Cessation Of Breathing Research Articles

Utility of Serum Markers in Obstructive Sleep Apnoea Syndrome: A Case-control Study

Introduction: Obstructive Sleep Apnoea Syndrome (OSAS) consists of cessation of breathing for at least 10 seconds during sleep in spite of inspiratory efforts. The OSAS is an independent risk factor for a number of cardiovascular diseases and cerebrovascular events. The OSAS is diagnosed and assessed by polysomnography which is time consuming and expensive. C-Reactive Protein (CRP) and Creatine Phosphokinase (CPK) are markers of systemic inflammation. Inflammatory component is present in OSA. Biomarkers like CRP and CPK may serve as diagnostic tools which are simpler, cheaper and quicker alternatives. Aim: To study the role of serum markers CRP and CPK in the diagnosis of sleep disordered breathing. Materials and Methods: This was a case-control study, conducted from May 2021 to October 2021, in the Department of Pulmonary Medicine, NRI Medical College, Guntur, Andhra Pradesh, India. Total 50 patients were studied for their various symptoms suggestive of OSAS and confirmed by polysomnography were selected for the study. Total 40 age and weight matched controls were included in the study. The association of serum CRP and CPK with OSA was assessed. The Z-test of difference between two proportions was used to compare gender and smoking status of study participants of the two groups. The p-value <0.05 was reported as statistically significant. Results: The mean CRP in those suffering from obstructive sleep apnoea was 12.075±7 mg/dL with 13.89 in moderate to severe OSAS group and 10.26 in mild cases. The CRP showed statistically significant association (p-value=0.00344) with OSA whereas CPK levels in OSA subjects showed no statistically significant association with OSAS. Sensitivity of CRP and CPK compared to the Apnoea Hypopnea Index (AHI) in the diagnosis of OSAS was 66% and 34%, respectively. Specificity of CRP and CPK was 87.5% for both. Positive predictive value for CRP and CPK was 86.8% and 77.2%, respectively. Conclusion: C-reactive protein, a systemic inflammatory marker has a potential role in the diagnosis of OSAS.

Comorbidity analysis in obstructive sleep apnea patients

Background/Aim: Obstructive sleep apnea (OSA) is a syndrome that causes complete or partial cessation of breathing and as a result of several pathways, hypertension (HT), type 2 diabetes mellitus (DM), and hyperlipidemia (HL) are usually seen as comorbidities. The main problem in the literature is, due to the presence of some confounders, especially body mass index (BMI), it is still not clear that if OSA is an independent risk factor for these comorbidities. This issue may be shown more clearly with BMI and age-matched subjects since they are strongly related to metabolic diseases and HT. Comparison of the ratios of the presence of DM, HL, and hypertension between the age and BMI matched groups is primarily aimed in the present study to see if moderate and severe OSA could be an independent risk factor for these comorbidities. Methods: Patients admitted with sleep problems were retrospectively scanned from the patient files and cases with polysomnography and routine blood test were included. The body mass indexes, ages, smoking, and alcohol habits of the cases were noted. Two groups were formed based on polysomnography, taking a threshold value of the apnea-hypopnea index (AHI) of 15. Group 1 had cases with AHI <15 (normal and mild apnea patients) and Group 2 had cases with AHI≥15 (moderate/severe apnea patients). Subjects were accepted as having DM, HL, or HT if they are on medication or if their examination and/or laboratory results show the presence of these diseases. The ratios of these diseases within the groups were compared. Statistical Analysis: Numerical variables were given as mean±standard deviation. Categorical variables were shown as a number. Categorical variables were tested with the Chi-Square test or Fisher’s exact test and an independent T-test was used for two independent groups. Statistical significance was accepted as p<0.05. Results: There were 22 cases with an AHI<15 and 17 cases with an AHI ≥15, with similar mean BMI and age (p= 0.206, p= 0.054 respectively). The ratio of hypertension was found significantly higher in moderate/severe OSA patients (47% vs 5%; p=0.005). On the other hand, the ratios of DM and HL were found statistically similar (p=0.49, p=1.0 respectively). Conclusion: This study aimed to show the possible independent role of sleep apnea in metabolic diseases and HT, by creating two groups with similar BMI, age, and cigarette and alcohol habits. The results support moderate/Severe OSA as an independent risk factor for hypertension, while DM and HL are thought to be in close relationship with BMI.

