A personalized semi-automatic sleep spindle detection (PSASD) framework.

BACKGROUND: Sleep spindles are distinct electroencephalogram (EEG) patterns of brain activity that have been posited to play a critical role in development, learning, and neurological disorders. Manual scoring for sleep spindles is labor-intensive and tedious but could supplement automated algorithms to resolve challenges posed with either approaches alone. NEW METHODS: A Personalized Semi-Automatic Sleep Spindle Detection (PSASD) framework was developed to combine the strength of automated detection algorithms and visual expertise of human scorers. The underlying model in the PSASD framework assumes a generative model for EEG sleep spindles as oscillatory components, optimized to EEG amplitude, with remaining signals distributed into transient and low-frequency components. RESULTS: A single graphical user interface (GUI) allows both manual scoring of sleep spindles (model training data) and verification of automatically detected spindles. A grid search approach allows optimization of parameters to balance tradeoffs between precision and recall measures. COMPARISON WITH EXISTING METHODS: PSASD outperformed DETOKS in F1-score by 19% and 4% on the DREAMS and P-DROWS-E datasets, respectively. It also outperformed YASA in F1-score by 25% in the P-DROWS-E dataset. Further benchmarking analysis showed that PSASD outperformed four additional widely used sleep spindle detectors in F1-score in the P-DROWS-E dataset. Titration analysis revealed that four 30-second epochs are sufficient to fine-tune the model parameters of PSASD. Associations of frequency, duration, and amplitude of detected sleep spindles matched those previously reported with automated approaches. CONCLUSIONS: Overall, PSASD improves detection of sleep spindles in EEG data acquired from both younger healthy and older adult patient populations.

Breathe-squeeze: pharmacodynamics of a stimulus-free behavioural paradigm to track conscious states during sedation☆.

BACKGROUND: Conscious states are typically inferred through responses to auditory tasks and noxious stimulation. We report the use of a stimulus-free behavioural paradigm to track state transitions in responsiveness during dexmedetomidine sedation. We hypothesised that estimated dexmedetomidine effect-site (Ce) concentrations would be higher at loss of responsiveness (LOR) compared with return of responsiveness (ROR), and both would be lower than comparable studies that used stimulus-based assessments. METHODS: Closed-Loop Acoustic Stimulation during Sedation with Dexmedetomidine data were analysed for secondary analysis. Fourteen healthy volunteers were asked to perform the breathe-squeeze task of gripping a dynamometer when inspiring and releasing it when expiring. LOR was defined as five inspirations without accompanied squeezes; ROR was defined as the return of five inspirations accompanied by squeezes. Brain states were monitored using 64-channel EEG. Dexmedetomidine was administered as a target-controlled infusion, with Ce estimated from a pharmacokinetic model. RESULTS: Counter to our hypothesis, mean estimated dexmedetomidine Ce was lower at LOR (0.92 ng ml-1; 95% confidence interval: 0.69-1.15) than at ROR (1.43 ng ml-1; 95% confidence interval: 1.27-1.58) (paired t-test; P=0.002). LOR was characterised by progressively increasing fronto-occipital EEG power in the 0.5-8 Hz band and loss of occipital alpha (8-12 Hz) and global beta (16-30 Hz) power. These EEG changes reverted at ROR. CONCLUSIONS: The breathe-squeeze task can effectively track changes in responsiveness during sedation without external stimuli and might be more sensitive to state changes than stimulus-based tasks. It should be considered when perturbation of brain states is undesirable. CLINICAL TRIAL REGISTRATION: NCT04206059.

Correlating electroconvulsive therapy response to electroencephalographic markers: Study protocol.

