NCT04966598

Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery

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

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 2,108 (actual)
• Sponsor: Yunlong Fan · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: —

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.

Conditions

• Machine Learning
• Acute Kidney Injury

Timeline

• Start date: 2020-09-01
• Primary completion: 2021-01-01
• Completion: 2021-01-01
• First posted: 2021-07-19
• Last updated: 2021-07-22

Locations

1 site across 1 country: China