Polysomnography Testing Research Articles

Night-to-Night Variability of Polysomnography-Derived Physiologic Endotypic Traits in Patients With Moderate to Severe OSA

Emerging data suggest that determination of physiologic endotypic traits (eg, loop gain) may enable precision medicine in OSA. Does a single-night assessment of polysomnography-derived endotypic traits provide reliable estimates in moderate to severe OSA? Two consecutive in-lab polysomnography tests from a clinical trial (n= 67; male, 69%; mean ± SD age, 61 ± 10 years; apnea-hypopnea index [AHI] 53 ± 22 events/h) were used for the reliability analysis. Endotypic traits, reflecting upper airway collapsibility (ventilation at eupneic drive [Vpassive]), upper airway dilator muscle tone (ventilation at the arousal threshold [Vactive]),loop gain (stability of ventilatory control, LG1), and arousal threshold (ArTh) were determined. Reliability was expressed as an intraclass correlation coefficient (ICC). Minimal detectable differences (MDDs) were computed to provide an estimate of maximum spontaneous variability. Further assessment across four repeated polysomnography tests was performed in a subcohort (n= 22). Reliability of endotypic traits between the two consecutive nights was moderate to good (ICC: Vpassive= 0.82, Vactive= 0.76, LG1= 0.72, ArTh= 0.83). Variability in AHI, but not in body position or in sleep stages, was associated with fluctuations in Vpassive and Vactive (r= -0.49 and r= -0.41, respectively; P< .001 for both). MDDs for single-night assessments were: Vpassive= 22, Vactive= 34, LG1= 0.17, and ArTh= 21. Multiple assessments (mean of two nights, n= 22) further reduced MDDs by approximately 20%to 30%. Endotypic trait analysis using a single standard polysomnography shows acceptable reliability and reproducibility in patients with moderate to severe OSA. The reported MDDs of endotypic traits may facilitate the quantification of relevant changes and may guide future evaluation of interventions in OSA.

RESPOSTAS DO SONO ÀS CARGAS DE TREINAMENTO E RECUPERAÇÃO EM JOVENS NADADORES DURANTE O POLIMENTO

ABSTRACT Introduction: Tapering is a decisive phase in planning a young swimmer's preparation for competition. During this period, not only training loads, but also recovery, which includes sleep quality, must be constantly monitored. Objective: This study aims to investigate sleep behavior as a variable directly influenced by training load during the tapering phase of training for young swimmers. Methods: A polysomnography test was performed at the beginning of the tapering phase, as a baseline for sleep variables. In each daily training session, the overload and recovery variables were measured. The internal training load was evaluated in the PSE session and the external load by quantifying the training. The recovery variables were divided into the recovery variable, assessed using the TQR questionnaire, and sleep variables, which included sleepiness, scored using the Karolinska scale, and sleep behavior, using an actigraph and a sleep diary. Conclusion: It is concluded that there is no significant influence between training loads and sleep variables. However, a strong association was observed between TST and EL (External load), in the irregular sleep group. Level of evidence III, Study of behavior.

A Deep Learning Approach to Automated Sleep Stages Classification Using Multi-Modal Signals

Sleep is one of the elements most vital to human life. However, the modern lifestyle continues to push people to neglect this critical requirement. With a vast majority of people falling victim to various sleep disorders, it has become increasingly essential to have a robust system for diagnosing and treating such ailments. Sleep stage classification is one of the primary steps for identifying sleep-related anomalies. Sleep stages are classified according to the frequency and nature of signals received during a polysomnography test. Since the early days, this has been performed manually with the help of trained technicians. However, manual scoring is often prone to error and subjectivity and requires tremendous time and effort. It is, therefore, essential to automatize this process. Several challenges from the correct selection of features remain to be faced in the machine learning-based sleep stage classification system. As an alternative, Deep Learning, capable of automatic feature extraction, proves far more reliable for this task. This experimental study analyses both techniques to compare and decide on a better approach. Three popular Machine Learning classifiers, namely Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machines (SVM), and a neural network comprising CNN and LSTM, have been trained on a vast base of diverse data. The proposed model reported an accuracy of 87.4% with CNN + LSTM.

