scholarly journals Association between the degree of obstructive sleep apnea and the severity of COVID-19: An explorative retrospective cross-sectional study

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257483
Author(s):  
J. P. T. F. Ho ◽  
H. C. M. Donders ◽  
N. Zhou ◽  
K. Schipper ◽  
N. Su ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Obstructive Sleep Apnea ◽  
Regression Analysis ◽  
Sleep Apnea ◽  
Patient Data ◽  
Sleep Study ◽  
Icu Admission ◽  
Obstructive Sleep ◽  
Osa Treatment

Obstructive sleep apnea (OSA) on its own, as well as its risk factors, have been found to be associated with the outcome of Coronavirus disease 2019 (COVID-19). However, the association between the degree of OSA and COVID-19 severity is unclear. Therefore, the aim of the study was to evaluate whether or not parameters to clinically evaluate OSA severity and the type of OSA treatment are associated with COVID-19 severity. Patient data from OSA patients diagnosed with COVID-19 were reviewed from outpatients from the Isala Hospital and patients admitted to the Isala Hospital, starting from March until December 2020. Baseline patient data, sleep study parameters, OSA treatment information and hospital admission data were collected. Apnea hypopnea index (AHI), low oxyhemoglobin desaturation (LSAT), oxygen desaturation index (ODI), respiratory disturbance index (RDI), and the type of OSA treatment were regarded as the independent variables. COVID-19 severity–based on hospital or intensive care unit (ICU) admission, the number of days of hospitalization, and number of intubation and mechanical ventilation days–were regarded as the outcome variables. Multinomial regression analysis, binary logistic regression analysis, and zero-inflated negative binomial regression analysis were used to assess the association between the parameters to clinically evaluate OSA severity and COVID-19 severity. A total of 137 patients were included. Only LSAT was found to be significantly associated with the COVID-19 severity (p<0.05) when COVID-19 severity was dichotomized as non-hospitalized or hospitalized and ICU admission or death. Therefore, our findings showed that LSAT seems to be a significant risk factor for COVID-19 severity. However, the degree of OSA–based on AHI, ODI, and RDI–and OSA treatment were not found to be risk factors for COVID-19 severity when looking at hospital or ICU admission, the number of days of hospitalization, and number of intubation and mechanical ventilation days.

Abstract P195: Lack of Association between Sleep Duration and ECG Arrhythmia Risk Measures: Chicago Area Sleep Study

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Jason Ng ◽  
Phyllis C Zee ◽  
Jeffrey J Goldberger ◽  
Kristen L Knutson ◽  
Kiang Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Low Risk ◽  
Qtc Interval ◽  
Sleep Study ◽  
Chicago Area ◽  
Obstructive Sleep ◽  
Pr Interval

Introduction Sleep duration is significantly associated with cardiovascular disease risk factors such as hypertension, diabetes, and obesity in adults at low risk for obstructive sleep apnea. Although it is known that apnea increases the risk for sudden cardiac death, it is not known whether adults with short sleep duration independent of apnea have a higher risk for cardiac arrhythmias Hypothesis We tested the hypothesis that sleep duration in adults at low risk for obstructive sleep apnea would be associated with ECG measures that are known risk factors for ventricular arrhythmias. Methods The Chicago Area Sleep Study recruited 610 participants via commercially available telephone listings. Participants were screened using in-home apnea detection equipment (ApneaLinkTM) for one night to exclude subjects with apnea/hypopnea index ≥ 15. Participants wore wrist actigraphs for 7 days to objectively determine sleep duration. A 10-minute 12-lead ECG was recorded for each subject. Standard measures of heart rate, PR interval, and QTc interval were obtained along with markers of ventricular repolarization, Tpeak to Tend interval (Tpe) and spatial QRS-T angle. Signal-averaged ECG analysis was performed to measure filtered QRS duration (fQRSd), RMS voltage of terminal 40 ms (RMS), and duration of terminal QRS signals <40μV (LAS). Participants with atrial fibrillation, >20% ectopic beats and those using antihypertensive and sleep medications were excluded from analysis. The effect of sleep duration on the ECG parameters was estimated using a multiple linear regression model adjusting for demographics (sex, age, and race) and cardiovascular risk factors (BMI, hypertension, coronary heart disease, and diabetes). Results ECGs from a total of 504 participants (200 male, 48±8 years old) were analyzed. Mean sleep duration was 7±1 hrs, heart rate was 64±9 bpm, PR interval was 165±18 ms, and QTc interval was 424±23 ms. Mean Tpe interval was 83±14 ms and spatial QRS-T angle was 29±26 deg. The signal-averaged ECG measures of fQRSd, RMS, and LAS had mean values of 78±12 ms, 58±34 μV, and 24±9 ms, respectively. In an unadjusted model, there was a borderline association between sleep duration and QTc (β=0.004 ms/hr, SE=0.0023, p=0.08). However, that association was no longer significant following adjustment with demographics and cardiovascular risk factors. No other ECG measures were associated with sleep duration. Conclusions In a population at low risk of obstructive sleep apnea, ECG-based measures of cardiovascular risks were not associated with sleep duration. Previously reported associations between short sleep and cardiovascular events may not be arrhythmic in origin.

