Machine Learning 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.

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Key information

Conditions

Machine Learning Acute Kidney Injury Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Kidney Diseases Male Urogenital Diseases Renal Insufficiency Urogenital Diseases Urologic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Chinese PLA General hospital

Beijing, Beijing Municipality, 100853, China

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

age over 18 years who underwent cardiac surgery

Exclusion criteria

data miss greater than 10%

Treatment and study plan

Primary outcomes

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.

Sponsors and collaborators

Lead sponsor

Yunlong Fan

Other

Registry information

Official study title

Using Machine Learning to Predict Acute Kidney Injury in Patients Following Cardiac Surgery

Important dates

Study start: 2020
Primary completion: 2021
Study completion: 2021
First posted: Jul 19, 2021
Registry last updated: Jul 22, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed