Abstract: SA-OR005
Preoperative Biomarkers for Enrichment of Clinical Trials in Cardiac Surgery-Associated AKI: A TRIBE Cohort Secondary Analysis
Session Information
- AKI Advances: Biomarkers, Outcomes, and Clinical Trials
November 08, 2025 | Location: Room 320A, Convention Center
Abstract Time: 05:10 PM - 05:20 PM
Category: Acute Kidney Injury
- 102 AKI: Clinical, Outcomes, and Trials
Authors
- Goeddel, Lee A., Johns Hopkins Medicine, Baltimore, Maryland, United States
- Thiessen Philbrook, Heather, Johns Hopkins Medicine, Baltimore, Maryland, United States
- Xue, Jiashu, Johns Hopkins Medicine, Baltimore, Maryland, United States
- Hu, David, Johns Hopkins Medicine, Baltimore, Maryland, United States
- Coca, Steven G., Mount Sinai Health System, New York, New York, United States
- Parikh, Manav C., University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Moledina, Dennis G., Yale University, New Haven, Connecticut, United States
- Parikh, Chirag R., Johns Hopkins Medicine, Baltimore, Maryland, United States
Background
AKI remains a major complication in cardiac surgery. While promising therapeutics are emerging, clinical trial efficiency is crucial. Urine and plasma biomarkers have been proposed to enrich trial enrollment of higher risk individuals to accelerate the evaluation of therapies and reduce cost. Although postoperative biomarkers predict AKI and its progression, the utility of preoperative biomarkers for trial enrichment remains unclear.
Methods
We conducted a secondary analysis of the TRIBE multicenter cohort in cardiac surgery to evaluate the prognostic performance of preoperative biomarkers for any AKI (>50% increase or >0.3mg/dL increase in serum creatinine) and persistent AKI (> 3days duration). We used Society of Thoracic Surgeons (STS) renal failure risk score as the clinical model. To develop the best biomarker model, we performed backward elimination of urine biomarkers (cystatin C, albumin to creatinine ratio, IL-18, NGAL) and plasma biomarkers (hs Trop, Pro BNP, Tumor Necrosis Factor Receptor 1 [TNF-R1], and TNF-R2). The process was completed for AKI and for persistent AKI. Cross validation assessed predictive performance of the clinical model only, biomarker model only, and clinical + biomarker model.
Results
In 1081 patients, 385 (36%) developed AKI and 152 (14%) had persistent AKI. TNF-R1 with NGAL was the optimal combination for AKI, and TNFR-R1 alone for persistent AKI. Predictive results are presented in table 1. AUC for the clinical model alone was 0.56 for both outcomes. The biomarker model achieved AUC of 0.66 for AKI and 0.74 for persistent AKI, with no improvement with the addition of the clinical model.
Conclusion
In a secondary analysis of the TRIBE-AKI multicenter cohort, preoperative TNF-R1, alone or in combination, outperformed other biomarkers and the STS clinical risk score for predicting both AKI and persistent AKI. Preoperative TNF-R1 assessment shows promise for enriching patient selection in cardiac surgery-associated AKI clinical trials.