian rhythm on core body temperature without an association with illness severity, nursing intervention or environmental measures. Conclusions: The ICU has low light intensity with relative humidity and ambient temperature not aligned to normal human circadian timing. Noise levels are commonly equivalent to conversational speech while patient care procedures interrupt overnight sleep. The contribution of these factors to disrupted CBT rhythmicity is unclear.

Ventilator Alarms in Intensive Care Units: Frequency, Duration, Priority, and Relationship to Ventilator Parameters

Ventilator alarms have long been presumed to contribute substantially to the overall alarm burden in the intensive care unit. In a prospective observational study, we determined that each ventilator triggered an alarm cascade of up to 8 separate notifications once every 6 minutes. In 1 intensive care unit with different ventilator manufacturers, the distribution of high-priority alarms was manufacturer dependent with 8.6% of alarms from 1 type and 89.8% of alarms from another type of ventilator. Alarm limits were not a function of patient-specific ventilator settings.

Metabolomics Pilot Study Identifies Desynchronization of 24-H Rhythms and Distinct Intra-patient Variability Patterns in Critical Illness: A Preliminary Report

Background: Synchronized circadian rhythms play a key role in coordinating physiologic health. Desynchronized circadian rhythms may predispose individuals to disease or be indicative of underlying disease. Intensive care unit (ICU) patients likely experience desynchronized circadian rhythms due to disruptive environmental conditions in the ICU and underlying pathophysiology. This observational pilot study was undertaken to determine if 24-h rhythms are altered in ICU patients relative to healthy controls by profiling 24-h rhythms in vital signs and plasma metabolites.

Methods: We monitored daily rhythms in 5 healthy controls and 5 ICU patients for 24 h. Heart rate and blood pressure were measured every 30 min, temperature was measured every hour, and blood was sampled for mass spectrometry-based plasma metabolomics every 4 h. Bedside sound levels were measured every minute. Twenty-four hours rhythms were evaluated in vitals and putatively identified plasma metabolites individually and in each group using the cosinor method.

Results: ICU patient rooms were significantly louder than healthy controls' rooms and average noise levels were above EPA recommendations. Healthy controls generally had significant 24-h rhythms individually and as a group. While a few ICU patients had significant 24-h rhythms in isolated variables, no significant rhythms were identified in ICU patients as a group, except in cortisol. This indicates a lack of coherence in phases and amplitudes among ICU patients. Finally, principal component analysis of metabolic profiles showed surprising patterns in plasma sample clustering. Each ICU patient's samples were clearly discernable in individual clusters, separate from a single cluster of healthy controls.

Conclusions: In this pilot study, ICU patients' 24-h rhythms show significant desynchronization compared to healthy controls. Clustering of plasma metabolic profiles suggests that metabolomics could be used to track individual patients' clinical courses longitudinally. Our results show global disordering of metabolism and the circadian system in ICU patients which should be characterized further in order to determine implications for patient care.

Effectiveness of a visual noise warning system on noise levels in a surgical ICU: A quality improvement programme

BACKGROUND

The effects of noise are harmful to patients in the ICU environment, and the latter are particularly noisy places. High noise levels seem to be a factor in sleep disturbance, which can, in turn, result in increased morbidity.

LOCAL PROBLEM

High noise levels are a recognised problem in ICUs worldwide.

OBJECTIVE(S)

The goal was to estimate the effect of a visual noise-warning system on noise levels in a surgical ICU before and after its implementation.

DESIGN

A quality improvement initiative.

SETTING

A 12-bedded surgical ICU in a tertiary care university hospital.

PATIENTS

A total of 148 adult nonintubated and nonsedated patients completed the study, during a 6-week period.

INTERVENTION

Noise levels were continuously recorded using a Type II sound level meter for 6 weeks. The study was divided into three phases. The first 2 weeks, baseline noise levels were measured (phase I). In week 3 of the study, a visual noise warning system (SoundEar II) that changed colour depending on noise levels within the ICU was installed and implemented (phase II). The alarm system was set to light up green at levels below 55 dBA, orange at levels between 55 and 60 dBA and red at levels above 60 dBA. The device was switched off at the beginning of week 5 and the sound level meter continued recording noise levels for another 2 weeks (phase III).

RESULTS

Mean night-time noise level was 55.98 dBA in the preintervention phase, 54.14 dB during the intervention, and 54.98 dBA in the postintervention phase. Mean noise level was reduced statistically significantly by 1.35 dBA, and there was a sustained reduction of 0.86 dBA from the baseline noise level 2 weeks after SoundEar II was switched off.

