The importance of screening questionnaires in detecting the severity of obstructive sleep apnea

2021 ◽  
Vol 70 (2) ◽  
pp. 75-81
Author(s):  
Šárka Solecká ◽  
Jan Betka ◽  
Karel Matler ◽  
Hana Tomášková
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Pittsburgh Sleep Quality Index ◽  
Neck Circumference ◽  
Berlin Questionnaire ◽  
Hip Circumference ◽  
Obstructive Sleep ◽  
Screening Questionnaires ◽  
Stop Questionnaire

ntroduction: The aim of this study is to compare the importance of screening questionnaires and risk factors in detecting the severity of obstructive sleep apnea (OSA). Methods: The study included 47 patients with suspected OSA. The patients completed 5 screening questionnaires – the Epworth Sleepiness Scale (ESS), the STOP BANG questionnaire, the STOP questionnaire, the Berlin questionnaire (BQ) and the Pittsburgh Sleep Quality Index (PSQI). Subsequently, they were examined by the limited polygraphy. AHI (number of apneas/ hypopneas per 1 hour), t90 desaturation (percentage of sleep time spent in desaturations below 90%) and ODI (number of desaturations ≥ 3% within 1 hour) were compared with questionnaire scores and selected risk factors for OSA (BMI, male gender, hypertension, age, neck circumference, abdominal circumference and abdominal/ hip circumference ratio). Results: The achieved score of any of the monitored questionnaires does not correlate with the value of AHI. BQ, STOP and STOP BANG questionnaires have the relatively highest sensitivity for OSA detection, while the sensitivity of PSQI and ESS is low. The correlation of the ESS, STOP BANG and BQ scores with the t90 desaturation, as well as the ESS and STOP BANG scores with the ODI is statistically signifi cant. The relationship of any of the selected risk factors with the AHI value has not been demonstrated. Desaturation values of t90 and ODI correlated best with BMI, neck circumference and abdominal/ hip circumference ratio. Conclusion: None of the monitored questionnaires is suitable for determining the severity of OSA, it is always necessary to perform a polygraphic or polysomnographic examination of sleep. BQ and STOPBANG are relatively most suitable for OSA screening. They both have high sensitivity and, at the same time, their score correlates with the value of nocturnal hypoxemia. Parameters measuring nocturnal hypoxemia (t90 desaturation, ODI) correlate better with risk factors than AHI. The most important parameters associated with hypoxemia are BMI, neck circumference and abdominal/ hip circumference ratio and it is appropriate to include them in the screening for OSA. Keywords: obstructive sleep apnea – Berlin questionnaire – STOP-Bang questionnaire – STOP questionnaire – Epworth sleepiness scale – Pittsburgh Sleep Quality Index

scholarly journals Usefulness of different screening questionnaires and scoring systems for obstructive sleep apnea in patients with atrial fibrillation

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
M Delesie ◽  
L Knaepen ◽  
A Wouters ◽  
A De Cauwer ◽  
A De Roy ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Gold Standard ◽  
Scoring Systems ◽  
Public Institution ◽  
Screening Tools ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
Screening Questionnaires

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This study is part of Limburg Clinical Research Center, supported by the foundation Limburg Sterk Merk, province of Limburg, Flemish government, Hasselt University, Ziekenhuis Oost-Limburg and Jessa Hospital. OnBehalf Research Group Cardiovascular Diseases, University of Antwerp Background Obstructive sleep apnea (OSA) influences the progression of atrial fibrillation (AF) but is underdiagnosed in this population. Studies have shown that its treatment can help to reduce AF recurrences and improve symptoms. Polysomnography (PSG) is currently the gold standard for diagnosing OSA but being expensive and requiring overnight examination it is therefore not the ideal screening method. Different OSA screening tools such as questionnaires and scoring systems already exist but their value in AF patients remains unclear. Purpose The aim of this study was to examine the performance of different screening questionnaires and scoring systems for diagnosing OSA in an AF cohort, compared with PSG as gold standard. Methods Prospective study of the predictive performance of seven screening questionnaires and scoring systems (the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), Sleep Apnea Clinical Score (SACS), OSA50, STOP-BANG, NoSAS, MOODS) in consecutive AF patients referred to two sleep clinics. Results A total of 100 AF patients presenting for PSG were included (64.0 ± 8.6 years, 73% male, 87% non-permanent AF, mean Body Mass Index 30.6 ± 5.9 kg/m2, mean CHA2DS2-VASc score 2.4 ± 1.7, mEHRA≥2 in 64%; mean AF history 5.4 ± 5.6 years).  Forty-two percent of patients were referred to the sleep clinic by cardiologists. PSG diagnosed ≥mild OSA in 90% of patients, ≥moderate in 69%, and severe OSA in 33%. In screening for mild OSA, NoSAS, STOP-BANG and MOODS screening questionnaires had a fair area under the curve (AUC) of 0.773, 0.710 and 0.709 respectively. For at least moderate OSA, only the SACS and the NoSAS questionnaires had an AUC of 0.704 and 0.712 respectively (Figure 1). None of the seven screening questionnaires/scoring systems were performant enough (i.e. a fair AUC > 0.7) to detect severe OSA. Conclusions Our analysis shows that screening questionnaires and scoring systems such as ESS, BQ, SACS, NoSAS, OSA50, STOP-BANG and MOODS are not very useful to predict clinically relevant OSA (i.e. at least moderate OSA) in AF patients. Therefore, other screening modalities for OSA in AF patients should be investigated and validated. Abstract Figure 1

Clinical Prediction Model for Obstructive Sleep Apnea among Adult Patients with Habitual Snoring

2019 ◽  
Vol 161 (1) ◽  
pp. 178-185 ◽  
Author(s):  
Hsin-Ching Lin ◽  
Chi-Chih Lai ◽  
Pei-Wen Lin ◽  
Michael Friedman ◽  
Anna M. Salapatas ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Waist Circumference ◽  
Neck Circumference ◽  
Adult Patients ◽  
Physical Parameters ◽  
Hip Circumference ◽  
Habitual Snoring ◽  
Obstructive Sleep ◽  
Size Grading

Objective To identify standard clinical parameters that may predict the presence and severity of obstructive sleep apnea/hypopnea syndrome (OSA). Design Case series with chart review. Setting Tertiary academic medical center. Subjects and Methods A total of 325 adult patients (274 men and 51 women; mean age, 44.2 years) with habitual snoring completed comprehensive polysomnography and anthropometric measurements, including modified Mallampati grade (also known as updated Friedman’s tongue position [uFTP]), tonsil size grading, uvular length, neck circumference, waist circumference, hip circumference, and body mass index (BMI). Results When the aforementioned physical parameters were correlated singly with the apnea/hypopnea index (AHI), we found that sex, uFTP, tonsil size grading, neck circumference, waist circumference, hip circumference, thyroid-mental distance, and BMI grade were reliable predictors of OSA. When all important factors were considered in a multiple stepwise regression analysis, an estimated AHI can be formulated by factoring sex, uFTP, tonsil size grading, and BMI grade as follows: –43.0 + 14.1 × sex + 12.8 × uFTP + 5.0 × tonsil size + 8.9 × BMI grade. Severity of OSA can be predicted with a receiver operating characteristic curve. Predictors of OSA can be further obtained by the “OSA score.” Conclusion This study has distinguished the correlations between sex, uFTP, tonsil size, and BMI grade and the presence and severity of OSA. An OSA score might be beneficial in identifying patients who should have a full sleep evaluation.

scholarly journals The Prevalence of High Risk of Obstructive Sleep Apnea and its Association with Sociodemographic Factors among Adults in Taman Dato' Rashid Salleh, Indera Mahkota, Kuantan

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Rawahah Husna Ramli ◽  
Artika Hassan ◽  
Jamalludin Abd Rahman ◽  
Razman Mohd Rus ◽  
Hafizah Pasi ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
High Risk ◽  
Demographic Data ◽  
Adult Population ◽  
Neck Circumference ◽  
P Value ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
Increased Risk