scholarly journals 864 New-onset Obstructive Sleep Apnea Diagnosis in a COVID-positive Patient

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A336-A336
Author(s):  
Nobel Nguyen ◽  
Kimberly Mebust
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Family History ◽  
Oxygen Saturation ◽  
Sleep Study ◽  
Obstructive Sleep ◽  
Study Results ◽  
Home Sleep Study ◽  
New Onset

Abstract Introduction Risk factors for the mortality of COVID-19, such as cardiovascular and lung disease, are commonly seen in patients with obstructive sleep apnea (OSA). Patients with OSA experience approximately 8-fold greater risk for COVID-19 infection compared to a similar age population. Among patients with COVID-19 infection, OSA was associated with an increased risk of hospitalization and approximately doubled the risk of developing respiratory failure. However, there is little information on whether COVID-19 can directly develop OSA. To the best of our knowledge, we describe the first case-presentation of a positive COVID-19 patient who developed sudden-onset OSA. Report of case(s) NL is a 47-year-old female who complains of new-onset snoring, excessive daytime sleepiness, and witnessed apnea events after testing positive for COVID-19 seven months prior after developing mild symptoms. Her ESS score is 12/24, neck circumference is 14.75 cm, BMI is 27.9, and Mallampati II. She has no pertinent PMH and is not a tobacco user. In regards to her sleep, she has no symptoms of restless legs, narcolepsy, or periodic limb movements. She denies any physical disturbances, psychiatric conditions, environmental factors, or medical issues that might affect her sleep. There is no family history of sleep apnea, snoring, or other sleeping disorders. The patient's presentation at the initial sleep visit prompted a home sleep study. Results of her home sleep study revealed 131 total number of sleep-related respiratory events, with an apnea-hypopnea index of 11.9 per hour. Mean oxygen saturation was 94% and the minimum oxygen saturation was 83%. Total estimated sleep time was 7 hours, 59 mins, and sleep quality and duration were deemed adequate. The results from NL's sleep study gave the final diagnosis of mild OSA. Conclusion Besides having a slightly overweight BMI, NL had relatively few risk factors for developing OSA (no family history, no comorbidities, and normal physical exam findings). The link between the virus and the development of OSA in healthy individuals is not readily apparent. We recommend sleep studies for healthy patients who develop OSA like-symptoms after being infected with COVID-19 to prevent unwanted health risks associated with OSA. Support (if any):

419 STOP-Bang Score and History of Radiation Predicts Risk of Obstructive Sleep Apnea in Cancer Patients: A Machine Learning Study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A166-A166
Author(s):  
Ankita Paul ◽  
Karen Wong ◽  
Anup Das ◽  
Diane Lim ◽  
Miranda Tan
Keyword(s):  
Machine Learning ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Cancer Patients ◽  
Prediction Accuracy ◽  
Screening Tools ◽  
Cancer Type ◽  
Sleep Study ◽  
Obstructive Sleep ◽  
History Of

