On-Call Duty Effects on Sleep-State Physiological Stability in Male Medical Interns

Background: On-call duty among medical interns is characterized by sleep deprivation and stressful working conditions, both of which alter cardiac autonomic modulation. We hypothesized that sleep stability decreased in medical interns during on-call duty. We used cardiopulmonary-coupling (CPC) analysis to test our hypothesis. Methods: We used electrocardiogram (ECG)-based CPC analysis to quantify physiological parameters of sleep stability in 13 medical interns during on-call and on-call duty-free periods. There were ten 33.5-h on-call duty shifts per month for interns, each followed by 2 on-call duty-free days, over 3 months. Measurements during sleep were collected before, during, and after an on-call shift. Measurements were repeated 3 months later during an on-call duty-free period. Results: The medical interns had significantly reduced stable sleep, and displayed increased latency to the first epoch of stable sleep during the on-call night shift, compared to the pre-call and on-call duty-free nights. Interns also had significantly increased rapid-eye-movement (REM) sleep during the on-call night shift, compared to the pre-call and on-call duty-free nights. Conclusion: Medical interns suffer disrupted sleep stability and continuity during on-call night shifts. The ECG-based CPC analysis provides a straightforward means to quantify sleep quality and stability in medical staff performing shift work under stressful conditions

Modulation of the Sympatho-Vagal Balance during Sleep: Frequency Domain Study of Heart Rate Variability and Respiration

Sleep is a complex state characterized by important changes in the autonomic modulation of the cardiovascular activity. Heart rate variability (HRV) greatly changes during different sleep stages, showing a predominant parasympathetic drive to the heart during non-rapid eye movement (NREM) sleep and an increased sympathetic activity during rapid eye movement (REM) sleep. Respiration undergoes important modifications as well, becoming deeper and more regular with deep sleep and shallower and more frequent during REM sleep. The aim of the present study is to assess both autonomic cardiac regulation and cardiopulmonary coupling variations during different sleep stages in healthy subjects, using spectral and cross-spectral analysis of the HRV and respiration signals. Polysomnographic sleep recordings were performed in 11 healthy women and the HRV signal and the respiration signal were obtained. The spectral and cross-spectral parameters of the HRV signal and of the respiration signal were computed at low frequency and at breathing frequency (high frequency, HF) during different sleep stages. Results attested a sympatho-vagal balance shift toward parasympathetic modulation during NREM sleep and toward sympathetic modulation during REM sleep. Spectral analysis of the HRV signal and of the respiration signal indicated a higher respiration regularity during deep sleep, and a higher parasympathetic drive was also confirmed by an increase in the coherence between the HRV and the respiration signal in the HF band during NREM sleep. Our findings about sleep stage-dependent variations in the HRV signal and in the respiratory activity are in line with previous evidences and confirm spectral analysis of the HRV and the respiration signal to be a suitable tool for investigating cardiac autonomic modulation and cardio-respiratory coupling during sleep

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave)

Effects of sound environment on the sleep of college students in China

Chinese college students reside primarily in four-person bedrooms and even six-person bedrooms, where the sound from roommates may affect their sleep. Therefore, the purpose of the present study is to investigate the effects of different sound sources and sound levels on sleep for college students in China. Based on sleep quality measurements, acoustic environment measurements, and a questionnaire survey with 90 participants in a typical residence hall in Harbin city, China, the results are as following: First, 68.89% of college students experienced sleep deprivation, and indoor noise was the most influential environmental factor among 15 disruptors that disturbed 50% of college students. Second, the number of occupants per room was a significant factor affecting the background sound level of sleep, which was highest when the number of occupants was two, and lowest when the number was five. Third, deep sleep time and rapid eye movements (REM) sleep time decreased 1.7 min and 1.4 min per 1 dBA (decibel with A-weight), with R2 = 0.352 and 0.332, respectively (p < .001). In terms of the effect of sound sources on sleep, sleep was mostly disturbed by roommate conversation (77.42%), and noise caused by roommate sleep-related activities was the most common source of activities (67.74%). The present study can provide guidelines to help enhance the sleep quality of Chinese college students through improvements in the sound environment

