SynthesisCritical care (London, England)2023
Performance of urinary C-C motif chemokine ligand 14 for the prediction of persistent acute kidney injury: a systematic review and meta-analysis.
Synthesis in Critical care (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Urine neutrophil gelatinase-associated lipocalin predicts kidney support therapy duration and liberation in critically ill children.Pediatric research · 2026Article
- Renal-tubular-mitochondrial sequentially targeted nanoagent breaks the vicious cycle of oxidative stress and mtDNA-driven inflammation in acute kidney injury therapy.Journal of nanobiotechnology · 2026Article
- What new renal biomarkers tell us about renal physiology: Collection: physiology applied to ICU.Annals of intensive care · 2026Review
- Acute Kidney Injury Biomarkers in Perioperative Care: A Scoping Review of Clinical Implementation.Diagnostics (Basel, Switzerland) · 2025Review
- Employing urinary biomarkers in predicting renal recovery three months after in-hospital acute kidney injury.Renal failure · 2025Article
- The use of urinary biomarkers as prognostic tools: predicting kidney outcomes in pediatric acute kidney injury.Pediatric nephrology (Berlin, Germany) · 2025Article
- Preventing acute kidney injury and its longer-term impact in the critically ill.Intensive care medicine · 2025Review
- C-C motif chemokine ligand 14 characterization for prediction of persistent severe AKI in post-cardiac surgery children.Pediatric nephrology (Berlin, Germany) · 2025Article
- Ten tips on how to reduce iatrogenic acute kidney injury.Clinical kidney journal · 2025Review
- Performance of urinary C-C motif chemokine ligand 14 and the renal resistive index in predicting persistent AKI.Renal failure · 2024Observational
- Biomarkers in acute kidney injury.Annals of intensive care · 2024Review
- Biomarkers in pursuit of precision medicine for acute kidney injury: hard to get rid of customs.Kidney research and clinical practice · 2024Article
- Development and external validation of a machine learning model for the prediction of persistent acute kidney injury stage 3 in multi-centric, multi-national intensive care cohorts.Critical care (London, England) · 2024Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundUrinary C-C motif chemokine ligand 14 (CCL14) has been described as an effective marker for delayed recovery of acute kidney injury (AKI), yet its efficacy has been found to vary between different trials. The goal of this research was to assess the predictive performance of urinary CCL14 as a marker for persistent AKI.
methodsIn accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched the PubMed, Embase, and Cochrane databases up to April 2023 for studies of adults (> 18 years) that reported the diagnostic performance of urinary CCL14. The sensitivity, specificity, number of events, true positive, and false positive results were extracted and evaluated. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence.
resultsWe included six studies with 952 patients in this meta-analysis. The occurrence of persistent AKI among these patients was 39.6% (377/952). The pooled sensitivity and specificity results of urinary CCL14 in predicting persistent AKI were 0.81 (95% CI 0.72-0.87) and 0.71 (95% CI 0.53-0.84), respectively. The pooled positive likelihood ratio (LR) was 2.75 (95% CI 1.63-4.66), and the negative LR was 0.27 (95% CI 0.18-0.41). The HSROC with pooled diagnostic accuracy was 0.84.
conclusionOur results suggest that urinary CCL14 can be used as an effective marker for predicting persistent AKI.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.