CONCLUSION

Visual noise warning systems can be effective in achieving a reduction in noise levels in critical care units.

The effects of noise levels on pain, anxiety, and sleep in patients

BACKGROUND

Intensive care is a noisy environment for patients and one that affects pain, anxiety levels, and sleep quality.

AIMS AND OBJECTIVES

To determine the relationship between noise levels and pain, anxiety, and sleep levels in patients in intensive care units.

DESIGN

A descriptive and observational study design was used.

METHODS

This study was conducted between June and December 2018 in a public hospital and included 111 patients admitted to surgical critical care for at least 24 hours. Three Benetech Gm1351 manual sound level metres were used to measure noise. A Patient Information Form, a pain Visual Analog Scale (VAS), the Spielberger State-Trait Anxiety Inventory, and the Richards Campbell Sleep Questionnaire (RCSQ) were used for data collection.

RESULTS

The mean age of the patients was 57.29 years. The mean noise level detected in the intensive care unit was 66.52 dB (dB). Patients' mean pain VAS score was 3.79 ± 1.72, the mean State Anxiety Inventory score was 39.74 ± 2.98, and the mean total RCSQ score was 25.10 ± 13.17. Our findings show that patients in the intensive care unit are exposed to high noise levels and that, while this has no effect on pain, it significantly impacts anxiety and quality of sleep.

CONCLUSIONS

Noise levels in intensive care units significantly exceed recommended thresholds, and this adversely affects patients' anxiety levels and sleep quality. It is important for suitably restful conditions to be provided for patients, to be aware of the potential for anxiety, and for these factors to be borne in mind when planning nursing interventions.

RELEVANCE TO CLINICAL PRACTICE

Further studies on the effects of noise levels on pain, anxiety, and sleep levels in patients admitted to intensive care units are needed.

Internal clock and the surgical ICU patient

PURPOSE OF REVIEW

The alteration of circadian rhythms in the postoperative period has been demonstrated to influence the outcomes. With this narrative review we would revise how anesthesia, surgery and intensive care can interfere with the circadian clock, how this could impact on the postsurgical period and how to limit the disruption of the internal clock.

RECENT FINDINGS

Anesthesia affects the clock in relation to the day-time administration and the type of anesthetics, N-methyl-D-aspartate receptor antagonists or gamma-aminobutyric acid receptors agonists. Surgery causes stress and trauma with consequent alteration in the circadian release of cortisol, cytokines and melatonin. ICU represents a further challenge for the patient internal clock because of sedation, immobility, mechanical ventilation and alarms noise.

SUMMARY

The synergic effect of anesthesia, surgery and postoperative intensive care on circadian rhythms require a careful approach to the patient considering a role for therapies and interventions aimed to re-establish the normal circadian rhythms. Over time, approach like the Awakening and Breathing Coordination, Delirium Monitoring and Management, Early Mobility and Family engagement and empowerment bundle can implement the clinical practice.

Music Therapy as a Potential Intervention for Sleep Improvement

Sleep deficiency is linked to chronic health problems, such as heart disease, kidney disease, high blood pressure, diabetes, stroke, obesity, and depression. Healthcare practitioners are increasingly paying close attention to sleep and its impact on health and wellness as a measure of critical vitality. Sleep's impact on neurologic function, and cognitive endurance affect capacity throughout the lifespan. This article will address recent findings related to the potential of music to induce sleep in illness and wellness. Music therapy research findings and its efficacy as a potent cost-effective intervention will be highlighted.

Estimation of respiratory rate using infrared video in an inpatient population: an observational study

Respiratory rate (RR) is one of the most sensitive markers of a deteriorating patient. Despite this, there is significant inter-observer discrepancy when measured by clinical staff, and modalities used in clinical practice such as ECG bioimpedance are prone to error. This study utilized infrared thermography (IRT) to measure RR in a critically ill population in the Intensive Care Unit. This study was carried out in a Single Hospital Centre. Respiratory rate in 27 extubated ICU patients was counted by two observers and compared to ECG Bioimpedance and IRT-derived RR at distances of 0.4-0.6 m and > 1 m respectively. IRT-derived RR using two separate computer vision algorithms outperformed ECG derived RR at distances of 0.4-0.6 m. Using an Autocorrelation estimator, mean bias was - 0.667 breaths/min. Using a Fast Fourier Transform estimator, mean bias was - 1.000 breaths/min. At distances greater than 1 m no statistically significant signal could be obtained. Over all frequencies, there was a significant relationship between the RR estimated using IRT and via manual counting, with Pearson correlation coefficients between 0.796 and 0.943 (p < 0.001). Correlation between counting and ECG-derived RR demonstrated significance only at > 19 bpm (r = 0.562, p = 0.029). Overall agreement between IRT-derived RR at distances of 0.4-0.6 m and gold standard counting was satisfactory, and outperformed ECG derived bioimpedance. Contactless IRT derived RR may be feasible as a routine monitoring modality in wards and subacute inpatient settings.

