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Machine learning–based prediction of acute kidney injury and renal function recovery after nephrectomy in patients with renal cell carcinoma

Machine learning–based prediction of acute kidney injury and renal function recovery after nephrectomy in patients with renal cell carcinoma

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104718
Enrollment
Unknown
Registered
2025-06-23
Start date
2025-06-23
Completion date
Unknown
Last updated
2025-06-30

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

Conditions

Acute kidney injury

Interventions

Group of patients with renal cell carcinoma:None

Sponsors

Affiliated Hospital of Xuzhou Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age>=18 years; 2. Diagnosed with kidney cancer by imaging report or pathological results; 3. Patients hospitalized to receive unilateral PN or RN.

Exclusion criteria

Exclusion criteria: 1. Severe preoperative renal insufficiency (defined as eGFR0; M stage >0); 3. History of previous nephrectomy; 4. Kidney transplant recipients; 5. Patients with bilateral kidney or solitary kidney tumors; 6. There are postoperative complications requiring reoperation; 7. Combined with other malignant tumors or organ failure; 8. Incomplete laboratory information.

Design outcomes

Primary

MeasureTime frame
Whether acute kidney injury occurred after nephrectomy in patients with renal cell carcinoma;—

Secondary

MeasureTime frame
Recovery of renal function after nephrectomy in patients with renal cell carcinoma who have undergone acute kidney injury;—

Countries

China

Contacts

Public ContactFang Gao

Department of Anesthesiology, The Affiliated Hospital of Xuzhou Medical University

gaofangxz@126.com+86 180 5226 8331

Outcome results

None listed

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