Prediction in obstructive sleep apnoea: diagnosis, comorbidity risk, and treatment outcomes

ABSTRACT Introduction: Obstructive sleep apnoea (OSA) is common disorder, under-diagnosed, and can be difficult to treat adequately across the lifespan. OSA is a heterogeneous disorder with different risk factors, clinical presentations, pathophysiology and morbidity. Prediction has an important role in OSA recognition and management, embodied in screening methods to circumvent the need for diagnosis by overnight sleep studies and prediction of treatment efficacy and adherence. Other opportunities exist in predicting susceptibility to comorbidity and health outcomes. Areas covered: This review summarizes current prediction strategies as applied to OSA, covering diagnosis, consequences and treatment outcomes, as well as potential emergent areas of focus. Expert commentary: Prediction of disease risk, susceptibility to comorbidity, and treatment outcomes are important aspects of precision medicine. The key to accurate prediction in OSA relies on comprehensive understanding of disease phenotypes.