Using sleep heart rate variability to investigate the sleep quality in children with obstructive sleep apnea

Background

Obstructive sleep apnea (OSA) is associated with impaired sleep quality and autonomic dysfunction. Adenotonsillectomy significantly improves subjective and objective sleep quality in children with OSA. However, the postoperative changes in heart rate variability (HRV) indices (indicators of cardiac autonomic function) and their importance remain inconclusive in childhood OSA. This retrospective case series aimed to investigate the association of sleep HRV indices, total OSA-18 questionnaire score (a subjective indicator of sleep quality) and polysomnographic parameters (objective indicators of sleep quality), and effects of adenotonsillectomy on HRV indices, total OSA-18 questionnaire score and polysomnographic parameters in children with OSA.

Methods

Seventy-six children with OSA were included in baseline analysis, of whom 64 (84%) completed at least 3 months follow-up examinations after adenotonsillectomy and were included in outcome analysis. Associations between baseline variables, and relationships with treatment-related changes were examined.

Results

Multivariable linear regression models in the baseline analysis revealed independent relationships between tonsil size and obstructive apnea-hypopnea index (OAHI), adenoidal-nasopharyngeal ratio and very low frequency (VLF) power of HRV (an indicator of sympathetic activity), and normalized low frequency power (an indicator of sympathetic activity) and OAHI. The outcome analysis showed that adenotonsillectomy significantly improved standard deviation of all normal-to-normal intervals, and high frequency power, QoL (in terms of reduced total OSA-18 questionnaire score), OAHI and hypoxemia. Using a conceptual serial multiple mediation model, % change in OSA-18 questionnaire score and % change in VLF power serially mediated the relationships between change in tonsil size and % change in OAHI.

Conclusions

The improvement in OAHI after adenotonsillectomy was serially mediated by reductions in total OSA-18 questionnaire score and VLF power. These preliminary findings are novel and provide a direction for future research to investigate the effects of VLF power-guided interventions on childhood OSA.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Diagnosis of Heart Failure Complicated with Sleep Apnea Syndrome by Thoracic Computerized Tomography under Artificial Intelligence Algorithm

The aim of this study was to explore the application effect of thoracic computerized tomography (CT) under single threshold segmentation algorithm in the diagnosis of heart failure (HF) complicated with sleep apnea syndrome. 30 patients diagnosed with HF complicated with sleep apnea syndrome were chosen for the research. Another 30 patients without sleep apnea syndrome were selected as the control group, whose age, height, and weight were similar to those of the experimental group. Then, a model for thoracic CT image segmentation was proposed under the single threshold segmentation algorithm, and the faster region convolutional neural network (Faster RCNN) was applied to label the thoracic respiratory lesions. All the patients underwent thoracic CT examination, and the obtained images were processed using the algorithm model above. After that, the morphology of the patient's respiratory tract after treatment was observed. The results suggested that the improved single threshold segmentation algorithm was effective for the image segmentation of patient lesions, and the Faster RCNN could effectively finish the labeling of the lesion area in the CT image. The classification accuracy of the Faster RCNN was about 0.966, and the loss value was about 0.092. With CT scanning under the algorithm, it was found that the airway collapse of the posterior palatal area, retrolingual area, and laryngopharyngeal area of the sleep apnea syndrome patients was significantly greater than that of the control group (P < 0.05). But there was no significant difference of the collapse of the nasopharyngeal area between the two groups (P > 0.05). The single threshold segmentation algorithm had a better segmentation accuracy for thoracic CT images in patients with HF and sleep apnea syndrome, so it had a highly promising application prospect in the diagnosis of the disease.

Interactions of central and autonomic nervous systems in patients with sleep apnea-hypopnea syndrome during sleep

PURPOSE

Sleep apnea-hypopnea syndrome (SAHS) is an independent risk factor for various cardiovascular and cerebrovascular diseases, but the underlying relationship of its physiological subsystems remains unclear. Thus, we aimed to investigate the effect of SAHS on central and autonomic nervous system (CNS-ANS) interactions during sleep.

METHODS

Thirty-five patients with SAHS and 19 healthy age-matched controls underwent overnight polysomnography. The absolute spectral powers of five frequency bands from six EEG channels and ECG morphological features (HR, PR interval, QT interval) were calculated. Multivariable transfer entropy was applied to analyze the differences of the CNS-ANS network interactions between patients with SAHS of different severities and healthy controls during deep, light, and rapid eye movement sleep.

