ArticleApplied microbiology and biotechnology2024
Prediction of delayed graft function by early salivary microbiota following kidney transplantation.
Article in Applied microbiology and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Kidney Transplantation and the Gut-Kidney Axis: Microbial, Metabolic, and Nutritional Implications for Graft and Patient Outcomes.Nutrients · 2026Review
- The impact of organ transplantation on changes in the oral microbiome, particularly on bacteria causing periodontal inflammation - narrative review.Frontiers in cellular and infection microbiology · 2026Review
- Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.Renal failure · 2025Article
- Unraveling salivary microbiota diversity following kidney transplantation: insights from baseline peripheral blood lymphocyte subsets.Journal of oral microbiology · 2025Article
- Periodontal disease and chronic kidney disease: mechanistic insights and novel therapeutic perspectives.Frontiers in cellular and infection microbiology · 2025Review
- Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.Frontiers in immunology · 2024Observational
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Authors and funding
8 authors.
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Abstract
Delayed graft function (DGF) is a frequently observed complication following kidney transplantation (KT). Our prior research revealed dynamic shifts in salivary microbiota post-KT with immediate graft function (IGF), yet its behavior during DGF remains unexplored. Five recipients with DGF and 35 recipients with IGF were enrolled. Saliva samples were collected during the perioperative period, and 16S rRNA gene sequencing was performed. The salivary microbiota of IGFs changed significantly and gradually stabilized with the recovery of renal function. The salivary microbiota composition of DGFs was significantly different from that of IGFs, although the trend of variation appeared to be similar to that of IGFs. Salivary microbiota that differed significantly between patients with DGF and IGF at 1 day after transplantation were able to accurately distinguish the two groups in the randomForest algorithm (accuracy = 0.8333, sensitivity = 0.7778, specificity = 1, and area under curve = 0.85), with Selenomonas playing an important role. Bacteroidales (Spearman's r = - 0.4872 and p = 0.0293) and Veillonella (Spearmen's r = - 0.5474 and p = 0.0125) were significantly associated with the serum creatinine in DGF patients. Moreover, the significant differences in overall salivary microbiota structure between DGF and IGF patients disappeared upon long-term follow-up. This is the first study to investigate the dynamic changes in salivary microbiota in DGFs. Our findings suggested that salivary microbiota was able to predict DGF in the early stages after kidney transplantation, which might help the perioperative clinical management and early-stage intervention of kidney transplant recipients. KEY POINTS: • Salivary microbiota on the first day after KT could predict DGF. • Alterations in salivary taxa after KT are related to recovery of renal function.
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