In this comprehensive systematic review, we identified 31 studies that identified promising alternative PSG metrics that have the potential to better predict OSA-related complications than standard metrics. These alternative metrics can leverage the richness of the raw PSG data into generating a more nuanced description of the disease. Broadly speaking, we found 4 general categories of alternative metrics pertaining to hydrodynamic-related, EEG-related, de-saturation indices, and respiratory event data. These metrics were used to predict a broad range of OSA-associated outcomes, including CVD, cognitive dysfunction, hypertension, CKD, car crash risk, and all-cause mortality. Identifying bio-metric profiles based on PSG may help stratify patients more at risk of the effects of OSA and could significantly affect patient management. For example, if a patient was identified as having a high risk of CVD, one would be more aggressive in terms of OSA management and management of other CV risk factors (eg, hypertension, hyperlipidemia, inactivity). In addition, these profiles may help identify potential pharmacologic targets for therapy; for example, if a patient with high sympathetic activity was identified based on PSG metrics, they might be more likely to benefit from a beta-blocker to improve CV risk.
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