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Diagnosis and Management of Obstructive Sleep Apnea

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A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 28566

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Dr. Bilgay Izci Balserak

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Guest Editor

Department Biobehavioral Nursing Science, Center for Sleep and Health Research, College of Nursing, University of Illinois, 845 South Damen Avenue (MC 802), Chicago, IL, USA
Interests: sleep apnea; upper airway; inflammation; screening tools; sleep interventions; sleep health; adverse health outcomes associated with sleep disturbances (specially in women); power-spectral analysis of EEG; mechanisms; imaging techniques; knowledge of obstructive sleep apnea in clinicians; health disparity

Special Issue Information

Dear Colleagues,

Obstructive sleep apnea (OSA) is repeated upper airway obstruction (complete/partial) caused by a loss of upper airway muscle tone during sleep, resulting in intermittent hypoxia and sleep fragmentation. OSA with daytime sleepiness affects 3–7% of men and 2–5% of women. OSA is more common in men, post-menopausal women, obese, and middle-aged or older individuals. Untreated OSA has been linked to increased risk of multiple adverse health outcomes including cardiovascular diseases, neurocognitive impairment, metabolic syndrome and gestational diabetes. The diagnosis of OSA is challenging. It is estimated that up to 80% of individuals remain undiagnosed. The first obstacle is the recognition of risk for OSA. Sleep studies (polysomnogram (PSG) and home sleep apnea testing (HSAT)) are considered positive for OSA if the apnea-hypopnea index (AHI) exceeds five events per hour.

Continuous positive airway pressure (CPAP) is a very effective treatment for OSA, but poor adherence significantly limits its use. Mandibular advancement devices and hypoglossal nerve stimulation are alternative treatments in patients who cannot tolerate CPAP. Weight-loss surgery, dietary weight-loss and exercise have been shown to improve OSA. There has been no effective pharmacotherapy, but promising drug candidates are emerging. Personalized medicine approaches are also being developed to guide OSA interventions.

For an upcoming Special Issue in Diagnostics entitled “The Diagnosis and Management of OSA”, we aim to gather a collection of comprehensive reviews and cutting-edge research from translational and clinical viewpoints that will stimulate continuing efforts to develop better diagnostic strategies and therapies for OSA (clinical studies will be given priority). We welcome submissions on, but not limited to, the following topics:

Diagnostic or prognostic biomarkers;
Diagnostic or prognostic scoring;
Precision medicine;
Predictors of treatment responses;
Novel therapeutic approaches;
Novel diagnostic techniques, including imaging techniques;
Diagnosis of OSA and treatment of OSA in women (e.g., pregnant and post-menopausal women);
Diagnosis and treatment of OSA in children;
Diagnosis and treatment of OSA in mission-critical workers (e.g., airline pilots, bus drivers, police, military posts etc.);
Novel aspects of CPAP treatment and interventions to improve CPAP adherence;
Oral appliances in OSA: state-of-the-art;
Hypoglossal nerve stimulation: novel approaches.

Dr. Bilgay Izci Balserak
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

obstructive sleep apnea
oral appliance
CPAP
lifestyle interventions
adherence
women’s sleep apnea
pediatrics
home sleep apnea testing
imaging techniques
novel diagnostics

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Published Papers (10 papers)

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Editorial

Jump to: Research

2 pages, 169 KiB

Open AccessEditorial

Special Issue: The Diagnosis and Management of OSA

by Bilgay Izci Balserak

Diagnostics 2022, 12(8), 1919; https://doi.org/10.3390/diagnostics12081919 - 8 Aug 2022

Cited by 1 | Viewed by 1268

Abstract

Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing (SDB) and is demonstrating an increasing prevalence worldwide [...] Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

Research

Jump to: Editorial

12 pages, 4318 KiB

Open AccessArticle

Racial Differences in Functional and Sleep Outcomes with Positive Airway Pressure Treatment

by Ikuyo Imayama, Bilgay Izci Balserak, Ahana Gupta, Tomas Munoz, Manassawee Srimoragot, Brendan T. Keenan, Samuel T. Kuna and Bharati Prasad

