Diagnostic accuracy of a questionnaire and simple home monitoring device in detecting obstructive sleep apnoea in a Chinese population at high cardiovascular risk
Abstract
Background and objective: OSA is a common condition associated with cardiovascular (CV) morbidity. It remains underdiagnosed globally in part due to the limited availability and technical requirements of polysomnography (PSG). The aim of this study was to test the accuracy of two simple methods for diagnosing OSA. Methods: Consecutive subjects identified from a community register with high CV risk were invited to complete the Berlin Sleep Questionnaire and undergo simultaneous, home, overnight PSG and ApneaLink device oximetry and nasal pressure recordings. The relative accuracies of the Berlin Questionnaire, oximetry and nasal pressure results in diagnosing PSG‐defined moderate‐severe OSA were assessed. Results: Of 257 eligible high CV risk subjects enrolled, 190 completed sleep studies and 143 subjects' studies were of sufficient quality to include in final analyses. Moderate‐severe OSA was confirmed in 43% of subjects. The Berlin Questionnaire had low overall diagnostic accuracy in this population. However, ApneaLink recordings of oximetry and nasal pressure areas had high diagnostic utility with areas under the receiver operating characteristic curves of 0.933 and 0.933, respectively. At optimal diagnostic thresholds, oximetry and nasal pressure measurements had similar sensitivity (84% vs 86%) and specificity (84% vs 85%). Technical failure was lower for oximetry than nasal pressure (5.8% vs 18.9% of tests). Conclusions: In patients with high CV risk overnight single‐channel oximetry and nasal pressure measurements may provide high diagnostic accuracy and offer an accessible alternative to full PSG.
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Using a cutoff of AHI ≥ 30, accuracy of 2-3 channel HSAT against unattended in-home PSG ranged from 83% to 91%.
“using a cutoff of AHI ≥ 30, accuracy ranged from 83% to 91%”
From Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline (2017) · cites this paper as [53]
When 2-3 channel HSAT was evaluated against unattended in-home PSG, using a cutoff of AHI ≥ 15, accuracy in a high-risk population was 86% (95% CI: 76% to 93%).
“When the performance of 2–3 channel HSAT was evaluated against unattended in-home PSG, using a cutoff of AHI ≥ 15, accuracy in a high-risk population was 86% (95% CI: 76% to 93%)”
From Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline (2017) · cites this paper as [53]
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965 · see citing works
The new AASM criteria for scoring hypopneas: impact on the apnea hypopnea index
Ruehland, W. R., Rochford, P. D., O’Donoghue, F. J., Pierce, R. J., Singh, P., & Thornton, A. T. (2009) · SLEEP · doi:10.1093/sleep/32.2.150 · Cited by 696 · see citing works
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Kapur, V. K., Auckley, D. H., Chowdhuri, S., Kuhlmann, D. C., Mehra, R., Ramar, K., & Harrod, C. G. (2017) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.6506 · Cited by 3,253 · see citing works
CPAP for Prevention of Cardiovascular Events in Obstructive Sleep Apnea
McEvoy, R. D., Antic, N. A., Heeley, E., Luo, Y., Ou, Q., Zhang, X., Mediano, O., Chen, R., Drager, L. F., Liu, Z., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1606599 · Cited by 2,101 · see citing works
Self-citationChiu, H.-Y., Chen, P.-Y., Chuang, L.-P., Chen, N.-H., Tu, Y.-K., Hsieh, Y.-J., Wang, Y.-C., & Guilleminault, C. (2017) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2016.10.004 · Cited by 650 · see citing works
