Sleep effects on breathing and respiratory diseases

Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns

Sleep staging is a crucial tool for diagnosing and monitoring sleep disorders, but the standard clinical approach using polysomnography (PSG) in a sleep lab is time-consuming, expensive, uncomfortable, and limited to a single night. Advancements in sensor technology have enabled home sleep monitoring, but existing devices still lack sufficient accuracy to inform clinical decisions. To address this challenge, we propose a deep learning architecture that combines a convolutional neural network and bidirectional long short-term memory to accurately classify sleep stages. By supplementing photoplethysmography (PPG) signals with respiratory sensor inputs, we demonstrated significant improvements in prediction accuracy and Cohen's kappa (k) for 2- (92.7 %; k = 0.768), 3- (80.2 %; k = 0.714), 4- (76.8 %, k = 0.550), and 5-stage (76.7 %, k = 0.616) sleep classification using raw data. This relatively translatable approach, with a less intensive AI model and leveraging only a few, inexpensive sensors, shows promise in accurately staging sleep. This has potential for diagnosing and managing sleep disorders in a more accessible and practical manner, possibly even at home.

Rural/nonrural sleep duration patterns among adults in middle and older adulthood

OBJECTIVES

To document sleep duration differences between rural and nonrural adults in middle/older adulthood.

METHODS

Data consisted of adults aged 50-80 from the 2014, 2016, 2018, and 2020 Behavioral Risk Factor Surveillance System (n = 669,978). Hierarchical multinomial logistic regression models were fit predicting self-reported short (ie, 6 or fewer hours per 24-hour period) and long (ie, 9 or more hours per 24-hour period) compared to normal-sleep duration (ie, 7-8hours per 24-hour period).

RESULTS

Rural adults aged 50+ had slightly but significantly lower levels of short sleep (30.0% vs. 30.8%), and slightly but significantly higher levels of long sleep (10.6% vs. 9.4%). In multinomial logistic models that accounted for demographics, rural adults had significantly higher levels of long sleep (OR 1.16, 95% CI 1.12-1.21). The long-sleep differences were explained by socioeconomic measures.

CONCLUSIONS

Sleep researchers should continue to investigate and conceptualize sleeping patterns and heterogeneity among rural adults.

Sleep disturbance increases the risk of severity and acquisition of COVID-19: a systematic review and meta-analysis

BACKGROUND

Understanding the association between sleep quality and COVID-19 outcomes is crucial for effective preventive strategies and patient management. This systematic review aims to evaluate the impact of sleep quality as a risk factor for acquiring COVID-19 infection and the severity of the disease.

METHODS

A comprehensive search of electronic databases was conducted to identify relevant studies published from the inception of the COVID-19 pandemic which was 31st of December 2019 until 30 April 2023. Studies investigating the relationship between sleep quality and COVID-19 infection, or disease severity were included. Random effect meta-analysis was performed with odds ratios (OR) and their 95% confidence intervals (95% CI) as effect measures.

RESULTS

Out of the initial 1,132 articles identified, 12 studies met the inclusion criteria. All studies were observational studies (cohort, case-control, and cross-sectional). The association between sleep quality and COVID-19 infection risk was examined in 6 studies, The results of our meta-analysis showed that participants with poor sleep quality showed a 16% increase regarding the risk of COVID-19 acquisition (OR 1.16; 95% CI 1.03, 1.32; I2 = 65.2%, p = 0.02). Our results showed that participants with poor sleep quality showed a 51% increase in the incidence of primary composite outcome (OR 1.51; 95% CI 1.25, 1.81; I2 = 57.85%, p < 0.001). The result of our subgroup analysis also showed significantly increased risk of mortality (RR 0.67; 95% CI 0.50, 0.90; I2 = 31%, p = 0.008), and disease severity (OR 1.47; 95% CI 1.19, 1.80; I2 = 3.21%, p < 0.001) when comparing poor sleep group to those with good sleep quality.