Effects of Obstructive Sleep Apnea Syndrome on Cardiovascular Risk

Obstructive sleep apnea harms sleep and health in about 2–4% of the adult population. It progresses with repeated respiratory breaks during sleep, alternating with strong snoring. An increased number of wakes leads to incomplete sleep with excessive daytime sleepiness, decreased working capacity, memory disorders, attention and concentration impairment. Breathing cessation puts the body in conditions of hypoxia and increased stress. Hypoxia damages all organs and systems, the cardiovascular and endocrine systems in particular. In the period 01/2017–06/2021 our team has diagnosed obstructive sleep apnea syndrome in 82 patients using polygraph testing at home. Patients were followed by clinical examination, measurement of arterial pressure, electrocardiogram, echocardiography, and BMI in order to assess the presence of cardiovascular complications (arterial hypertension, arrhythmias, ischemic heart disease, heart failure).

Sleep apnoea and heart failure

Heart failure and sleep disordered breathing (SDB) are two common conditions that frequently overlap and have been studied extensively in the past three decades. Obstructive sleep apnoea (OSA) may result in myocardial damage due to intermittent hypoxia that leads to increased sympathetic activity and transmural pressures, low-grade vascular inflammation, and oxidative stress. On the other hand, central sleep apnoea and Cheyne-Stokes respiration (CSA-CSR) occurs in heart failure, irrespective of ejection fraction, either reduced (HFrEF), preserved (HFpEF) or mildly reduced (HFmrEF). The pathophysiology of CSA-CSR relies on several mechanisms leading to hyperventilation, breathing cessation and periodic breathing. Pharyngeal collapse may result at least in part from fluid accumulation in the neck, owing to daytime fluid retention and overnight rostral fluid shift from the legs. Although both OSA and CSA-CSR occur in heart failure, the symptoms are less suggestive than in typical (non-heart failure-related) OSA. Overnight monitoring is mandatory for a proper diagnosis, with accurate measurement and scoring of central and obstructive events, since the management will be different depending on whether the sleep apnoea in heart failure is predominantly OSA or CSA-CSR. SDB in heart failure is associated with worse prognosis, including higher mortality, than in patients with heart failure but without SDB. However, there is currently no evidence that treating SDB improves clinically important outcomes in patients with heart failure, such as cardiovascular morbidity and mortality.

Automatic Home-based Screening of Obstructive Sleep Apnea using Single Channel Electrocardiogram and SPO2 Signals

Obstructive sleep apnea (OSA) is one of the most widespread respiratory diseases today. Complete or relative breathing cessations due to upper airway subsidence during sleep is OSA. It has confirmed potential influence on Covid-19 hospitalization and mortality, and is strongly associated with major comorbidities of severe Covid-19 infection. Un-diagnosed OSA may also lead to a variety of severe physical and mental side-effects. To score OSA severity, nocturnal sleep monitoring is performed under defined protocols and standards called polysomnography (PSG). This method is time-consuming, expensive, and requiring professional sleep technicians. Automatic home-based detection of OSA is welcome and in great demand. It is a fast and effective way for referring OSA suspects to sleep clinics for further monitoring. On-line OSA detection also can be a part of a closed-loop automatic control of the OSA therapeutic/assistive devices. In this paper, several solutions for online OSA detection are introduced and tested on 155 subjects of three different databases. The best combinational solution uses mutual information (MI) analysis for selecting out of ECG and SpO2-based features. Several methods of supervised and unsupervised machine learning are employed to detect apnoeic episodes. To achieve the best performance, the most successful classifiers in four different ternary combination methods are used. The proposed configurations exploit limited use of biological signals, have online working scheme, and exhibit uniform and acceptable performance (over 85%) in all the employed databases. The benefits have not been gathered all together in the previous published methods.

Apnea Spells in a Term Neonate.

Apnea Spells in a Term Neonate.

Polysomnographic Plethysmography Excursions are Reduced in Obese Elderly Men.

