A diagnostic algorithm for obstructive sleep apnea in primary care

Obstructive sleep apnea (OSA) is underdiagnosed and has a long waiting list in Hospital Sleep Units (HSU). We proposed a diagnostic algorithm in primary care (PC), INNOBICS-SAHS, which requires a PC sleep nurse (PCSN), a sleep specific platform for OSA (SSP) and a Virtual Sleep Unit (VSU). It is partially funded by EIT Health. <bold>Methods:</bold> A prospective and descriptive study was performed from January 2022 to September 2023 involving 11 PC centers in Girona (Catalonia). PC physicians applied a STOP-Bang test to subjects who attended for any reason. If the result was ≥3 they were referred to the PCSN who evaluated exclusion criteria, performed a sleep clinical history and a home respiratory poligraphy (HRP). The HRP was downloaded to SSP Airview (Resmed®). The VSU analysed it, revised the clinical history, made a diagnosis and informed the subjects electronically classifying them in 3 groups: 1) no sleep respiratory disorders (apnea-hypoapnea index –AHI- <5/h or 5-14.9/h without the following criteria: ≥15% of time with oxygen saturation <90% or sleep symptoms that affect daily life or recent onset of cardiovascular disease), 2) OSA requiring CPAP (AHI 5-29.9/h with at least one of the previous criteria, or AHI ≥30/h) and 3) doubtful cases (the remaining ones). The first were discharged, the second were followed up by the PCSN and the third were referred to the HSU. <bold>Results:</bold> A total of 2478 subjects were screened with STOP-Bang ≥3. A HRP was performed in 2087 (84.4%). Of them, 94.3% were assessed by the VSU in <30 days (Figure 1). Subjects who performed a HRP 24.1% were discharged, 56.5% were diagnosed with OSA requiring CPAP and 19.3% were referred to the HSU (Figure 2). <bold>Conclusion:</bold> This algorithm seemed fast and reliable.