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Clinical Validation of Vital-PICASO for Predicting Hypoxia Within 24 Hours in General Ward Inpatients
Sponsor: Huinno AIM
Summary
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.
Official title: Clinical Validity of an AI-Based Biological Signal Analysis Software Vital-PICASO for Predicting the Risk of Hypoxia Within 24 Hrs Using Vital Sign (SBP, DBP, HR, RR, BT, SpO₂) From General Ward Inpatients; A Retrospective, Single-Center, Single-Arm, Superiority-confirmatory Clinical Trial
Key Details
Gender
All
Age Range
19 Years - Any
Study Type
OBSERVATIONAL
Enrollment
2250
Start Date
2025-08-20
Completion Date
2026-07-07
Last Updated
2026-08-03
Healthy Volunteers
No
Conditions
Locations (1)
Seoul National University Hospital
Seoul, South Korea