Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery
NCT ID: NCT04966598
Last Updated: 2021-07-22
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
2108 participants
OBSERVATIONAL
2020-09-01
2021-01-01
Brief Summary
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The retrospective study comprised 2108 consecutive patients who underwent cardiac surgery from January 2017 to December 2020.
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Detailed Description
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Conditions
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Study Design
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OTHER
RETROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Yunlong Fan
OTHER
Responsible Party
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Yunlong Fan
Clinical Professor
Locations
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Chinese PLA General hospital
Beijing, Beijing Municipality, China
Countries
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References
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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.
Other Identifiers
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chinaPLAGH-08983218
Identifier Type: -
Identifier Source: org_study_id
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