Introduction: Obstructive sleep apnea (OSA) is an insidious sleep breathing disorder, with cardinal manifestations of snoring, witnessed breathing pause during sleep and excessive daytime sleepiness. The aim of the study was to estimate the prevalence of OSA and its associated factors among adult population in Taman Dato’ Rashid Salleh, Kuantan. Materials and  method: A cross-sectional study was carried out among 157 participants who lived in Taman Dato’ Rashid Salleh from May 2018 to June 2018. Obstructive sleep apnea was quantified using the self-administered Malaynvalidated Berlin questionnaire which apart from the demographic data included three categories (10 questions) designed to elicit information regarding snoring (category 1), daytime somnolence (category 2) and the presence of obesity and/or hypertension (category 3). The respondents were considered as high risk of OSA if two or more categories were positive. Weight, height and neck circumference were measured by using Secca© weight scales, Secca© stadiometer and non-elastic plastic tape, respectively. Descriptive statistics was used to measure the prevalence, while chi-square test was used to explore the association of OSA and its background variables. Results: Out of 157 respondents, female and Malay were dominant with the 56.7% and 91.0 %, respectively. The mean age of the respondents was 36.7 (12.2) years old. The prevalence of high risk of OSA in was 18.5%. There was no association between gender, age, race, smoking and neck circumference with risk of OSA while Body Mass Index (BMI) and hypertension were significantly related to an increased risk for developing OSA (p-value < 0.001 and p=0.001, respectively).  Conclusions: Two in every 10 adults in Taman Dato’ Rashid Salleh, Kuantan were at high risk of OSA. It is recommended that appropriate health promotion should be targeted to this community to instill awareness and increase the level of understanding of the public on OSA.

scholarly journals Risk factors and clinical prediction formula for the evaluation of obstructive sleep apnea in Asian adults

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246399
Author(s):  
Do-Yang Park ◽  
Ji-Su Kim ◽  
Bumhee Park ◽  
Hyun Jun Kim
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Goodness Of Fit ◽  
Upper Airway ◽  
Physical Exam ◽  
Berlin Questionnaire ◽  
Clinical Prediction ◽  
Obstructive Sleep ◽  
Tongue Position

Obstructive sleep apnea is a highly prevalent cyclic repetitive hypoxia-normoxia respiratory sleep disorder characterized by intermittent upper-airway collapse. It is mainly diagnosed using in-laboratory polysomnography. However, the time-spatial constraints of this procedure limit its application. To overcome these limitations, there have been studies aiming to develop clinical prediction formulas for screening of obstructive sleep apnea using the risk factors for this disorder. However, the applicability of the formula is restricted by the group specific factors included in it. Therefore, we aimed to assess the risk factors for obstructive sleep apnea and develop clinical prediction formulas, which can be used in different situations, for screening and assessing this disorder. We enrolled 3,432 Asian adult participants with suspected obstructive sleep apnea who had successfully undergone in-laboratory polysomnography. All parameters were evaluated using correlation analysis and logistic regression. Among them, age, sex, hypertension, diabetes mellitus, anthropometric factors, Berlin questionnaire and Epworth Sleepiness Scale scores, and anatomical tonsil and tongue position were significantly associated with obstructive sleep apnea. To develop the clinical formulas for obstructive sleep apnea, the participants were divided into the development (n = 2,516) and validation cohorts (n = 916) based on the sleep laboratory visiting date. We developed and selected 13 formulas and divided them into those with and without physical examination based on the ease of application; subsequently, we selected suitable formulas based on the statistical analysis and clinical applicability (formula including physical exam: sensitivity, 0.776; specificity, 0.757; and AUC, 0.835; formula without physical exam: sensitivity, 0.749; specificity, 0.770; and AUC, 0.839). Analysis of the validation cohort with developed formulas showed that these models and formula had sufficient performance and goodness of fit of model. These tools can effectively utilize medical resources for obstructive sleep apnea screening in various situations.

Abstract MP031: Prospective Association of Obstructive Sleep Apnea Risk Factors with Heart Failure with Preserved Ejection Fraction and Not Heart Failure with Reduced Ejection Fraction in Postmenopausal Women

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Patrick Koo ◽  
Umama Gorsi ◽  
Mary Roberts ◽  
Charles Eaton
Keyword(s):  
Risk Factors ◽  
Heart Failure ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Ejection Fraction ◽  
Postmenopausal Women ◽  
Summary Score ◽  
Sleep Fragmentation ◽  
Berlin Questionnaire ◽  
Obstructive Sleep