Diagnostics 2021, 11(12), 2176; https://doi.org/10.3390/diagnostics11122176 - 23 Nov 2021

Cited by 2 | Viewed by 1772

Abstract

It is unclear if the response to positive airway pressure (PAP) treatment is different between African American (AA) and European Americans (EA). We examined whether race modifies the effects of PAP on sleep and daytime function. We assessed Epworth Sleepiness Scale (ESS), Functional Outcomes of Sleep Questionnaire, Psychomotor Vigilance Task and actigraphy in 185 participants with moderate-to-severe obstructive sleep apnea before and 3–4 months after PAP treatment. The participants were middle-aged (mean, 55.1 years), 83.8% men and 60.5% AA. Linear regression models were used to examine the effect of race on outcomes. The AA had smaller reductions in ESS (mean change (95% confidence interval, CI) AA, −2.30 [−3.35, −1.25] vs. EA, −4.16 [−5.48, −2.84] and frequency of awakenings (AA, −0.73 [−4.92, 3.47] vs. EA, −9.35 [−15.20, −3.51]). A race × PAP usage interaction term was added to the model to examine if the change in outcomes per 1 h increase in PAP usage differed by race. AA exhibited greater improvement in wake after sleep onset (β (95% CI) AA, −8.89 [−16.40, −1.37] vs. EA, 2.49 [−4.15, 9.12]) and frequency of awakening (β (95% CI) AA, −2.59 [−4.44, −0.75] vs. EA, 1.71 [−1.08, 4.50]). The results indicate the importance of race in evaluating outcomes following PAP treatment. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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14 pages, 2532 KiB

Open AccessArticle

Classification of Sleep Apnea Based on Sub-Band Decomposition of EEG Signals

by Rajeswari Jayaraj and Jagannath Mohan

Diagnostics 2021, 11(9), 1571; https://doi.org/10.3390/diagnostics11091571 - 30 Aug 2021

Cited by 14 | Viewed by 3055

Abstract

To classify between normal and sleep apnea subjects based on sub-band decomposition of electroencephalogram (EEG) signals. This study comprised 159 subjects obtained from the ISRUC (Institute of System and Robotics—University of Coimbra), Sleep-EDF (European Data Format), and CAP (Cyclic Alternating Pattern) Sleep database, which consists of normal and sleep apnea subjects. The wavelet packet decomposition method was incorporated to categorize the EEG signals into five frequency bands, namely, alpha, beta, delta, gamma, and theta. Entropy and energy (non-linear) for all bands was calculated and as a result, 10 features were obtained for each EEG signal. The ratio of EEG bands included four parameters, including heart rate, brain perfusion, neural activity, and synchronization. In this study, a support vector machine with kernels and random forest classifiers was used for classification. The performance measures demonstrated that the improved results were obtained from the support vector machine classifier with a kernel polynomial order 2. The accuracy (90%), sensitivity (100%), and specificity (83%) with 14 features were estimated using the data obtained from ISRUC database. The proposed study is feasible and seems to be accurate in classifying the subjects with sleep apnea based on the extracted features from EEG signals using a support vector machine classifier. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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14 pages, 1045 KiB

Open AccessArticle

Association of Excessive Daytime Sleepiness with the Zung Self-Rated Depression Subscales in Adults with Coronary Artery Disease and Obstructive Sleep Apnea

by Yeliz Celik, Hale Yapici-Eser, Baran Balcan and Yüksel Peker

Diagnostics 2021, 11(7), 1176; https://doi.org/10.3390/diagnostics11071176 - 28 Jun 2021

