ReviewInternational journal of molecular sciences2020
Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction.
Review in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 70 citations in OpenAlex.
- Urinary CXCL-10, a prognostic biomarker for kidney graft injuries: a systematic review and meta-analysis.BMC nephrology · 2024Pooled it
- Urinary Biomarkers for Diagnosis and Prediction of Acute Kidney Allograft Rejection: A Systematic Review.International journal of molecular sciences · 2020Pooled it
- Efficacy of Integrated Risk Score Using Omics-Based Biomarkers for the Prediction of Acute Rejection in Kidney Transplantation: A Randomized Prospective Pilot Study.International journal of molecular sciences · 2024Trial
- Growth and development following paediatric kidney transplantation: Mechanisms, influencing factors, and clinical management.World journal of transplantation · 2026Review
- Review
- Diagnostic and Prognostic Value of Donor-Derived Cell-Free DNA in Acute Rejection After Kidney Transplantation: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Successful treatment of pediatric acute phosphate nephropathy: a case report and literature review.Frontiers in medicine · 2026Article
- Noninvasive diagnosis and classification of kidney transplantation rejection byEuropean journal of nuclear medicine and molecular imaging · 2025Article
- The New Horizon: A Viewpoint of Novel Drugs, Biomarkers, Artificial Intelligence, and Self-Management in Improving Kidney Transplant Outcomes.Journal of clinical medicine · 2025Article
- Orai1 Expression and Vascular Function in Kidney Donors Determine Graft Outcomes at Short/Mid-Term.Cells · 2025Article
- Genomic and Biomarker Innovations in Predicting Kidney Transplant Rejection.Journal of clinical medicine · 2025Review
- Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.Medicine · 2025Article
- Non-Invasive Biomarkers for Early Diagnosis of Kidney Allograft Dysfunction: Current and Future Applications in the Era of Precision Medicine.Medicina (Kaunas, Lithuania) · 2025Review
- Prediction of delayed graft function by early salivary microbiota following kidney transplantation.Applied microbiology and biotechnology · 2024Article
- Analysis of IL-17A, IL-17F, and miR-146a-5p Prior to Transplantation and Their Role in Kidney Transplant Recipients.Journal of clinical medicine · 2024Article
- Renal graft function in transplanted patients correlates with CD45RC T cell phenotypic signature.PloS one · 2024Article
- Proteomic analysis investigating kidney transplantation outcomes- a scoping review.BMC nephrology · 2023Article
- Donor-Derived Cell-Free DNA at 1 Month after Kidney Transplantation Relates to HLA Class II Eplet Mismatch Load.Biomedicines · 2023Article
- All That Glitters in cfDNA Analysis Is Not Gold or Its Utility Is Completely Established Due to Graft Damage: A Critical Review in the Field of Transplantation.Diagnostics (Basel, Switzerland) · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
New biomarkers of early and late graft dysfunction are needed in renal transplant to improve management of complications and prolong graft survival. A wide range of potential diagnostic and prognostic biomarkers, measured in different biological fluids (serum, plasma, urine) and in renal tissues, have been proposed for post-transplant delayed graft function (DGF), acute rejection (AR), and chronic allograft dysfunction (CAD). This review investigates old and new potential biomarkers for each of these clinical domains, seeking to underline their limits and strengths. OMICs technology has allowed identifying many candidate biomarkers, providing diagnostic and prognostic information at very early stages of pathological processes, such as AR. Donor-derived cell-free DNA (ddcfDNA) and extracellular vesicles (EVs) are further promising tools. Although most of these biomarkers still need to be validated in multiple independent cohorts and standardized, they are paving the way for substantial advances, such as the possibility of accurately predicting risk of DGF before graft is implanted, of making a "molecular" diagnosis of subclinical rejection even before histological lesions develop, or of dissecting etiology of CAD. Identification of "immunoquiescent" or even tolerant patients to guide minimization of immunosuppressive therapy is another area of active research. The parallel progress in imaging techniques, bioinformatics, and artificial intelligence (AI) is helping to fully exploit the wealth of information provided by biomarkers, leading to improved disease nosology of old entities such as transplant glomerulopathy. Prospective studies are needed to assess whether introduction of these new sets of biomarkers into clinical practice could actually reduce the need for renal biopsy, integrate traditional tools, and ultimately improve graft survival compared to current management.
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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.