Management of children with co-occurring sleep disordered breathing and hearing loss.

To examine hearing loss incidence in a pediatric otolaryngology patients with sleep disordered breathing, and secondarily, identify possible disparities in management. A retrospective case-control study of pediatric patients with sleep-disordered breathing or obstructive sleep apnea from 2012 to 2019 was conducted at a private, not-for-profit, academic, tertiary care center. Study parameters were extracted from the electronic medical record and compared in study groups of patients with sleep-disordered breathing generated based on presence of hearing loss (cases) versus absence (controls). Study parameters were also compared in study groups based on timing of hearing loss onset. 14.8% of patients with sleep disordered breathing had hearing loss. Hearing loss was associated with an increased risk of undergoing adenotonsillectomy (OR 1.632 [1.294-2.058], p<0.001, adjusted for age). In patients who underwent polysomnographic testing, 9.8% patients had pre-existing hearing loss and 12% patients developed hearing loss over the study period. Patients with pre-existing hearing loss and those who developed hearing loss had significantly more visits with otolaryngology compared to controls (p<0.001). Hearing loss did not significantly delay adenotonsillectomy. More patients who developed hearing loss had adenotonsillectomies (OR 2.475 [1.672-3.663], p<0.001, adjusted for age) versus controls. This difference was not identified in patients with pre-existing hearing loss. Patients with evidence of hearing loss in addition to sleep disordered breathing had more adenotonsillectomies performed and more clinic visits. Further work must be done to understand the associations and implications of hearing loss in this population.

Automatic detection of sleep apnea from single-lead ECG signal using enhanced-deep belief network model

Sleep apnea (SLA) is a commonly reported sleep disorder that is characterized by frequent breathing interruptions during sleep. In recent years, various approaches have been made to developing a less complex and cost-effective process for diagnosing SLA patients, as opposed to using the inconvenient, complex and costly polysomnography test. This study proposed a novel approach of cascading two different types of Restricted Boltzmann Machine (RBM) in Deep Belief Networks (DBN) method for the SLA classification using single-lead electrocardiogram (ECG) signals. The proposed framework uses two types of RBM, namely Gaussian-Bernoulli, and Bernoulli-Bernoulli, which are modified forms of the Boltzmann Machine, to develop an enhanced- DBN (E-DBN) structure for significant feature learning and detection of SLA and normal events. At each ECG data signal, Heart Rate Variability (HRV) and ECG-Derived Respiration (EDR) signals are obtained from the 1-minute segmented ECG signal. The E-DBN model can also enhance the parameter detection performance as a keyfeature extractor and classification method. The Apnea-ECG datasets from physionet were used to train the presented fine-tuned E-DBN model and validate its performance for detecting SLA incidents. The proposed method shows significant improvements in performance when compared to other SLA detection methods for per-segment detection and achieved the highest accuracy of 89.11%, with specificity, sensitivity, and F1-score of 92.28%, 83.89%, and 0.913, respectively. For per-recording detection, accuracy of 97.17% and correction coefficient values of 0.938 are obtained. The proposed approach develops a method that analyses single-lead electrocardiography data from patients and diagnoses the SLA condition of patients.

Influence of Lingual Tonsillar Volume in Patients with Obstructive Sleep Apnea.

