Evidence map›Paper›PMID 30374033›Full record

ArticleScientific reports2018

Novel Urinary Biomarkers For Improved Prediction Of Progressive Egfr Loss In Early Chronic Kidney Disease Stages And In High Risk Individuals Without Chronic Kidney Disease.

María E Rodríguez-Ortiz, Claudia Pontillo, Mariano Rodríguez, Petra Zürbig, Harald Mischak, Alberto Ortiz

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
4.6field-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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Contemporary Perspectives on Chronic Renal Disorders.Chronic diseases and translational medicine · 2025
    Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Urine MMP7 as a kidney injury biomarker.Clinical kidney journal · 2024
    Article
  14. Dynamics of urine proteomics biomarker and disease progression in patients with IgA nephropathy.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2023
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 3 countries.

María E Rodríguez-OrtizInstituto de Investigación Sanitaria Fundación Jiménez Díaz, Fundación Renal Iñigo Álvarez de Toledo, Universidad Autónoma de Madrid. REDinREN, Avda. Reyes Católicos, 2, 28040, Madrid, Spain. marien_rguez@hotmail.com.
Claudia PontilloMosaiques Diagnostics GmbH, Rotenburger Str. 20, 30659, Hannover, Germany.
Mariano RodríguezNephrology Service, Reina Sofía University Hospital/University of Córdoba. Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC). Avda. Menéndez Pidal, S/N. 14004, Córdoba(Spain). REDinREN, Madrid, Spain.
Petra ZürbigMosaiques Diagnostics GmbH, Rotenburger Str. 20, 30659, Hannover, Germany.
Harald MischakMosaiques Diagnostics GmbH, Rotenburger Str. 20, 30659, Hannover, Germany.
Alberto OrtizInstituto de Investigación Sanitaria Fundación Jiménez Díaz, Fundación Renal Iñigo Álvarez de Toledo, Universidad Autónoma de Madrid. REDinREN, Avda. Reyes Católicos, 2, 28040, Madrid, Spain.ORCID http://orcid.org/0000-0002-9805-9523
Mosaiques Diagnostics and Therapeutics (Germany) · DEFundación Renal Española · ESInstituto Maimónides de Investigación Biomédica de Córdoba · ES

Funding

EC | Seventh Framework Programme (European Union Seventh Framework Programme) 608332Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI16/01900Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI16/02057
6 · The paper itself

Abstract

Chronic kidney disease is associated with increased risk of CKD progression and death. Therapeutic approaches to limit progression are limited. Developing tools for the early identification of those individuals most likely to progress will allow enriching clinical trials in high risk early CKD patients. The CKD273 classifier is a panel of 273 urinary peptides that enables early detection of CKD and prognosis of progression. We have generated urine capillary electrophoresis-mass spectrometry-based peptidomics CKD273 subclassifiers specific for CKD stages to allow the early identification of patients at high risk of CKD progression. In the validation cohort, the CKD273 subclassifiers outperformed albuminuria and CKD273 classifier for predicting rapid loss of eGFR in individuals with baseline eGFR > 60 ml/min/1.73 m

Indexed as

AdultAgedAlbuminuriaArea Under CurveBiomarkersDisease ProgressionEarly DiagnosisFemaleGlomerular Filtration RateHumansMaleMiddle AgedPeptidesPrognosisRenal Insufficiency, ChronicRisk FactorsBiomarkersPeptides

Identifiers

PMID30374033
PMCPMC6206033
OpenAlexW2896978834

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.