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

Evaluation of Sleep Quality in Clinical Practice

A major problem in clinical sleep medicine is that the most comprehensive and sophisticated investigative tool, the polysomnography, fails to provide a reason for the patient's complaints in all but those with sleep apnea and movement disorders. The reasons why conventional metrics of sleep quality are of limited value are discussed in detail. This is followed by description of several well-established features that have not been implemented in clinical practice because of the impracticality of doing the measurements visually. Automation is pending. Finally, several automated features recently derived from spectral analysis of the electroencephalogram were described.

Pharmacologic Sleep Aids in the Intensive Care Unit: A Systematic Review

Background: Patients in the intensive care unit (ICU) often experience poor sleep quality. Pharmacologic sleep aids are frequently used as primary or adjunctive therapy to improve sleep, although their benefits in the ICU remain uncertain. This review aims to provide a comprehensive assessment of the objective and subjective effects of medications used for sleep in the ICU, as well as their adverse effects. Methods: PubMed, Web of Science, Scopus, Embase, and Cochrane Central Register of Controlled Trials were systematically searched from their inception until June 2023 for comparative studies assessing the effects of pharmacologic sleep aids on objective and subjective metrics of sleep. Results: Thirty-four studies with 3498 participants were included. Medications evaluated were melatonin, ramelteon, suvorexant, propofol, and dexmedetomidine. The majority of studies were randomized controlled trials. Melatonin and dexmedetomidine were the best studied agents. Objective sleep metrics included polysomnography (PSG), electroencephalography (EEG), bispectral index, and actigraphy. Subjective outcome measures included patient questionnaires and nursing observations. Evidence for melatonin as a sleep aid in the ICU was mixed but largely not supportive for improving sleep. Evidence for ramelteon, suvorexant, and propofol was too limited to offer definitive recommendations. Both objective and subjective data supported dexmedetomidine as an effective sleep aid in the ICU, with PSG/EEG in 303 ICU patients demonstrating increased sleep duration and efficiency, decreased arousal index, decreased percentage of stage N1 sleep, and increased absolute and percentage of stage N2 sleep. Mild bradycardia and hypotension were reported as side effects of dexmedetomidine, whereas the other medications were reported to be safe. Several ongoing studies have not yet been published, mostly on melatonin and dexmedetomidine. Conclusions: While definitive conclusions cannot be made for most medications, dexmedetomidine improved sleep quantity and quality in the ICU. These benefits need to be balanced with possible hemodynamic side effects.

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.

New insights and potential clinical implications of the odds ratio product

The odds ratio product (ORP) is a continuous metric of sleep depth that ranges from 0 (very deep sleep) to 2. 5 (full wakefulness). Its advantage over the conventional method recommended by AASM is that it discloses different levels of stage wake (sleep propensity) and different sleep depths within the same sleep stage. As such, it can be used to identify differences in sleep depth between subjects, and in the same subjects under different circumstances, when differences are not discernible by conventional staging. It also identifies different sleep depths within stage rapid-eye-movement sleep, with possible implications to disorders during this stage. Epoch-by-epoch ORP can be displayed graphically across the night or as average values in conventional sleep stages. In addition, ORP can be reported as % of recording time in specific ORP ranges (e.g., deciles of the total ORP range) where it produces distinct distribution patterns (ORP-architecture) that have been associated with different clinical disorders and outcomes. These patterns offer unique research opportunities to identify different mechanisms and potential therapy for various sleep complaints and disorders. In this review I will discuss how ORP is measured, its validation, differences from delta power, and the various phenotypes, and their postulated mechanisms, identified by ORP architecture and the opportunities for research to advance management of sleep-disordered breathing, insomnia and idiopathic hypersomnia.

Effects of Propofol on Perioperative Sleep Quality in Patients Undergoing Gastrointestinal Endoscopy: A Prospective Cohort Study

PURPOSE

Some patients experience sleep disturbances after endoscopy performed under sedation. This study aimed to evaluate the effects of propofol on sleep quality after gastrointestinal endoscopy (GE).

DESIGN

This study was a prospective cohort study.

METHODS

This study enrolled 880 patients who underwent GE. Patients who chose to undergo GE under sedation received intravenous propofol, whereas the control group did not. The Pittsburgh Sleep Quality Index (PSQI) was measured before GE (PSQI-1) and 3 weeks (PSQI-2) after GE. The Groningen Sleep Score Scale (GSQS) was used before GE (GSQS-1) and 1 (GSQS-2) and 7 days (GSQS-3) after GE.

