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.

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

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 Children with Upper Airway Dysfunction: At Risk of Obstructive Sleep Apnea

2019 ◽  
Vol 09 (01) ◽  
pp. e59-e67
Author(s):  
Carlos Sisniega ◽  
Umakanth Katwa
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Airway Obstruction ◽  
Upper Airway ◽  
Adverse Outcomes ◽  
Upper Airway Obstruction ◽  
Lymphoid Tissues ◽  
Obstructive Sleep ◽  
Potential Risk Factors

AbstractObstructive sleep apnea is characterized by prolonged partial upper airway obstruction or intermittent complete obstruction that disrupts normal ventilation during sleep and alters normal sleep patterns. Patients with obstructive sleep apnea tend to develop neurocognitive, cardiovascular, behavioral, attention issues, and poor academic performance. Therefore, it is essential to diagnose and treat obstructive sleep apnea early and avoid significant and long-lasting adverse outcomes. Most commonly, upper airway obstruction is caused by enlarged lymphoid tissues within the upper airway, and therefore adenotonsillectomy is considered as the first-line treatment of obstructive sleep apnea in children. Fifty to 70% of patients who have obstructive sleep apnea and treated by surgery are not entirely cured on follow-up polysomnography. In light of this, it is recommended that patients with suspected obstructive sleep apnea undergo a thorough evaluation, and all potential risk factors are identified and treated. The purpose of this review is to familiarize pediatricians with developmental, anatomical, and physiological risk factors involved in the development of obstructive sleep apnea. Additionally, we will present an array of evaluation techniques that can offer adequate assessment of the patient's upper airway anatomy and physiology.

Abstract P246: Obstructive Sleep Apnea and Particulate Matter Exposure

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Mary Ann McLaughlin ◽  
Rupa L Iyengar ◽  
Jessica Janneck ◽  
Heather N Beebe ◽  
Sarah Sanghavi ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Logistic Regression ◽  
Particulate Matter ◽  
Sleep Apnea ◽  
High Risk ◽  
World Trade Center ◽  
Upper Airway ◽  
Binary Logistic Regression ◽  
Berlin Questionnaire ◽  
Obstructive Sleep

Background: Recent studies have found a high prevalence of obstructive sleep apnea (OSA) among responders of the World Trade Center (WTC) disaster. Exposure to particulate matter (PM) causing upper airway inflammation is considered a significant contributing factor in the pathogenesis of OSA. The Berlin Questionnaire (BQ) is a widely used questionnaire to screen for OSA with published sensitivity up to 86% and specificity of 87% for OSA risk. We aim to investigate whether a relationship exists between OSA risk using the BQ and exposure to PM using the Wisnevsky exposure score. Methodology: We evaluated 808 participants in the WTC-CHEST Program from January 2011 to September 2013. High risk for OSA was identified as 2 or more positive categories in the BQ. The subjects were categorized into four exposure groups: very high, high, intermediate and low (Wisnevsky exposure score). Chi-square and Binary Logistic Regression analyses were performed to determine if there was a significant relationship between OSA risk and PM exposure. Results: High risk for OSA is associated with PM exposure in the study population (p=0.002). Using a binary logistic regression adjusting for gender and age, high risk for OSA was still found to be significantly associated with PM exposure (p = 0.022). Conclusion: Prior investigations have demonstrated a link between PM exposure and pulmonary disease, digestive disorders and PTSD. These results provide strong evidence for the association of PM exposure and OSA. In fact, PM exposure in this cohort of WTC first responders is one of the most significant contributors to increased OSA risk. Assessment of both OSA risk and exposure to PM are important as both have been linked to an increase in cardiovascular risk.

scholarly journals Physiology in Medicine: Obstructive sleep apnea pathogenesis and treatment—considerations beyond airway anatomy

2014 ◽  
Vol 116 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jerome A. Dempsey ◽  
Ailiang Xie ◽  
David S. Patz ◽  
David Wang
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Muscle Activation ◽  
Upper Airway ◽  
Airway Anatomy ◽  
Output Stability ◽  
Dilator Muscle ◽  
Obstructive Sleep ◽  
Treatment Considerations