Sleep apnea is a widespread disorder and is defined by the complete or partial cessation of breathing. Obstructive sleep apnea (OSA) is caused by an obstruction in the upper airway while central sleep apnea (CSA) is characterized by a diminished or absent respiratory effort. It is crucial to differentiate between these respiratory subtypes as they require radically different treatments. Currently, diagnostic polysomnography (PSG) is used to determine respiratory thoracic and abdominal movement patterns using plethysmography belt signals, to distinguish between OSA and CSA. There is significant manual technician interrater variability between these classifications, especially in the evaluation of CSA. We hypothesize that an increased body mass index (BMI) will cause decreased belt signal excursions that increase false scorings of CSA. The hypothesis was investigated by calculating the envelope as a continuous signal of belt signals in 2833 subjects from the MrOS Sleep Study and extracting a mean value of each of the envelopes for each subject. Using linear regression, we found that an increased BMI was associated with lower excursions during REM sleep (-0.013 [mV] thoracic and -0.018 [mV] abdominal, per BMI) and non-REM (-0.014 [mV] thoracic and -0.012 [mV] abdominal, per BMI). We conclude that increased BMI leads to lower excursions in the belt signals during event-free sleep, and that OSA and CSA events are harder to distinguish in subjects with high BMI. This has a major implication for the correct identification of CSA/OSA and its treatment.

Noncontact Sleep Monitoring With Infrared Video Data to Estimate Sleep Apnea Severity and Distinguish Between Positional and Nonpositional Sleep Apnea: Model Development and Experimental Validation.

BackgroundSleep apnea is a respiratory disorder characterized by frequent breathing cessation during sleep. Sleep apnea severity is determined by the apnea-hypopnea index (AHI), which is the hourly rate of respiratory events. In positional sleep apnea, the AHI is higher in the supine sleeping position than it is in other sleeping positions. Positional therapy is a behavioral strategy (eg, wearing an item to encourage sleeping toward the lateral position) to treat positional apnea. The gold standard of diagnosing sleep apnea and whether or not it is positional is polysomnography; however, this test is inconvenient, expensive, and has a long waiting list.ObjectiveThe objective of this study was to develop and evaluate a noncontact method to estimate sleep apnea severity and to distinguish positional versus nonpositional sleep apnea.MethodsA noncontact deep-learning algorithm was developed to analyze infrared video of sleep for estimating AHI and to distinguish patients with positional vs nonpositional sleep apnea. Specifically, a 3D convolutional neural network (CNN) architecture was used to process movements extracted by optical flow to detect respiratory events. Positional sleep apnea patients were subsequently identified by combining the AHI information provided by the 3D-CNN model with the sleeping position (supine vs lateral) detected via a previously developed CNN model.ResultsThe algorithm was validated on data of 41 participants, including 26 men and 15 women with a mean age of 53 (SD 13) years, BMI of 30 (SD 7), AHI of 27 (SD 31) events/hour, and sleep duration of 5 (SD 1) hours; 20 participants had positional sleep apnea, 15 participants had nonpositional sleep apnea, and the positional status could not be discriminated for the remaining 6 participants. AHI values estimated by the 3D-CNN model correlated strongly and significantly with the gold standard (Spearman correlation coefficient 0.79, P<.001). Individuals with positional sleep apnea (based on an AHI threshold of 15) were identified with 83% accuracy and an F1-score of 86%.ConclusionsThis study demonstrates the possibility of using a camera-based method for developing an accessible and easy-to-use device for screening sleep apnea at home, which can be provided in the form of a tablet or smartphone app.

Opioids and obstructive sleep apnea.

Freire C, Sennes LU, Polotsky VY. Opioids and obstructive sleep apnea. J Clin Sleep Med. 2022;18(2):647-652.

P021 Does Obstructive Sleep Apnea (OSA) lead to impairment within the cochlea?

