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Serum and urinary biomarkers to predict acute kidney injury in premature infants: a systematic review and meta-analysis of diagnostic accuracy

BACKGROUND: Premature infants are at high risk for acute kidney injury (AKI) and current diagnostic criteria are flawed. The objective of this study was to determine the diagnostic accuracy of urine and serum biomarkers not currently used in routine clinical practice to predict AKI in premature infa...

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Detalles Bibliográficos
Autores principales: Kuo, Jenny, Akison, Lisa K., Chatfield, Mark D., Trnka, Peter, Moritz, Karen M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584850/
https://www.ncbi.nlm.nih.gov/pubmed/35384606
http://dx.doi.org/10.1007/s40620-022-01307-y
Descripción
Sumario:BACKGROUND: Premature infants are at high risk for acute kidney injury (AKI) and current diagnostic criteria are flawed. The objective of this study was to determine the diagnostic accuracy of urine and serum biomarkers not currently used in routine clinical practice to predict AKI in premature infants. METHOD: A systematic review was performed that followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA). Data were extracted on the diagnostic accuracy of AKI biomarkers using serum creatinine or urine output as the reference standard. Quality and validity were assessed using modified Standards for Reporting Diagnostic Accuracy (STARD) criteria. RESULTS: We identified 1024 articles, with 15 studies (791 infants) eligible for inclusion. Twenty-seven biomarkers were identified including serum cystatin C and urinary neutrophil gelatinase-associated lipocalin (uNGAL), osteopontin, kidney injury molecule-1, epidermal growth factor, and protein S100-P. However, many were only reported by one study each. A meta-analysis could only be conducted on uNGAL (288 infants from 6 studies) using a hierarchical, random-effects logistic-regression model. uNGAL had a summary sensitivity of 77% (95% CI 58–89%), specificity of 76% (95% CI 57–88%) and AUC-SROC of 0.83 (95% CI 0.80–0.86) for the diagnosis of AKI. By utilising uNGAL, the post-test probability of AKI increased to 52% (95% CI 37–66%) with a positive test and decreased to 9% (95% CI 5–16%) with a negative test if the pre-test probability was 25%. CONCLUSION: uNGAL shows promise as a diagnostically accurate biomarker for AKI in premature infants. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40620-022-01307-y.