Factors affecting sleep quality in Intensive Care Units

Functional independence, frailty and perceived quality of life in patients who developed delirium during ICU stay: a prospective cohort study

BACKGROUND

Survivors of critical illness are frequently left with a long-lasting disability. We hypothesised that patients who developed delirium during ICU stay, compared with patients who did not, would have worse health-related quality of life following a critical illness.

METHODS

Prospective longitudinal observational and analytical study assessing functional independence, frailty and perceived quality of life measured with the Barthel Index, the Clinical Frailty Scale, and the SF-36, comparing patients who developed delirium during ICU stay and patients who did not. The questionnaires were used at different times during the follow-up (upon ICU admission, at ICU discharge, at hospital discharge and 2 years after hospital discharge).

RESULTS

In a cohort of 1462 patients, we matched 93 patients who developed delirium (delirium group) with 93 patients who did not develop delirium (no-delirium group). Of 156 completed questionnaires (84.7%), we observed that (a) in each of the two groups of patients, the scores related to functional independence (Barthel Index) and frailty (Clinical Frailty Scale) tended to improve over time (p < 0.001), being consistently less favourable in the delirium group compared to the no-delirium group (p < 0.001); (b) the patients who developed delirium also presented lower scores on the SF-36 scale, these differences being statistically significant, and therefore evidencing a worse quality of life, with impact on both the psychological and social spheres (p < 0.001).

CONCLUSIONS

Patients who developed delirium had significantly lower scores 2 years after hospital discharge on the three used questionnaires, displaying a clear negative impact on the physical, psychological, and social dimensions. The study's results reinforce the need to support and strengthen the care of ICU survivors.

Ambient intelligence-based monitoring of staff and patient activity in the intensive care unit

BACKGROUND

Caregiver workload in the ICU setting is difficult to numerically quantify. Ambient Intelligence utilises computer vision-guided neural networks to continuously monitor multiple datapoints in video feeds, has become increasingly efficient at automatically tracking various aspects of human movement.

OBJECTIVES

To assess the feasibility of using Ambient Intelligence to track and quantify allpatient and caregiver activity within a bedspace over the course of an ICU admission and also to establish patient specific factors, and environmental factors such as time ofday, that might contribute to an increased workload in ICU workers.

METHODS

5000 images were manually annotated and then used to train You Only LookOnce (YOLOv4), an open-source computer vision algorithm. Comparison of patientmotion and caregiver activity was then performed between these patients.

RESULTS

The algorithm was deployed on 14 patients comprising 1762800 framesof new, untrained data. There was a strong correlation between the number ofcaregivers in the room and the standardized movement of the patient (p < 0.0001) withmore caregivers associated with more movement. There was a significant difference incaregiver activity throughout the day (p < 0.05), HDU vs. ICU status (p < 0.05), delirious vs. non delirious patients (p < 0.05), and intubated vs. not intubated patients(p < 0.05). Caregiver activity was lowest between 0400 and 0800 (average .71 ± .026caregivers per hour) with statistically significant differences in activity compared to 0800-2400 (p < 0.05). Caregiver activity was highest between 1200 and 1600 (1.02 ± .031 caregivers per hour) with a statistically significant difference in activity comparedto activity from 1600 to 0800 (p < 0.05). The three most dominant predictors of workeractivity were patient motion (Standardized Dominance 78.6%), Mechanical Ventilation(Standardized Dominance 7.9%) and Delirium (Standardized Dominance 6.2%).

CONCLUSION

Ambient Intelligence could potentially be used to derive a single standardized metricthat could be applied to patients to illustrate their overall workload. This could be usedto predict workflow demands for better staff deployment, monitoring of caregiver workload, and potentially as a tool to predict burnout.

Evaluation of sleep quality and duration using wearable sensors in shift laborers of construction industry: A public health perspective

Approximately 21% of the workers in developing and developed countries are shift laborers. The laborer's work shifts can affect personal life and sleep standards, adversely impacting laborers and their manage. This study assesses the impact of various shift plans (seven evenings/7 days, fixed-night or fixed-day, and backup shifts) on shift laborers, considering four shift schedules. Most laborers were on rotational shifts, whereas others were on a permanent day, permanent night, and standby shifts. In a cross-sectional study, 45 development laborers from the National Construction firm were enlisted. Bio-wearable sensors were provided to monitor sleep. Participants were approached and asked to complete a survey bundle comprising the Pittsburgh sleep quality index (PSQI) and Epworth sleepiness scale (ESS). Differences in sleep models were estimated using a Fitbit watch at various shift schedules. The average age of laborers who participated in the study was 37.5 years, and their average experience in the construction company was 6.5 years. The average total sleep time was 346 ± 46 min. The rotational shift laborers yielded the minimum total sleep time compared to the average PSQI and ESS scores of 7.66 ± 1.3 and 6.94 ± 3.4, respectively. Fifteen shift laborers (33.33%) were affected by a sleeping disorder in the present experimental investigation, and 30 participants had inadequate standards of sleep based on the PSQI scores. Poor sleep quality and duration among construction shift laborers decrease productivity at work. Additional studies are expected to assess sleep-related issues affecting construction shift laborers.

Effects of nursing interventions to improve inpatients' sleep in intensive and non-intensive care units: Findings from an umbrella review

AIM

This review aimed to synthesise the available reviews on the effects of nursing interventions on sleep quality among patients hospitalised in intensive care and non-intensive care units.

BACKGROUND

Poor sleep quality is a common fact in hospitalised patients. Nurses can contribute to the improvement of patients' sleep quality and duration.

DESIGN

A review of intervention reviews was carried out and reported following the PRISMA guidelines and checklist.

METHODS

We systematically searched for reviews published from January 2009 to December 2019 in PubMed, CINAHL Plus, Scopus, Institute for Scientific Information Web of Science, Joanna Briggs Database of Systematic Reviews and Cochrane Central Register of Controlled Trials databases. Searches were repeated at 24 November 2020 to include the most recent evidence. A narrative synthesis of the results was conducted.

RESULTS

Nine reviews (representing 109 original papers) met the selection criteria and were included for critical appraisal. Overall, nursing interventions and sleep quality were poorly defined. We grouped the interventions into 3 categories (environmental, barrier and internal interventions) to provide a more comprehensive overview and examine effects of nursing interventions on inpatients sleep quality. Inconsistent results were obtained and low quality of the original articles was reported, making it difficult to establish absolute conclusions.

CONCLUSION

The impact of environmental changes on patients' sleep was positive but inconclusive, while use of earplugs and eye masks, music and acupuncture generally showed positive results with moderate quality of evidence, and no harmful effects were reported.