Deep Learning Model for Predicting a Peripheral Venous Waveform-based Pulse Pressure Variation

Condition(s) studied

Investigational drug(s) / intervention(s)

peripheral waveform collection: The peripheral venous pressure waveform is collected by connecting a pressure transducer that is currently in use to the placed central venous line. In addition, the pulse pressure variation or stroke volume variation value that can be obtained from the arterial catheter. This extracts the medical records and bio-signal information of the subjects registered through the previously approved 'Establishment of a Bio-signal and Clinical Information Registry for the Development of Patient Monitoring Algorithm' study (B-2202-738-401).

Study summary

Pulse pressure variation is a monitoring index that indicates the response to fluid therapy in patients receiving mechanical ventilation, and is used as a reference for patients with unstable hemodynamic conditions. However, it is invasive because it requires arterial puncture to collect it. In a previous study by the investigators, the investigators developed and verified an artificial intelligence model that predicts stroke volume variation, in real time using only the central venous pressure waveform. However, since a large vein such as the jugular vein must be punctured to collect the central venous pressure waveform, it is still invasive, and its clinical utility is low. Therefore, in this study, the investigators collected waveforms from peripheral veins that are less invasive and can be a wide range of applications because all surgical patients have them. The investigators aimed to develop and verify an artificial intelligence model that predicts pulse pressure variation obtained from peripheral venous waveforms .

Eligibility

Primary outcome measure(s)

• Pulse pressure variation — intraoperative period
  from arterial waveform

Trial sites (1)

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