This study aimed to evaluate the influence of lingual tonsil (LT) volume measured using a three-dimensional (3D) reconstruction volume rendering program on clinical parameters and polysomnography (PSG) results. A total of 100 patients who underwent PSG, computed tomography (CT), and allergy test from April 2016 to April 2020 were randomly selected. LT volume was measured using an imaging software program that enables 3D reconstruction of CT images. PSG parameters were analyzed by dividing the subjects into two groups according to LT volume (each 50 people). Based on the medial volume of 0.863 cm3, the upper half LT volume group and the lower half LT volume group were analyzed. Clinical factors such as body weight, neck circumference, body mass index (BMI), and age showed no difference between the two groups. Among PSG parameters, supine arousal index and non-rapid eye movement (NREM) arousal index were significantly higher in the upper half LT volume group (p = 0.012, 0.037). However, there was no significant difference in apnea-hypopnea index (AHI) between the upper and lower half LT volume groups (p = 0.749). Arousal snoring index and REM arousal index also showed no difference between the two groups. The prevalence of allergic rhinitis was not different in the two groups. High LT volume is associated with NREM arousal and arousal in the supine position, but it is not related to AHI.

Abstract 15443: Association Between Central Sleep Apnea and P2y12 Inhibitors in Patients With Coronary Heart Disease

Introduction: Central sleep apnea (CSA) is common in patients with heart failure and is associated with a poor prognosis. A number of studies have linked the P2Y12 inhibitor, ticagrelor, with CSA. We aimed to evaluate CSA prevalence in patients with coronary heart disease (CHD) and whether ticagrelor use is associated with CSA in this population. Methods: We reviewed consecutive patients with CHD data who underwent a clinically indicated polysomnography (PSG) test over a 5-year period from three academic sleep centers. We sampled patients who were on ticagrelor or clopidogrel during their PSG test at a 1:4 ticagrelor:clopidogrel ratio. Patients with an active opioid prescription at time of PSG test were excluded. Age, left ventricle (LV) dysfunction (ejection fraction &lt;45%), and P2Y12 inhibitor use were included in a multivariate logistic regression. Results: A total of 141 patients (age 63.7 ± 11.4, 33% female) were included with 30 on ticagrelor and 111 on clopidogrel. 106 (75.2%) patients had undergone percutaneous coronary intervention for ACS. 33 (23.4%) patients had LV dysfunction. The mean apnea hypopnea index (AHI) was 29 (/hr). High CSA burden (central apnea index [CAI] ≥5/h) and strict CSA (AHI ≥5/h and CAI &gt;50% of AHI) were present in 16 (11.3%) and 5 (3.5%) patients, respectively. High CSA burden and strict CSA were more common in patients on ticagrelor than in those on clopidogrel (7 [23.3%] vs. 9 [8.1%] and 3 [10.0%] vs. 2 [1.8%]). In multivariable analysis ticagrelor use was associated with high CSA burden adjusting for LV dysfunction and age (OR 3.27, 95% CI 0.99-10.7, p=0.048). No variables were associated with strict CSA. Conclusions: Ticagrelor use was associated with high CSA burden in patients with coronary heart disease. Future studies should verify these results in a larger cohort and explore their clinical significance.

Ambulatory transcutaneous carbon dioxide monitoring for children with neuromuscular disease

ObjectiveEarly screening and diagnosis of nocturnal hypoventilation can slow progression to diurnal hypercapnia and mortality in children with neuromuscular disease (NMD). However, gold standard, laboratory-based polysomnography (PSG) testing is a limited resource. Therefore, we evaluated the diagnostic accuracy of ambulatory transcutaneous carbon dioxide (tcCO2) monitoring used in the home compared to PSG in children with NMD. MethodsProspective, cross-sectional study in children 0–18 years old with a confirmed diagnosis of NMD and a clinically indicated need for PSG. Ambulatory tcCO2 was assessed by a respiratory therapist in participant's homes. Demographics, and PSG (including tcCO2). ResultsWe enrolled 39 children with NMD; 3 had unusable ambulatory tcCO2 data because of failure of drift correction on the machine (n = 2) or an air bubble (n = 1). The remaining 36 patients aged 11 months to 16 years (median (IQR) 12.5 years (6.0–15.8)) had ambulatory tcCO2 and outpatient level 1 PSG data. Ambulatory tcCO2 monitoring had a sensitivity of 20.0% (95% confidence interval [CI] 0.5–71.6%) and a specificity of 93.5% (95% CI 78.6–99.2%). Almost all children and/or parents (34/36, 94%) preferred ambulatory monitoring over in-hospital PSG. ConclusionsAmbulatory transcutaneous carbon dioxide monitoring was not sufficiently accurate as a clinical tool for the diagnosis of nocturnal hypoventilation our cohort of children with neuromuscular disease despite being preferred over PSG by both children and parents.