Background: The relationship between obstructive sleep apnea (OSA) and heart failure (HF) has been under-researched especially in postmenopausal women. We therefore evaluated relationship between OSA risk factors and HFpEF and HFrEF in post-menopausal women. Methods: We performed a prospective analysis of a subset of participants who had adjudicated heart failure outcomes (n=42,362) in the Women Health Initiative Observational, Clinical Trial, and Extension Studies (1998-Present). The cohort was followed over an average of 13.4 years. Inverse probability weighting was employed to account for potential selection bias. Cox proportional hazards regression was used to examine the association between OSA risk factors and time to first hospitalized HF. Type of heart failure was determined using the ejection fraction (EF) obtained from 2D echocardiography. EF of ≥45% was categorized as HFpEF, and EF of < 45% was categorized as HFrEF. Models were adjusted for age, race/ethnicity, education, income, marital status, systolic blood pressure, waist-to-hip ratio, diabetes, coronary heart disease, atrial fibrillation, use of hormone replacement therapy, use of sleep medications, modified Charlson comorbidity index, smoking, alcohol consumption, physical activity, and hysterectomy. We also created an OSA summary score (obesity, snoring, poor sleep quality, sleep fragmentation, daytime sleepiness, and hypertension) based on the Berlin questionnaire, which reliably predicts OSA, to examine its relationship with HF. Results: Of the 42,362 women, 1,054 (2.49%) had preserved EF, and 631 (1.49%) had reduced EF. Four of the 6 risk factors (obesity (HR=1.51, 95% CI 1.29-1.76), snoring (HR=1.23, 95% CI 1.04-1.45), sleep fragmentation (HR=1.15, 95% CI 1.01-1.31), and hypertension (HR=1.46, 95% CI 1.31-1.62)) were associated HFpEF after adjusting for confounders. Each additional OSA risk factor in an OSA summary score compared to no risk factors significantly increased the risk of HFpEF in a dose-response fashion (HR=1.36, 1.61, 2.01, 1.97, 2.02, and 2.74 for scores of 1-6, respectively; P trend <0.001) and not HFrEF (P trend =0.26). Only hypertension was associated with HFrEF (HR=1.39, 95% CI 1.22-1.60). Conclusion: Having more OSA risk factors increases the risk of HFpEF but not HFrEF in postmenopausal women. Early recognition and management of OSA risk factors may play an important role in reducing risk of HFpEF in this population.

scholarly journals Neck Grasp Predicts Obstructive Sleep Apnea in Type 2 Diabetes Mellitus

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
P. J. Edmonds ◽  
K. Gunasekaran ◽  
L. C. Edmonds
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Neck Circumference ◽  
Berlin Questionnaire ◽  
Type 2 Dm ◽  
Obstructive Sleep

Aims. Obstructive sleep apnea (OSA) is a common disorder with high morbidity, mortality, and an increasing prevalence in the general population. It has an even higher prevalence among individuals with type 2 diabetes mellitus (DM). The snoring, tiredness, observed apnea, high blood pressure, body-mass-index, age, neck circumference and male gender (STOP-BANG) questionnaire and Berlin Questionnaire can be cumbersome in clinical practice and require subjective data on sleepiness. We proposed prospectively studying a primary care population with type 2 DM comparing neck grasp, neck circumference, and common screening questionnaires to identify OSA.Methods. Persons with a diagnosis of type 2 DM were recruited from a primary care clinic. Participants were screened using Easy Sleep Apnea Predictor (ESAP), STOP-Bang questionnaire, and Berlin questionnaire. A positive ESAP was defined as a 1cm gap when a patient encircled their hands around the neck. All subjects underwent in-laboratory PSG testing.Results. Forty-three participants were enrolled and the prevalence of OSA was 90.7% (AHI ≥ 5). The median BMI was 38.0. The prevalence of mild OSA by PSG (AHI 5-14) was 27.9%, moderate OSA (AHI 15-29) was 25.6%, and severe OSA (AHI >30) was 37.2%. For mild OSA both ESAP and neck circumference showed 100% specificity.Conclusions. This study reinforces the need for screening diabetic persons for obstructive sleep apnea. ESAP and neck circumference are useful for identifying persons with type 2 DM who are at risk for OSA. Together these findings could improve recognition of OSA in persons at risk for cardiovascular disease. Trial Registration of “Neck grasp as a predictor of Sleep Apnea,”https://clinicaltrials.gov/ct2/show/NCT02474823, Clinical Trials.gov Identifier, isNCT02474823.

