Evidence map›Paper›PMID 33125003›Full record

ArticleClinical kidney journal2020

Prediction scores for risk of allograft loss in patients receiving kidney transplants: nil satis nisi optimum.

Nuria Montero, Sergi Codina, Josep M Cruzado

Abstract readEditorial
In one paragraph

Article in Clinical kidney journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Nuria MonteroDepartment of Nephrology, Hospital Universitari de Bellvitge, L' Hospitalet de Llobregat, Barcelona, Spain.ORCID 0000-0002-5123-4603
Sergi CodinaDepartment of Nephrology, Hospital Universitari de Bellvitge, L' Hospitalet de Llobregat, Barcelona, Spain.
Josep M CruzadoDepartment of Nephrology, Hospital Universitari de Bellvitge, L' Hospitalet de Llobregat, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-term graft survival is the main concern of kidney transplantation. Some strategies have been tested to predict graft survival using estimated glomerular filtration rate or proteinuria at different time points, histologic assessment, non-invasive biomarkers or even machine-learning methods. However, the 'magical formulae' for allograft survival prediction does not exist yet.

Indexed as

graft functiongraft survivalkidney transplantationprognosis

Identifiers

PMID33125003
PMCPMC7577772

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.