CONCLUSION

This study highlights a significant association between poor sleep quality and an increased risk of COVID-19 infection as well as worse disease clinical outcomes.

Chronic lung diseases and sleep

Sleep is vitally important part of our life. Its quality and quantity influence all physiological processes in our organism. The relationship between the lung diseases and sleep is bidirectional - the lack of quality sleep worsens the compensation and the course of the diseases and in the same time chronic lung diseases are negatively affecting sleep quality. The coexistence of the sleep disordered breathing and lung disorders is another important issue to discuss. In case of chronic obstructive pulmonary disease the overlap with sleep disordered breathing is characterized by higher prevalence of hypercapnia and overall worse prognosis. Moreover, there is a growing body of evidence about possible links of sleep disordered breathing to lung fibrosis and tumors. The complex healthcare in patients with respiratory diseases should not omit sleep examination.

Acute effects of noninvasive ventilation on sleep physiology in patients with moderate to severe stable chronic obstructive pulmonary disease: a pilot study

OBJECTIVE/BACKGROUND

Changes in sleep architecture in patients with Chronic Obstructive Pulmonary Disease (COPD) can be explained by a combination of physiological changes in breathing during sleep, with impairment of respiratory mechanics and reduction of arterial oxygenation. This study aimed to evaluate the acute effects of noninvasive ventilation (NIV) - compared to spontaneous breathing - on sleep latency and stages, and on the occurrence of sleep-related respiratory events, nocturnal hypoxemia, and changes in heart rate (HR) in patients with moderate to severe stable COPD.

PATIENTS/METHODS

Patients completed two polysomnography (PSG) studies: one during spontaneous breathing and one while receiving NIV in bilevel mode and with backup respiratory rate (RR.) setting. Sleepware G3 software was used for the analysis of PSG and pressure, volume, and ventilator flow curves × time.

RESULTS

Participants were 10 female patients with a mean age of 68.1 ± 10.2 years. NIV during sleep decreased sleep onset latency (17 ± 18.8 min vs 46.8 ± 39.5 min; p = 0.02), increased REM sleep time (41.2 ± 24.7 min vs 19.7 ± 21.7 min; p = 0.03), and decreased the obstructive apnea index (OAI) (0 vs 8.7 ± 18.8; p = 0.01). Lower mean HR (66.6 ± 4.1 bpm vs 70.6 ± 5.9 bpm; p = 0.03) and lower maximum HR (84.1 ± 7.3 bpm vs 91.6 ± 7.8 bpm; p = 0.03) were observed in PSG with NIV.

CONCLUSIONS

The use of NIV in patients with moderate to severe stable COPD while they were sleeping increased REM sleep time and decreased sleep onset latency, the number of obstructive respiratory events, and the mean and maximum HR.

Arnold‐Chiari malformation type 1 as an unusual cause of acute respiratory failure: A case report

The authors urge clinicians to consider the possibility of Arnold‐Chiari Malformation type 1 with other central causes especially in cases where acute respiratory failure is unexplainable.

Evolving relationship between respiratory functions & impairment in sleep and cognition in patients with multiple sclerosis

BACKGROUND

The most apparent source of disability in patients with multiple sclerosis (MS) is the physical and mental impact. The pathophysiological mechanisms of cognitive dysfunction are multifactorial although hypoventilation secondary to respiratory dysfunction may contribute to cognitive decline.

METHODS

This study was conducted on 146 MS patients with baseline clinical assessments including the Epworth sleepiness scale (ESS) and physical disability was assessed using the Expanded Disability Status Scale (EDSS). Cognitive testing was performed utilizing the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and the Perceived Deficits Questionnaire (PDQ). Respiratory functions were assessed by spirometry and the respiratory muscle functional assessment was done by maximal mouth pressure measurement.

