Abstract

Abstract Obstructive sleep apnea is conventionally diagnosed using the apnea-hypopnea index (AHI), which measures only the frequency of respiratory events. However, AHI ignores key event features and effects, such as hypoxemia patterns, ventilatory drops, and autonomic responses, hindering accurate evaluation of CPAP benefits and cardiovascular risk prediction. New metrics from polysomnography (PSG) secondary analysis provide valuable complementary data. This review focuses on four: Hypoxic burden (HB), ventilatory burden (VB), delta heart rate (ΔHR), and pulse arrival time (PAT). High HB correlates with increased cardiovascular events, cardiovascular mortality, and all-cause mortality in diverse studies. ΔHR, indicating heart rate changes during events, links to subclinical cardiovascular disease, mortality, and possible CPAP interactions. VB, from airflow and effort, predicts new cardiovascular disease. PAT, reflecting blood pressure changes, associates with subclinical pathology. Combining these with AHI could improve risk assessment and treatment decisions.