Abstract Introduction The cessation of breathing with OSA is linked to the continuous decrease in oxygen saturation throughout the night which could impact the inner ear as it is sensitive to hypoxic changes. Inner ear hair cells response from the cochlea is measured through Transient Otoacoustic Emission (TEOAEs). This study aimed to evaluate TEOAEs in suspected OSA patients and its correlation with oxygen saturation. Methods TEOAEs were measured before sleep and in the morning in suspected OSA patients and healthy participants. The following frequencies were measured: 1000Hz, 1500Hz, 2000Hz, 3000Hz and 4000Hz. Polysomnography with oxygen saturation was completed overnight. Preliminary analysis was completed on 11 no OSA, 22 mild OSA, 13 moderate OSA and 27 severe OSA patients. Results One-way ANOVA with Tukey post-hoc analysis revealed a difference between severe vs mild with average TEOAE only (p = 0.04). A moderate correlation was found between average TEOAE and minimum O2 saturation, rs (72) = 0.444, p&amp;lt; 0.0001) through Spearman’s rank-order correlation. As middle ear function can impact TEOAE results, regression analysis revealed an association between a decrease in TEOAE and lowered minimum O2 saturation (F (1,63) = 8.951, p = 0.004, partial n2 = 0.124) when middle ear pressure was controlled. Discussion Oxygen desaturation with OSA is associated with a decrease in inner ear hair cells response, which was independent from middle ear function. Despite this association, a difference in TEOAE was only found between severe vs mild, which could be due to the current sample size of the preliminary data.

Sleep-disordered breathing-related symptoms and risk of stroke: cohort study and Mendelian randomization analysis

BackgroundSleep-disordered breathing (SDB) may contribute to development of stroke. However, findings are inconclusive. We investigated whether SDB-related symptoms are associated with incidence of stroke and its types in a general community sample of adult men and women as well as to perform Mendelian randomization (MR) analysis.MethodsWe used data from a cohort of 41,742 Swedish adults (56–94 years of age) who completed questionnaires regarding snoring, cessation of breathing, lifestyle and health characteristics. Participants were followed up for incident stroke and death over 8 years through linkage to the Swedish Registers. Hazard ratios, adjusted for potential confounders, were estimated by Cox proportional hazards regression. MR analyses were performed using single-nucleotide polymorphisms associated with sleep apnea at the genome-wide significance level and summary-level data for stroke and its subtypes from consortia and a meta-analysis of Genome-Wide Association Studies.ResultsIn the cohort study, symptoms of disturbing snoring and/or cessation of breathing were associated with increased risk of total stroke (hazard ratio 1.12, 95% confidence interval 1.02–1.24) and intracerebral hemorrhage (hazard ratio 1.59, 95% confidence interval 1.23–2.05) but not with ischemic stroke or subarachnoid hemorrhage. MR analyses showed no association of genetic liability to sleep apnea with the risk of overall stroke or any specific types of stroke or ischemic stroke subtypes.ConclusionsSDB-related symptoms were associated with increased risk of total stroke, specifically intracerebral hemorrhage, in the observational analyses but not in the MR analyses. There was limited evidence of an association of SDB with ischemic stroke and subarachnoid hemorrhage.

The timing of intermittent hypoxia differentially affects macronutrient intake and energy substrate utilization in mice.

Sleep apnea is a common sleep disorder characterized by periodic breathing cessation and intermittent hypoxia (IH). Although previous studies have demonstrated that IH alone can influence metabolic outcomes such as body weight, it remains unclear how the timing of IH can specifically affect these outcomes. Here, we examine how pairing 10-h periods of IH to either the animals' resting phase (e.g., IH during the day) or active phase (e.g., IH during the night) differentially affects body weight, macronutrient selection, energy expenditure, respiratory exchange rate, and glucose tolerance. We find that in contrast to mice exposed to IH during the night, mice exposed to IH during the day preferentially decrease their carbohydrate intake and switch to fat metabolism. Moreover, when the IH stimulus was removed, mice that had been exposed to day IH continued to eat a minimal amount of carbohydrates and consumed a higher percentage of kilocalorie from fat for at least 5 days. These data demonstrate that food choice and substrate utilization are secondary to the timing of IH but not IH itself. Taken together, these data have key clinical implications for individuals with sleep apnea and particularly those who are also experiencing circadian disruption such as night-shift workers.NEW & NOTEWORTHY Pairing repeated hypoxic episodes to a mouse's resting phase during the day preferentially decreases carbohydrate intake and results in a switch to metabolic fat oxidation. These data indicate that the timing of intermittent hypoxia should be considered when calculating sleep apnea's effects on metabolic outcomes.

