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.

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 COMPARISON OF ANTHROPOMETRIC PARAMETERS BETWEEN OBESE MALE PARTICIPANTS WITH AND WITHOUT OBSTRUCTIVE SLEEP APNEA

2021 ◽  
Vol 12 (3) ◽  
Author(s):  
Shagufta Khaliq ◽  
Mudassar Ali Roomi ◽  
Muniza Saeed ◽  
Komal Iqbal ◽  
Shaheena Naz ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Waist Circumference ◽  
Neck Circumference ◽  
Medical Institute ◽  
Anthropometric Parameters ◽  
Group I ◽  
Obstructive Sleep ◽  
Group Ii ◽  
Obese Male

BACKGROUND & OBJECTIVE: The most common risk factors for Obstructive Sleep Apnea includes: Obesity and increased neck circumference in male gender. The objective of the study was to compare the anthropometric parameters between obese male participants with and without obstructive sleep apnea (OSA). METHODOLOGY:  Study was conducted at Department of Physiology, Post Graduate Medical Institute, Lahore during 24 August 2014 to 26 May 2015. Obese males (n=64) with body mass index (BMI) >25kg/m2 and aged 20-45 years were recruited by convenience sampling. Screening of OSA was made by two subjective tools: STOP BANG Questionnaire, and Berlin Questionnaire while final diagnosis was made by overnight portable pulse oximetry. Study population was divided into two groups. Group-I comprised of 32 obese males with OSA. Group II had 32 obese males without OSA. BMI, neck circumference, and waist circumference were measured by standard methods.Comparison of variables was done between the groups by Mann-WhitneyUtest and t-test. RESULTS:  BMI was higher in group-I than in group-II (p=0.004). Median BMI for group-I was 30.83 (28.16–32.80) and for group-II was 27.99 (26.59–30.08) Kg/m2. A significantly higher neck circumference (p<0.001) was present in group-I (41.95±2.40cm) than group-II (39.66±2.07cm). Moreover, significantly higher median waist circumference (p<0.001) was present in group I (107.5cm)  as compared to group-II (98.5cm). CONCLUSION: Anthropometric parameters (BMI, neck circumference, and waist circumference) are higher in obese individuals with OSA as compared to obese males without OSA.

Mean Platelet Volume Decreases in Adult Patients With Obstructive Sleep Apnea After Uvulopalatal Flap Surgery

2015 ◽  
Vol 26 (7) ◽  
pp. 2152-2154 ◽  
Author(s):  
Gokce Simsek ◽  
Suheyl Haytoglu ◽  
Nuray Bayar Muluk ◽  
Osman Kursat Arikan ◽  
Mustafa Cortuk ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Mean Platelet Volume ◽  
Adult Patients ◽  
Flap Surgery ◽  
Platelet Volume ◽  
Obstructive Sleep

scholarly journals 0560 EFFECTS OF MEDICAL THERAPY ON MILD OBSTRUCTIVE SLEEP APNEA IN ADULT PATIENTS

SLEEP ◽  
2017 ◽  
Vol 40 (suppl_1) ◽  
pp. A208-A208 ◽  
Author(s):  
DF Smith ◽  
SL Ishman ◽  
CP Spiceland ◽  
AM Romaker
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Medical Therapy ◽  
Adult Patients ◽  
Obstructive Sleep ◽  
Mild Obstructive Sleep Apnea

Sex related differences in inflammation markers in adult patients with obstructive sleep apnea

2021 ◽  
Vol 429 ◽  
pp. 118667
Author(s):  
Chiara Rocchi ◽  
Valentina Conti ◽  
Viviana Totaro ◽  
Serena Broggi ◽  
Simona Lattanzi ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Adult Patients ◽  
Inflammation Markers ◽  
Obstructive Sleep

Risk Screening of Obstructive Sleep Apnea Syndrome by Body Profiles via Random Forests Model

2020 ◽  
Author(s):  
Cheng-Yu Tsai ◽  
Wen-Te Liu ◽  
Yin-Tzu Lin ◽  
Shang-Yang Lin ◽  
Arnab Majumdar ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Waist Circumference ◽  
Sleep Disorder ◽  
Random Forests ◽  
Sleep Apnea Syndrome ◽  
Obstructive Sleep ◽  
Gender And Age ◽  
Apnea Syndrome ◽  
And Gender

Abstract Background Obstructive Sleep Apnea Syndrome (OSAS) is a major global health concern and is typically diagnosed by in-lab polysomnography (PSG). This examination though has high medical manpower costs and alternative portable methods have further limitations. This paper develops a new model for screening the risk of OSAS in different age groups and gender by using body profiles. The effects of body profiles for different subgroups in sleep stage alteration and OSAS severity are also investigated. Methods The data is derived from 6614 Han-Taiwanese subjects who have previously undergone PSG in order to assess the severity of OSAS in the sleep center of Taipei Medical University Shuang-Ho Hospital between March 2015 and October 2019. Characteristics of subjects, including age, gender, body mass index (BMI), neck circumference, and waist circumference, were obtained from a questionnaire. Pearson regression was used to evaluate the correlations between body profiles and sleep stages as well as sleep disorder indexes. To develop an age and gender independent model, random forests (RF), which is an ensemble learning method with high explainability, were trained by the four groups by gender and age (older or younger than 50 years old) with ratios of 70% (training dataset) and 30% (testing dataset), respectively. Prediction performance was evaluated by sensitivity, specificity and accuracy. Variable importance was assessed by averaging the impurity decrease to account for the effect of different factors. Results Results indicate that high BMI, neck circumference and waist circumference decreased the duration of slow-wave sleep and increased the sleep disorder indices and the percentage of wake and N1. Additionally, screening models for different gender and age utilizing anthropometric features as predictors via RF were established and demonstrated to have high accuracy (75.63% for younger males, 74.72% for elder males, 78.81% for younger females, and 72.10% for elder females). Feature importance indicated that waist circumference was the highest contributing factor in females and elder males, whereas the BMI was the highest contribution in younger males. Conclusions The authors recommend the use of the prediction models for those with Han-Taiwanese craniofacial features.

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