Poor performance of screening questionnaires for obstructive sleep apnea in male commercial drivers

2021 ◽  
Author(s):  
Alessandro Adami ◽  
Davide Tonon ◽  
Antonio Corica ◽  
Deborah Trevisan ◽  
Giovanni Cipriano ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Poor Performance ◽  
Obstructive Sleep ◽  
Screening Questionnaires ◽  
Commercial Drivers

414 Deep Neural Networks: A Survey Tool for Obstructive Sleep Apnea Prediction

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A164-A164
Author(s):  
Pahnwat Taweesedt ◽  
JungYoon Kim ◽  
Jaehyun Park ◽  
Jangwoon Park ◽  
Munish Sharma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Deep Neural Networks ◽  
Support Vector ◽  
Learning Models ◽  
Obstructive Sleep ◽  
Screening Questionnaires ◽  
Machine Learning Models

Abstract Introduction Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder with an estimation of one billion people. Full-night polysomnography is considered the gold standard for OSA diagnosis. However, it is time-consuming, expensive and is not readily available in many parts of the world. Many screening questionnaires and scores have been proposed for OSA prediction with high sensitivity and low specificity. The present study is intended to develop models with various machine learning techniques to predict the severity of OSA by incorporating features from multiple questionnaires. Methods Subjects who underwent full-night polysomnography in Torr sleep center, Texas and completed 5 OSA screening questionnaires/scores were included. OSA was diagnosed by using Apnea-Hypopnea Index ≥ 5. We trained five different machine learning models including Deep Neural Networks with the scaled principal component analysis (DNN-PCA), Random Forest (RF), Adaptive Boosting classifier (ABC), and K-Nearest Neighbors classifier (KNC) and Support Vector Machine Classifier (SVMC). Training:Testing subject ratio of 65:35 was used. All features including demographic data, body measurement, snoring and sleepiness history were obtained from 5 OSA screening questionnaires/scores (STOP-BANG questionnaires, Berlin questionnaires, NoSAS score, NAMES score and No-Apnea score). Performance parametrics were used to compare between machine learning models. Results Of 180 subjects, 51.5 % of subjects were male with mean (SD) age of 53.6 (15.1). One hundred and nineteen subjects were diagnosed with OSA. Area Under the Receiver Operating Characteristic Curve (AUROC) of DNN-PCA, RF, ABC, KNC, SVMC, STOP-BANG questionnaire, Berlin questionnaire, NoSAS score, NAMES score, and No-Apnea score were 0.85, 0.68, 0.52, 0.74, 0.75, 0.61, 0.63, 0,61, 0.58 and 0,58 respectively. DNN-PCA showed the highest AUROC with sensitivity of 0.79, specificity of 0.67, positive-predictivity of 0.93, F1 score of 0.86, and accuracy of 0.77. Conclusion Our result showed that DNN-PCA outperforms OSA screening questionnaires, scores and other machine learning models. Support (if any):

Association between obstructive sleep apnea and persistent-postural perceptual dizziness

2021 ◽  
pp. 1-6
Author(s):  
Anand K. Bery ◽  
Jayson Lee Azzi ◽  
Andre Le ◽  
Naomi S. Spitale ◽  
Judith Leech ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sensitivity And Specificity ◽  
Berlin Questionnaire ◽  
Future Studies ◽  
Obstructive Sleep ◽  
Chronic Dizziness ◽  
Patients At Risk ◽  
The Mean ◽  
The Relationship

BACKGROUND: Obstructive sleep apnea (OSA) has been linked to vestibular dysfunction, but no prior studies have investigated the relationship between Persistent Postural Perceptual Dizziness (PPPD), a common cause of chronic dizziness, and OSA. OBJECTIVE AND METHODS: We determined the frequency of OSA in an uncontrolled group of PPPD patients from a tertiary dizziness clinic based on polysomnogram (PSG). We then assessed the sensitivity and specificity of common OSA questionnaires in this population. RESULTS: Twenty-five patients with PPPD underwent PSG (mean age 47, 60% female, mean BMI 29.5). A majority, or 56%, of patients were diagnosed with OSA, and in most, the OSA was severe. OSA patients were older (56 years versus 40 years, p = 0.0006) and had higher BMI (32 versus 26, p = 0.0078), but there was no clear gender bias (56% versus 64% female, p = 1.00). The mean sensitivity and specificity of the STOP BANG questionnaire for detecting OSA was 86% and 55%, respectively. Sensitivity and specificity of the Berlin Questionnaire was 79% and 45%, respectively. CONCLUSIONS: The prevalence of OSA was much higher in our small PPPD group than in the general population. Screening questionnaires appear to demonstrate good sensitivity to detect PPPD patients at risk of OSA in this small study. Future studies should confirm these findings and determine whether treatment of OSA improves symptoms in PPPD.

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