Beyond the Apnea–Hypopnea Index: A Paradigm Shift Toward Multidimensional Physiological Phenotyping in Obstructive Sleep Apnea: A Narrative Review

Background: The apnea-hypopnea index (AHI) has long served as the primary metric for diagnosing and classifying the severity of obstructive sleep apnea (OSA).However, growing evidence suggests that the AHI provides an incomplete representation of the disease's physiological burden, failing to account for event duration, the depth of hypoxemia, sleep fragmentation, and autonomic instability.This narrative review explores the inherent limitations of the AHI and evaluates emerging physiological markers that offer superior risk stratification and clinical utility.Methods: A comprehensive review of PubMed-indexed literature was conducted to analyze the limitations of the AHI and the prognostic value of alternative markers, including the oxygen desaturation index (ODI), arousal index (ARL), hypoxic burden, and pulse transit time (PTT).Results: The AHI demonstrates an inconsistent correlation with cardiovascular outcomes because it treats all respiratory events as equal, regardless of their physiological impact.In contrast, hypoxic burden, which integrates the depth and duration of desaturations, is a potent independent predictor of cardiovascular mortality.The ARL effectively quantifies sleep fragmentation and its associated sympathetic overactivity.Furthermore, PTT indices capture subcortical autonomic arousals and beat-to-beat blood pressure variability that are often missed by traditional scoring.Advances in artificial intelligence (AI) and machine learning are increasingly facilitating the integration of these multidimensional variables into a precision medicine framework.Conclusion: Moving "Beyond AHI" is essential for accurate cardiovascular risk assessment and personalized management of OSA.Integrating markers of hypoxic load, sleep continuity, and autonomic function into routine clinical practice will improve diagnostic efficiency, particularly in specific phenotypes like "lean OSA".