Year: 2024
Type: article
Study design: Observational Study
Abstract: PURPOSE: To evaluate the effectiveness of a two-stage screening model for obstructive sleep apnea (OSA) in primary care that combines the STOP-BANG questionnaire (SBQ) with an automated home sleep apnea test (HSAT). METHODS: This cross-sectional study was conducted from August 2018 to August 2022 in four Slovenian primary care practices. It included 153 randomly selected patients aged 18 to 70 years who visited the practice for any reason. Participants completed the SBQ and underwent HSAT with type III polygraphy on the same night. The HSAT recordings were scored automatically and by an experienced, accredited somnologist. RESULTS: There was a strong correlation between manual and automated HSAT scorings for the detection of OSA (Pearson's r = 0.93). Cohen's kappa was 0.80 for OSA (respiratory event index (REI) ≥ 5) and 0.77 for OSA severity categorization. The two-stage model demonstrated sensitivity of 64%, a specificity of 97.4%, a positive predictive value (PPV) of 96.0%, a negative predictive value (NPV) of 73.8% and an accuracy of 81.1% for any OSA (REI ≥ 5). For moderate to severe OSA (REI ≥ 15), the model showed 72.7% sensitivity, 96.7% specificity, 85.7% PPV, 92.8% NPV and 91.5% accuracy. CONCLUSIONS: The two-stage model for OSA screening combining the SBQ and automated HSAT was shown to be effective in primary care, especially for moderate and severe OSA. This method provides a practical and efficient approach for the early detection of OSA.
Source: Sleep And Breathing
Institutions: University of Ljubljana, Ljubljana University Medical Centre
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,590
OpenAlex ID: W4402398766