Postoperative Acute Kidney InjuryNCT06146829
Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
An observational study of Postoperative Acute Kidney Injury, run by Rao Sun at 1 site in China.
Trial summary
Acute kidney injury (AKI) is a common surgical complication characterized by a rapid decline in renal function. Patients with AKI are at an increased risk of developing chronic kidney disease and end-stage renal disease, which has been associated with an increased risk of morbidity, mortality and financial burdens. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Postoperative Acute Kidney Injury
- How many people
- 88,367 participants
- Where
- 1 siteChina
- Study dates
- 27 Nov 2023to 15 Dec 2023
- 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 noncardiac surgical procedures at Tongji hospital between July 2018 and October 2022 were included.
Who may be able to join
- Adult patients (age ≥ 18 years) who had a serum creatinine measurement within 10 days before surgery and at least one measurement within 7 days after surgery.
- Eligible surgeries encompassed general, thoracic, orthopedic, obstetric, gynecology, and neurosurgery procedures lasting longer than 1 hour
Who cannot join
- Patients with concurrent cardiac, vascular, urological, or transplant surgeries.
- Patients with an American Society of Anesthesiologists (ASA) physical status V.
- Patients with end-stage renal disease (i.e., a glomerular filtration rate [eGFR] of 15 mL/min/1.73 m² or receiving hemodialysis).
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Development of Interpretable Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
Acute kidney injury (AKI) is a common surgical complication characterized by a rapid decline in renal function. Patients with AKI are at an increased risk of developing chronic kidney disease and end-stage renal disease, which has been associated with an increased risk of morbidity, mortality and financial burdens. Identifying high-risk patients for postoperative AKI early can facilitate the development of preventive and therapeutic management strategies, and prediction models can be helpful in this regard.
The goal of this retrospective study is to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms, and to simplify the models by including only preoperative variables or only important predictors.
- Conditions
- Postoperative Acute Kidney Injury
- Being tested
- no intervention
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
no interventionOther
no intervention
What is being measured
The primary outcome is the main question the study is designed to answer.
Postoperative acute kidney injury
In accordance with the KDIGO creatinine criteria: a serum creatinine increases of 26.5 mmol/L within 48 hours or 1.5 times baseline within 7 days after surgery.
Measured: Within 7 days after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Nov 2023
- Study start27 Nov 2023
- Primary completion15 Dec 2023
- Study completion15 Dec 2023
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 Postoperative Acute Kidney InjuryStudies 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
- 88,367 participants (actual)
Sponsor and investigators
- Lead sponsor
- Rao Sun
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Rao Sun, Tongji Hospital
- Investigators
- Rao Sun, Principal investigator, Tongji Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06146829
- Sponsor's protocol ID
- TJH-20230608C
- Status last verified
- Apr 2024
- First submitted
- 19 Nov 2023
- Last updated
- 10 Apr 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Sun R, Li S, Wei Y, Hu L, Xu Q, Zhan G, Yan X, He Y, Wang Y, Li X, Luo A, Zhou Z. Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study. Int J Surg. 2024 May 1;110(5):2950-2962. doi: 10.1097/JS9.0000000000001237.
PubMed 38445452
Study at a glance
From the registry record, last updated by the sponsor on 10 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Interpretable Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
- ClinicalTrials.gov ID
- NCT06146829
- Acronym / sponsor ID
- TJH-20230608C
- Conditions
- Postoperative Acute Kidney Injury
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 88,367 participants (actual)
- Lead sponsor
- Rao SunUniversity, hospital or other
- Study start
- 27 Nov 2023 (actual)
- Primary completion
- 15 Dec 2023 (actual)
- Study completion
- 15 Dec 2023 (actual)
- First posted
- 27 Nov 2023 (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.
Acute kidney injury (AKI) is a common surgical complication characterized by a rapid decline in renal function. Patients with AKI are at an increased risk of developing chronic kidney disease and end-stage renal disease, which has been associated with an increased risk of morbidity, mortality and financial burdens. Identifying high-risk patients for postoperative AKI early can facilitate the development of preventive and therapeutic management strategies, and prediction models can be helpful in this regard.
The goal of this retrospective study is to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms, and to simplify the models by including only preoperative variables or only important predictors.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
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 noncardiac surgical procedures at Tongji hospital between July 2018 and October 2022 were included.
Key inclusion criteria (2 listed)
- Adult patients (age ≥ 18 years) who had a serum creatinine measurement within 10 days before surgery and at least one measurement within 7 days after surgery.
- Eligible surgeries encompassed general, thoracic, orthopedic, obstetric, gynecology, and neurosurgery procedures lasting longer than 1 hour
Key exclusion criteria (3 listed)
- Patients with concurrent cardiac, vascular, urological, or transplant surgeries.
- Patients with an American Society of Anesthesiologists (ASA) physical status V.
- Patients with end-stage renal disease (i.e., a glomerular filtration rate [eGFR] of 15 mL/min/1.73 m² or receiving hemodialysis).
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 |
|---|---|---|
| no interventionno intervention | Other | – |
Primary outcome
Postoperative acute kidney injury
Time frame: Within 7 days after surgery
In accordance with the KDIGO creatinine criteria: a serum creatinine increases of 26.5 mmol/L within 48 hours or 1.5 times baseline within 7 days after surgery.
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 10 Apr 2024.
- Derived from this study: PubMed 38445452Sun R, Li S, Wei Y, Hu L, Xu Q, Zhan G, Yan X, He Y, Wang Y, Li X, Luo A, Zhou Z. Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study. Int J Surg. 2024 May 1;110(5):2950-2962. doi: 10.1097/JS9.0000000000001237.
- 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.
Rao Sun principal investigator
Tongji Hospital
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 Postoperative Acute Kidney Injury, run by Rao Sun 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 3 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 10 Apr 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?
Postoperative acute kidney injury (time frame: Within 7 days after surgery). 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 NCT06146829, 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 10 Apr 2024.