Clinical Validation of Vital-PICASO for Predicting Hypoxia Within 24 Hours in General Ward Inpatients

The purpose of this retrospective study is to evaluate the clinical performance of Vital-PICASO, an artificial intelligence-based biological signal analysis software designed to predict the risk of hypoxia within 24 hours using vital-sign data from adult general ward inpatients. Electronic medical record data from patients aged 19 years or older who were admitted to a general ward at Seoul National University Hospital will be retrospectively reviewed. Hypoxia will be evaluated using two separate reference-standard criteria: oxygen saturation below 94% and administration of oxygen at 4 L/min or more. Eligible hypoxia-positive and hypoxia-negative datasets will be randomly selected. The selected vital-sign datasets will be analyzed using Vital-PICASO while the device operator is blinded to the reference-standard classification. The software-generated hypoxia risk scores will be compared with the reference-standard classifications to evaluate predictive performance. Because the study uses previously collected medical records, there is no direct participant contact and the software results will not affect patient care.