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Evaluating Biomarkers for Contrast-Induced Nephropathy Following Coronary Interventions: An Umbrella Review on Meta-Analyses Publisher Pubmed



Mahapatro A1 ; Nobakht S2 ; Mukesh S3 ; Daryagasht AA2 ; Korsapati AR4 ; Jain SM5 ; Soltani Moghadam S2 ; Moosavi R6 ; Javid M2 ; Hassanipour S9 ; Prabhu SV7 ; Keivanlou MH10 ; Aminisalehi E2 ; Nayak SS8
Authors
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Authors Affiliations
  1. 1. Hi-Tech Medical College and Hospital, Odisha, Rourkela, India
  2. 2. Guilan University of Medical Sciences, Rasht, Iran
  3. 3. Liaquat University of Medical and Health Sciences, Jamshoro, Pakistan
  4. 4. University of Buckingham Medical School, Buckingham, United Kingdom
  5. 5. MVJ Medical College and Research Hospital, Bengaluru, India
  6. 6. Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Kasturba Medical College, Mangalore, India
  8. 8. Department of Internal Medicine, Yale New Haven Health Bridgeport Hospital, Bridgeport, CT, United States
  9. 9. Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran
  10. 10. Student Research Committee, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran

Source: European Journal of Medical Research Published:2024


Abstract

Background: Contrast-induced nephropathy (CIN) is a form of acute kidney injury (AKI) occurring in patients undergoing cardiac catheterization, such as coronary angiography (CAG) or percutaneous coronary intervention (PCI). Although the conventional criterion for CIN detection involves a rise in creatinine levels within 72 h after contrast media injection, several limitations exist in this definition. Up to now, various meta-analyses have been undertaken to assess the accuracy of different biomarkers of CIN prediction. However, the existing body of research lacks a cohesive overview. To address this gap, a comprehensive umbrella review was necessary to consolidate and summarize the outcomes of prior meta-analyses. This umbrella study aimed to offer a current, evidence-based understanding of the prognostic value of biomarkers in predicting CIN. Methods: A systematic search of international databases, including PubMed, Scopus, and Web of Science, from inception to December 12, 2023, was conducted to identify meta-analyses assessing biomarkers for CIN prediction. Our own meta-analysis was performed by extracting data from the included studies. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were assessed using Meta-Disc and CMA softwares. Results: Twelve studies were ultimately included in the umbrella review. The results revealed that neutrophil gelatinase-associated lipocalin (NGAL) exhibited the highest area under the curve (AUC), followed by cystatin-C, urinary kidney injury molecule-1 (uKIM-1), and brain natriuretic peptide (BNP) with AUCs of 0.91, 0.89, 0.85, and 0.80, respectively. NGAL also demonstrated the highest positive likelihood ratio [effect size (ES): 6.02, 95% CI 3.86–9.40], followed by cystatin-C, uKIM-1, and BNP [ES: 4.35 (95% CI 2.85–6.65), 3.58 (95% CI 2.75–4.66), and 2.85 (95% CI 2.13–3.82), respectively]. uKIM-1 and cystatin-C had the lowest negative likelihood ratio, followed by NGAL and BNP [ES: 0.25 (95% CI 0.17–0.37), ES: 0.25 (95% CI 0.13–0.50), ES: 0.26 (95% CI 0.17–0.41), and ES: 0.39 (0.28–0.53) respectively]. NGAL emerged as the biomarker with the highest diagnostic odds ratio for CIN, followed by cystatin-C, uKIM-1, BNP, gamma-glutamyl transferase, hypoalbuminemia, contrast media volume to creatinine clearance ratio, preprocedural hyperglycemia, red cell distribution width (RDW), hyperuricemia, neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), high-sensitivity CRP, and low hematocrit (P < 0.05). Conclusion: NGAL demonstrated superior diagnostic performance, exhibiting the highest AUC, positive likelihood ratio, and diagnostic odds ratio among biomarkers for CIN, followed by cystatin-C, and uKIM-1. These findings underscore the potential clinical utility of NGAL, cystatin-C and uKIM-1 in predicting and assessing CIN. Graphical Abstract: (Figure presented.) © The Author(s) 2024.
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