Abstract Introduction Cancer patients are at an increased risk of moderate-to-severe obstructive sleep apnea (OSA). The STOP-Bang score is a commonly used screening questionnaire to assess risk of OSA in the general population. We hypothesize that cancer-relevant features, like radiation therapy (RT), may be used to determine the risk of OSA in cancer patients. Machine learning (ML) with non-parametric regression is applied to increase the prediction accuracy of OSA risk. Methods Ten features namely STOP-Bang score, history of RT to the head/neck/thorax, cancer type, cancer stage, metastasis, hypertension, diabetes, asthma, COPD, and chronic kidney disease were extracted from a database of cancer patients with a sleep study. The ML technique, K-Nearest-Neighbor (KNN), with a range of k values (5 to 20), was chosen because, unlike Logistic Regression (LR), KNN is not presumptive of data distribution and mapping function, and supports non-linear relationships among features. A correlation heatmap was computed to identify features having high correlation with OSA. Principal Component Analysis (PCA) was performed on the correlated features and then KNN was applied on the components to predict the risk of OSA. Receiver Operating Characteristic (ROC) - Area Under Curve (AUC) and Precision-Recall curves were computed to compare and validate performance for different test sets and majority class scenarios. Results In our cohort of 174 cancer patients, the accuracy in determining OSA among cancer patients using STOP-Bang score was 82.3% (LR) and 90.69% (KNN) but reduced to 89.9% in KNN using all 10 features mentioned above. PCA + KNN application using STOP-Bang score and RT as features, increased prediction accuracy to 94.1%. We validated our ML approach using a separate cohort of 20 cancer patients; the accuracies in OSA prediction were 85.57% (LR), 91.1% (KNN), and 92.8% (PCA + KNN). Conclusion STOP-Bang score and history of RT can be useful to predict risk of OSA in cancer patients with the PCA + KNN approach. This ML technique can refine screening tools to improve prediction accuracy of OSA in cancer patients. Larger studies investigating additional features using ML may improve OSA screening accuracy in various populations Support (if any):

scholarly journals Subjective and Objective Appraisal of Activity in Adults with Obstructive Sleep Apnea

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Eileen R. Chasens ◽  
Susan M. Sereika ◽  
Martin P. Houze ◽  
Patrick J. Strollo
Keyword(s):  
Physical Activity ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Epworth Sleepiness Scale ◽  
Functional Outcomes ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Obstructive Sleep ◽  
Subjective Sleepiness ◽  
Aging Adults

Objective.This study examined the association between obstructive sleep apnea (OSA), daytime sleepiness, functional activity, and objective physical activity.Setting.Subjects (N=37) being evaluated for OSA were recruited from a sleep clinic.Participants. The sample was balanced by gender (53% male), middle-aged, primarily White, and overweight or obese with a mean BMI of 33.98 (SD=7.35;median BMI=32.30). Over 40% reported subjective sleepiness (Epworth Sleepiness Scale (ESS) ≥10) and had OSA (78% with apnea + hypopnea index (AHI) ≥5/hr).Measurements.Evaluation included questionnaires to evaluate subjective sleepiness (Epworth Sleepiness Scale (ESS)) and functional outcomes (Functional Outcomes of Sleep Questionnaire (FOSQ)), an activity monitor, and an overnight sleep study to determine OSA severity.Results.Increased subjective sleepiness was significantly associated with lower scores on the FOSQ but not with average number of steps walked per day. A multiple regression analysis showed that higher AHI values were significantly associated with lower average number of steps walked per day after controlling patient's age, sex, and ESS.Conclusion.Subjective sleepiness was associated with perceived difficulty in activity but not with objectively measured activity. However, OSA severity was associated with decreased objective physical activity in aging adults.

Obstructive Sleep Apnea: Epidemiology, Causes, and Consequences

2020 ◽  
Author(s):  
Diane C Lim ◽  
Richard J Schwab
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Cushing Syndrome ◽  
Upper Airway ◽  
Fat Distribution ◽  
Epidemiologic Studies ◽  
Obstructive Sleep ◽  
Upper Airway Muscles ◽  
Underlying Diseases

As part one of the three chapters on sleep-disordered breathing, this chapter reviews obstructive sleep apnea (OSA) epidemiology, causes, and consequences. When comparing OSA prevalence between 1988 to 1994 and 2007 to 2010, we observe that OSA is rapidly on the rise, paralleling increasing rates in obesity. Global epidemiologic studies indicate that there are differences specific to ethnicity with Asians presenting with OSA at a lower body mass index than Caucasians. We have learned that structural and physiologic factors increase the risk of OSA and both can be influenced by genetics. Structural risk factors include craniofacial bony restriction, changes in fat distribution, and the size of the upper airway muscles. Physiologic risk factors include airway collapsibility, loop gain, pharyngeal muscle responsiveness, and arousal threshold. The consequences of OSA include daytime sleepiness and exacerbation of many underlying diseases. OSA has been associated with cardiovascular diseases including hypertension, coronary heart disease, stroke, atrial fibrillation, and other cardiac arrhythmias; pulmonary hypertension; metabolic disorders such as type 2 diabetes, hypothyroidism, acromegaly, Cushing syndrome, and polycystic ovarian syndrome; mild cognitive impairment or dementia; and cancer. This review contains 4 figures, 1 table and 48 references. Key Words: cardiac consequences, craniofacial bony restriction, epidemiology, fat distribution, metabolic disease, neurodegeneration, obesity, obstructive sleep apnea

