Development and validation of a model for diagnosis of obstructive sleep apnoea in primary care. Issue 10 (2nd August 2021)

• Record Type: Journal Article
• Authors: Chapman, Julia L.; Hoyos, Camilla M.; Killick, Roo; Sutherland, Kate; Cistulli, Peter A.; Zwar, Nick; Yee, Brendon J.; Marks, Guy; Grunstein, Ronald R.; Wong, Keith K. H.
• Other Names: Siebers Amanda investigator.; Dungan George investigator.; Dennis Sarah investigator.; Rofail Lydia Makarie investigator.; Buchanan Peter investigator.; Harrington Zinta investigator.; Lee Richard investigator.; Chan Andrew S. L. investigator.; Williams Mark investigator.
• Is Part Of: Respirology. Volume 26:Issue 10(2021)
• Page Start: 989
• Page End: 996
• Publication Date: 2021-08-02
• Subjects: development and validation -- diagnostic model -- obstructive sleep apnoea -- predictive value -- primary care; Respiratory organs -- Diseases -- Periodicals; Respiratory organs -- Periodicals; 612.2
• DOI: 10.1111/resp.14122
• Languages: English
• ISSNs: 1323-7799

Abstract

Abstract: Background and objective: Use of in‐laboratory polysomnography (PSG) to diagnose obstructive sleep apnoea (OSA) is cost and resource intensive. Questionnaires, physical measurements and home monitors have been studied as potential simpler alternatives. This study aimed to develop a diagnostic model for OSA for use in primary care. Methods: Primary care practitioners were trained to recognize symptoms of sleep apnoea and recruited patients based on the clinical need to investigate OSA. Assessment was by symptom questionnaires, anthropomorphic measurements, digital facial photography, and a single‐channel nasal flow monitor (Flow Wizard©, DiagnoseIT, Sydney, Australia) worn at home for 3 nights. The in‐laboratory PSG was the reference test, with OSA defined as apnoea–hypopnoea index (AHI) ≥10 events/h. Results: In the model development phase, 25 primary care practitioners studied 315 patients in whom they suspected OSA, of which 57% had AHI≥10 and 22% had AHI≥30. Published OSA questionnaires provided low to moderate prediction of OSA (area under the curve [AUC] 0.53–0.73). The nasal flow monitor alone yielded high accuracy for predicting OSA with AUC of 0.87. Sensitivity was 0.87 and specificity 0.77 at a threshold respiratory event index (REI) of 18 events/h. A model adding age, gender, symptoms and BMI to the nasal flow monitor REI only modestly improved OSA prediction (AUC 0.89), with similar AUC (0.88) confirmed in the validation population of 114 patients. Conclusion: Sleep apnoea can be diagnosed in the primary care setting with a combination of clinical judgement and portable monitor test outcomes. Abstract : We developed and validated a simplified diagnostic technique with a home‐worn device for use in the primary care setting to reliably diagnose obstructive sleep apnoea without the need for polysomnography. This model allows primary care physicians to identify patients at high suspicion of sleep apnoea. We show that generally recommended screening questionnaires provide little added benefit. See related Editorial