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

Role of EEG spindle-like activity in post cardiac arrest prognostication

AIM

EEG is considered in guidelines for poor outcome prognostication in comatose patients after cardiac arrest (CA), but elements related to favorable prognosis have also been increasingly described. While spindle EEG activity is known to herald good outcome in critically ill patients, its occurrence in CA has received limited attention, essentially in pediatric cohorts. We postulated that this feature is related to favorable outcome in adults.

METHODS

Retrospective assessment of comatose adults following CA in a prospective institutional registry (09.2021-09.2023). Spindle-like activity, noted prospectively on early (12-36 h) and late (36-72 h) routine EEGs, was tested using 2x2 tables and comparisons of proportions for the likelihood of favorable outcome (CPC 1-2 at 3 months), including combinations with existing benign EEG descriptions (Westhall: no malignant or highly malignant features; modified: also allowing background discontinuity, low voltage, inverse development). Spindles were correlated with peak serum neuron-specific enolase (NSE) at 24-48 h as a marker of neuronal damage.

RESULTS

Among 276 patients, spindle-like activity was observed in 66 (23.9 %) of them, more often in early EEGs. While, in isolation, this feature detected within 72 h showed high specificity for CPC 1-2 (82.2 %) and low sensitivity (36.8 %), its addition significantly enhanced sensitivity of modified benign EEG (from 90.5 % to 95.8 %; p < 0.001; specificity at 54.4 %). Patients with spindle-like activity had significantly lower NSE (median 25.7µg/l, interquartile range 16.1-24.4, vs. 39.4 µg/l, interquartile range 21.1-95.1; p < 0.001).

CONCLUSION

Spindle-like EEG activity may orient on prognostication of favorable outcome in adult post CA patients, and correlates with lower neuronal damage.

Multiscale neural dynamics in sleep transition volatility across age scales: a multimodal EEG-EMG-EOG analysis of temazepam effects

Recent advances in computational modeling techniques have facilitated a more nuanced understanding of sleep neural dynamics across the lifespan. In this study, we tensorize multiscale multimodal electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals and apply Generalized Autoregressive Conditional Heteroskedasticity (GARCH) modeling to quantify interactions between age scales and the use of pharmacological sleep aids on sleep stage transitions. Our cohort consists of 22 subjects in a crossover design study, where each subject received both a sleep aid and a placebo in different sessions. To understand these effects across the lifespan, three evenly distributed age groups were formed: 18-29, 30-49, and 50-66 years. The methodological framework implemented here employs tensor-based machine learning techniques to compute continuous wavelet transform time-frequency features and utilizes a GARCH model to quantify sleep signal volatility across age scales. Support Vector Machines are used for feature ranking, and our analysis captures interactions between signal entropy, age, and sleep aid status across frequency bands, sleep transitions, and sleep stages. GARCH model results reveal statistically significant volatility clustering in EEG, EMG, and EOG signals, particularly during transitions between REM and non-REM sleep. Notably, volatility was higher in the 50-66 age group compared to the 18-29 age group, with marked fluctuations during transitions from deep sleep to REM sleep (standard deviation of 0.35 in the older group vs. 0.30 in the 18-29 age group, p < 0.05). Statistical comparisons of volatility across frequency bands, age scales, and sleep stages highlight significant differences attributable to sleep aid use. Mean conditional volatility parameterization of the GARCH model reveals directional influences, with a causality index of 0.75 from frontal to occipital regions during REM sleep transition periods. Our methodological framework identifies distinct neural behavior patterns across age groups associated with each sleep stage and transition, offering insights into the development of targeted interventions for sleep regularity across the lifespan.

Cyclic Alternating EEG Patterns: From Sleep to Encephalopathy

SUMMARY

In the 2021 version of the Standardized Critical Care EEG Terminology, the American Clinical Neurophysiology Society introduced new definitions, including for the cyclic alternating pattern of encephalopathy (CAPE). CAPE refers to changes in background EEG activity, with two patterns alternating spontaneously in a regular manner. CAPE shares remarkable similarities with the cyclic alternating pattern, a natural EEG phenomenon occurring in normal non-rapid eye movement sleep, considered the main electrophysiological biomarker of sleep instability. This review explores similarities and differences between cyclic alternating pattern and CAPE and, leveraging the existing expertise on cyclic alternating pattern, aims to extend knowledge on CAPE. A standardized assessment of CAPE features is key to ascertain its prevalence and clinical significance among critically ill patients and to encompass the impact of confounding factors such as anesthetic and sedative agents. Although the preservation of non-rapid eye movement sleep-related elements has a well-known prognostic value in the critical care setting, the clinical importance of cyclic oscillating patterns and the prognostic significance of CAPE remain to be elucidated.