Cited by 8 | Viewed by 2693

Abstract

Excessive daytime sleepiness (EDS) is a factor associated with both obstructive sleep apnea (OSA) and depressive symptoms. Continuous positive airway pressure (CPAP) treatment may decrease EDS in adults with OSA; however, the modulatory role of depressive symptoms on the improvement of EDS is not known. We aimed to explore the association between subscales of the Zung Self-rated Depression Scale (SDS) and Epworth Sleepiness Scale (ESS) over a 2-year period in coronary artery disease (CAD) patients with OSA. This was a post-hoc analysis of the RICCADSA cohort, in which 399 adults with CAD (155 sleepy OSA [apnea–hypopnea index ≥ 15/h] and ESS score ≥ 10, who were offered CPAP; and 244 nonsleepy OSA [ESS < 10]), randomized to CPAP [n = 122] or no-CPAP [n = 122]) were included. Three factors were extracted from the Zung SDS, based on the principal component analysis: F1, cognitive symptoms and anhedonia; F2, negative mood; and F3, appetite. In a mixed model, the ESS score decreased by 3.4 points (p < 0.001) among the sleepy OSA phenotype, which was predicted by the decline in the F2, but not in the F1 and F3 scores. The fixed effects of time were not significant in the nonsleepy OSA groups, and thus, further analyses were not applicable. Additional within-group analyses showed a significant decrease in all subscales over time both in the sleepy and nonsleepy OSA patients on CPAP whereas there was a significant increase in the nonsleepy OSA group randomized to no-CPAP. We conclude that the improvement in negative mood symptoms of depression, but not changes in cognitive symptoms and anhedonia as well as appetite, was a significant predictor of decline in the ESS scores over a 2-year period in this CAD cohort with sleepy OSA on CPAP treatment. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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15 pages, 844 KiB

Open AccessArticle

Screening Severe Obstructive Sleep Apnea in Children with Snoring

by Hui-Shan Hsieh, Chung-Jan Kang, Hai-Hua Chuang, Ming-Ying Zhuo, Guo-She Lee, Yu-Shu Huang, Li-Pang Chuang, Terry B.-J. Kuo, Cheryl C.-H. Yang, Li-Ang Lee and Hsueh-Yu Li

Diagnostics 2021, 11(7), 1168; https://doi.org/10.3390/diagnostics11071168 - 26 Jun 2021

Cited by 11 | Viewed by 3475

Abstract

Efficient screening for severe obstructive sleep apnea (OSA) is important for children with snoring before time-consuming standard polysomnography. This retrospective cross-sectional study aimed to compare clinical variables, home snoring sound analysis, and home sleep pulse oximetry on their predictive performance in screening severe OSA among children who habitually snored. Study 1 included 9 (23%) girls and 30 (77%) boys (median age of 9 years). Using univariate logistic regression models, 3% oxygen desaturation index (ODI3) ≥ 6.0 events/h, adenoidal-nasopharyngeal ratio (ANR) ≥ 0.78, tonsil size = 4, and snoring sound energy of 801–1000 Hz ≥ 22.0 dB significantly predicted severe OSA in descending order of odds ratio. Multivariate analysis showed that ODI3 ≥ 6.0 events/h independently predicted severe pediatric OSA. Among several predictive models, the combination of ODI3, tonsil size, and ANR more optimally screened for severe OSA with a sensitivity of 91% and a specificity of 94%. In Study 2 (27 (27%) girls and 73 (73%) boys; median age, 7 years), this model was externally validated to predict severe OSA with an accuracy of 76%. Our results suggested that home sleep pulse oximetry, combined with ANR, can screen for severe OSA more optimally than ANR and tonsil size among children with snoring. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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20 pages, 1122 KiB

Open AccessArticle

Prediction Models of Obstructive Sleep Apnea in Pregnancy: A Systematic Review and Meta-Analysis of Model Performance

by Sukanya Siriyotha, Visasiri Tantrakul, Supada Plitphonganphim, Sasivimol Rattanasiri and Ammarin Thakkinstian

Diagnostics 2021, 11(6), 1097; https://doi.org/10.3390/diagnostics11061097 - 15 Jun 2021