RESULTS

The respiratory muscle function test had a significant negative correlation with the score of ESS and PDQ scale and a significant positive correlation with the BICAMS scale score (p < 0.001). The ESS and PDQ scores were significantly negatively correlated with forced expiratory volume in the first second (FEV1)/ forced vital capacity (FVC) (p = 0.03, 0.02), FVC supine (p = 0.03, 0.01), FVC upright- FVC supine (ΔFVC) (p < 0.001, <0.001) FEV1 (p < 0.001) and FVC (L) (p < 0.001), respectively. While the BICAMS showed a significant positive correlation with spirometry results except FVC upright. ESS scores were significantly correlated with the BICAMS and PDQ scale score (p < 0.001).

CONCLUSION

Among MS patients, impaired respiratory functions are significantly associated with sleep disturbance and cognitive impairment. Thus the spirometry and respiratory muscle strength assessment are necessary from the early phase of MS.

Sleep Posture Classification using a Convolutional Neural Network

Sleep is a process of rest and renewal that is vital for humans. However, there are several sleep disorders such as rapid eye movement (REM) sleep behaviour disorder (RBD), sleep apnea, and restless leg syndrome (RLS) that can have an impact on a significant portion of the population. These disorders are known to be associated with particular behaviours such as specific body positions and movements. Clinical diagnosis requires patients to undergo polysomnography (PSG) in a sleep unit as a gold standard assessment. This involves attaching multiple electrodes to the head and body. In this experiment, we seek to develop non-contact approach to measure sleep disorders related to body postures and movement. An Infrared (IR) camera is used to monitor body position unaided by other sensors. Twelve participants were asked to adopt and then move through a set of 12 pre-defined sleep positions. We then adopted convolutional neural networks (CNNs) for automatic feature generation from IR data for classifying different sleep postures. The results show that the proposed method has an accuracy of between 0.76 & 0.91 across the participants and 12 sleepposes with, and without a blanket cover, respectively. The results suggest that this approach is a promising method to detect common sleep postures and potentially characterise sleep disorder behaviours.

Phosphorylated delta sleep inducing peptide restores spatial memory and p-CREB expression by improving sleep architecture at high altitude

AIMS

Sleep loss at high altitude (HA) play major role in worsening of neuropsychological functions, such as attention, memory and decision making. This study investigates the role of phosphorylated delta sleep inducing peptide (p-DSIP) in improving sleep architecture during chronic hypobaric hypoxia (HH) exposure and restoration of spatial navigational memory.

METHODS

Morris water maze (MWM) trained rats were exposed to HH at 7620 m. p-DSIP was injected intra-peritoneally (10 μg/Kg bw) during HH exposure as an intervention against sleep alteration. Sleep architecture was recorded telemetrically before and during HH exposure. Monoamines were estimated by high performance liquid chromatography from brain stem (BS) and hypothalamus. CREB and p-CREB level in hippocampus was studied by western blotting and expression of different monoamine regulatory enzymes in BS was measured by flow cytometry. Naloxone (1 mg/kg bw), a μ opioid receptor antagonist of sleep inducing effect of DSIP was also studied.

KEY FINDINGS

p-DSIP injection daily in circadian active period (18.30 h) during chronic HH enhanced non rapid eye movement sleep, rapid eye movement sleep as well as improved MWM performance of rats. p-DSIP treatment showed lower monoamine level and tyrosine hydroxylase (TH) expression and increased monoamine oxidase A (MAO A), glutamic acid decarboxylase (GAD) and Choline acetyltransferase (ChAT) expression. Further, naloxone altered navigational memory by decreasing the CREB and p-CREB level in hippocampus suggesting suppression of sleep inducing effect of p-DSIP.

SIGNIFICANCE

Our study demonstrates that improvement of sleep quality by p-DSIP restores spatial memory by up regulating CREB phosphorylation during simulated high altitude hypoxia.