Review of Application of Machine Learning as a Screening Tool for Diagnosis of Obstructive Sleep Apnea

Obstructive sleep apnea syndrome (OSAS) is a pervasive disorder with an incidence estimated at 5-14 percent among adults aged 30-70 years. It carries significant morbidity and mortality risk from cardiovascular disease, including ischemic heart disease, atrial fibrillation, and cerebrovascular disease, and risks related to excessive daytime sleepiness. The gold standard for diagnosis of OSAS is the polysomnography (PSG) test which requires overnight evaluation in a sleep laboratory and expensive infrastructure, which renders it unsuitable for mass screening and diagnosis. Alternatives such as home sleep testing need patients to wear diagnostic instruments overnight, but accuracy continues to be suboptimal while access continues to be a barrier for many. Hence, there is a continued significant underdiagnosis and under-recognition of sleep apnea in the community, with at least one study suggesting that 80-90% of middle-aged adults with moderate to severe sleep apnea remain undiagnosed. Recently, we have seen a surge in applications of artificial intelligence and neural networks in healthcare diagnostics. Several studies have attempted to examine its application in the diagnosis of OSAS. Signals included in data analytics include Electrocardiogram (ECG), photo-pletysmography (PPG), peripheral oxygen saturation (SpO2), and audio signals. A different approach is to study the application of machine learning to use demographic and standard clinical variables and physical findings to try and synthesize predictive models with high accuracy in assisting in the triage of high-risk patients for sleep testing. The current paper will review this latter approach and identify knowledge gaps that may serve as potential avenues for future research.

Head-Of-Bed Elevation (HOBE) for Improving Positional Obstructive Sleep Apnea (POSA): An Experimental Study.

Purpose: Evaluate the effectiveness of the head-of-bed elevation position (HOBE) with a 30° elevation of the head and trunk, in improving obstruction of the upper airways in obstructive sleep apnea (OSA) patients. A prospective trial simultaneously performing drug-induced sleep endoscopy (DISE) and polysomnography (PSG) tests was performed. Methods: Forty-five patients were included in the prospective study protocol. All patients enrolled in the study and underwent the following evaluations: (1) a drug-induced sleep endoscopy, with an evaluation of obstructions and collapse of the upper airways at 0° and in a HOBE position, with head and trunk elevation of 30°; (2) an overnight PSG assessment in the hospital with head and trunk elevation from 0° to 30° during the night; (3) a questionnaire to evaluate the feedback of patients to sleeping with head-of-bed elevation. Results: Velum (V) and oropharynx lateral wall (O) collapses were reduced in the 30° up position. There were no statistical differences that emerged in the obstruction of the tongue base and epiglottis between the 0° position and the 30° up position (p > 0.05). The average AHI score changed from 23.8 ± 13.3 (0° supine position) to 17.7 ± 12.4 (HOBE position), with a statistical difference (p = 0.03); the same statistical difference emerged in the percentage of apneas that decreased from 55 ± 28.1 to 44 ± 25.8 (p = 0.05). Conclusions: By adopting the HOBE position with 30° elevation of the head and trunk, it is possible to obtain a reduction of upper airways collapses and an improvement of apnea/hypopnea events and nightly respiratory outcomes.

Determining the effect of obstructive sleep apnea syndrome on peripheral vestibular system and hearing.