FINDINGS

There was a significant increase in GSQS scores from baseline to days 1 and 7 after GE (GSQS-2 vs GSQS-1, P < .001, GSQS-3 vs GSQS-1, P = .008). However, no significant changes were observed in the control group (GSQS-2 vs GSQS-1, P = .38, GSQS-3 vs GSQS-1, P = .66). On day 21, there were no significant changes in the baseline PSQI scores over time in either group (sedation group, P = .96; control group, P = .95).

CONCLUSIONS

GE with propofol sedation negatively affected sleep quality for 7 days after GE but not 3 weeks after GE.

Effects of propofol and sevoflurane on social and anxiety-related behaviours in sleep-deprived rats

BACKGROUND

Sleep disorders can profoundly affect neurological function. We investigated changes in social and anxiety-related brain functional connectivity induced by sleep deprivation, and the potential therapeutic effects of the general anaesthetics propofol and sevoflurane in rats.

METHODS

Twelve-week-old male Sprague-Dawley rats were subjected to sleep deprivation for 20 h per day (from 14:00 to 10:00 the next day) for 4 consecutive weeks. They were free from sleep deprivation for the remaining 4 h during which they received propofol (40 mg kg-1 i.p.) or sevoflurane (2% for 2 h) per day or no treatment. These cohorts were instrumented for EEG/EMG recordings on days 2, 14, and 28. Different cohorts were used for open field and three-chambered social behavioural tests, functional MRI, nuclear magnetic resonance spectroscopy, and positron emission tomography imaging 48 h after 4 weeks of sleep deprivation.

RESULTS

Propofol protected against sleep deprivation-induced anxiety behaviours with more time (44.7 [8.9] s vs 24.2 [4.1] s for the sleep-deprivation controls; P<0.001) spent in the central area of the open field test and improved social preference index by 30% (all P<0.01). Compared with the sleep-deprived rats, propofol treatment enhanced overall functional connectivity by 74% (P<0.05) and overall glucose metabolism by 30% (P<0.01), and improved glutamate kinetics by 20% (P<0.05). In contrast, these effects were not found after sevoflurane treatment.

CONCLUSIONS

Unlike sevoflurane, propofol reduced sleep deprivation-induced social and anxiety-related behaviours. Propofol might be superior to sevoflurane for patients with sleep disorders who receive anaesthesia, which should be studied in clinical studies.

Sleep Assessment in Critically Ill Adults: Established Methods and Emerging Strategies

Sleep is a biological mandate with an integral role in optimizing functions that maintain psychological and physical health. During critical illness, however, sleep may be disrupted at best and elusive at worst. Sleep improvement efforts and research endeavors evaluating interventions to improve sleep in critically ill adults are hampered by limited methods available to measure sleep in this setting. This narrative review summarizes available modalities for sleep assessment in the ICU, describes new ICU sleep assessment methods under development, and highlights features of the ideal ICU sleep measurement tool.

DATA SOURCES

The most relevant literature and author experiences were assessed for inclusion from PubMed and textbooks.

STUDY SELECTION

The authors selected studies for inclusion by consensus.

DATA EXTRACTION

The authors reviewed each study and selected appropriate data for inclusion by consensus.

DATA SYNTHESIS

Currently available tools to measure sleep in critically ill adults have important flaws. Subjective measurements are limited by recall bias, the inability of many patients to communicate, and poorly correlate with objective measures when completed by surrogates. Actigraphy does not consider the effects of sedating medications or myopathy leading to an over estimation of sleep time. Polysomnography, the gold standard for sleep assessment, is limited by interpretation issues and practical application concerns. Single and multiple channel electroencephalogram devices offer real-time physiologic data and are more practical to use than polysomnography but are limited by the scope of sleep-specific information they can measure and poorly characterize the circadian system.

CONCLUSIONS

A measurement tool that offers real-time sleep and circadian assessment and is practical for broad application in the ICU does not exist. Newer sleep assessment devices have shown promise in measuring physiologic data in real time; when used in combination with other assessment modalities, and analyzed by computational techniques, they may revolutionize sleep monitoring in the ICU.