Evidence map›Paper›PMID 31964937›Full record

ArticleScientific reports2020

Kidney transplant monitoring by urinary flow cytometry: Biomarker combination of T cells, renal tubular epithelial cells, and podocalyxin-positive cells detects rejection.

Nina Goerlich, Hannah Antonia Brand, Valerie Langhans, Sebastian Tesch, Thomas Schachtner, Benjamin Koch, Alexander Paliege, Wolfgang Schneider, Andreas Grützkau, Petra Reinke and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Review
  6. Urinary CD4Scientific reports · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Toll-Like Receptor as a Potential Biomarker in Renal Diseases.International journal of molecular sciences · 2020
    Review
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

11 authors.

Nina Goerlich *Charité University Hospital, Berlin, Germany. nina.goerlich@charite.de.
Hannah Antonia Brand *Charité University Hospital, Berlin, Germany.
Valerie LanghansCharité University Hospital, Berlin, Germany.
Sebastian TeschCharité University Hospital, Berlin, Germany.
Thomas SchachtnerUniversity Hospital Zurich, Zurich, Switzerland.
Benjamin KochGoethe University Hospital Frankfurt, Frankfurt, Germany.
Alexander PaliegeUniversity Hospital Carl Gustav Carus, Dresden, Germany.
Wolfgang SchneiderCharité University Hospital, Berlin, Germany.
Andreas GrützkauGerman Rheumatism Research Centre, Berlin, Germany.
Petra ReinkeCharité University Hospital, Berlin, Germany.
Philipp EnghardCharité University Hospital, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Creatinine and proteinuria are used to monitor kidney transplant patients. However, renal biopsies are needed to diagnose renal graft rejection. Here, we assessed whether the quantification of different urinary cells would allow non-invasive detection of rejection. Urinary cell numbers of CD4

Indexed as

Kidney TransplantationAdultAgedAllograftsBiomarkersCase-Control StudiesCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCell CountEpithelial CellsFemaleFlow CytometryGraft RejectionHumansKidney TubulesMacrophagesBiomarkerspodocalyxinSialoglycoproteins

Identifiers

PMID31964937
PMCPMC6972704

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.