Non-cardiac SurgeryNCT04705064
Artificial Intelligence and Postoperative Acute Kidney Injury
An observational study of Non-cardiac Surgery, run by Seoul National University Hospital at 1 site in South Korea.
Trial summary
The main objective of this study is to develop and validate an artificial intelligence model that predicts postoperative acute kidney injury. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Non-cardiac Surgery
- What is being tested?
- Prediction of postoperative acute kidney injury using an artificial intelligence
- How many people
- 2,000 participants
- Where
- 1 siteSouth Korea
- Study dates
- 1 Mar 2021to 1 Feb 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- Adult, Older adult
Study population: Adults patients undergoing non-cardiac surgery
Who may be able to join
- Adults patients undergoing non-cardiac surgery
Who cannot join
- Age under 18 years
- Surgery duration < 1 hour
- Transplantation surgery
- Nephrectomy
- Cardiac surgery
- Patients who had severe kidney dysfunction preoperatively as follows:
Show all 10Show fewer
- Serum creatinine ≥ 4 mg/dl
- Estimated glomerular filtration rate <15 ml/min/1.73m2
- History of renal replacement therapy
- Patients who had no results of preoperative or postoperative serum creatinine
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Development and Prospective Validation of an Artificial Intelligence Model to Predict Postoperative Acute Kidney Injury
The main objective of this study is to develop and validate an artificial intelligence model that predicts postoperative acute kidney injury.
Read the detailed description
Postoperative acute kidney injury is known to increase the length of hospital stay and healthcare cost. A lot of risk prediction models have been developed for identifying patients at increased risk of postoperative acute kidney injury. Recent advances in artificial intelligence make it possible to manage and analyze big data. Prediction model using an artificial intelligence and large-scale data can improve the accuracy of prediction performance. Furthermore, the use of an artificial intelligence may be a useful adjuvant tool in making clinical decisions or real-time prediction if it is integrated into the electrical medical record systems. However, before implementing an artificial intelligence model into the clinical setting, prospective evaluation of an artificial intelligence model's real performance is essential. However, to our knowledge, there was no artificial intelligence model for prediction of postoperative acute kidney injury, which was prospectively evaluated. Therefore, we aimed to develop an artificial intelligence model which predicts postoperative acute kidney injury and evaluate the model's performance prospectively.
- Conditions
- Non-cardiac Surgery
- Being tested
- Prediction of postoperative acute kidney injury using an artificial intelligence
- Keywords
- Artificial Intelligence, Postoperative acute kidney injury, Prospective validation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Prediction of postoperative acute kidney injury using an artificial intelligenceDiagnostic test
The performance of an artificial intelligence model to predict postoperative acute kidney injury will be tested prospectively.
| Study group | Role | What they receive |
|---|---|---|
| AI_AKI | Adults patients undergoing non-cardiac surgery Receives: Diagnostic Test: Prediction of postoperative acute kidney injury using an artificial intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
the incidence of postoperative acute kidney injury
postoperative acute kidney injury (diagnosed by KDIGO criteria using peak serum creatinine level) included all acute kidney injury events regardless of acute kidney injury severity
Measured: during the postoperative seven days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Jan 2021
- Study start1 Mar 2021 (estimated)
- Primary completion31 May 2021 (estimated)
- Study completion1 Feb 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Non-cardiac SurgeryStudies of the same condition, open and under way.
- More trials run by Seoul National University HospitalThe 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
- 2,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Seoul National University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hyung-Chul Lee, Seoul National University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04705064
- Sponsor's protocol ID
- 2012-069-1180
- Status last verified
- Jan 2021
- First submitted
- 8 Jan 2021
- Last updated
- 12 Jan 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 Jan 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Prospective Validation of an Artificial Intelligence Model to Predict Postoperative Acute Kidney Injury
- ClinicalTrials.gov ID
- NCT04705064
- Acronym / sponsor ID
- 2012-069-1180
- Conditions
- Non-cardiac Surgery
- Keywords
- Artificial Intelligence, Postoperative acute kidney injury, Prospective validation
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- Seoul National University HospitalUniversity, hospital or other
- Study start
- 1 Mar 2021 (estimated)
- Primary completion
- 31 May 2021 (estimated)
- Study completion
- 1 Feb 2022 (estimated)
- First posted
- 12 Jan 2021 (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 main objective of this study is to develop and validate an artificial intelligence model that predicts postoperative acute kidney injury.
Detailed description
Postoperative acute kidney injury is known to increase the length of hospital stay and healthcare cost. A lot of risk prediction models have been developed for identifying patients at increased risk of postoperative acute kidney injury. Recent advances in artificial intelligence make it possible to manage and analyze big data. Prediction model using an artificial intelligence and large-scale data can improve the accuracy of prediction performance. Furthermore, the use of an artificial intelligence may be a useful adjuvant tool in making clinical decisions or real-time prediction if it is integrated into the electrical medical record systems. However, before implementing an artificial intelligence model into the clinical setting, prospective evaluation of an artificial intelligence model's real performance is essential. However, to our knowledge, there was no artificial intelligence model for prediction of postoperative acute kidney injury, which was prospectively evaluated. Therefore, we aimed to develop an artificial intelligence model which predicts postoperative acute kidney injury and evaluate the model's performance prospectively.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| AI_AKI | – | Diagnostic Test: Prediction of postoperative acute kidney injury using an artificial intelligenceAdults patients undergoing non-cardiac surgery |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Adults patients undergoing non-cardiac surgery
Key inclusion criteria (1 listed)
- Adults patients undergoing non-cardiac surgery
Key exclusion criteria (10 listed)
- Age under 18 years
- Surgery duration < 1 hour
- Transplantation surgery
- Nephrectomy
- Cardiac surgery
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 of postoperative acute kidney injury using an artificial intelligenceThe performance of an artificial intelligence model to predict postoperative acute kidney injury will be tested prospectively. | Diagnostic test | AI_AKI |
Primary outcome
the incidence of postoperative acute kidney injury
Time frame: during the postoperative seven days
postoperative acute kidney injury (diagnosed by KDIGO criteria using peak serum creatinine level) included all acute kidney injury events regardless of acute kidney injury severity
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Jan 2021.
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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. This study is not recruiting at the moment.
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 Non-cardiac Surgery, run by Seoul National University Hospital 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 1 inclusion and 10 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: status not confirmed, as of the sponsor's last update on 12 Jan 2021. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Hyung-Chul Lee, MD.PhD (+821024566336, vital@snu.ac.kr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
the incidence of postoperative acute kidney injury (time frame: during the postoperative seven days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 12 Jan 2021.