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Not yet recruitingNCT06734650Updated Dec 16, 2024

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

An observational study in Peripheral Vein, Arterial Wave Reflections and Pulse Pressure Variation, sponsored by Seoul National University Bundang Hospital. Not yet recruiting at 1 site in Korea, Republic of. Open to participants aged 19 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-12-16.

Sponsored by Seoul National University Bundang Hospital · Observational

From the registry’s dates

  • Primary completion was expected by Nov 2025, 10 months ago, but the record still lists the study as not yet recruiting.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
150
Ages
19 Years to 80 Years
Sex
All
01

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 .

Read the detailed description

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 .

02

Conditions studied

  • Peripheral Vein
  • Arterial Wave Reflections
  • Pulse Pressure Variation
  • Stroke Volume Variation
  • Deep Learning Model
03

In context

Lead sponsor

Seoul National University Bundang Hospital is the lead sponsor of 368 studies on the registry; 55 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
19 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Probability sample

Study population

Patients scheduled for elective hepatectomy under general anesthesia

Inclusion criteria

  • Patients who voluntarily agreed and signed the written informed consent form before participating in this study
  • Adult aged 19 years or older
  • American Society of Anesthesiologists physical class (ASA) 1-3
  • Patients scheduled for elective hepatectomy under general anesthesia
  • Patients who require arterial pressure monitoring and additional peripheral venous access for routine anesthesia preparation
  • Non-smokers with normal pulmonary function

Exclusion criteria

Exclusion Criteria:

  • Patients with abnormal findings on electrocardiogram before surgery
  • Patients who cannot undergo peripheral venous puncture
05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
150 participants (estimated)
Target follow-up
1 Day
Patient registry
Yes

Groups and cohorts

  • Peripheral waveform collection group

    1. Peripheral Venous Pressure Variation 2. Stroke Volume Variation 3. Pulse Pressure Variation 4. Pleth Variability Index

    Other: peripheral waveform collection

Interventions

  • Otherperipheral 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).

06

What researchers measure

Primary outcomes

  1. Pulse pressure variation

    from arterial waveform

    Time frame: intraoperative period

07

Study locations

1 site
  • Seoul National University Bundang Hospital
    Seongnam-si, Gyunggi-do 13620, Korea, Republic of
08

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 16, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
09

Registry details

Key details

Study ID
NCT06734650
Lead sponsor
Seoul National University Bundang Hospital
Responsible party
Park InSun (Principal investigator, Seoul National University Bundang Hospital) — Principal investigator
First posted
Dec 16, 2024
Start date
Dec 28, 2024 (estimated)
Primary completion
Nov 28, 2025 (estimated)
Completion
Nov 28, 2026 (estimated)
Last update
Dec 16, 2024

Study contacts

Insun Park, M.D./Ph.D.
Contact
pis121@hanmail.net
82317877499
Insun Park, M.D./Ph.D.
principal investigator · assistant professor

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Dec 2024. You cannot join it, but the record below documents what was studied.

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