Autonomic pain responses during sleep: a study of heart rate variability

The autonomic nervous system (ANS) reacts to nociceptive stimulation during sleep, but whether this reaction is contingent to cortical arousal, and whether one of the autonomic arms (sympathetic/parasympathetic) predominates over the other remains unknown. We assessed ANS reactivity to nociceptive stimulation during all sleep stages through heart rate variability, and correlated the results with the presence of cortical arousal measured in concomitant 32-channel EEG. Fourteen healthy volunteers underwent whole-night polysomnography during which nociceptive laser stimuli were applied over the hand. RR intervals (RR) and spectral analysis by wavelet transform were performed to assess parasympathetic (HF(WV)) and sympathetic (LF(WV) and LF(WV)/HF(WV) ratio) reactivity. During all sleep stages, RR significantly decreased in reaction to nociceptive stimulations, reaching a level similar to that of wakefulness, at the 3rd beat post-stimulus and returning to baseline after seven beats. This RR decrease was associated with an increase in sympathetic LF(WV) and LF(WV)/HF(WV) ratio without any parasympathetic HF(WV) change. Albeit RR decrease existed even in the absence of arousals, it was significantly higher when an arousal followed the noxious stimulus. These results suggest that the sympathetic-dependent cardiac activation induced by nociceptive stimuli is modulated by a sleep dependent phenomenon related to cortical activation and not by sleep itself, since it reaches a same intensity whatever the state of vigilance

Multimodal Signal Processing for Diagnosis of Cardiorespiratory Disorders

This thesis addresses the use of multimodal signal processing to develop algorithms for the automated processing of two cardiorespiratory disorders. The aim of the first application of this thesis was to reduce false alarm rate in an intensive care unit. The goal was to detect five critical arrhythmias using processing of multimodal signals including photoplethysmography, arterial blood pressure, Lead II and augmented right arm electrocardiogram (ECG). A hierarchical approach was used to process the signals as well as a custom signal processing technique for each arrhythmia type. Sleep disorders are a prevalent health issue, currently costly and inconvenient to diagnose, as they normally require an overnight hospital stay by the patient. In the second application of this project, we designed automated signal processing algorithms for the diagnosis of sleep apnoea with a main focus on the ECG signal processing. We estimated the ECG-derived respiratory (EDR) signal using different methods: QRS-complex area, principal component analysis (PCA) and kernel PCA. We proposed two algorithms (segmented PCA and approximated PCA) for EDR estimation to enable applying the PCA method to overnight recordings and rectify the computational issues and memory requirement. We compared the EDR information against the chest respiratory effort signals. The performance was evaluated using three automated machine learning algorithms of linear discriminant analysis (LDA), extreme learning machine (ELM) and support vector machine (SVM) on two databases: the MIT PhysioNet database and the St. Vincent’s database. The results showed that the QRS area method for EDR estimation combined with the LDA classifier was the highest performing method and the EDR signals contain respiratory information useful for discriminating sleep apnoea. As a final step, heart rate variability (HRV) and cardiopulmonary coupling (CPC) features were extracted and combined with the EDR features and temporal optimisation techniques were applied. The cross-validation results of the minute-by-minute apnoea classification achieved an accuracy of 89%, a sensitivity of 90%, a specificity of 88%, and an AUC of 0.95 which is comparable to the best results reported in the literature

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation

The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients’ readiness, there is still around 15–20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation –being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness

The association between sleep quality and telomere length: A systematic literature review

Several sleep parameters present an elevated risk for processes that contribute to cellular aging. Short sleep duration, sleep apnoea, and insomnia are significantly associated with shorter telomeres, a biological marker of cellular aging. However, there has been no review or analysis of studies that have examined the association between the psychological construct of sleep quality and telomere length. The present study aimed to provide a systematic review of the association between sleep quality and telomere length. A systematic review of English articles was conducted using MEDLINE/PubMed, PsycINFO, Google Scholar, and Web of Science electronic databases, with the final search conducted on 3rd September 2021. Search terms included sleep quality, poor sleep, insomnia, sleep difficulties, sleep issue*, non-restorative sleep, telomere*, cellular aging, and immune cell telomere length. Study eligibility criteria included human participants aged 18 years or older and a reproducible methodology. Study appraisal and synthesis were completed using a systematic search in line with a PICOS approach (P = Patient, problem, or population; I = Intervention, prognostic factor, exposure; C = Comparison, control, or comparator; O = Outcomes; S = Study designs). Twenty-two studies met review inclusion criteria. Qualitative synthesis of the literature indicated insufficient evidence overall to support a significant association between sleep quality and telomere length. Limitations across studies were addressed, such as the assessment of examined constructs. Findings highlight important targets for future research, including the standardised operationalisation of the sleep quality construct and experimental study designs. Research in this area has clinical significance by identifying possible mechanisms that increase the risk for age-related disease and mortality. PROSPERO Registration No.: CRD 42021233139