CompletedNot Applicable

Deep Learning Models for Prediction of Intraoperative Hypotension Using Non-invasive Parameters

South Korea5,175 participantsStarted 2023-04-01

Plain-language summary

The investigators aimed to investigate the deep learning model to predict intraoperative hypotension using non-invasive monitoring parameters.

Who can participate

SexALL

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Inclusion Criteria: * The patients who are included in the open database, VtialDB. * The patients who underwent inhaled general anesthesia for non-cardiac surgery. * The patients who have non-invasive monitoring data including blood pressure, electrocardiography, pulse oximetry, bispectral index, and capnography. Exclusion Criteria: * The patient with missing data.

What they're measuring

Deep learning model's prediction ability on intraoperative hypotension event

Timeframe: through study completion, an average of 3 hour

Trial details

NCT IDNCT05762237

SponsorSamsung Medical Center

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2024-05-01

View on ClinicalTrials.gov More Intraoperative Hypotension trials