Sleeping, Smoking, and Kidney Diseases: Evidence From the NHANES 2017-2018.

Study Objectives: Smoking and sleep are modifiable factors associated with the chronic kidney diseases. However, the interaction of smoking and sleep on the renal function are still unclear. Therefore, we aimed to evaluate the interactive impacts of smoking and sleep on the renal function.Methods: Data were obtained from the National Health and Nutrition Examination Survey. The study population were categorized into nine subgroups by smoking (smoking every day, sometimes, and non-smokers recently) and sleep duration (short duration ≤ 6 h, normal duration 6–9 h, and longer duration ≥ 9 h on the weekdays).Results: The study group with a short sleep duration had significantly higher serum cotinine and hydrocotinine levels compared with the other two sleep groups. After adjusting the demographic characteristics (age, race, body mass index, and marital status), sleep quality (snoring or breathing cessation), and comorbidities (diabetes mellitus, hypertension, high cholesterol, anemia, congestive heart failure, coronary heart disease, and stroke), non-smokers with short or long sleep duration had significant lower estimated glomerular filtration rate (eGFR) levels than the study group who smoked every day and slept ≤ 6 h. The effects of sleep duration on eGFR levels varied with smoking status. For the study group smoking every day, eGFR levels increased as sleep duration decreased, whereas for the study group smoking sometimes, eGFR levels increased as sleep duration increased. The U-shaped effects of eGFR levels were observed among non-smokers whose normal sleep duration was associated with better eGFR levels. Normal sleep duration was an important protective factor of the renal function for non-smokers than smokers.Conclusions: The effects of sleep duration on eGFR levels varied with smoking status. Normal sleep duration was a protective factor and more crucial for non-smokers than for smokers.

Detection of sleep apnea using deep neural networks and single-lead ECG signals

Sleep apnea causes frequent cessation of breathing during sleep. Feature extraction approaches play a key role in the performance of apnea detection algorithms that use single-lead electrocardiogram signals. Handcrafted features have high computational complexity due to their large dimensions and are usually not robust. To cope with the mentioned problems, in the current paper, an automatic feature extraction method is developed by combining the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) recurrent network. Also, the fully connected layers are utilized to distinguish apnea events from the normal segments. Then, the apnea-hypopnea index (AHI) is applied to discriminate apnea subjects from healthy ones. Finally, in order to assess the usefulness of the proposed method, some experiments are conducted on the publicly accessible Apnea-ECG and UCDDB datasets. The results based on the sensitivity (94.41%), specificity (98.94%), and accuracy (97.21%), indicate that our proposed method provides significant improvements compared to the other sleep apnea detection methods. Our model also achieves an accuracy of 93.70%, sensitivity of 90.69%, and specificity of 95.82% for UCDDB dataset. It can be inferred that using the deep-learning based algorithm for detecting apnea patients would help physicians in making a decision more accurately.

Changes in Sleep Parameters in Different Age Groups between Genders

Aim: To examine the changes in sleep parameters related to sex between the patients over 65 years old and younger group. Method:A total of 293 patients who applied to the sleep clinic with complaints such as snoring, cessation of breathing during sleep, and excessive daytime sleepiness (GAUH) and whose Polysomnography (PSG) were taken were included in the study. Of these patients, 71 people were in the group over 65 (Male: 43, Female: 28) and 222 people (Male: 139, Female: 83) were in the group between the ages of 45-60. The medical histories of the patients were retrospectively scanned from the patient files. Among the PSG parameters, Total Sleep Time, Sleep Efficiency (%), REM sleep rate (%), NREM sleep rate (%), AHI (Apnea Hypopnea index), REM AHI, NREM AHI, minimum oxygen saturation (min O2 hours), mean oxygen saturation (mean O2 hours), oxygen desaturation time (min) and oxygen desaturation index (ODI) were recorded. Results: When sleep parameter changes between age groups were examined, regardless of gender, it was observed that sleep efficiency (the ratio of total sleep time to length of stay in bed) was significantly decreased in the 65+ age group compared to the younger group (73.69±17.49 and 79.44±14.65 p: 0.014). When the total sleep duration (244.38±97.44 and 284.51±93.40) and sleep efficiency data (73.55±16.16 and 82.19±14.13 p:0.002 ) of PSG parameters in male patients were examined, it was seen that the data of the over 65 age group were lower than the young group. When the minimum and mean oxygen saturation in female patients was examined, it was observed that the group over 65 years had lower levels (minimum oxygen saturation: 71.14±13.52 and 77.97±11.01 p:0.021, mean oxygen saturation: 89.78±4.52 and 91.93±3.70 p:0.030). Desaturation (%) was found to be lower in the elderly group also.(30.52±33.71 and 12.22±18.97 p:0.012) Conclusion: In this study, decreases in total sleep duration, sleep efficiency, minimum oxygen saturation, average oxygen saturation and desaturation (%) were detected in sleep parameters in advanced age compared to younger ages. Further studies with larger participation and younger patients are needed to support the results and for the new results.

