Acute Kidney Injury Clinical Trial
Official title:
Using Machine Learning to Predict Acute Kidney Injury in Patients Following Cardiac Surgery
Verified date | July 2021 |
Source | Chinese PLA General Hospital |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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.
Status | Completed |
Enrollment | 2108 |
Est. completion date | January 1, 2021 |
Est. primary completion date | January 1, 2021 |
Accepts healthy volunteers | |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - age over 18 years who underwent cardiac surgery Exclusion Criteria: - data miss greater than 10% |
Country | Name | City | State |
---|---|---|---|
China | Chinese PLA General hospital | Beijing | Beijing |
Lead Sponsor | Collaborator |
---|---|
Yunlong Fan |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 |
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