Hypotension During SurgeryNCT06897514
External Validation of Prediction Algorithm Using Non-invasive Monitoring Device for Intraoperative Hypotension
An observational study of Hypotension During Surgery, run by Samsung Medical Center at 1 site in South Korea.
Trial summary
The goal of this prospective observational study is to externally validate the prediction algorithm using non-invasive monitoring device for intraoperative hypotension. The main question it aims to answer is: Does the prediction algorithm predict intraoperative hypotension effectively? Read more about this study
- Who is it for?
- Ages 19 years and older
- Conditions the study is for
- Hypotension During Surgery
- What is being tested?
- Prediction algorithm for intraoperative hypotension
- How many people
- 200 participants
- Where
- 1 siteSouth Korea
- Study dates
- 11 Apr 2025to 31 Dec 2025
- How long will I take part?
- 30 Days
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The patients who undergoing general anesthesia with five non-invasive monitoring device (non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and Bispectral Index)
Who may be able to join
- Adults patients aged 19 or more
- Elective surgery under general anesthesia
- American Society of Anesthesiologists physical status I - III
Who cannot join
- Vasopressor/Inotrope usage before surgery
- Patients who needs invasive arterial cannulation
- Emergency surgery
- Pregnant or lactating women
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
South Korea1 site, 1 recruiting
- Recruiting
Samsung Medical Center
Seoul, 06351
Heejoon Jeong, MD, +82-2-3410-0841, heejoonjeong@skku.edu
About this study
The goal of this prospective observational study is to externally validate the prediction algorithm using non-invasive monitoring device for intraoperative hypotension. The main question it aims to answer is: Does the prediction algorithm predict intraoperative hypotension effectively?
Read the detailed description
The hypotension that occurs during surgery is associated with the poor prognosis of patients after surgery. Previous studies have reported that even a short period of time of hypotension increases the risk of postoperative complications such as kidney injury. If anesthesiologists can predict intraoperative hypotension in advance, they can prevent or minimize the damage.
Recently, there are many reports on medical artificial intelligence models that predict the intraoperative hypotension. Among them, the Hypotension Prediction Index (HPI) model has already been commercialized and used in clinical practice. However, HPI has limitations in that it is necessary to perform invasive techniques (arterial cannulation) or to use dedicated equipment at high cost. However, since many of the general anesthesia are performed without invasive monitoring devices, the use of HPI medical devices is subject to considerable restrictions.
The investigators have reported the prediction algorithm for intraoperative hypotension using five non-invasive monitoring devices commonly used in general anesthesia: 1) blood pressure (NBP, number), 2) electrocardiogram (ECG, waveform), 3) end-oxygen saturation waveform (PPG, waveform), 4) end-stage carbon dioxide waveform (ETCO2, waveform), and 5) an anesthesia depth (BIS, number) By conducting a retrospective external validation process using public clinical data from other institutions (tertiary hospital in Korea), the final model was able to have good predictability with an Area Under the Receiver-Operating Characteristic Curve (AUROC) value of 0.917.
However, investigators did not externally validate that algorithm through a prospective designed study. This study intends to externally validate the "hypertension prediction model during surgery using non-invasive monitoring device", which has already reported It is expected that the usefulness and limitations of the prediction model can be evaluated again, and the model can be advanced based on the results.
- Conditions
- Hypotension During Surgery
- Being tested
- Prediction algorithm for intraoperative hypotension
- Keywords
- intraoperative hypotension, prediction algorithm
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Prediction algorithm for intraoperative hypotensionDiagnostic test
All participants will receive five non-invasive monitoring during their surgery. Data from these monitoring device will be put into the prediction algorithm.
| Study group | Role | What they receive |
|---|---|---|
| Study group (single group) | All participants are enrolled in single group. Receives: Diagnostic Test: Prediction algorithm for intraoperative hypotension |
What is being measured
The primary outcome is the main question the study is designed to answer.
Value of the Area Under the Receiver-Operating Characteristic curve analysis
The area under the receiver operating characteristic curve is a measurement of how well a prediction model can predict intraoperative hypotension. It is used to assess the performance of algorithm.
Measured: 5 minutes before the occurrence of hypotension during general anesthesia
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Mar 2025
- Study start11 Apr 2025
- Primary completionDec 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Hypotension During SurgeryStudies of the same condition, open and under way.