Introduction: Electroconvulsive therapy (ECT) is an effective intervention for patients with major depressive disorder (MDD). Despite longstanding use, the underlying mechanisms of ECT are unknown, and there are no objective prognostic biomarkers that are routinely used for ECT response. Two electroencephalographic (EEG) markers, sleep slow waves and sleep spindles, could address these needs. Both sleep microstructure EEG markers are associated with synaptic plasticity, implicated in memory consolidation, and have reduced expression in depressed individuals. We hypothesize that ECT alleviates depression through enhanced expression of sleep slow waves and sleep spindles, thereby facilitating synaptic reconfiguration in pathologic neural circuits. Methods: Correlating ECT Response to EEG Markers (CET-REM) is a single-center, prospective, observational investigation. Wireless wearable headbands with dry EEG electrodes will be utilized for at-home unattended sleep studies to allow calculation of quantitative measures of sleep slow waves (EEG SWA, 0.5-4 Hz power) and sleep spindles (density in number/minute). High-density EEG data will be acquired during ECT to quantify seizure markers. Discussion: This innovative study focuses on the longitudinal relationships of sleep microstructure and ECT seizure markers over the treatment course. We anticipate that the results from this study will improve our understanding of ECT.

Protocol for the Prognosticating Delirium Recovery Outcomes Using Wakefulness and Sleep Electroencephalography (P-DROWS-E) study: a prospective observational study of delirium in elderly cardiac surgical patients.

INTRODUCTION: Delirium is a potentially preventable disorder characterised by acute disturbances in attention and cognition with fluctuating severity. Postoperative delirium is associated with prolonged intensive care unit and hospital stay, cognitive decline and mortality. The development of biomarkers for tracking delirium could potentially aid in the early detection, mitigation and assessment of response to interventions. Because sleep disruption has been posited as a contributor to the development of this syndrome, expression of abnormal electroencephalography (EEG) patterns during sleep and wakefulness may be informative. Here we hypothesise that abnormal EEG patterns of sleep and wakefulness may serve as predictive and diagnostic markers for postoperative delirium. Such abnormal EEG patterns would mechanistically link disrupted thalamocortical connectivity to this important clinical syndrome. METHODS AND ANALYSIS: P-DROWS-E (Prognosticating Delirium Recovery Outcomes Using Wakefulness and Sleep Electroencephalography) is a 220-patient prospective observational study. Patient eligibility criteria include those who are English-speaking, age 60 years or older and undergoing elective cardiac surgery requiring cardiopulmonary bypass. EEG acquisition will occur 1-2 nights preoperatively, intraoperatively, and up to 7 days postoperatively. Concurrent with EEG recordings, two times per day postoperative Confusion Assessment Method (CAM) evaluations will quantify the presence and severity of delirium. EEG slow wave activity, sleep spindle density and peak frequency of the posterior dominant rhythm will be quantified. Linear mixed-effects models will be used to evaluate the relationships between delirium severity/duration and EEG measures as a function of time. ETHICS AND DISSEMINATION: P-DROWS-E is approved by the ethics board at Washington University in St. Louis. Recruitment began in October 2018. Dissemination plans include presentations at scientific conferences, scientific publications and mass media. TRIAL REGISTRATION NUMBER: NCT03291626.

Pacifier use in newborns: related to socioeconomic status but not to early feeding performance.

AIM: Mothers are often advised not to use pacifiers until breastfeeding has been well-established. This study determined the infant and social factors that were related to pacifier use during the first few days of life and whether it led to alterations in feeding performance. METHODS: We enroled 51 full-term infants and their mothers at Barnes-Jewish Hospital in urban St. Louis, USA, in 2015. Before they were discharged the mothers completed a questionnaire, and infant feeding was assessed using a standardised assessment. RESULTS: There were 24 (47%) infants who used a pacifier during the first few days of life and seven (29%) of these were exclusively breastfed. Pacifier use was less common among mothers who exclusively breastfed (p = 0.04). Pacifier use was more common among mothers whose income was less than 25 000 US dollars (p = 0.02), who were single (p = 0.002) and who did not have a college education (p = 0.03). No associations between pacifier use and feeding performance were observed. CONCLUSION: While lower socioeconomic status was related to pacifier use, feeding performance in the first few days of life was no different between those infants who did and did not use pacifiers after a full-term birth.