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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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      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\u20139.40], followed by cystatin-C, uKIM-1, and BNP [ES: 4.35 (95% CI 2.85\u20136.65), 3.58 (95% CI 2.75\u20134.66), and 2.85 (95% CI 2.13\u20133.82), respectively]. uKIM-1 and cystatin-C had the lowest negative likelihood ratio, followed by NGAL and BNP [ES: 0.25 (95% CI 0.17\u20130.37), ES: 0.25 (95% CI 0.13\u20130.50), ES: 0.26 (95% CI 0.17\u20130.41), and ES: 0.39 (0.28\u20130.53) 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 (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1186\/s40001-024-01782-y","type":"journal-article","created":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T05:13:44Z","timestamp":1711948424000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Evaluating biomarkers for contrast-induced nephropathy following coronary interventions: an umbrella review on meta-analyses"],"prefix":"10.1186","volume":"29","author":[{"given":"Abinash","family":"Mahapatro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Nobakht","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sindu","family":"Mukesh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amir Ali","family":"Daryagasht","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aishwarya Reddy","family":"Korsapati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shika M","family":"Jain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saman","family":"Soltani Moghadam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rozhin","family":"Moosavi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mona","family":"Javid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soheil","family":"Hassanipour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shrinidhi Vilas","family":"Prabhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad-Hossein","family":"Keivanlou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ehsan","family":"Amini-Salehi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandeep S.","family":"Nayak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,1]]},"reference":[{"key":"1782_CR1","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1111\/j.0954-6820.1957.tb15742.x","volume":"158","author":"SA Killmann","year":"1957","unstructured":"Killmann SA, Gjorup S, Thaysen JH. 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