Environmental noise levels in hospital settings: A rapid review of measurement techniques and implementation in hospital settings

BACKGROUND

Hospitals provide treatment to improve patient health and well-being but the characteristics of the care environment receive little attention. Excessive noise at night has a negative impact on in-patient health through disturbed sleep. To address this hospital staff must measure night-time environmental noise levels. Therefore, an understanding of environmental noise measurement techniques is required. In this review, we aim to 1) provide a technical overview of factors to consider when measuring environmental noise in hospital settings; 2) conduct a rapid review on the equipment and approaches used to objectively measured noise in hospitals and identify methodological limitations.

DESIGN

: A rapid review of original research articles, from three databases, published since 2008. Studies were included if noise levels were objectively measured in a hospital setting where patients were receiving treatment.

RESULTS

1429 articles were identified with 76 included in the review. There was significant variability in the approaches used to measure environmental noise in hospitals. Only 14.5% of studies contained sufficient information to support replication of the measurement process. Most studies measured noise levels using a sound level meter positioned closed to a patient's bed area in an intensive care unit.

CONCLUSION

: Unwanted environmental noise in hospital setting impacts negatively on patient and staff health and well-being. However, this literature review found that the approaches used to objectively measure noise level in hospital settings have been inconsistent and poorly reported. Recommendations on best-practice methods to measure noise levels in hospital environments are provided.

Correlation between APACHE III score and sleep quality in ICU patients

Objective

To reveal the correlation between APACHE III score and sleep quality in patients in the intensive care unit (ICU).

Methods

This prospective, observational study included patients aged ≥18 years, who had been admitted to an integrated ICU for ≥48 h. Age, sex, Pittsburgh Sleep Quality Index (PSQI) prior to ICU, Numeric Rating Scales (NRS), noise, illumination, number of nursing interventions, Richards Campbell Sleep Questionnaire (RCSQ), and APACHE III score during sleep were evaluated.

Results

A total of 124 ICU patients were included, all with APACHE III scores < 60. APACHE III scores were not significantly associated with RCSQ scores. There were significant inverse associations between sleep quality in the ICU and PSQI score prior to ICU (odds ratio [OR] 0.587, 95% confidence interval [CI] 0.365, 0.945) and noise (OR 0.628, 95% CI 0.522, 0.756).

Conclusion

In ICU patients with APACHE III scores below 60 points, APACHE III score was not associated with sleep quality. PSQI score prior to ICU and noise were significantly inversely associated with sleep quality in this ICU patient population.

The effectiveness of noise interventions in the ICU

PURPOSE OF REVIEW

Excessive noise has direct adverse physiological and psychological effects, and may also have indirect negative health consequences by reducing sleep quality and quantity. This review presents a synthesis of the epidemiology of noise in the ICU, and the potential interventions designed to attenuate noise and protect patients.

RECENT FINDINGS

Noise increases cortisol release, oxygen consumption, and vasoconstriction. ICU noise levels are excessive throughout the 24-h cycle, irrespective of level of intervention or whether the patient is in a side room or open ward. Direct measurement suggests that noise is a substantial contributor to poor sleep quantity and quality in the ICU and is frequently recalled by survivors of critical illness as a negative experience of ICU admission. Noise abatement, environmental masking and pharmacological interventions may all reduce the impact of noise on patients. However, the sustainability of behavioural interventions remains uncertain and high-quality evidence demonstrating the benefit of any intervention on patient-centered outcomes is lacking.

SUMMARY

Noise levels in the ICU are consistently reported to reach levels likely to have both direct and indirect adverse health consequences for both patients and staff. Noise reduction, abating the transmission of noise and pharmacological modulation of the adverse neural effects of noise are all potentially beneficial strategies, although definitive evidence of improved patient-centered outcomes is lacking.

Impact of a Nurse Intervention to Improve Sleep Quality in Intensive Care Units: Results From a Randomized Controlled Trial

BACKGROUND

Patients of adult intensive care units (ICUs) often suffer from a lack of sleep. Reducing anxiety by promoting adaptation to the ICU prior to admission may be an appropriate way to increase sleep quality.