Obstructive Sleep Apnea Devices for Out-Of-Center (OOC) Testing: Technology Evaluation
Collop, N. A., Tracy, S. L., Kapur, V., Mehra, R., Kuhlmann, D., Fleishman, S. A., & Ojile, J. M. (2011) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.1328 · Cited by 427 · see citing works
Screening Questionnaires for Obstructive Sleep Apnea: An Updated Systematic Review
Amra, B., Rahmati, B., Soltaninejad, F., & Feizi, A. (2018) · Oman Medical Journal · doi:10.5001/omj.2018.36 · Cited by 142 · see citing works
Van Ryswyk, E., Anderson, C. S., Antic, N. A., Barbe, F., Bittencourt, L., Freed, R., Heeley, E., Liu, Z., Loffler, K. A., Lorenzi-Filho, G., et al. (2019) · Sleep · doi:10.1093/sleep/zsz152 · Cited by 115 · see citing works
Self-citationJinmei, L., Rong, H., Xu, Z., Yi, X., & Jiong, Z. (2014) · Chinese Medical Journal · doi:10.3760/cma.j.issn.0366-6999.20141196 · Cited by 104 · see citing works
European Respiratory Society statement on sleep apnoea, sleepiness and driving risk
Bonsignore, M. R., Randerath, W., Schiza, S., Verbraecken, J., Elliott, M. W., Riha, R., Barbe, F., Bouloukaki, I., Castrogiovanni, A., Deleanu, O., et al. (2021) · European Respiratory Journal · doi:10.1183/13993003.01272-2020 · Cited by 84 · see citing works
Linz, D., Kadhim, K., Brooks, A. G., Elliott, A. D., Hendriks, J. M. L., Lau, D. H., Mahajan, R., Gupta, A. K., Middeldorp, M. E., Hohl, M., et al. (2018) · International Journal of Cardiology · doi:10.1016/j.ijcard.2018.07.124 · Cited by 37 · see citing works
Lin, S. H., Branson, C., Park, L., Leung, J., Doshi, N., & Auerbach, S. H. (2018) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.7538 · Cited by 26 · see citing works
Modesti-Vedolin, G., Chies, C., Chaves-Fagondes, S., Piza-Pelizzer, E., & Lima-Grossi, M. (2018) · Medicina oral, patología oral y cirugía bucal · doi:10.4317/medoral.22580 · Cited by 22 · see citing works
de Vries, G. E., van der Wal, H. H., Kerstjens, H. A. M., van Deursen, V. M., Stegenga, B., van Veldhuisen, D. J., van der Hoeven, J. H., van der Meer, P., & Wijkstra, P. J. (2015) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2015.06.009 · Cited by 17 · see citing works
- Authors
- GANTNER, D., GE, J., LI, L., ANTIC, N., WINDLER, S., WONG, K., HEELEY, E., HUANG, S., CUI, P., ANDERSON, C., WANG, J., & MCEVOY, D.
- Affiliations
- The University of Sydney (AU)
- Shanghai Jiao Tong University (CN)
- Flinders University (AU)
- Ruijin Hospital (CN)
- Venue
- Respirology
- Publisher
- Wiley
- Published
- 2010-07-21
- Volume
- 15
- Issue
- 6
- Pages
- 952-960
- ISSN
- 1323-7799 (ISSN-L)
- 1440-1843
- OpenAlex
- W1498237688
- Cited by
- 64
- References
- 2
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 4 · 2021: 6 · 2020: 3 · 2019: 6 · 2018: 8 · 2017: 9 · 2016: 5 · 2015: 6 · 2014: 6 · 2013: 3 · 2012: 2
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Respirology (publishedVersion)
- PubMed (publishedVersion)
- Flinders Academic Commons (Flinders University) (submittedVersion)
- Funders
- Ruijin Hospital
- Topics
- Health Sciences › Medicine › Physiology › Obstructive Sleep Apnea Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Neuroscience of respiration and sleep
- Keywords
- obstructive sleep apnea, diagnostic accuracy, home sleep monitoring, ApneaLink, oximetry, nasal pressure, cardiovascular risk, polysomnography alternative, Chinese population
- MeSH terms
- Aged, Cardiovascular Diseases, Female, Humans, Male, Manometry, Middle Aged, Oximetry, Surveys and Questionnaires, Smoking, Comorbidity, Polysomnography, Sleep Apnea, Obstructive, Asian People
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