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Incidence and Prognostic of Cardiac Surgery-Associated Acute Kidney Injury: A Spanish Multicenter Study (SCARS-AKI)

External Validation Study of a Laboratory-based Perioperative Prediction Model for Acute Kidney Injury After Cardiac Surgery.

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07370831
Acronym
SCARS-AKI
Enrollment
2500
Registered
2026-01-27
Start date
2023-09-01
Completion date
2024-09-01
Last updated
2026-01-27

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

Conditions

Acute Kidney Disease, Acute Kidney Injury, Cardiac Surgery Associated - Acute Kidney Injury, CKD (Chronic Kidney Disease) Stage 5D

Keywords

CSA AKI, AKI

Brief summary

To predict the renal damage caused by cardiac surgery in patients to try to mitigate it as soon as possible

Detailed description

Acute Kidney Injury (AKI) is a major complication of cardiac surgery and its most severe forms are associated with significant morbidity and mortality . Identification of patients at risk may facilitate early use of management protocoolos recommended by KDIGO (Kidney Disease: Improving Global Outcomes), such as haemodynamic and volume optimisation, monitoring of renal function and discontinuation or reduction of nephrotoxic drugs . The rate associated with cardiac surgery varies according to its different historical definitions, from 0.3% to 29.7% . Cases requiring renal replacement therapy (RRT) occur between 1 .2%-3.0% in the studied cardiac surgery cohorts and their presence is a n independent predictor of mortality. Because AKI still lacks effective treatments in addition to support and elimination of the cause, early and specific diagnosis is an unmet but critical need f o r successful and personalised patient management. Creatinine, urea and urine output have been and are the main ways to diagnose and treat renal failure. Other types of biomarkers that seem to be related to risk of postoperative AKI are currently under study. Although more research is needed, they may eventually become predictive diagnostic tools. Several studies have indicated that the urinary level of NGAL excreted intraoperatively and after surgery is effective in predicting AKI in both adult and paediatric populations. Similar results have been obtained with other urinary biomarkers, such as the cell cycle arrest biomarkers TIMP-2 and IGFBP7) KIM-1, NAG, IL-18 and L-FAP . The major limitation of these biomarkers is that they are not easily accessible in all hospitals and clinical settings. Recently Demirjian developed a predictive model in which they observed that perioperative change in serum creatinine and postoperative blood urea nitrogen, serum sodium, potassium, bicarbonate and albumin from the first metabolic panel after cardiac surgery show good predictive value for moderate to severe AKI within 72 hours and 14 days after the surgical procedure. 3\. Hypothesis The score developed by Demirjian et al has a good predictive ability for moderate to severe AKI after cardiac surgery in the European population. 4\. Objectives 4.1 Main * Confirm the usefulness and externally validate the scale. * Compare this scale with other models of AKI prediction after cardiac surgery: Thakar, Mehta, ISR, Callejas, Leicester, CRATE. 4.2 Secondary * Identify new risk factors for Acute Kidney Injury (AKI) * Understanding the incidence of AKI after cardiac surgery in Europe * Validating a model for predicting discharge dialysis after cardiac surgery * Investigate the performance of these models in specific surgeries: coronary surgery without cardiopulmonary bypass and heart transplantation. * Assess the performance of other scales and compare them. * Determine the prevalence and risk factors for Acute Kidney Disease (AKD) (renal injury beyond 7 days, up to 90 days). * Determine the prevalence and risk factors for new Chronic Kidney Disease (CKD) (follow-up for 120 days or 4 months). * Determine the prevalence and risk factors for CKD progression, defined by a one-stage progression in patients with pre-existing CKD. Follow-up for 120 days (4 months).

Interventions

PROCEDURECARDIAC SURGERY

PATIENTS UNDERGOING CARDIAC SURGERY

Sponsors

Universidad de Oviedo
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* All patients over 18 years of age undergoing cardiac surgery.

Exclusion criteria

* Exitus in the first 48h postoperative period * Patient undergoing renal replacement therapy or preoperative dialysis * Minor" cardiac surgery ( sternal dehiscence, MCP removal or implantation, pericardial window)

Design outcomes

Primary

MeasureTime frameDescription
- Confirm the usefulness and externally validate the Demijirian scale.up to 14th postoperative dayValidate scale
- Compare this scale with other models of AKI prediction after cardiac surgery: Thakar, Mehta, ISR, Callejas, Leicester, CRATE.up to 14th postoperative dayScore validation

Secondary

MeasureTime frameDescription
- Identify new risk factors for Acute Kidney Injury (AKI)from surgery to 4months postoperativeAKI risk factor
- Validating a model for predicting discharge dialysis after cardiac surgeryfrom surgery to 4monts postoperativeDevelope a dialysis after cardiac surgery score
risk factors for new Chronic Kidney Disease (CKD)from surgery to 4months postoperativeDetermine the prevalence and risk factors for new Chronic Kidney Disease (CKD) (follow-up for 120 days or 4 months).
Drugs related with CSA AKIfrom surgery to 4months postoperativeStudy relation of : ISGLP2, GLP2, IDPP4, Sacubitril/valsartan with CS AKI

Countries

Spain

Contacts

PRINCIPAL_INVESTIGATORLuis Baeza Alvarez, MD

Universidad de Oviedo

STUDY_DIRECTORMarc Vives Santacana, PhD

Clinica Universidad de Navarra

STUDY_DIRECTORPablo Avanzas Fernández, PhD

Universidad de Oviedo

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026