NCT04977687

Machine Learning Predict Renal Replacement Therapy After Cardiac Surgery

Using Machine Learning to Predict Acute Kidney Injury Requiring Renal Replacement Therapy After Cardiac Surgery

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 2,108 (actual)
• Sponsor: Chinese PLA General Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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 researcher here 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
• Renal Replacement Therapy
• Prediction Models

Timeline

• Start date: 2020-09-01
• Primary completion: 2021-01-01
• Completion: 2021-01-01
• First posted: 2021-07-27
• Last updated: 2021-08-02

Locations

1 site across 1 country: China