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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: a scoping review

BACKGROUND

Discomfort and distressing symptoms are common at the end of life, while people in this stage are often no longer able to express themselves. Technologies may aid clinicians in detecting and treating these symptoms to improve end-of-life care. This review provides an overview of noninvasive monitoring technologies that may be applied to persons with limited communication at the end of life to identify discomfort.

METHODS

A systematic search was performed in nine databases, and experts were consulted. Manuscripts were included if they were written in English, Dutch, German, French, Japanese or Chinese, if the monitoring technology measured discomfort or distressing symptoms, was noninvasive, could be continuously administered for 4 hours and was potentially applicable for bed-ridden people. The screening was performed by two researchers independently. Information about the technology, its clinimetrics (validity, reliability, sensitivity, specificity, responsiveness), acceptability, and feasibility were extracted.

RESULTS

Of the 3,414 identified manuscripts, 229 met the eligibility criteria. A variety of monitoring technologies were identified, including actigraphy, brain activity monitoring, electrocardiography, electrodermal activity monitoring, surface electromyography, incontinence sensors, multimodal systems, and noncontact monitoring systems. The main indicators of discomfort monitored by these technologies were sleep, level of consciousness, risk of pressure ulcers, urinary incontinence, agitation, and pain. For the end-of-life phase, brain activity monitors could be helpful and acceptable to monitor the level of consciousness during palliative sedation. However, no manuscripts have reported on the clinimetrics, feasibility, and acceptability of the other technologies for the end-of-life phase.

CONCLUSIONS

Noninvasive monitoring technologies are available to measure common symptoms at the end of life. Future research should evaluate the quality of evidence provided by existing studies and investigate the feasibility, acceptability, and usefulness of these technologies in the end-of-life setting. Guidelines for studies on healthcare technologies should be better implemented and further developed.

Intensive care unit interventions to promote sleep and circadian biology in reducing incident delirium: a scoping review

RATIONALE/OBJECTIVES

Despite plausible pathophysiological mechanisms, research is needed to confirm the relationship between sleep, circadian rhythm and delirium in patients admitted to the intensive care unit (ICU). The objective of this review is to summarise existing studies promoting, in whole or in part, the normalisation of sleep and circadian biology and their impact on the incidence, prevalence, duration and/or severity of delirium in ICU.

METHODS

A sensitive search of electronic databases and conference proceedings was completed in March 2023. Inclusion criteria were English-language studies of any design that evaluated in-ICU non-pharmacological, pharmacological or mixed intervention strategies for promoting sleep or circadian biology and their association with delirium, as assessed at least daily. Data were extracted and independently verified.

RESULTS

Of 7886 citations, we included 50 articles. Commonly evaluated interventions include care bundles (n=20), regulation or administration of light therapy (n=5), eye masks and/or earplugs (n=5), one nursing care-focused intervention and pharmacological intervention (eg, melatonin and ramelteon; n=19). The association between these interventions and incident delirium or severity of delirium was mixed. As multiple interventions were incorporated in included studies of care bundles and given that there was variable reporting of compliance with individual elements, identifying which components might have an impact on delirium is challenging.

CONCLUSIONS

This scoping review summarises the existing literature as it relates to ICU sleep and circadian disruption (SCD) and delirium in ICU. Further studies are needed to better understand the role of ICU SCD promotion interventions in delirium mitigation.

Imputing missing sleep data from wearables with neural networks in real-world settings

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles. Based on this, we develop two approaches: the individual approach imputes missing data based on the data from only one participant, while the global approach imputes missing data based on the data across multiple participants. Our models are tested with shift and non-shift workers' data from three independent hospitals. Both approaches can accurately impute missing data up to 24 hours of long dataset (>50 days) even for shift workers with extremely irregular sleep-wake patterns (AUC > 0.86). On the other hand, for short dataset (~15 days), only the global model is accurate (AUC > 0.77). Our approach can be used to help clinicians monitor sleep-wake cycles of patients with sleep disorders outside of laboratory settings without relying on sleep diaries, ultimately improving sleep health outcomes.

Psychometric properties and structural validity of traditional Chinese version of the Richards-Campbell Sleep Questionnaire in intensive care unit patients without physical restraint

BACKGROUND

Sleep assessment in the intensive care unit (ICU) is difficult and often unreliable. The most commonly used questionnaire for assessing ICU sleep, the Richards-Campbell Sleep Scale (RCSQ), has not been tested for reliability and construct validity in the Mandarin-Taiwanese speaking population.

OBJECTIVE

The objective of this study was to test the construct validity and criterion validity of the traditional Chinese version of RCSQ (TC-RCSQ) in critically ill patients without physical restraint.

METHODS

We adopted a cross-sectional study design. Adults aged 20 years and above were recruited from a plastic surgery ICU of a medical center. The Cronbach's alpha was used to test internal consistency; the validity testing included content validity, criterion validity, and construct validity. Criterion validity was analysed by testing the association of TC-RCSQ with the Chinese version of Verran and Snyder-Halpern Sleep Questionnaire and sleep parameter of actigraphy using the Pearson correlation coefficient; construct validity was analysed using exploratory factor analysis.

RESULTS

A total of 100 patients were included with a mean age of 49.78 years. Internal consistency reliability suggested Cronbach's alpha of 0.93. Moderate to strong correlations of TC-RCSQ with Verran-Snyder-Halpern Sleep Questionnaire were identified (r = 0.36 to 0.80, P < 0.05). We found significant correlations of actigraphic sleep efficiency with difficulty of falling sleep, awakening times, sleep quality, and total score of the TC-RCSQ (r = 0.23, 0.23, 0.20, and 0.23, P < 0.05). One factor (named as overall sleep quality) was extracted by exploratory factor analysis with a total variance explained of 78.40 %, which had good construction validity.

CONCLUSIONS

The TC-RCSQ yields satisfactory reliability and validity in critically ill patients. Actigraphic sleep efficiency may be a single index for objectively sleep assessment of sleep quality in patients without physical restraint. Both the TC-RCSQ and actigraphy can aid nurses to evaluate the sleep quality in critically ill patients without physical restraint.

Sleep and mental health in recruit paramedics: a 6-month longitudinal study

STUDY OBJECTIVES

To explore potential relationships and longitudinal changes in sleep and mental health in recruit paramedics over the first 6 months of work, and whether sleep disturbances pre-emergency work predict future mental health outcomes.

METHODS

Participants (N = 101, 52% female, Mage = 26 years) completed questionnaires prior to (baseline), and after 6 months of emergency work to assess for symptoms of insomnia, obstructive sleep apnea, post-traumatic stress disorder (PTSD), depression, anxiety, and trauma exposure. At each timepoint, participants also completed a sleep diary and wore an actigraph for 14 days to assess sleep patterns. Correlations between baseline sleep and mental health were conducted and changes in these variables across timepoints were examined using linear mixed models. Hierarchical regressions assessed whether sleep at baseline predicted mental health at follow-up.

RESULTS

Insomnia and depression symptoms, and total sleep time increased while sleep onset latency decreased across the first 6 months of emergency work. Participants experienced an average of 1 potentially traumatic event during the 6-month period. Baseline insomnia predicted increased depression symptoms at the 6-month follow-up, while baseline wake after sleep onset predicted follow-up PTSD symptoms.

CONCLUSION

Results highlight an increase in insomnia and depression across the initial months of emergency work, while sleep disturbances before emergency work were identified as potential risk factors for the development of depression and PTSD among paramedics in their early career. Screening and early interventions targeting poor sleep at the beginning of emergency employment may assist in reducing the risk of future mental health outcomes in this high-risk occupation.

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.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

Anatomic pathology services study disease in hospitals on the basis of macroscopic and microscopic examination of organs and tissues. The focus of this research investigation was on improving clinical biopsy diagnosis times through simulation based on the Box-Muller algorithm to reduce the waiting time in the diagnosis of clinical biopsies. The data were provided by a hospital in San José (Costa Rica). They covered 5 years and showed waiting times for a pathological diagnosis that for some biopsies were close to 120 days. The correlation between the main causes identified and the cycle time in the biopsy diagnostic process was defined. A statistical analysis of the variables most representative of the process and of the waiting times was carried out. It followed the DMAIC structure (Define, Measure, Analyse, Improve, Control) for the continuous improvement of processes. Two of the activities of the process were identified as being the main bottlenecks. Their processing times had a normal distribution, for which reason a Box-Muller algorithm was used to generate the simulation model. The results showed that waiting times for a diagnosis can be reduced to 3 days, for a productive capacity of 8 000 biopsies per annum, optimizing the logistics performance of health care.

The accuracy of simple, feasible alternatives to polysomnography for assessing sleep in intensive care: An observational study

BACKGROUND

Sleep disturbance is common in intensive care patients. Understanding the accuracy of simple, feasible sleep measurement techniques is essential to informing their possible role in usual clinical care.

OBJECTIVE

The aim of the study was to investigate whether sleep monitoring techniques such as actigraphy (ACTG), behavioural assessments, and patient surveys are comparable with polysomnography (PSG) in accurately reporting sleep quantity and quality among conscious, intensive care patients.

METHODS

An observational study was conducted in 20 patients admitted to the intensive care unit (ICU) for a minimum duration of 24 h, who underwent concurrent sleep monitoring via PSG, ACTG, nursing-based observations, and self-reported assessment using the Richards-Campbell Sleep Questionnaire.

RESULTS

The reported total sleep time (TST) for the 20 participants measured by PSG was 328.2 min (±106 min) compared with ACTG (362.4 min [±62.1 min]; mean difference = 34.22 min [±129 min]). Bland-Altman analysis indicated that PSG and ACTG demonstrated clinical agreement and did not perform differently across a number of sleep variables including TST, awakening, sleep-onset latency, and sleep efficiency. Nursing observations overestimated sleep duration compared to PSG TST (mean difference = 9.95 ± 136.3 min, p > 0.05), and patient-reported TST was underestimated compared to PSG TST (mean difference = -51.81 ± 144.1 7, p > 0.05).

CONCLUSIONS

Amongst conscious patients treated in the ICU, sleep characteristics measured by ACTG were similar to those measured by PSG. ACTG may provide a clinically feasible and acceptable proxy approach to sleep monitoring in conscious ICU patients.