There have been studies in the literature regarding the effect of obstructive sleep apnea syndrome on hearing function, but studies on the effect of obstructive sleep apnea syndrome on the peripheral vestibular system are limited. The aim of the present study was to determine whether obstructive sleep apnea syndrome causes functional neurological changes, particularly in the peripheral vestibular system, using the video head impulse test. Overall, 57 patients with obstructive sleep apnea syndrome were included; the 'Snorers' group comprised 20 volunteers diagnosed with simple snoring in the polysomnography test. The severity of apnea was assessed by monitoring cardiac and respiratory functions during sleep in both groups. The video head impulse test and audiological evaluations were performed in both groups. Statistically significant differences were found in the cochlea and semicircular canals of our patients in the video head impulse test and audiological battery tests. It may be assumed that decreased blood oxygen concentrations and chronic hypoxaemia have negative effects on the vestibule, cochlear sensory epithelium, and the auditory pathways. We think that inner ear structures and pathways may be affected due to hypoxia in obstructive sleep apnea syndrome. Therefore, screening patients with obstructive sleep apnea syndrome with an audiometry battery may help to detect inner ear pathologies early.

Correlation between self-reported and questioned Epworth sleepiness scale results including polysomographic outcomes

IntroductionObstructive sleep apnea (OSA) is characterized by a recurrent complete or partial obstruction in the upper airways accompanied by desaturation attacks and recurrent awakenings (arousal) during sleep and is associated with excessive sleepiness and poor quality of life. Excessive daytime sleepiness (EDS) has long been recognized as the most important symptom of OSA and Epworth sleepiness scale (ESS) is a simple, easy-to-understand, self-reported, validated scale used in the evaluation of patients with obstructive sleep apnea syndrome (OSAS).ObjectiveSome researchers have reported that ESS has controversial results in evaluating OSAS due to the fact that it is based on self-reporting. It is known that ESS is a self-administered patient questionnaire, but it can also be administered by the doctor, and the information about the latter’s validity, reliability, and correlation with OSAS is limited. This study was conducted to compare the outcomes of ESS self-administered by the patient and administered by a doctor in patients with OSAS.MethodsNinety-three patients with OSAS symptoms, with polysomnography test results, and who were presented in a tertiary hospital in 2019 for snoring and apnea problems were included in this study. ESS, consisting of eight questions and used to measure daytime sleepiness in various situations on the basis of self-reporting, was used. Subsequently, ESS was repeated, but this time verbally administered by the doctor to the patient. ESS is a 4-point Likert-type scale scored with 0, 1, 2, and 3. Excessive daytime sleepiness is accepted in individuals with a total score of 11 or more. The data were analyzed using the Statistical Package for the Social Sciences (SPSS) program.ResultsOf the patients who participated in this study, 57% (n = 53) were male and 43% (n = 40) were female. The average age of the patients was 48.1±9.71. The body mass index (BMI) average was 29.7±5.66 kg/m2, and the average neck circumference was 38.6±4.62 cm. The mean value of the completed ESS self-administered by the patient (ESSp) was calculated as 11.0±5.25 and that of the ESS administered by the doctor (ESSd) was 7.9±4.76. For the results, while daytime sleepiness was 35.5% in ESSd, it was 52.7% in ESSp. A positive correlation was found between the ESSd and ESSp values and BMI. A positive correlation was also found between the apnea-hypopnea index (AHI) and BMI.ConclusionsThe ESS administered by a doctor will yield more accurate data about the severity of OSAS than the ESS self-administered by the patient.

The correlation between the body shape and otolithic function in patients with obstructive sleep apnea

ObjectiveTo identify the typical pattern of changes of vestibular-evoked myogenic potentials (VEMPs) and explore the relationship between VEMPs and the anthropometry factors in patients with obstructive sleep apnea (OSA). MethodsPatients diagnosed as OSA after overnight polysomnography (PSG) tests were enrolled as the study group. Healthy volunteers were recruited as the control group. Anthropometry data of the body shape and VEMPs results were collected completely. The correlation analysis was conducted among those parameters. ResultsForty-nine patients with OSA who were diagnosed in the Therapy Center of Sleep-disordered Breathing in our hospital and sex- and age-matched healthy controls as well. Significant changes in ocular and cervical VEMPs (oVEMP and cVEMP) in the study group were observed, which were reduced response rates, elevated thresholds, decreased amplitudes, and prolonged first wave latencies. In oVEMP, the first wave (n1) latency was significantly correlated with weight, body mass index (BMI), neck circumference, waist circumference, hip circumference, and apnea hypopnea index (AHI). In a tentative application, combined use of BMI and oVEMP n1 latency increased the detection rate during OSA screening prior to PSG. ConclusionOSA can negatively affect function of otolithic organs and their pathways. The first wave latency of the VEMPs waveform may be another important parameter to define peripheral nervous system lesions caused by systemic diseases as OSA.