OBJECTIVE

The aim of this study was to evaluate the impact on sleep quality of a brief nurse intervention.

METHODS

This was a pilot randomized controlled trial in Spain. Forty patients admitted in hospital for valve cardiac surgery were randomly allocated to (1) control group (n = 20), receiving usual care, and to (2) experimental group (EG, n = 20), receiving a nurse intervention the day before surgery and admission in the ICU. The intervention was based on Roy Adaptation Model. A trained nurse anticipated the stressful stimulus to patients in order to develop functional adaptive behaviors. A set of photographs and videos was used to illustrate the environment and assistance in the ICU. Sleep quality in the ICU was measured with the Richards-Campbell Sleep Questionnaire and usual sleep quality with the Pittsburgh Sleep Quality Index.

RESULTS

After the intervention, sleep quality was lower in the EG compared with the control group (-4 points in Richards-Campbell Sleep Questionnaire, P = .69). Adjustment for main confounders led this reduction to -1.9 points (P = .87) among patients in EG. Stratified analyses shown a positive impact for people who usually slept well (+5.2 points, P = .77), but negative for those who had previous poor sleep quality (-20.0 points, P = .24).

CONCLUSION

A nurse intervention prior to ICU admission did not increase patients' sleep quality. In addition, the intervention could have incremented anxiety over the patients who used to sleep poorly at their homes.

Clinical chronobiology: a timely consideration in critical care medicine

A fundamental aspect of human physiology is its cyclical nature over a 24-h period, a feature conserved across most life on Earth. Organisms compartmentalise processes with respect to time in order to promote survival, in a manner that mirrors the rotation of the planet and accompanying diurnal cycles of light and darkness. The influence of circadian rhythms can no longer be overlooked in clinical settings; this review provides intensivists with an up-to-date understanding of the burgeoning field of chronobiology, and suggests ways to incorporate these concepts into daily practice to improve patient outcomes. We outline the function of molecular clocks in remote tissues, which adjust cellular and global physiological function according to the time of day, and the potential clinical advantages to keeping in time with them. We highlight the consequences of "chronopathology", when this harmony is lost, and the risk factors for this condition in critically ill patients. We introduce the concept of "chronofitness" as a new target in the treatment of critical illness: preserving the internal synchronisation of clocks in different tissues, as well as external synchronisation with the environment. We describe methods for monitoring circadian rhythms in a clinical setting, and how this technology may be used for identifying optimal time windows for interventions, or to alert the physician to a critical deterioration of circadian rhythmicity. We suggest a chronobiological approach to critical illness, involving multicomponent strategies to promote chronofitness (chronobundles), and further investment in the development of personalised, time-based treatment for critically ill patients.

Systematic review of the effects of intensive-care-unit noise on sleep of healthy subjects and the critically ill

Intensive-care-unit (ICU) patients exhibit disturbed sleeping patterns, often attributed to environmental noise, although the relative contribution of noise compared to other potentially disrupting factors is often debated. We therefore systematically reviewed studies of the effects of ICU noise on the quality of sleep to determine to what extent noise explains the observed sleep disruption, using the Cochrane Collaboration method for non-randomized studies. Searches in Scopus, PubMed, Embase, CINAHL, Web of Science, and the Cochrane Library were conducted until May 2017. Twenty papers from 18 studies assessing sleep of adult patients and healthy volunteers in the ICU environment, whilst recording sound levels, were included and independently reviewed by two reviewers. We found that the numbers of arousals between the baseline and the ICU noise condition in healthy subjects differed significantly (mean difference 9.59; 95% confidence interval 2.48-16.70). However, there was considerable heterogeneity between studies (I² 94%, P < 0.00001), and all studies suffered from a considerable risk of bias. The meta-analysis of results was hampered by widely varying definitions of sound parameters between studies and a general lack of detailed description of methods used. It is, therefore, currently impossible to quantify the extent to which noise contributes to sleep disruption among ICU patients, and thus, the potential benefit from noise reduction remains unclear. Regardless, the majority of the observed sleep disturbances remain unexplained. Future studies should, therefore, also focus on more intrinsic sleep-disrupting factors in the ICU environment.

