Machine LearningNCT04966598
Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery
An observational study of Machine Learning and Acute Kidney Injury, run by Yunlong Fan at 1 site in China.
Trial summary
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication which may result in adverse impact on short- and long-term mortality. The investigatorshere developed several prediction models based on machine learning technique to allow early identification of patients who at the high risk of… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Machine Learning, Acute Kidney Injury
- How many people
- 2,108 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2020to 1 Jan 2021
- 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: age over 18 years who underwent cardiac surgery
Who may be able to join
- age over 18 years who underwent cardiac surgery
Who cannot join
- data miss greater than 10%
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using Machine Learning to Predict Acute Kidney Injury in Patients Following Cardiac Surgery
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication which may result in adverse impact on short- and long-term mortality. The investigatorshere developed several prediction models based on machine learning technique to allow early identification of patients who at the high risk of unfavorable kidney outcomes.
The retrospective study comprised 2108 consecutive patients who underwent cardiac surgery from January 2017 to December 2020.
- Conditions
- Machine Learning, Acute Kidney Injury
- Medical subject headings
- Acute Kidney Injury
What is being measured
The primary outcome is the main question the study is designed to answer.
acute kidney injury
postoperative AKI was defined according to KDIGO criteria during the first 7 days after operation. Postoperative AKI was defined as either at an increase of at least 50% within 7 days or 0.3 mg/dL elevation within 48 h compared with the reference serum creatinine level.
Measured: 7 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Jul 2021
- Study start1 Sep 2020
- Primary completion1 Jan 2021
- Study completion1 Jan 2021
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 Machine LearningStudies 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 2,108 participants (actual)
Sponsor and investigators
- Lead sponsor
- Yunlong Fan
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Yunlong Fan, Chinese PLA General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04966598
- Sponsor's protocol ID
- chinaPLAGH-08983218
- Status last verified
- Jul 2021
- First submitted
- 8 Jul 2021
- Last updated
- 22 Jul 2021
- Results posted
- No
- Individual data sharing
- Undecided
Publications
Shao J, Liu F, Ji S, Song C, Ma Y, Shen M, Sun Y, Zhu S, Guo Y, Liu B, Wu Y, Qin H, Lai S, Fan Y. Development, External Validation, and Visualization of Machine Learning Models for Predicting Occurrence of Acute Kidney Injury after Cardiac Surgery. Rev Cardiovasc Med. 2023 Aug 9;24(8):229. doi: 10.31083/j.rcm2408229. eCollection 2023 Aug.
PubMed 39076716
Study at a glance
From the registry record, last updated by the sponsor on 22 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Machine Learning to Predict Acute Kidney Injury in Patients Following Cardiac Surgery
- ClinicalTrials.gov ID
- NCT04966598
- Acronym / sponsor ID
- chinaPLAGH-08983218
- Conditions
- Machine Learning, Acute Kidney Injury
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 2,108 participants (actual)
- Lead sponsor
- Yunlong FanUniversity, hospital or other
- Study start
- 1 Sep 2020 (actual)
- Primary completion
- 1 Jan 2021 (actual)
- Study completion
- 1 Jan 2021 (actual)
- First posted
- 19 Jul 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.
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication which may result in adverse impact on short- and long-term mortality. The investigatorshere developed several prediction models based on machine learning technique to allow early identification of patients who at the high risk of unfavorable kidney outcomes.
The retrospective study comprised 2108 consecutive patients who underwent cardiac surgery from January 2017 to December 2020.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- age over 18 years who underwent cardiac surgery
Key inclusion criteria (1 listed)
- age over 18 years who underwent cardiac surgery
Key exclusion criteria (1 listed)
- data miss greater than 10%
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
acute kidney injury
Time frame: 7 days
postoperative AKI was defined according to KDIGO criteria during the first 7 days after operation. Postoperative AKI was defined as either at an increase of at least 50% within 7 days or 0.3 mg/dL elevation within 48 h compared with the reference serum creatinine level.
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 22 Jul 2021.
- Derived from this study: PubMed 39076716Shao J, Liu F, Ji S, Song C, Ma Y, Shen M, Sun Y, Zhu S, Guo Y, Liu B, Wu Y, Qin H, Lai S, Fan Y. Development, External Validation, and Visualization of Machine Learning Models for Predicting Occurrence of Acute Kidney Injury after Cardiac Surgery. Rev Cardiovasc Med. 2023 Aug 9;24(8):229. doi: 10.31083/j.rcm2408229. eCollection 2023 Aug.
- Individual participant dataSharing planned: Undecided
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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 Machine Learning and Acute Kidney Injury, run by Yunlong Fan 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 1 inclusion and 1 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 22 Jul 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 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?
acute kidney injury (time frame: 7 days). 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 NCT04966598, 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 22 Jul 2021.