- More trials run by Samsung Medical CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 200 participants (estimated)
- Target duration
- 30 Days
Sponsor and investigators
- Lead sponsor
- Samsung Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hyun Joo Ahn, Samsung Medical Center
- Investigators
- Hyun Joo Ahn, MD PhD, Principal investigator, Samsung Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06897514
- Sponsor's protocol ID
- SMC 2025-02-006
- Status last verified
- May 2025
- First submitted
- 25 Mar 2025
- Last updated
- 15 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Jeong H, Kim D, Kim DW, Baek S, Lee HC, Kim Y, Ahn HJ. Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices. J Clin Monit Comput. 2024 Dec;38(6):1357-1365. doi: 10.1007/s10877-024-01206-6. Epub 2024 Aug 19.
PubMed 39158783
Study at a glance
From the registry record, last updated by the sponsor on 15 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- External Validation of Prediction Algorithm Using Non-invasive Monitoring Device for Intraoperative Hypotension
- ClinicalTrials.gov ID
- NCT06897514
- Acronym / sponsor ID
- SMC 2025-02-006
- Conditions
- Hypotension During Surgery
- Keywords
- intraoperative hypotension, prediction algorithm
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Samsung Medical CenterUniversity, hospital or other
- Study start
- 11 Apr 2025 (actual)
- Primary completion
- Dec 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 27 Mar 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this prospective observational study is to externally validate the prediction algorithm using non-invasive monitoring device for intraoperative hypotension. The main question it aims to answer is: Does the prediction algorithm predict intraoperative hypotension effectively?
Detailed description
The hypotension that occurs during surgery is associated with the poor prognosis of patients after surgery. Previous studies have reported that even a short period of time of hypotension increases the risk of postoperative complications such as kidney injury. If anesthesiologists can predict intraoperative hypotension in advance, they can prevent or minimize the damage.
Recently, there are many reports on medical artificial intelligence models that predict the intraoperative hypotension. Among them, the Hypotension Prediction Index (HPI) model has already been commercialized and used in clinical practice. However, HPI has limitations in that it is necessary to perform invasive techniques (arterial cannulation) or to use dedicated equipment at high cost. However, since many of the general anesthesia are performed without invasive monitoring devices, the use of HPI medical devices is subject to considerable restrictions.
The investigators have reported the prediction algorithm for intraoperative hypotension using five non-invasive monitoring devices commonly used in general anesthesia: 1) blood pressure (NBP, number), 2) electrocardiogram (ECG, waveform), 3) end-oxygen saturation waveform (PPG, waveform), 4) end-stage carbon dioxide waveform (ETCO2, waveform), and 5) an anesthesia depth (BIS, number) By conducting a retrospective external validation process using public clinical data from other institutions (tertiary hospital in Korea), the final model was able to have good predictability with an Area Under the Receiver-Operating Characteristic Curve (AUROC) value of 0.917.
However, investigators did not externally validate that algorithm through a prospective designed study. This study intends to externally validate the "hypertension prediction model during surgery using non-invasive monitoring device", which has already reported It is expected that the usefulness and limitations of the prediction model can be evaluated again, and the model can be advanced based on the results.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 30 Days
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Study group (single group) | – | Diagnostic Test: Prediction algorithm for intraoperative hypotensionAll participants are enrolled in single group. |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The patients who undergoing general anesthesia with five non-invasive monitoring device (non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and Bispectral Index)
Key inclusion criteria (3 listed)
- Adults patients aged 19 or more
- Elective surgery under general anesthesia
- American Society of Anesthesiologists physical status I - III
Key exclusion criteria (4 listed)
- Vasopressor/Inotrope usage before surgery
- Patients who needs invasive arterial cannulation
- Emergency surgery
- Pregnant or lactating women
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Prediction algorithm for intraoperative hypotensionAll participants will receive five non-invasive monitoring during their surgery. Data from these monitoring device will be put into the prediction algorithm. | Diagnostic test | Study group (single group) |
Primary outcome
Value of the Area Under the Receiver-Operating Characteristic curve analysis
Time frame: 5 minutes before the occurrence of hypotension during general anesthesia
The area under the receiver operating characteristic curve is a measurement of how well a prediction model can predict intraoperative hypotension. It is used to assess the performance of algorithm.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 May 2025.
- Results publication: PubMed 39158783Jeong H, Kim D, Kim DW, Baek S, Lee HC, Kim Y, Ahn HJ. Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices. J Clin Monit Comput. 2024 Dec;38(6):1357-1365. doi: 10.1007/s10877-024-01206-6. Epub 2024 Aug 19.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Hyun Joo Ahn, MD PhD principal investigator
Samsung Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hypotension During Surgery, run by Samsung Medical Center at 1 site in South Korea.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 15 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in South Korea. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hyun Joo Ahn, MD PhD (821099330784, hyunjooahn@skku.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Value of the Area Under the Receiver-Operating Characteristic curve analysis (time frame: 5 minutes before the occurrence of hypotension during general anesthesia). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06897514, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 May 2025.