It is well recognized that sleep is severely disturbed in patients in intensive care units (ICU) and that this can compromise their rehabilitation potential. However, it is still difficult to objectively assess sleep quantity and quality and the determinants of sleep disturbance remain unclear. The aim of this study was therefore to evaluate carefully the impact of ICU sound intensity levels and their sources on ICU patients’ sleep over a 24-h period. Sleep and sound levels were recorded in 11 ICU intubated patients who met the criteria. Sleep was recorded using a miniaturized multi-channel ambulatory recording device. Sound intensity levels and their sources were recorded with the Nox-T3 monitor. A 30-s epoch-by-epoch analysis of sleep stages and sound data was carried out. Multinomial and binomial logistic regressions were used to associate sleep stages, wakefulness and sleep–wake transitions with sound levels and their sources. The subjects slept a median of 502.2 [283.2–718.9] min per 24 h; 356.9 [188.6–590.9] min at night (22.00–08.00) and 168.5 [142.5–243.3] during daytime (8 am–10 pm). Median sound intensity level reached 70.2 [65.1–80.3] dBC at night. Sound thresholds leading to disturbed sleep were 63 dBC during the day and 59 dBC during the night. With levels above 77 dBC, the incidence of arousals (OR 3.9, 95% CI 3.0–5.0) and sleep-to-wake transitions (OR 7.6, 95% CI 4.1–14) increased. The most disturbing noises sources were monitor alarms (OR 4.5, 95% CI 3.5–5.6) and ventilator alarms (OR 4.2, 95% CI 2.9–6.1). We have shown, in a small group of 11 non-severe ICU patients, that sound level intensity, a major disturbance factor of sleep continuity, should be strictly controlled on a 24-h profile.

Background Noise in the vicinity of airports is a public health problem. Many laboratory studies have shown that heart rate is altered during sleep after exposure to road or railway noise. Fewer studies have looked at the effects of exposure to aircraft noise on heart rate during sleep in populations living near airports. Objective The aim of this study was to investigate the relationship between the sound pressure level (SPL) of aircraft noise and heart rate during sleep in populations living near airports in France. Methods In total, 92 people living near the Paris-Charles de Gaulle and Toulouse-Blagnac airports participated in this study. Heart rate was recorded every 15 s during one night, using an Actiheart monitor, with simultaneous measurements of SPL of aircraft noise inside the participants’ bedrooms. Energy and event-related indicators were then estimated. Mixed linear regression models were applied, taking into account potential confounding factors, to investigate the relationship between energy indicators and heart rate during sleep measured every 15 s. Event-related analyses were also carried out in order to study the effects of an acoustic event associated with aircraft noise on heart rate during sleep. Results The more the SPL from all sources (L_Aeq,15s) and the SPL exceeded for 90% of the measurement period (L_A90,15s) increased, the more heart rate also increased. No significant associations were observed between the maximum 1-s equivalent SPL associated with aircraft overflight (L_Amax,1s) and differences between the heart rate recorded during or 15 or 30 s after an aircraft noise event and that recorded before the event. On the other hand, a positive and significant association was found between L_Amax,1s and the heart rate amplitude calculated during an aircraft noise event. Results were unchanged when analyses were limited to participants who had lived more than five years in their present dwelling. Conclusion Our study shows that exposure to the maximum SPL linked to aircraft overflight affect the heart rate during sleep of residents near airports. However, further studies on a larger number of participants over several nights are needed to confirm these results.

Optimizing the measurement of Continuous Positive Airway Pressure (CPAP) compliance and treatment efficacy is paramount for patients with obstructive sleep apnea syndrome (OSAS). Compliance knowledge is currently based on data coming from CPAP machines; however algorithms and measured parameters vary from one machine to another. This study was conducted to clinically evaluate a novel device, NOWAPI®, designed to assess compliance remotely in conjunction with any CPAP machine. NOWAPI® was tested against polygraphy, the gold standard for the measurement of CPAP treatment duration and residual apnea-hypopnea index (AHI). Single group assignment, open label, non-randomized. Sleep laboratory setting. 22 adult patients with OSAS treated by CPAP were included. Recordings were performed during one night while the patient was treated with his/her usual CPAP and interface. NOWAPI® data were collected electronically and compared to data acquisition and visual scoring using an EMBLETTA® GOLD polygraph. Statistics were only descriptive. Recordings were performed with six different CPAP machines and three different interfaces (full facemask, nasal pillow, nasal mask). The median [Q1; Q3] absolute difference in CPAP treatment duration between NOWAPI® and polygraphy was of 1.0 min [0.0; 12.0], corresponding to a relative difference of 0.21 % [0.0; 2.2] (Per Protocol data set, n = 20). NOWAPI® tended to underestimate residual AHI in a magnitude of two events per hour as compared to polygraphy. The device was well tolerated and the patient satisfaction was good. This clinical study confirmed prior bench tests, showing that NOWAPI® estimate of CPAP treatment duration was clinically acceptable and in agreement with polygraphy. Although a limited number of OSAS patients treated by CPAP were included, relevant findings for the device improvement were identified. Trial Registration ClinicalTrials.gov identifier: NCT01441622. The study was funded by Air Liquide HealthCare

Prospective memory (PM) is essential in everyday life because it concerns the ability to remember to perform an intended action in the future. This ability could be influenced by poor sleep quality, the role of which, however, is still being debated. To examine the role of sleep quality in PM in depth, we decided to perform a retrospective naturalistic study examining different clinical populations with a primary sleep disorder or comorbid low sleep quality. If sleep is important for PM function, we could expect poor sleep to affect PM performance tasks both directly and indirectly. We examined a total of 3600 nights, recorded using actigraphy in participants belonging to the following groups: primary insomnia (731 nights); narcolepsy type 1 (1069 nights); attention deficit hyperactivity disorder (152 nights in children and 239 in adults); severe obesity (232 nights); essential hypertension (226 nights); menopause (143 nights); healthy controls (808 nights). In a naturalistic activity-based PM task, each participant originally wore an actigraph around the non-dominant wrist and was requested to push the event-marker button at two specific times of day: bedtime (activity 1) and get-up time (activity 2). Each clinical group showed significantly lower sleep quality in comparison to the control group. However, only narcolepsy type 1 patients presented a significantly impaired PM performance at get-up time, remembering to push the event-marker button around half the time compared not only to healthy controls but also to the other clinical groups. Overall, the present results seem to point to sleep quality having no effect on the efficiency of a naturalistic activity-based PM task. Moreover, the data indicated that narcolepsy type 1 patients may show a disease-specific cognitive deficit of PM.

Since its first description in Wuhan, China, the novel Coronavirus (SARS-CoV-2) has spread rapidly around the world. The management of this major pandemic requires a close coordination between clinicians, scientists, and public health services in order to detect and promptly treat patients needing intensive care. The development of consumer wearable monitoring devices offers physicians new opportunities for the continuous monitoring of patients at home. This clinical case presents an original description of 55 days of SARS-CoV-2-induced physiological changes in a patient who routinely uses sleep-monitoring devices. We observed that sleep was specifically affected during COVID-19 (Total Sleep time, TST, and Wake after sleep onset, WASO), within a seemingly bidirectional manner. Sleep status prior to infection (e.g., chronic sleep deprivation or sleep disorders) may affect disease progression, and sleep could be considered as a biomarker of interest for monitoring COVID-19 progression. The use of habitual data represents an opportunity to evaluate pathologic states and improve clinical care.