NCT04966598

Brief 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 unfavorable kidney outcomes. The retrospective study comprised 2108 consecutive patients who underwent cardiac surgery from January 2017 to December 2020.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
2,108

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Sep 2020

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 1, 2020

Completed
4 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

January 1, 2021

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

January 1, 2021

Completed
6 months until next milestone

First Submitted

Initial submission to the registry

July 8, 2021

Completed
11 days until next milestone

First Posted

Study publicly available on registry

July 19, 2021

Completed
Last Updated

July 22, 2021

Status Verified

July 1, 2021

Enrollment Period

4 months

First QC Date

July 8, 2021

Last Update Submit

July 16, 2021

Conditions

Machine LearningAcute Kidney Injury

Outcome Measures

Primary Outcomes (1)

  • 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.

    7 days

Eligibility Criteria

Age18 Years+
Sexall
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

age over 18 years who underwent cardiac surgery

You may qualify if:

  • age over 18 years who underwent cardiac surgery

You may not qualify if:

  • data miss greater than 10%

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Chinese PLA General hospital

Beijing, Beijing Municipality, 100853, China

Location

Related Publications (1)

  • 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.

    PMID: 39076716DERIVED

MeSH Terms

Conditions

Acute Kidney Injury

Condition Hierarchy (Ancestors)

Renal InsufficiencyKidney DiseasesUrologic DiseasesFemale Urogenital DiseasesFemale Urogenital Diseases and Pregnancy ComplicationsUrogenital DiseasesMale Urogenital Diseases

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR INVESTIGATOR
PI Title
Clinical Professor

Study Record Dates

First Submitted

July 8, 2021

First Posted

July 19, 2021

Study Start

September 1, 2020

Primary Completion

January 1, 2021

Study Completion

January 1, 2021

Last Updated

July 22, 2021

Record last verified: 2021-07

Locations

CN(1)