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NCT07482683
Predicting Post-Cardiac Surgery Acute Kidney Disease: A Machine Learning Approach
trial in Acute Kidney Disease in 820 participants. Not yet recruiting.
30 June 2027
Quick facts
| Lead sponsor | China National Center for Cardiovascular Diseases |
|---|---|
| Status | Not yet recruiting |
| Study type | OBSERVATIONAL |
| Enrollment | 820 |
| Start date | 1 March 2026 |
| Primary completion | 30 June 2027 |
| Estimated completion | 30 June 2027 |
| Sites | 1 location across China |
Conditions studied
- Acute Kidney Disease — all drugs for Acute Kidney Disease →
Sponsor
China National Center for Cardiovascular Diseases — full company profile →
Who can join
18 and older, any sex, with Acute Kidney Disease. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Renal injury after cardiac surgery is one of the common complications with high incidence rate, high risk of death and progression to chronic kidney disease (CKD). Previous evaluations of perioperative renal function mainly focused on acute kidney injury (AKI) related to cardiac surgery within seven days after surgery. The newly proposed concept of acute kidney disease (AKD) in recent years refers to acute or subacute kidney injury lasting seven to ninety days. Research has found that AKD can occur after AKI or in patients without AKI, and the two are both related and independent of each other, possibly indicating different subtypes of kidney injury. AKD is not uncommon and is a more significant predictor of mortality and end-stage kidney disease (ESKD). Therefore, AKD may be an important window for identifying and managing high-risk patients after cardiac surgery. Due to limited research on AKD after cardiac surgery, the risk factors for AKD are currently unclear, and there are no clinically practical and effective risk stratification tools available. This study aims to establish a multimodal perioperative data platform through a retrospective cohort, and use machine learning methods to construct a risk prediction model for AKD after cardiac surgery. The accuracy and stability of the model will be validated in a prospective study cohort, and an online risk prediction and clinical decision-making tool will be developed to help clinicians quickly conduct personalized risk assessments and optimize diagnosis and treatment strategies, thereby improving patient prognosis and reducing medical costs.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
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Related trials
Other recruiting trials for Acute Kidney Disease
Currently open trials in the same condition.
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- NCT05325099 — Demethylating Agent Azacitidine on Prevention of Acute Kidney Injury-chronic Kidney Disease Continuum · Phase 1, PHASE2 · recruiting
Other China National Center for Cardiovascular Diseases trials
Trials by the same sponsor.
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT07482683 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by China National Center for Cardiovascular Diseases
- Last refreshed: 19 March 2026
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