A Study on the Effects of Mucous Membrane of the Sinus by Severity of Sleep Breathing Disorder

Background and Objectives Obstructive sleep apnea (OSA) is an obstructive airflow disorder that occurs in the upper respiratory tract during sleep and is therefore associated with the occurrence of cardiovascular diseases. By examining the Lund-Mackay (L-M) scores and maxillary sinus mucosal conditions according to the severity of sleep breathing disorder (SBD), we tried to find out the association between SBD and sinus mucosal change.Subjects and Method Of the 189 patients who underwent sinus CT with a polysomnography test, 175 patients were enrolled in our study. We investigated the average L-M score and L-M score of five or higher, and the ratio of maxillary sinus mucosal thickness (MSMT) of 2 mm or higher.Results The average L-M score of study population was 0.98 points and the L-M score of five or more was found in 14 patients (8%). The MSMT of 2 mm or more was found in 25.5% of the study group. The average L-M scores for the different groups, namely, the simple snoring group, the mild OSA, the moderate OSA, and the severe OSA were 1.31 points, 0.77 points, 0.91 points, and 1.08 points, respectively. There was no significant difference (&lt;i&gt;p&lt;/i&gt;=0.736) among them, and there was no correlation between the apnea-hypopnea index score and the L-M score (r=-0.052, &lt;i&gt;p&lt;/i&gt;=0.499). There was no significant difference between OSA severity and MSMT (&lt;i&gt;p&lt;/i&gt;=0.490).Conclusion There was no significant difference between the L-M score and MSMT depending on the severity of SBD. Therefore, it is believed that SBD will have little effect on the sinus mucosa.

Classification of Sleep using Polysomnography

Sleep is often recognized as a necessary component of a person’s well-being and is an extremely vital component of a healthy person’s well-being. Sleep is a state in which a person is both physiologically and psychically at ease. The sleep conception is appraised exceedingly unusual, and it has piqued the interest of researchers all around the world. The stages of sleep are examined in order give benefits for studying sleep utilized for the purpose of research. The ability to diagnose sleep disorders has been demonstrated by carefully examining the sleep score system and its various stages. As can be seen, manual sleep stage classification is a time-consuming method that requires adequate measure for sleep professionals to undertake statistical and quantitative analysis. Furthermore, errors and abnormalities in the categoization of the similar facts can occur frequently. As a result, the adoption of an autonomous scoring system to enable trustworthy classification is becoming increasingly popular. The scheduled task teaches you how to apply an automatic system based on EEG (Electroencephalogram), EMG (Electromyogram) and EOG (Electrooculogram), which is known as a polysomnography test or PSG test. For a total of 30 seconds, the recording was measured in length segments. The standard collection of parameters, which gives the distinct stages of sleep, was obtained from several hospitals in sleep laboratories. Sleep waking, Non-Rapid Eye Movement (Stage 1, Stage2, Stage3), and Rapid Eye Movement are the stages. In clinics, the procedure can be highly effective, especially for neurologist detecting sleep problems.

The Weighted Combination of the Epworth Sleepiness Scale and the STOP-Bang Questionnaire Improved the Predictive Value of for OSAHS in Hypertensive Patients.

