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Machine Learning Based Risk Prediction Model for Acute Kidney Injury after Surgical Procedures

Machine Learning Based Risk Prediction Model for Acute Kidney Injury after Surgical Procedures

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400089726
Enrollment
Unknown
Registered
2024-09-13
Start date
2023-06-01
Completion date
Unknown
Last updated
2024-09-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

acute kidney injury

Interventions

Postoperative stage 2 or 3 AKI group:None
Non-postoperative stage 2 or 3 AKI group:None

Sponsors

Nanjing First Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: (i) Patients undergoing heart transplantation cardiopulmonary bypass surgery. (ii) 18-75 years of age. (iii) Informed consent and voluntary participation in this study.

Exclusion criteria

Exclusion criteria: (i) the age less than 18 years at the time of transplantation; (ii) patients with severe preoperative renal dysfunction (preoperative renal replacement therapy (RRT) dependence, creatinine concentration > 300 µmol/L or urine output less than 400 mL/d); (iii) retransplant patients or patients with combined heart and other organ transplantation; and (iv) death within 48 hours after surgery.

Design outcomes

Primary

MeasureTime frame
acute kidney injury;—

Countries

China

Contacts

Public ContactYanna Si

Nanjing First Hospital, Nanjing Medical University

siyanna@163.com+86 153 6615 5715

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026