Two-stage screening for obstructive sleep apnea in the primary practice setting

Area of Science:

• Sleep Medicine
• Primary Care Diagnostics
• Medical Technology Evaluation

Background:

• Obstructive sleep apnea (OSA) is a prevalent condition often underdiagnosed in primary care settings.
• Early detection of OSA is crucial for preventing associated comorbidities and improving patient outcomes.
• Current screening methods may lack efficiency or accessibility in routine primary care.

Purpose of the Study:

• To evaluate the diagnostic effectiveness of a novel two-stage screening model for obstructive sleep apnea (OSA).
• The model integrates the STOP-BANG questionnaire (SBQ) with automated home sleep apnea testing (HSAT).
• To assess the model's performance within a primary care environment.

Main Methods:

• A cross-sectional study involving 153 adult patients in Slovenian primary care practices.
• Participants completed the SBQ and underwent simultaneous HSAT (type III polygraphy).
• HSAT data were analyzed using both automated scoring and expert manual scoring for comparison.

Main Results:

• High correlation observed between automated and manual HSAT scoring for OSA detection (Pearson's r = 0.93).
• The two-stage model achieved 97.4% specificity and 81.1% accuracy for detecting any OSA (REI ≥ 5).
• For moderate to severe OSA (REI ≥ 15), the model demonstrated 96.7% specificity, 92.8% NPV, and 91.5% accuracy.

Conclusions:

• The combined SBQ and automated HSAT model is an effective screening tool for OSA in primary care.
• This pragmatic approach facilitates efficient and early identification of OSA, particularly moderate to severe cases.
• The study supports the implementation of this two-stage model for improved OSA diagnosis in primary care settings.