PurposeHypertension interrelated with obstructive sleep apnea hypopnea syndrome (OSAHS), worsening morbidity and mortality. It is urgent to screening OSAHS from hypertensive patients. An ideal effective questionnaire screening approach for OSAHS is lacking. In this study, we aimed to explore a new OSAHS screening method via weighted combining the current used Epworth sleepiness scale (ESS) and STOP-Bang questionnaire (SBQ) upon calculation.Patients and MethodsThree hundred and sixteen hypertensive patients with suspicion of the OSAHS were enrolled and randomized in the study into ESS, SBQ and portable respiratory polysomnography (RP) tests. The predictive value of ESS, SBQ and weighted combination were evaluated by calculating the area under curve (AUC), sensitivity and specificity, positive and negative likelihood ratio.ResultsBoth the two scales alone and weighted combination were closely related with apnea hypopnea index (AHI), minimum oxygen saturation and average oxygen saturation at night (P < 0.05). The AUC, sensitivity and specificity, positive predictive value (PPV) and negative predictive value (NPV) of ESS in predicting OSAHS were 79.0%, 74.8%, 75.6%, 80.1% and 57.5%, respectively. For SBQ, they were 73.6%, 67.0%, 68.6%, 65.1% and 75.2%, respectively. In contrast, the AUC, sensitivity, and specificity of the combined approach were 82.5%, 73.9% and 82.6%.ConclusionThe weighted combination of ESS and SBQ could improve the diagnostic ability of OSAHS in patients with hypertension, not only in the accuracy and sensitivity, but also for its easy procedure and accessibility and in hospital. Therefore, the weighted combination approach of ESS and SBQ is promising for OSAHS screening.

Relationship of Neck Circumference and Obstructive Sleep Apnea: A Cross-sectional Study in Pakistani Population

Objective: This study aimed to determine the reliability of neck circumference in comparison to BMI for a measure of Obstructive Sleep Apnea and determine the interaction between neck circumference and the severity of apnea in the Pakistani adult population.&#x0D; Materials and Methods: A total of 306 subjects, were recruited retrospectively for the cross-sectional research in the Department of Pulmonary Vascular and Sleep Disorders in Dow University Hospital, Karachi. We reviewed the hospital records to evaluate the BMI, neck circumference, and AHI from June 2018 to February 2022 by non-Random Purposive sampling. The patients 1) who were adults with age more than 18 years and 2) patients with obstructive sleep apnea who were diagnosed through the Polysomnography test were included. IBM SPSS statistics 25 was used for data analysis. Statistical significance was considered as a p-value &lt;0.05.&#x0D; Results: The average age was 52.3 ± 11.4 years. Results showed that sleep apnea was found to be more prevalent and severe in males than in females. Increased neck circumference is associated with the severity of sleep apnea and is found to be significant in male subjects (p=0.018) but not in females (0.577). The neck circumference and the BMI had a statistically significant relationship among the male group and female group (p=0.006 and p=&lt;0.001) which shows that individually neck circumference is not a significant risk factor to diagnose OSA. In multivariate regression, we found a strong association between obesity (OR: 4.3; 95% CI: 2.03-9.38; p-value: 0.00) and males (OR: 2.3; 95% CI: 1.41-3.73; p-value: 0.001) among obstructive sleep apnea patients.&#x0D; Conclusion: In conclusion, the individuals who have large neck circumference have raised BMI, and the traditional indicators for instance males, older age, and BMI were associated with OSA but a larger neck circumference as an independent element was not linked to OSA. In addition, the correlation of large necks with OSA is found to be significant in male subjects but not in females.

Associations between sleep, obesity, and asthma in urban minority children.