Abstract 14771: Obstructive Sleep Apnea is Associated With Cardiac Dysfunction in Children With Congenital Heart Disease

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Daniel Combs ◽  
Vanessa Fernandez ◽  
brent j barber ◽  
Wayne J Morgan ◽  
Chiu-Hsieh Hsu ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Obstructive Sleep Apnea ◽  
Heart Disease ◽  
Sleep Apnea ◽  
Right Ventricular ◽  
Cardiac Dysfunction ◽  
Congenital Heart ◽  
Left Ventricular ◽  
Sleep Study ◽  
Obstructive Sleep

Introduction: Obstructive sleep apnea (OSA) is associated with cardiac dysfunction in children without congenital heart disease (CHD). Children with CHD are at increased risk for OSA and may be susceptible to further cardiovascular consequences due to OSA but the extent and nature of such cardiovascular effects of OSA are unknown. Methods: Children (6-17 years old) with corrected CHD without current cyanosis or Down syndrome were recruited from pediatric cardiology clinic. Home sleep tests were done to determine the presence and severity of OSA. OSA was defined as an obstructive apnea hypopnea index (oAHI) ≥1. Mild OSA was defined as an oAHI of ≥1 to <5 and moderate OSA was defined as an oAHI of ≥5 to <10. Standard clinically indicated echocardiograms were performed in clinic. Echocardiographic findings were compared between children with CHD with and without comorbid OSA using t-tests, Wilcoxon-sign rank tests as well as linear or logistic regression as appropriate. Results: Thirty-two children had sleep study and echocardiographic data available. OSA was present in 18 children (56%). OSA was mild in 89% and moderate in 11% of cases. There were no significant differences in age, body mass index, CHD severity, gender or ethnicity between children with and without OSA. Children with OSA had larger height-indexed right ventricular end-diastolic diameter (RVDi) compared to those without OSA (median 1.35, 95% CI 1.09, 1.56 vs. 1.21, 95% CI 1.01, 1.57; p=0.04). Children with moderate OSA had a reduced left ventricular shortening fraction compared to both those with mild OSA and no OSA (30.0 ± 6.1% vs. 38.7 ± 4.4%; p=0.009 and 39.2 ± 3.6%; p=0.007, respectively). Children with moderate OSA had increased left ventricular end-systolic diameter compared to those with mild OSA and no OSA (3.4 ± 0.4 cm vs. 2.5 ± 0.4; p=0.007 and 2.4 ± 0.5; p=0.001, respectively). Children with an RVDi above the median were seven times more likely to have OSA than those with an RVDi below the median (odds ratio 6.9.; 95% CI 1.3, 35; p=0.02). Conclusions: OSA is associated with changes in cardiac morphology and reduced contractility in children with CHD. Additionally, the presence of right ventricular dilation may suggest the need for OSA evaluation in children with CHD.

scholarly journals Impact of the type of mask on the effectiveness of and adherence to continuous positive airway pressure treatment for obstructive sleep apnea

2014 ◽  
Vol 40 (6) ◽  
pp. 658-668 ◽  
Author(s):  
Rafaela Garcia Santos de Andrade ◽  
Vivien Schmeling Piccin ◽  
Juliana Araújo Nascimento ◽  
Fernanda Madeiro Leite Viana ◽  
Pedro Rodrigues Genta ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Continuous Positive Airway Pressure ◽  
Airway Pressure ◽  
Positive Airway Pressure ◽  
Treatment Effectiveness ◽  
Obstructive Sleep ◽  
Pubmed Database ◽  
Osa Treatment ◽  
The Impact

Continuous positive airway pressure (CPAP) is the gold standard for the treatment of obstructive sleep apnea (OSA). Although CPAP was originally applied with a nasal mask, various interfaces are currently available. This study reviews theoretical concepts and questions the premise that all types of interfaces produce similar results. We revised the evidence in the literature about the impact that the type of CPAP interface has on the effectiveness of and adherence to OSA treatment. We searched the PubMed database using the search terms "CPAP", "mask", and "obstructive sleep apnea". Although we identified 91 studies, only 12 described the impact of the type of CPAP interface on treatment effectiveness (n = 6) or adherence (n = 6). Despite conflicting results, we found no consistent evidence that nasal pillows and oral masks alter OSA treatment effectiveness or adherence. In contrast, most studies showed that oronasal masks are less effective and are more often associated with lower adherence and higher CPAP abandonment than are nasal masks. We concluded that oronasal masks can compromise CPAP OSA treatment adherence and effectiveness. Further studies are needed in order to understand the exact mechanisms involved in this effect.

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