Liver Transplant; ComplicationsNCT06535217
Explainable Machine Learning for the Assessment of Donor Grafts in Liver Transplantation
An observational study of Liver Transplant; Complications, run by Third Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
Trial summary
Clinically, organ evaluation generally performed by the senior surgeons based on their experience and the visual and tactual inspection of the graft during procurement. However, it is proved that transplant surgeons intuition in the evaluation of donor risk and the estimation of steatosis is inconsistent and usually… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Liver Transplant; Complications
- What is being tested?
- Liver transplantation
- Type of treatment
- Surgery or procedure
- How many people
- 5,636 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2017to 30 Jun 2024
- 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
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients who underwent deceased donor liver transplantation
Who may be able to join
- Age≥18 years-old
- Underwent deceased donor liver transplantation
Who cannot join
- Underwent living-donor LT;
- Missing rates of data were more than 80%
Trial locations and contacts
1 site in 1 country.
China1 site
The Third Affiliated Hospital of Sun Yat-Sen University
Guangzhou, Guangdong
About this study
Clinically, organ evaluation generally performed by the senior surgeons based on their experience and the visual and tactual inspection of the graft during procurement. However, it is proved that transplant surgeons intuition in the evaluation of donor risk and the estimation of steatosis is inconsistent and usually inaccurate. Besides, graft assessment is a dynamic process refer to amount of complex factors, which is considered to be an incredibly complicated relationship that is nonlinear in nature. Unfortunately, the classical statistic techniques in vogue such as multiple regression require the statistical assumption of independent and linear relationships between explanatory and outcome variables, and fail to analyse a large number of variables. We attempted to develop liver graft assessment models by predicting postoperative DGF using several ML techniques. Secondly, the best prediction model was selected by comparing the performance of different AI algorithms and logistic regression. Finally, we sought to explain the decision made by AI algorithms using a visualization algorithm based on the best prediction model, helping clinicians evaluate specific organ and whether to receive that may develop DGF postoperatively.
- Conditions
- Liver Transplant; Complications
- Being tested
- Liver transplantation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Liver transplantationProcedure or surgery
Liver transplantation
| Study group | Role | What they receive |
|---|---|---|
| DGF | patients occured delayed graft function after liver transplantation Receives: Procedure: Liver transplantation | |
| non-DGF | patients NOT occured delayed graft function after liver transplantation Receives: Procedure: Liver transplantation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Delayed Graft Function (DGF)
defined as early graft dysfunction without the need for a second liver transplant or death
Measured: Within 7 days after liver transplantation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Aug 2024
- Study start1 Jan 2017
- Primary completion30 Jun 2023
- Study completion30 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Liver Transplant; ComplicationsStudies of the same condition, open and under way.
- 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
- Retrospective
- Enrolment
- 5,636 participants (actual)
Sponsor and investigators
- Lead sponsor
- Third Affiliated Hospital, Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Collaborators
- the China Liver Transplant Registry
- Responsible party
- Principal investigator, Zhixing Liang, Third Affiliated Hospital, Sun Yat-Sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06535217
- Sponsor's protocol ID
- ZSSY-2403
- Status last verified
- Jul 2024
- First submitted
- 28 Jul 2024
- Last updated
- 2 Aug 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Explainable Machine Learning for the Assessment of Donor Grafts in Liver Transplantation
- ClinicalTrials.gov ID
- NCT06535217
- Acronym / sponsor ID
- ZSSY-2403
- Conditions
- Liver Transplant; Complications
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 5,636 participants (actual)
- Lead sponsor
- Third Affiliated Hospital, Sun Yat-Sen UniversityUniversity, hospital or other
- Collaborators
- the China Liver Transplant Registry
- Study start
- 1 Jan 2017 (actual)
- Primary completion
- 30 Jun 2023 (actual)
- Study completion
- 30 Jun 2024 (actual)
- First posted
- 2 Aug 2024 (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.
Clinically, organ evaluation generally performed by the senior surgeons based on their experience and the visual and tactual inspection of the graft during procurement. However, it is proved that transplant surgeons intuition in the evaluation of donor risk and the estimation of steatosis is inconsistent and usually inaccurate. Besides, graft assessment is a dynamic process refer to amount of complex factors, which is considered to be an incredibly complicated relationship that is nonlinear in nature. Unfortunately, the classical statistic techniques in vogue such as multiple regression require the statistical assumption of independent and linear relationships between explanatory and outcome variables, and fail to analyse a large number of variables. We attempted to develop liver graft assessment models by predicting postoperative DGF using several ML techniques. Secondly, the best prediction model was selected by comparing the performance of different AI algorithms and logistic regression. Finally, we sought to explain the decision made by AI algorithms using a visualization algorithm based on the best prediction model, helping clinicians evaluate specific organ and whether to receive that may develop DGF postoperatively.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| DGF | – | Procedure: Liver transplantationpatients occured delayed graft function after liver transplantation |
| non-DGF | – | Procedure: Liver transplantationpatients NOT occured delayed graft function after liver transplantation |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients who underwent deceased donor liver transplantation
Key inclusion criteria (2 listed)
- Age≥18 years-old
- Underwent deceased donor liver transplantation
Key exclusion criteria (2 listed)
- Underwent living-donor LT;
- Missing rates of data were more than 80%
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 |
|---|---|---|
| Liver transplantationLiver transplantation | Procedure or surgery | DGF, non-DGF |
Primary outcome
Delayed Graft Function (DGF)
Time frame: Within 7 days after liver transplantation
defined as early graft dysfunction without the need for a second liver transplant or death
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Aug 2024.
- 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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
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 Liver Transplant; Complications, run by Third Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
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 2 inclusion and 2 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: finished, as of the sponsor's last update on 2 Aug 2024. 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 China. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Delayed Graft Function (DGF) (time frame: Within 7 days after liver transplantation). 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 2 Aug 2024.