Sleep & breathing = Schlaf & Atmung · 2024
Two-stage screening for obstructive sleep apnea in the primary practice setting.
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Pangerc Andrej, Petek Šter Marija, Dolenc Grošelj Leja
Аннотация
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.
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.