RESULTS

The CNS-ANS network interacted bidirectionally in all researched groups, with the cardiac information modulating the brain activity. The information strength from QT to most EEG components and PR to some EEG components was significantly affected by SAHS severity during light sleep, which indicates the coupling features of QT-brain nodes are important indicators. The driver effects from the β-band significantly increased in patients with SAHS.

CONCLUSIONS

Respiratory events may be the main reason for the CNS-ANS interaction changes in SAHS. These findings help explain the physiological regulation process of SAHS and provide valuable information for analysis of the development of SAHS-related cardiovascular and chronic diseases.

Sleep-Dependent Directional Interactions of the Central Nervous System-Cardiorespiratory Network

OBJECTIVE

We investigated the nature of interactions between the central nervous system (CNS) and the cardiorespiratory system during sleep.

METHODS

Overnight polysomnography recordings were obtained from 33 healthy individuals. The relative spectral powers of five frequency bands, three ECG morphological features and respiratory rate were obtained from six EEG channels, ECG, and oronasal airflow, respectively. The synchronous feature series were interpolated to 1 Hz to retain the high time-resolution required to detect rapid physiological variations. CNS-cardiorespiratory interaction networks were built for each EEG channel and a directionality analysis was conducted using multivariate transfer entropy. Finally, the difference in interaction between Deep, Light, and REM sleep (DS, LS, and REM) was studied.

RESULTS

Bidirectional interactions existed in central-cardiorespiratory networks, and the dominant direction was from the cardiorespiratory system to the brain during all sleep stages. Sleep stages had evident influence on these interactions, with the strength of information transfer from heart rate and respiration rate to the brain gradually increasing with the sequence of REM, LS, and DS. Furthermore, the occipital lobe appeared to receive the most input from the cardiorespiratory system during LS. Finally, different ECG morphological features were found to be involved with various central-cardiac and cardiac-respiratory interactions.

CONCLUSION

These findings reveal detailed information regarding CNS-cardiorespiratory interactions during sleep and provide new insights into understanding of sleep control mechanisms.

SIGNIFICANCE

Our approach may facilitate the investigation of the pathological cardiorespiratory complications of sleep disorders.

Repercussion of medium and long treatment period with continuous positive airways pressure therapy in heart rate variability of obstructive sleep apnea

INTRODUCTION

Obstructive sleep apnea (OSA) is a respiratory sleep disorder. Many of these patients also exhibit autonomic alterations which can be observed through heart rate variability (HRV). Currently, one of the treatments for apnea is continuous positive airway pressure (CPAP).

OBJECTIVE

To observe OSA patients treated with CPAP exhibit HRV changes at medium and long treatment period.

METHODS

This is an integrative literature review conducted in May of 2018. The databases used for this research were PubMed, Scopus, Scielo and Pedro, the keywords used were "heart rate variability", "obstructive sleep apnea" and "CPAP". In this review was included original, published, randomized and non-randomized articles, released in the English language, before and up to April 2018, which specified the effects of CPAP therapy in autonomic dysfunction through the analysis of the HRV of patients diagnosed with OSA after at least one month of therapy.

RESULTS

The research of the literature produced 113 articles. After excluding duplicates and applying the inclusion and exclusion criteria, 8 articles were selected for this review.

CONCLUSION

It was concluded that CPAP therapy is related to change in heart rate variability in patients with obstructive sleep apnea.

Variation of Electrocardiogram Features Across Sleep Stages in Healthy Controls and in Patients with Sleep Apnea Hypopnea Syndrome

Sleep apnea hypopnea syndrome (SAHS) is an independent risk factor for various cardiovascular diseases. Electrocardiogram (ECG) features such as the RR, PR, QT, QTc, Tpe intervals and the Tpe/QT, Tpe/QTc ratios are used to predict and study cardiovascular diseases. It is not clear whether regular patterns of PR and Tpe-related features across sleep stages exist in SAHSs or healthy controls nor whether sleep stages affect the short- and long-range influences of respiratory events on ECG indices. We enrolled 36 healthy controls and 35 patients with SAHS in our study and analyzed the abovementioned ECG features. In the healthy controls, a significant regularity existed in these indices across sleep stages, which were weakened or disturbed in the patient group, especially the Tpe-related features. The differences between the patients and healthy controls were generally consistent across all sleep stages: patients had smaller RR, PR, QT and Tpe/QTc values, but larger QTc, Tpe and Tpe/QT values. After filtering the short-range influence of respiratory events, the differences in most features remained highly significant, except the QT interval. In the patient group, respiratory events decreased RR and PR intervals in most sleep stages and increased the Tpe-related features' values in deep sleep stages. These results may aid in the study of the relationships among SAHS, sleep disorders and cardiovascular diseases.