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Research on the Construction and Validation of an Early Prediction Model for Acute Kidney Injury after Major Tumor Surgery Based on Machine Learning Method

Research on the Construction and Validation of an Early Prediction Model for Acute Kidney Injury after Major Tumor Surgery Based on Machine Learning Method

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500114660
Enrollment
Unknown
Registered
2025-12-16
Start date
2026-01-01
Completion date
Unknown
Last updated
2026-01-05

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

Conditions

Acute kidney injury

Interventions

Gold Standard:Blood creatinine level
Index test:Creatinine

Sponsors

Zhejiang Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.All patients who were admitted to the ICU for monitoring and treatment after abdominal surgery in our hospital from 2023 to 2025;

Exclusion criteria

Exclusion criteria: 1.Patients under the age of 18; 2.Patients who have undergone multiple surgeries within 7 days;3.Patients with stage 5 chronic kidney disease who have undergone kidney transplantation or are on dialysis;4.Patients who did not have creatinine measurement before the operation, those who did not have creatinine measurement within 7 days after the operation, and those with data loss greater than half?

Design outcomes

Primary

MeasureTime frame
Blood creatinine level;—

Secondary

MeasureTime frame
Urine output;—

Countries

China

Contacts

Public ContactLihong Shan

Zhejiang Cancer Hospital

slhjiayou2010@163.com+86 571 88122110

Outcome results

None listed

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