Quality Improvement Initiative to Reduce Pediatric Intensive Care Unit Noise Pollution With the Use of a Pediatric Delirium Bundle

OBJECTIVES:

Noise pollution in pediatric intensive care units (PICU) contributes to poor sleep and may increase risk of developing delirium. The Environmental Protection Agency (EPA) recommends <45 decibels (dB) in hospital environments. The objectives are to assess the degree of PICU noise pollution, to develop a delirium bundle targeted at reducing noise, and to assess the effect of the bundle on nocturnal noise pollution.

METHODS:

This is a QI initiative at an academic PICU. Thirty-five sound sensors were installed in patient bed spaces, hallways, and common areas. The pediatric delirium bundle was implemented in 8 pilot patients (40 patient ICU days) while 108 non-pilot patients received usual care over a 28-day period.

RESULTS:

A total of 20,609 hourly dB readings were collected. Hourly minimum, average, and maximum dB of all occupied bed spaces demonstrated medians [interquartile range] of 48.0 [39.0-53.0], 52.8 [48.1-56.2] and 67.0 [63.5-70.5] dB, respectively. Bed spaces were louder during the day (10AM to 4PM) than at night (11PM to 5AM) (53.5 [49.0-56.8] vs. 51.3 [46.0-55.3] dB, P < 0.01). Pilot patient rooms were significantly quieter than non-pilot patient rooms at night (n=210, 45.3 [39.7-55.9]) vs. n=1841, 51.2 [46.9-54.8] dB, P < 0.01). The pilot rooms compliant with the bundle had the lowest hourly nighttime average dB (44.1 [38.5-55.5]).

CONCLUSIONS:

Substantial noise pollution exists in our PICU, and utilizing the pediatric delirium bundle led to a significant noise reduction that can be perceived as half the loudness with hourly nighttime average dB meeting the EPA standards when compliant with the bundle.

The nocturnal acoustical intensity of the intensive care environment: an observational study

BACKGROUND

The intensive care unit (ICU) environment exposes patients to noise levels that may result in substantial sleep disruption. There is a need to accurately describe the intensity pattern and source of noise in the ICU in order to develop effective sound abatement strategies. The objectives of this study were to determine nocturnal noise levels and their variability and the related sources of noise within an Australian tertiary ICU.

METHODS

An observational cross-sectional study was conducted in a 24-bed open-plan ICU. Sound levels were recorded overnight during three nights at 5-s epochs using Extech (SDL 600) sound monitors. Noise sources were concurrently logged by two research assistants.

RESULTS

The mean recorded ambient noise level in the ICU was 52.85 decibels (dB) (standard deviation (SD) 5.89), with a maximum noise recording at 98.3 dB (A). All recorded measurements exceeded the WHO recommendations. Noise variability per minute ranged from 9.9 to 44 dB (A), with peak noise levels >70 dB (A) occurring 10 times/hour (SD 11.4). Staff were identified as the most common source accounting for 35% of all noise. Mean noise levels in single-patient rooms compared with open-bed areas were 53.5 vs 53 dB (p = 0.37), respectively.

CONCLUSION

Mean noise levels exceeded those recommended by the WHO resulting in an acoustical intensity of 193 times greater than the recommended and demonstrated a high degree of unpredictable variability, with the primary noise sources coming from staff conversations. The lack of protective effects of single rooms and the contributing effects that staffs have on noise levels are important factors when considering sound abatement strategies.

Sleep quality and circadian rhythm disruption in the intensive care unit: a review

Sleep and circadian rhythm are reported to be severely abnormal in critically ill patients. Disturbed sleep can lead to the development of delirium and, as a result, can be associated with prolonged stay in the intensive care unit (ICU) and increased mortality. The standard criterion method of sleep assessment, polysomnography (PSG), is complicated in critically ill patients due to the practical challenges and interpretation difficulties. Several PSG sleep studies in the ICU reported the absence of normal sleep characteristics in many critically ill patients, making the standard method of sleep scoring insufficient in this patient group. Watson et al proposed a modified classification for sleep scoring in critically ill patients. This classification has not yet been validated. Sleep disturbance in the ICU is a multifactorial problem. The ICU environment, mechanical ventilation, medication, as well as the critical illness itself have been reported as important sleep disturbing factors. Secretion of sleep hormone, melatonin, expressing circadian rhythmicity was found abolished or phase delayed in critically ill patients. Various interventions have been tested in several studies aiming to improve sleep quality and circadian rhythm in the ICU. The results of these studies were inconclusive due to using the sleep assessment methods other than PSG or the absence of a reliable sleep scoring tool for the analysis of the PSG findings in this patient population. Development of a valid sleep scoring classification is essential for further sleep research in critically ill patients.