수면무호흡증 선별을 위한 STOP-Bang 설문과 스마트워치의 2단계 접근법
STOP-Bang and Smartwatch’s Two-Step Approach for Obstructive Sleep Apnea Screening
3
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Background and Objectives Obstructive sleep apnea (OSA) is associated with varioushealth risks, including hypertension, cerebrovascular disease, myocardial infarction, diabetes,cognitive impairment, and all-cause mortality. While overnight polysomnography (PSG) isthe gold standard for diagnosing OSA, it is costly and time-consuming. The STOP-Bang ques-tionnaire is a convenient tool for OSA screening, but its high sensitivity comes at the expenseof low specificity. The purpose of this study was to investigate the usefulness of combiningthe STOP-Bang questionnaire and a smartwatch capable of measuring oxygen saturation inscreening for OSA. Subjects and Method Of the patients scheduled for PSG due to OSA, 109 patients volun-tarily participated in the study by filling out a STOP-Bang questionnaire during their first visitand wearing a smartwatch during PSG. Results There were 80 males and 29 females, with the patients’ mean age of 45±13.3 years. Based on the apnea-hypopnea index (AHI), 19 patients (17.4%) were normal, 28 (25.7%) hadmild OSA, 23 (21.1%) had moderate OSA, and 39 (35.8%) had severe OSA. When using theAHI threshold of AHI ≥15/h, the STOP-Bang alone showed sensitivity of 85.5% and specifici-ty of 61.7%. Combining the STOP-Bang questionnaire with a smartwatch resulted in a slightdecrease in sensitivity and a significant increase in specificity, yielding the values of 80.5%and 84.4%, respectively. Conclusion A two-step approach using the STOP-Bang and a smartwatch was implementedto enhance the diagnostic accuracy of screening OSA.
Abstract
Background and Objectives Obstructive sleep apnea (OSA) is associated with varioushealth risks, including hypertension, cerebrovascular disease, myocardial infarction, diabetes,cognitive impairment, and all-cause mortality. While overnight polysomnography (PSG) isthe gold standard for diagnosing OSA, it is costly and time-consuming. The STOP-Bang ques-tionnaire is a convenient tool for OSA screening, but its high sensitivity comes at the expenseof low specificity. The purpose of this study was to investigate the usefulness of combiningthe STOP-Bang questionnaire and a smartwatch capable of measuring oxygen saturation inscreening for OSA. Subjects and Method Of the patients scheduled for PSG due to OSA, 109 patients volun-tarily participated in the study by filling out a STOP-Bang questionnaire during their first visitand wearing a smartwatch during PSG. Results There were 80 males and 29 females, with the patients’ mean age of 45±13.3 years. Based on the apnea-hypopnea index (AHI), 19 patients (17.4%) were normal, 28 (25.7%) hadmild OSA, 23 (21.1%) had moderate OSA, and 39 (35.8%) had severe OSA. When using theAHI threshold of AHI ≥15/h, the STOP-Bang alone showed sensitivity of 85.5% and specifici-ty of 61.7%. Combining the STOP-Bang questionnaire with a smartwatch resulted in a slightdecrease in sensitivity and a significant increase in specificity, yielding the values of 80.5%and 84.4%, respectively. Conclusion A two-step approach using the STOP-Bang and a smartwatch was implementedto enhance the diagnostic accuracy of screening OSA.
참고문헌 (19)
- Punjabi NM, "Sleep-disordered breathing and cardiovascular disease : An outcome-based definition of hypopneas", Am J Respir Crit Care Med, 177(10), pp.1150~1155 (2008)
- Young T, "Sleep disordered breathing and mortality : Eighteen-year follow-up of the Wisconsin sleep cohort", Sleep, 31(8), pp.1071~1078 (2008)
- Young T, "Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women", Sleep, 20(9), pp.705~706 (1997)
- Chung F, "STOP questionnaire : A tool to screen patients for obstructive sleep apnea", Anesthesiology, 108(5), pp.812~821 (2008)
- Luo J, "STOP-Bang questionnaire is superior to Epworth sleepiness scales, Berlin questionnaire, and STOP questionnaire in screening obstructive sleep apnea hypopnea syndrome patients", Chin Med J(Engl), 127(17), pp.3065~3070 (2014)
- Mashaqi S, "Combined nocturnal pulse oximetry and questionnaire-based obstructive sleep apnea screening – A cohort study", Sleep Med, 72, pp.157~163 (2020)
- Nagappa M, "Validation of the STOP-Bang questionnaire as a screening tool for obstructive sleep apnea among different populations : A systematic review and meta-analysis", PLoS One, 10(12), pp.e0143697~ (2015)
- Orbea CAP, "Predictive ability and reliability of the STOP-BANG questionnaire in screening for obstructive sleep apnea in midlife women", Maturitas, 135, pp.1~5 (2020)
- Berry RB, "Rules for scoring respiratory events in sleep: Update of the 2007 AASM manual for the scoring of sleep and associated events. Deliberations of the sleep apnea definitions task force of the American Academy of Sleep Medicine", J Clin Sleep Med, 8(5), pp.597~619 (2012)
- Chung F, "STOP-Bang questionnaire : A practical approach to screen for obstructive sleep apnea", Chest, 149(3), pp.631~638 (2016)
- Garvey JF, "Epidemiological aspects of obstructive sleep apnea", J Thorac Dis, 7(5), pp.920~929 (2015)
- US Preventive Services Task Force, "Screening for obstructive sleep apnea in adults : US Preventive Services Task Force recommendation statement", JAMA, 328(19), pp.1945~1950 (2022)
- Aurora RN, "Quality measure for screening for adult obstructive sleep apnea by primary care physicians", J Clin Sleep Med, 12(8), pp.1185~1187 (2016)
- Martins EF, "Exploring the STOP-BANG questionnaire for obstructive sleep apnea screening in seniors", J Clin Sleep Med, 16(2), pp.199~206 (2020)
- Mou J, "The discriminative power of STOP-Bang as a screening tool for suspected obstructive sleep apnea in clinically referred patients : Considering gender differences", Sleep Breath, 23(1), pp.65~75 (2019)
- Min Woo Kim, "Diagnostic Performance of Photoplethysmography-Based Smartwatch for Obstructive Sleep Apnea", Journal of Rhinology, 29(3), pp.155~162 (2022), 대한비과학회[DOI]
- Rashid NH, "The value of oxygen desaturation index for diagnosing obstructive sleep apnea : A systematic review", Laryngoscope, 131(2), pp.440~447 (2021)
- "Research on 2012-2021 smartphone adoption rate and brand, smart watch and wireless earphone"[URL]
- Le VL, "Real-time detection of sleep apnea based on breathing sounds and prediction reinforcement using home noises : Algorithm development and validation", J Med Internet Res, 25, pp.e44818~ (2023)