Seasonality, morningness-eveningness, and sleep in common non - communicable medical conditions and chronic diseases in a population

The seasonal pattern for mood and behaviour, the behavioural trait of morningness-eveningness, and sleep are interconnected features, that may serve as etiological factors in the development or exacerbation of medical conditions. Methods: The study was based on a random sample of inhabitants aged 25 to 74 years living in Finland. As part of the national FINRISK 2012 study participants were invited (n=9905) and asked whether the doctor had diagnosed or treated them during the past 12 months for chronic diseases. Results: A total of 6424 participants filled in the first set of questionnaires and 5826 attended the physical health status examination, after which the second set of questionnaires were filled. Regression models were built in which each condition was explained by the seasonal, diurnal and sleep features, after controlling for a range of background factors. Of the chronic diseases, depressive disorder was associated with longer total sleep duration (p<.0001) and poor sleep quality (p<.0001). Of the measurements for health status assessment, none associated with sleep features, but systolic blood pressure yielded significant (p<.0001) associations with both seasonal and diurnal features at large. Conclusion: Sleep quality was the most sensitive probe in yielding associations with chronic diseases in this population-based study. The seasonal variations in mood and social activity, and the ease in getting up and tiredness in the morning were the most sensitive probes in yielding associations with blood pressure and waist circumference. Assessment of sleep quality, seasonal and diurnal features provides thus added value for health surveys of the general population.

Neurological and Sleep Disturbances in Bronchiectasis

Bronchiectasis unrelated to cystic fibrosis is a chronic lung disease that is increasingly recognised worldwide. While other common chronic lung conditions such as chronic obstructive lung disease have been associated with cardiovascular disease, there is a paucity of data on the relationship between bronchiectasis and cardiovascular risks such as stroke and sleep disturbance. Furthermore, it is unclear whether other neuropsychological aspects are affected, such as cognition, cerebral infection, anxiety and depression. In this review, we aim to highlight neurological and sleep issues in relation to bronchiectasis and their importance to patient care.

Associations of common chronic non-communicable diseases and medical conditions with sleep-related problems in a population-based health examination study

A cross-sectional population-based survey, the National FINRISK 2012 Study, designed to monitor chronic diseases and their risk factors in Finland. A random sample of 10,000 adults aged 25-74 years, and of them, 64% (n=6424) participated the study. Participants subjectively reported the total durations for sleep and naps (n=6238), sleep quality (n=5878), bedtimes and wake-up times separately for working days and weekends yielding the amount of sleep debt (n=5878), and the seasonal variation in sleep duration (n=4852). The participants were asked whether they were diagnosed or treated for common chronic diseases in the past 12 months. Logistic regression models were adopted to analysis and adjusted for a range of covariates as potential confounding factors. Total sleep duration and nap duration prolonged in depression and other mental disorder (p<.001 for all). Seasonal variation in sleep duration was associated with depression (p=.014), hypertension (p=.018) and angina pectoris (p=.024). Participants with gallstones, cardiac insufficiency, depression, or degenerative arthritis had poor sleep quality (odds ratios of 1.6-6.3, p=.001 or less for each). Those with degenerative arthritis had sleep debt less (p<.05) and those with angina pectoris more (p<.05) than individuals without these medical conditions. Depression is significantly associated with sleep problems, albeit no sleep debt. Cardiovascular diseases, degenerative arthritis, and gallstones had significant associations with one or more sleep problems. There is therefore a need for more successful management of sleep problems in chronic diseases to improve the quality of life, to reduce treatment relapses, and to increase health and longevity in a population.

Role of preoperative screening for adult patients for obstructive sleep apnea

Obstructive sleep apnea (OSA) is a chronic disease with increasing prevalence. Underdiagnosed in the surgical population, OSA can reach a prevalence of up to 70% in bariatric surgery, and be associated with difficult airways and postoperative cardiopulmonary adverse events. Despite its association with escalation of care, increased health care resource utilization, and length of hospital stay, < 25% of health care institutions in the United States have OSA perioperative protocols to improve patient safety. This is explained in part by a lack of studies that support a widely accepted systematic approach to preoperative screening and risk stratification. This review evaluates the role of preoperative screening tools for adult patients with suspected OSA.