We review evidence in support of significant contributions to the pathogenesis of obstructive sleep apnea (OSA) from pathophysiological factors beyond the well-accepted importance of airway anatomy. Emphasis is placed on contributions from neurochemical control of central respiratory motor output through its effects on output stability, upper airway dilator muscle activation, and arousability. In turn, we consider the evidence demonstrating effective treatment of OSA via approaches that address each of these pathophysiologic risk factors. Finally, a case is made for combining treatments aimed at both anatomical and ventilatory control system deficiencies and for individualizing treatment to address a patient 's own specific risk factors.

scholarly journals Risk factors and fraction of exhaled nitric oxide in obstructive sleep apnea in adults

2020 ◽  
Vol 48 (7) ◽  
pp. 030006052092601
Author(s):  
Xiaokai Feng ◽  
Xiheng Guo ◽  
Junling Lin ◽  
Zhiling Zhao ◽  
Zhaohui Tong
Keyword(s):  
Nitric Oxide ◽  
Risk Factors ◽  
Body Mass Index ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Soft Palate ◽  
Upper Airway ◽  
Transverse Diameter ◽  
Obstructive Sleep ◽  
Male Sex

Objective This study aimed to evaluate the relationship between obstructive sleep apnea (OSA) and the fraction of exhaled nitric oxide (FENO), and to assess the effect of risk factors of airway inflammation on OSA. Methods Medical records of patients in the Respiratory Sleep Center at Chao-Yang Hospital in Beijing between January 2015 and June 2017 were analyzed. All patients were diagnosed with OSA. Data of the medical history, clinical examinations, FENO, and upper airway computed tomographic findings were collected. Logistic regression was used to evaluate risk factors of OSA. Results A total of 181 patients were admitted to the Respiratory Sleep Center during the study and 170 had a diagnosis of OSA and were included in the study. Single factor analysis showed that male sex, age, body mass index, smoking index, alcohol consumption, FENO, soft palate thickness, soft palate length, the narrowest transverse diameter of the upper airway, tonsil size, and nasal sinusitis were risk factors for sleep-disordered breathing and disease severity. Conclusions Male sex, age, body mass index, FENO, the narrowest transverse diameter of the upper airway, and normal tonsil size are associated with OSA and disease severity. The severity of OSA is associated with FENO levels.

scholarly journals Characteristics and risk factors of snoring and the prevalence of suspected obstructive sleep apnea in children

2016 ◽  
Vol 45 (1) ◽  
pp. 40
Author(s):  
Bambang Supriyatno ◽  
Rusmala Deviani ◽  
Alan R Tumbelaka ◽  
Evita KB Ifran ◽  
Nastiti N Rahajoe
Keyword(s):  
Risk Factors ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Physical Examination ◽  
Upper Airway ◽  
Cross Sectional Study ◽  
Adenoid Hypertrophy ◽  
Sectional Study ◽  
Cross Sectional ◽  
Obstructive Sleep

Background Snoring as a consequence of upper airway obstruc-tion is common in children. Snoring can be considered as normal,but might also reflect a disease such as obstructive sleep apnea(OSA), which is associated with serious morbidities. In Indonesia,data on the characteristics and risk factors of snoring and obstruc-tive sleep apnea is limitedObjectives The aims of this study were to find out the character-istics and risk factors of snoring in children and to determine theprevalence of suspected OSA in snoring children.Methods A cross-sectional study was carried out on children aged5-13 years using parental questionnaires scored according to theBrouilette formula. All children underwent physical examination forweight, height and tonsil size. Adenoid radiology was performedon part of the samples.Results Of the 917 questionnaires distributed, only 658 were com-pleted. The ratio of boys to girls was equal. Obesity was detectedin 18.3% of children, among whom 54.2% snored. Obese childrenwere 2.1 times more likely to snore. Besides obesity, rhinitis andatopy were found to be associated with snoring (PR= , 95%CI ;and PR= , 95%CI ; respectively). Asthma and tonsil hypertrophywere shown not to be predisposing factors of snoring. Childrenwith adenoid hypertrophy were 1.8 times more likely to snore ha-bitually. The prevalence of snoring and suspected OSA in childrenaged 5-13 years were 31.6% and 5.9%, respectively.Conclusion Risk factors of snoring were obesity, adenoid hyper-trophy, atopy and rhinitis. Prevalence of snoring in children age 5-13 years was 31.6% and that of suspected OSA cases was 5.9%.

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.

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