Cited by 10 | Viewed by 2933

Abstract

Background: Gestational obstructive sleep apnea (OSA) is associated with adverse maternal and fetal outcomes. Timely diagnosis and treatment are crucial to improve pregnancy outcomes. Conventional OSA screening questionnaires are less accurate, and various prediction models have been studied specifically during pregnancy. Methods: A systematic review and meta-analysis were performed for multivariable prediction models of both development and validation involving diagnosis of OSA during pregnancy. Results: Of 1262 articles, only 6 studies (3713 participants) met the inclusion criteria and were included for review. All studies showed high risk of bias for the construct of models. The pooled C-statistics (95%CI) for development prediction models was 0.817 (0.783, 0850), I² = 97.81 and 0.855 (0.822, 0.887), I² = 98.06 for the first and second–third trimesters, respectively. Only multivariable apnea prediction (MVAP), and Facco models were externally validated with pooled C-statistics (95%CI) of 0.743 (0.688, 0.798), I² = 95.84, and 0.791 (0.767, 0.815), I² = 77.34, respectively. The most common predictors in the models were body mass index, age, and snoring, none included hypersomnolence. Conclusions: Prediction models for gestational OSA showed good performance during early and late trimesters. A high level of heterogeneity and few external validations were found indicating limitation for generalizability and the need for further studies. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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20 pages, 1680 KiB

Open AccessArticle

Predicting Polysomnography Parameters from Anthropometric Features and Breathing Sounds Recorded during Wakefulness

by Ahmed Elwali and Zahra Moussavi

Diagnostics 2021, 11(5), 905; https://doi.org/10.3390/diagnostics11050905 - 19 May 2021

Cited by 4 | Viewed by 2899

Abstract

Background: The apnea/hypopnea index (AHI) is the primary outcome of a polysomnography assessment (PSG) for determining obstructive sleep apnea (OSA) severity. However, other OSA severity parameters (i.e., total arousal index, mean oxygen saturation (SpO2%), etc.) are crucial for a full diagnosis of OSA and deciding on a treatment option. PSG assessments and home sleep tests measure these parameters, but there is no screening tool to estimate or predict the OSA severity parameters other than the AHI. In this study, we investigated whether a combination of breathing sounds recorded during wakefulness and anthropometric features could be predictive of PSG parameters. Methods: Anthropometric information and five tracheal breathing sound cycles were recorded during wakefulness from 145 individuals referred to an overnight PSG study. The dataset was divided into training, validation, and blind testing datasets. Spectral and bispectral features of the sounds were evaluated to run correlation and classification analyses with the PSG parameters collected from the PSG sleep reports. Results: Many sound and anthropometric features had significant correlations (up to 0.56) with PSG parameters. Using combinations of sound and anthropometric features in a bilinear model for each PSG parameter resulted in correlation coefficients up to 0.84. Using the evaluated models for classification with a two-class random-forest classifier resulted in a blind testing classification accuracy up to 88.8% for predicting the key PSG parameters such as arousal index. Conclusions: These results add new value to the current OSA screening tools and provide a new promising possibility for predicting PSG parameters using only a few seconds of breathing sounds recorded during wakefulness without conducting an overnight PSG study. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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10 pages, 1669 KiB

Open AccessArticle

Short-Term CPAP Improves Biventricular Function in Patients with Moderate-Severe OSA and Cardiometabolic Comorbidities

by Ioana Mădălina Zota, Radu Andy Sascău, Cristian Stătescu, Grigore Tinică, Maria Magdalena Leon Constantin, Mihai Roca, Daniela Boișteanu, Larisa Anghel, Ovidiu Mitu and Florin Mitu

Diagnostics 2021, 11(5), 889; https://doi.org/10.3390/diagnostics11050889 - 17 May 2021

Cited by 5 | Viewed by 3063

Abstract

Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing, exhibiting an increasing prevalence and several cardiovascular complications. Continuous positive airway pressure (CPAP) is the gold-standard treatment for moderate-severe OSA, but it is associated with poor patient adherence. We performed a prospective study that included 57 patients with newly diagnosed moderate-severe OSA, prior to CPAP initiation. The objective of our study was to assess the impact of short-term CPAP on ventricular function in patients with moderate-severe OSA and cardiometabolic comorbidities. The patients underwent a clinical exam, ambulatory blood pressure monitoring and comprehensive echocardiographic assessment at baseline and after 8 weeks of CPAP. Hypertension, obesity and diabetes were highly prevalent among patients with moderate-severe OSA. Baseline echocardiographic parameters did not significantly differ between patients with moderate and severe OSA. Short-term CPAP improved left ventricular global longitudinal strain (LV-GLS), isovolumetric relaxation time, transmitral E wave amplitude, transmitral E/A ratio, right ventricular (RV) diameter, RV wall thickness, RV systolic excursion velocity (RV S‘) and tricuspid annular plane systolic excursion (TAPSE). Short-term CPAP improves biventricular function, especially the LV-GLS, which is a more sensitive marker of CPAP-induced changes in LV systolic function, compared to LVEF. All these benefits are dependent on CPAP adherence. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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10 pages, 410 KiB

