Accurate diagnosis of obstructive sleep apnea (OSA) is critical to effective patient care, yet growing evidence shows that a single-night of testing might not tell the full story. Night-to-night variability in the apnea-hypopnea index (AHI), as well as the first night effect, can lead to underdiagnosis and misclassification, potentially delaying appropriate treatment.
Yoav Nygate, EnsoData’s VP of Artificial Intelligence, explores the science behind AHI variability and its clinical implications, drawing on analysis from over 50,000 patients tested across multiple nights. See how multi-night testing reveals cases of moderate to severe OSA that are frequently missed with single-night studies.
Gain a deeper understanding of how reliance on a single night can lead to patient misclassification and how adopting a multi-night approach offers a more accurate, comprehensive view of true sleep health.
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