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Biomarkers for prediction of acute kidney injury in pediatric patients: a systematic review and meta-analysis of diagnostic test accuracy studies

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Abstract

Background

Severity of acute kidney injury (AKI) confers higher odds of mortality. Timely recognition and early initiation of preventive measures may help mitigate the injury further. Novel biomarkers may aid in the early detection of AKI. The utility of these biomarkers across various clinical settings in children has not been evaluated systematically.

Objective

To synthesize the currently available evidence on different novel biomarkers for the early diagnosis of AKI in pediatric patients.

Data sources

We searched four electronic databases (PubMed, Web of Science, Embase, and Cochrane Library) for studies published between 2004 and May 2022.

Study eligibility criteria

Cohort and cross-sectional studies evaluating the diagnostic performance of biomarkers in predicting AKI in children were included.

Participants and interventions

Participants in the study included children (aged less than 18 years) at risk of AKI.

Study appraisal and synthesis methods

We used the QUADAS-2 tool for the quality assessment of the included studies. The area under the receiver operating characteristics (AUROC) was meta-analyzed using the random-effect inverse-variance method. Pooled sensitivity and specificity were generated using the hierarchical summary receiver operating characteristic (HSROC) model.

Results

We included 92 studies evaluating 13,097 participants. Urinary NGAL and serum cystatin C were the two most studied biomarkers, with summary AUROC of 0.82 (0.77–0.86) and 0.80 (0.76–0.85), respectively. Among others, urine TIMP-2*IGFBP7, L-FABP, and IL-18 showed fair to good predicting ability for AKI. We observed good diagnostic performance for predicting severe AKI by urine L-FABP, NGAL, and serum cystatin C.

Limitations

Limitations were significant heterogeneity and lack of well-defined cutoff value for various biomarkers.

Conclusions and implications of key findings

Urine NGAL, L-FABP, TIMP-2*IGFBP7, and cystatin C showed satisfactory diagnostic accuracy in the early prediction of AKI. To further improve the performance of biomarkers, they need to be integrated with other risk stratification models.

Systematic review registration

PROSPERO (CRD42021222698).

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Data Availability

Data used in this manuscript is already available in public domain.

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Authors and Affiliations

  1. Division of Nephrology, Department of Pediatrics, ICMR Centre for Advanced Research in Nephrology, All India Institute of Medical Sciences, New Delhi, India

    Jitendra Meena & Arvind Bagga

  2. Department of Pediatrics, Government Medical College, Thiruvananthapuram, Kerala, India

    Christy Catherine Thomas

  3. Advanced Pediatric Center, Postgraduate Institute of Medical Education and Research, Chandigarh, India

    Jogender Kumar

  4. Division of Nephrology, Department of Pediatrics, Christian Medical College, Vellore, Tamil Nadu, India

    Georgie Mathew

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Contributions

JM had full access to all of the data in the study and will be responsible for the integrity and accuracy of the data analysis.

Study concept and design: JM, JK, CCT.

Acquisition, analysis, or interpretation of data: CCT, JM, JK, AB, GM.

Drafting of the manuscript: JM, JK, GM, CCT.

Critical manuscript revision for important intellectual content: JM, AB, JK.

Statistical analysis: JM, JK, GM.

Administrative, technical, or material support: CCT, GM, JM.

Study supervision: AB, JK, JM.

Corresponding author

Correspondence to Arvind Bagga.

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Meena, J., Thomas, C.C., Kumar, J. et al. Biomarkers for prediction of acute kidney injury in pediatric patients: a systematic review and meta-analysis of diagnostic test accuracy studies. Pediatr Nephrol 38, 3241–3251 (2023). https://doi.org/10.1007/s00467-023-05891-4

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