Prediction of obstructive sleep apnea using ensemble of recurrence plot convolutional neural networks (RPCNNs) from polysomnography signals

Obstructive Sleep Apnea (OSA) is a common disorder characterized by periodic cessation of breathing during sleep. OSA affects daily life and poses a severe threat to human health. The standard clinical method for identifying and predicting OSA events is the use of Polysomnography signals.In this paper, a novel scheme based on an ensemble of recurrence plots (RPs) and pre-trained convolutional neural networks (RPCNNs) is proposed to improve the prediction rate of OSA. First, RPs were used to represent the dynamic behavior of single electroencephalogram (EEG) and electrocardiogram (ECG) signals for 60 s before and during OSA events. Then, using RPs, three prompt CNNs named ResNet-50 were fine-tuned, and their classification results were fused via the Majority Voting (MV) method to produce a final result concerning prediction. Next, the subject-independent Leave-One-Subject-Out Cross-Validation (LOSO-CV) and subject-dependent 10-fold Cross-Validation (10-fold CV) methods were used to validate the prediction rate from signals derived from the University College Dublin Sleep Apnea Database. Finally, the highest achieved average accuracy for the fusion level was 91.74% and 89.45% at the 10-fold CV and LOSO-CV. Additionally, our results outperformed state-of-the-art findings and could be recommended to predict and detect other biomedical signals. As a result, this predictive system can also be used to adjust the air pressure in sleep apnea patients' Automatic Positive Airway Pressure (APAP) devices.

ОБРАЗ СМЕРТИ В ТЕКСТАХ КЕТСКОЙ ЛИНГВОКУЛЬТУРЫ

A fragment of the linguistic view of the world of the Kets, a minority ethnos, whose language is going through a period of shift, is reconstructed. The category of mortality is implicated on the basis of vocabulary united by the meanings “death”, “to die”. Through the analysis of contexts, including this vocabulary, the peculiarities of the linguistic representation of ideas about the category of death are revealed and cognitive-figurative models that order these representations are identified. As a result of the study, it is found that metaphorization and description of visual signs in the Ket language act as key mechanisms for the linguization of the phenomenon of death, and the meanings expressed in discourse reveal an ambivalent and antinomic character. Along with such metaphors as “eternal sleep,” “withdrawal into another world,” the Ket discourse of death also contains direct descriptions of objective ones, i.e. visible manifestations of the category under discussion - cessation of breathing, inability to move, etc. An analysis of the Ket discourse of death indicates that the belief in the immortality of the soul and the other world, expressed in it, is intended to neutralize the fear of death. On the other hand, plots are revealed that express the possibility of struggle and victory over death. This indicates that death is understood as an undesirable, frightening phenomenon that opposes the successful course of a person’s life events.