Open AccessArticle

Sleep Disordered Breathing Measures in Early Pregnancy Are Associated with Depressive Symptoms in Late Pregnancy

by Margaret H. Bublitz, Meghan Sharp, Taylor Freeburg, Laura Sanapo, Nicole R. Nugent, Katherine Sharkey and Ghada Bourjeily

Diagnostics 2021, 11(5), 858; https://doi.org/10.3390/diagnostics11050858 - 11 May 2021

Cited by 6 | Viewed by 2338

Abstract

Sleep disordered breathing (SDB) and depression are both common complications of pregnancy and increase risk for adverse maternal and neonatal outcomes. SDB precedes onset of depression in non-pregnant adults; however, the longitudinal relationship has not been studied in pregnancy. The present research examined temporal associations between SDB and depressive symptoms in 175 pregnant women at risk for SDB (based on frequent snoring and obesity), but without an apnea hypopnea index of ≥5 events per hour at enrollment. Women completed a self-report assessments of depressive symptoms using PHQ-9 and in-home level III sleep apnea monitoring at approximately 12- and 32-weeks’ gestation. We also assessed the risk for SDB using the Berlin Questionnaire in early pregnancy. Results revealed that measures of SDB in early pregnancy as assessed by in-home sleep study, but not by self-reported SDB, predicted elevated depressive symptoms in late pregnancy. SDB in late pregnancy was not associated with depressive symptoms. To conclude, these findings suggest that SDB may increase the risk for elevated depressive symptoms as pregnancy progresses. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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15 pages, 1280 KiB

Open AccessArticle

Analyzing Neck Circumference as an Indicator of CPAP Treatment Response in Obstructive Sleep Apnea with Network Medicine

by Stefan Mihaicuta, Lucreţia Udrescu, Mihai Udrescu, Izabella-Anita Toth, Alexandru Topîrceanu, Roxana Pleavă and Carmen Ardelean

Diagnostics 2021, 11(1), 86; https://doi.org/10.3390/diagnostics11010086 - 7 Jan 2021

Cited by 6 | Viewed by 3567

Abstract

We explored the relationship between obstructive sleep apnea (OSA) patients’ anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (

D_{1}

D_{2}

D_{3}

) with 1046 patients from four sleep laboratories in [...] Read more.

We explored the relationship between obstructive sleep apnea (OSA) patients’ anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (

D_{1}

D_{2}

D_{3}

) with 1046 patients from four sleep laboratories in Western Romania, including 145 subjects (

D_{1}

) with one-night CPAP therapy. Using

D_{1}

data, we created a CPAP-response network of patients, and found neck circumference (NC) as the most significant qualitative indicator for apnea–hypopnea index (AHI) improvement. We also investigated a quantitative NC cutoff value for OSA screening on cohorts

D_{2}

(OSA-diagnosed) and

D_{3}

(control), using the area under the curve. As such, we confirmed the correlation between NC and AHI (

ρ = 0.35

p < 0.001

) and showed that 71% of diagnosed male subjects had bigger NC values than subjects with no OSA (area under the curve is 0.71, with 95% CI 0.63–0.79,

p < 0.001

); the optimal NC cutoff is 41 cm, with a sensitivity of 0.8099, a specificity of 0.5185, positive predicted value (PPV) = 0.9588, negative predicted value (NPV) = 0.1647, and positive likelihood ratio (LR+) = 1.68. Our NC

= 41

cm threshold classified the

D_{1}

patients’ CPAP responses—measured as the difference in AHI prior to and after the one-night use of CPAP—with a sensitivity of 0.913 and a specificity of 0.859. Full article

(This article belongs to the Special Issue Diagnosis and Management of Obstructive Sleep Apnea)

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