The efficacy of earplugs and eye masks for delirium severity and sleep quality in patients undergoing coronary artery bypass grafting in cardiac intensive care units: A single-blind, randomised controlled trial

BACKGROUND AND PURPOSE

Delirium is a neuropsychiatric syndrome with a wide range of possible causes and multiple complications in patients admitted to intensive care units. It is, therefore, necessary to seek appropriate and safe strategies to prevent and manage delirium. This study is intended to examine the efficacy of eye masks and earplugs for delirium severity and sleep quality in patients with coronary artery bypass grafting in a cardiac intensive care unit.

MATERIALS AND METHODS

This single-blind, randomised controlled trial was conducted on 114 patients who were consecutively enrolled and randomly assigned to either the experimental group or the control group. The experimental group received routine care plus eye masks and earplugs, and the control group received only routine care. The delirium severity and sleep quality were measured with the Neelon and Champagne confusion scale and the Verran and Snyder-Halpern sleep scale.

RESULTS

The mean delirium severity score differed significantly between the two groups on the second, third, and fourth postoperative days (p < 0.001). Although the trend of changes in the mean delirium severity score from the first postoperative day (before the intervention) to the second, third, and fourth postoperative days was downward in the two groups (trending towards higher delirium severity), the control group experienced greater changes than the experimental group. An intragroup analysis of delirium severity detected a statistically significant difference in both the experimental and control groups (p < 0.001). The sleep quality domains (sleep disturbance, sleep effectiveness, sleep supplementation) showed a statistically significant difference between the two groups across the three intervention days (p < 0.001).

CONCLUSION

The overnight use of eye masks and earplugs were found to have positive effects on sleep quality domains (sleep disturbance, sleep effectiveness, sleep supplementation) and delirium severity in coronary artery bypass grafting patients admitted to the cardiac intensive care unit for several days. It was also found that a significant interaction effect between the sleep disturbance subscale and delirium severity exists.

CLINICAL TRIAL REGISTRATION NUMBER

(https://en.irct.ir): IRCT20210523051370N2.

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.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Electroencephalogram in the intensive care unit: a focused look at acute brain injury

Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. With the widespread utilization of EEG (spot and continuous EEG), rhythmic and periodic patterns that do not fulfill strict seizure criteria have been identified, epidemiologically quantified, and linked to pathophysiological events across a wide spectrum of critical and acute illnesses, including acute brain injury. Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.

Effect Evaluation of Dexmedetomidine Intravenous Anesthesia on Postoperative Agitation in Patients with Craniocerebral Injury by Magnetic Resonance Imaging Based on Sparse Reconstruction Algorithm

The effect of dexmedetomidine on postoperative agitation of patients with craniocerebral injury was investigated based on magnetic resonance imaging (MRI) with the sparse reconstruction algorithm. Sixty patients with craniocerebral injury who underwent tracheal intubation and craniotomy hematoma removal under general anesthesia in hospital were selected as the research objects. Patients were randomly and averagely divided into the normal saline group (group A) and the dexmedetomidine (DEX) group (group B). DEX was added to patients in group A during anesthesia. Other operations in group B were the same as those in group A, where DEX needed to be used was replaced by an equal amount of the normal saline. All patients received the MRI examination, and the images were processed by using the sparse reconstruction algorithm. After the surgery, some indexes, such as hemodynamics (mean arterial pressure (MAP) and hear rate (HR)), the Riker sedation agitation score, the Ramsay sedation score, and the visual analogue scale (VAS) score were recorded and compared. The results showed that the MRI image quality processed by sparse reconstruction algorithm was observably improved. After reconstruction, the sharpness of the image was significantly improved, and the distinction between lesions and tissues was also increased. The Riker sedation agitation score and the incidence of agitation in group A were greatly lower than those in group B (16% VS 76%, P < 0.05). The Ramsay sedation score of group A was manifestly higher than that of group B. The cases of postoperative nausea, vomiting, chills, delirium, and bradycardia in group A were 2, 1, 1, 0, and 1, respectively. The cases of postoperative nausea, vomiting, chills, delirium, and bradycardia in group B were 3, 9, 6, 5, and 0, respectively. The cases of chills and delirium in group A were observably less than those in group B (P < 0.05). In conclusion, based on the sparse reconstruction algorithm, the MRI technology and DEX had high adoption value in preventing postoperative agitation of patients with craniocerebral injury. Compared with group B, the hemodynamics of patients in group A was more stable.