CORRELATION BETWEEN SLEEP APNEA AND METHADONE THERAPY

Introduction: Methadone therapy is the mainstay of treatment of addict patients. The most common side effects are: dizziness, drowsiness, vomiting, sweating, dry mouth and constipation. The more serious complications that can be observed are: sleep apnea, аbnormal heart rhythms, respiratory problems, euphoria, disorientation, anxiety, seizures and more. Purpose: The purpose of this study is to determine the correlation between methadone maintenance treatment and sleep apnea in addict patients. Materials and methods: The subject of the study are 81 methadone-treated drug-dependent patients, mean age 39 ± 9,07 years. Results: The answers we received: 79% (64) of drug addicts have problems with sleep; 30.9% of them (25) reported having insomnia; 44.4% (36) experience morning fatigue; 56.8% (46) of the respondents said they were drowsy during the day and 63% of the respondents reported a change in mood; 21% (17) had a short sleep, and 26% (21)reported snoring and 18 of them have loud bothering snoring; 68% answered that they don't have problems with falling asleep and only 21% don’t wake up frequently in the evening. In 83.9% nobody noticed cessation of breathing during sleep. 73.8% never nodded off or fallen asleep while driving a vehicle. 16.1% have been treated for high blood preasure, and only 2.5% have obesity. Conclusions: Our survey found that there is a correlation between methadone therapy and sleep of patients. The key to improving the condition and reducing the risk of central sleep apnea is the monitoring of patients, as well as a combination of different types of treatment.

Neonate Apnea Nursing Care in Neonatal Intensive Care Unit

Apnea is a common occurrence in sick neonates, characterized as a cessation of breathing those results inpathological changes in heart rate and oxygen saturation. In the neonatal age, apnea is the most commonform of breathing disorder. A neonate with apnea must be admitted to a special ward known as a neonatalintensive care unit (NICU) (1)The study aims to study nurse’s knowledge regarding nursing management of apnea in neonate and to detectassociation between nurse’s knowledge of apnea in neonate and nurses demographic data.A descriptive hospital based is carried out at neonatal intensive care unit at Bint Al-Huda teaching hospitaland Al-Musawi pediatric hospital, the study period from 3 January 2021 and 15 Abril 2021. Total coverage(50) nurses were participated in the study to achieve the objective of the study the researcher has establishedthe constructed questionnaire which consists of two parts (1) sociodemographic data for nurses 4 items,(2) knowledge of nurses about apnea in neonate that consist of 17- items. Data were coded &amp; analyzed byelectronic was sent to the nurses participants in the study through social media after taking the approval ofDhi Qar health directorate to research in hospitals covered by the study and statistical tables and pie chartswere construct from the data using a statistical package for social sciences (SPSS) program version 20 andexcel.Results: The finding of the present study suggested that assessment of nurses’ Knowledge about nursingmanagement for apnea in neonate. The level of knowledge (16% good, (48 % )fair,(36%) poor knowledge,because their relative sufficiency (76%) were under cutoff point(4), there is a significant association betweennurses’ knowledge about nursing management and demographic data such (age –level of education and levelof experience) in neonatal intensive care unit by P value &lt; 0.05. The study indicated to provide Nursingmanagement of apnea in neonates’ educational program for nurses, including updating booklets, pamphlets,and boosters to help nurses improve their awareness of apnea in neonates.

Evaluation of a Modified STOP-BANG Questionnaire for Sleep Apnea in Adults from the Korean General Population

Background and Objective There are few studies assessing diagnostic accuracy of the STOP-BANG questionnaire, which is a screening tool for detecting obstructive sleep apnea (OSA), in the general population. Our study aimed to develop a modified version of this screening questionnaire and compare its diagnostic accuracy to the standard version in general Korean adults. Methods A cross-sectional polysomnographic study was conducted among 2065 male and female participants aged 48–79 years, who were members of a population-based cohort study. Half of them were assigned to the exploratory sample and the other half to the validation sample. Results In this study, 958 individuals (487 in an exploratory sample) were identified to have OSA. To develop a model in an exploratory sample, stepwise analysis was used with information from the standard version and additional variables; snoring, witnessed breathing cessation, hypertension, body mass index > 25 kg/m2, age groups, male, diabetes, and waist circumference > 85 cm were included in a final modified model. In the evaluation of diagnostic accuracy in a validation sample, the modified model showed higher sensitivity [79.1%, 95% confidence interval (CI): 77.3, 80.9] in detecting severe OSA than that of the standard version model (66.0%, 95% CI: 64.0, 68.0). Overall accuracy indicated as area under the receiver-operating characteristic curve for the modified model was greater (p = 0.001) than that of the standard version model. Conclusions These findings suggest that the modified version of the STOP-BANG questionnaire may be useful in detecting severe OSA in general adults. Key words: Obstructive sleep apnea, Mass screening, Polysomnography