Evidence map›Paper›PMID 30069677›Full record

ReviewJournal of nephrology2019

Microbiota issue in CKD: how promising are gut-targeted approaches?

Carmela Cosola, Maria Teresa Rocchetti, Alice Sabatino, Enrico Fiaccadori, Biagio Raffaele Di Iorio, Loreto Gesualdo

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Journal of nephrology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04689074 (Costituzione Della Biobanca Del Microbiota Intestinale e Salivare Umano), which is not on this map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT04689074 completednot on this mapstarted 2021, after this paper: background citation

Costituzione Della Biobanca Del Microbiota Intestinale e Salivare Umano: Dalla Disbiosi Alla Simbiosi

TypeobservationalSponsorAzienda Ospedaliero-Universitaria Consorziale Policlinico di BariRan2021 to 2022Enrolled150ConditionsAutosomal Dominant Polycystic Kidney Disease (ADPKD), Advanced-Chronic Kidney Disease (CKD), Diabetic Kidney Disease (DKD), IgA Nephropathy (IgAN)ArmsBiological sample collection, Questionnaire, Medical examination
3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
  2. Effects ofNutrients · 2026
    Trial
  3. Trial
  4. Trial
  5. Review
  6. Article
  7. Gut-Adipose Tissue Axis and Metabolic Health.Current issues in molecular biology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Plasma concentration of TMAO is an independent predictor of adverse outcomes in patients after acute myocardial infarction.Postepy w kardiologii interwencyjnej = Advances in interventional cardiology · 2023
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Carmela CosolaNephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy. carmela.cosola@uniba.it.ORCID http://orcid.org/0000-0002-7941-8420
Maria Teresa RocchettiNephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
Alice SabatinoRenal Unit, Department of Clinical and Experimental Medicine, Parma University Medical School, Parma, Italy.
Enrico FiaccadoriRenal Unit, Department of Clinical and Experimental Medicine, Parma University Medical School, Parma, Italy.
Biagio Raffaele Di IorioDivision of Nephrology, A. Landolfi Hospital, Solofra, Italy.
Loreto GesualdoNephrology, Dialysis and Transplantation Unit, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
University of Bari Aldo Moro · ITUniversity of Parma · ITOspedale Civile di Voghera · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In chronic kidney disease (CKD), the progressive decline in the renal excretory function leads to accumulation of urea and toxins in the blood. The CKD-associated dysbiosis of gut microbiota further contributes to uremia by increasing intestinal toxins production. Gut microbiota is involved in a complex network of human organs, mediated by microbial metabolites: in CKD, gut-heart and gut-brain axes may have a role in increased cardiovascular risk and neuropsychiatric disorders. While the cardiovascular toxicity of some microbial molecules is well known, their presumptive neurotoxicity needs to be confirmed by specific studies. In this review, we describe gut-heart and gut-brain axes in CKD, with an overview of the experimental and human studies characterizing CKD-associated gut microbiota, and we discuss the benefits coming from new approaches aimed at gut manipulation. Microbiota metabolism is emerging as a modifiable non-traditional risk factor in nephrology. In order to take advantage of this issue, it is necessary to consider the microbiota manipulation as part of the nutritional management of CKD. Integrating the low-protein nutritional approach with prebiotic, probiotic and synbiotic supplementation is a promising tool to control disease progression and comorbidities, though an extensive validation in large-scale clinical trials is still required.

Indexed as

Gastrointestinal MicrobiomeRenal EliminationAnimalsBacteriaBrainCardiovascular SystemDiet, Protein-RestrictedDysbiosisHost-Pathogen InteractionsHumansIntestinesKidneyPrebioticsProbioticsRenal Insufficiency, ChronicSynbioticsPrebioticsUreaCardiovascular diseaseCKDGut–brain axisGut microbiotaNutritionUremic toxins

Identifiers

PMID30069677
OpenAlexW2887487553

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.