Although obesity, asthma, and sleep-disordered breathing are interrelated, there is limited understanding of the independent contributions of body-mass index and pulmonary function on polysomnography in children with asthma. We conducted a retrospective chart review on 448 7- to 18-year-old children with asthma who had undergone polysomnography testing between 1/2007-12/2011 to elucidate the association between spirometry variables, body-mass index, and polysomnography parameters, adjusting for asthma and antiallergic medications. Obese children had poorer sleep architecture and more severe gas exchange abnormalities compared to healthy weight children. Multivariate analysis revealed an independent association of body-mass index with sleep efficiency, with more light and less deep sleep in both obese and healthy-weight children, and with baseline oxygen saturation and oxygen nadir in obese children. In obese children, forced vital capacity was independently associated with less deep sleep (time in N3 sleep) as well as with oxygen nadir, while among healthy-weight children, forced expiratory volume directly correlated but forced vital capacity inversely correlated with deep sleep. In obese children, inhaled corticosteroid was associated with baseline oxygen saturation, and montelukast was associated with lower end-tidal carbon dioxide. In healthy-weight children, inhaled corticosteroid was associated with arousal awakening index, and montelukast was associated with light sleep. Antiallergic medications were not independently associated with polysomnography parameters. Pulmonary function, body-mass index, and asthma medications have independent and differing influences on sleep architecture and gas exchange polysomnography parameters in obese and healthy-weight children with asthma. Asthma medications are associated with improved gas exchange in obese children and improved sleep architecture in healthy-weight children with asthma. Conrad LA, Nandalike K, Rani S, Rastogi D. Associations between sleep, obesity, and asthma in urban minority children. J Clin Sleep Med. 2022;18(10):2377-2385.

Idiopathic central sleep apnea with periodicity presenting as Cheyne-Stokes breathing – Case report

Cheyne-Stokes breathing (CSB) is described by a cyclic variation in breathing with periods of central apneas or hypopneas alternating with periods of hypopneas in a gradual waxing and waning manner. It is usually seen in patients with congestive cardiac failure or neurologic disorders. We describe this rare case of idiopathic central sleep apnea coming in a periodic fashion presenting as CSB pattern without specific causes. Overnight polysomnography test showed central sleep apnea; but cardiac evaluation and magnetic resonance imaging of the brain could not find any cause of this sleep-disordered breathing. Idiopathic central sleep apnea usually presents with poor quality of sleep, but many of them easily misdiagnosed and do not get any proper treatment.

Inpatient CPAP adherence may predict post-discharge adherence in hospitalized patients screened high risk for OSA.

Despite increased recognition of sleep disordered breathing in hospitalized patients, studies are lacking on the impact of inpatient adherence with positive airway pressure (PAP) therapy on post-discharge adherence. To assess the predictive value of inpatient adherence to PAP therapy on post-discharge compliance and adherence. We reviewed data on individuals as part of a registry of a hospital-based sleep medicine program between August 2019 and December 2020. Consecutive patients identified as high risk for sleep disordered breathing based on our 2-tier screening process and initiated on Auto-PAP (APAP) therapy were included. Their adherence and post-discharge course were recorded. Primary objectives were polysomnography (PSG) compliance, sleep medicine clinic follow-up compliance, and 30-day adherence to PAP therapy if indicated by PSG. In total, 900 individuals were screened during the study period. Of these, 281 were offered inpatient PAP therapy. Patients on bilevel PAP therapy (88 patients) were excluded due to lack of objective compliance recording. Final analysis was performed on 193 patients. Of the 193 patients placed on inpatient APAP, 140 (73%) were adherent to the therapy with average usage of 367min per day versus 140min per day in the non-adherent (p < 0.001). There was no significant difference in oxygen desaturation index between the adherent and non-adherent groups (32.4 ± 21.9 events per hour and 34.5 ± 21.9 events per hour consistent; p = 0.5). No demographic and anthropometric characteristics or comorbid conditions were noted. Those who were adherent to PAP therapy in-hospital 47/140 (34%) underwent ambulatory PSG post-discharge compared to 7/53 (13%) of those non-adherent in-hospital (p = 0.002). The adherent group also had significantly higher likelihood for post-discharge clinic follow-up (p = 0.01) and adherence to outpatient PAP therapy (p = 0.01). Hospitalized patients identified as high risk for sleep disordered breathing have high adherence to PAP therapy during hospitalization and inpatient adherence predicts outpatient follow-up (both PSG testing and sleep clinic) and home PAP adherence.