Evidence map›Paper›PMID 35559386›Full record

ReviewAmerican journal of translational research2022

Methods for identifying biomedical translation: a systematic review.

Javier Padilla-Cabello, Antonio Santisteban-Espejo, Ruben Heradio, Manuel J Cobo, Miguel A Martin-Piedra, Jose A Moral-Munoz

Abstract readReview
In one paragraph

Review in American journal of translational research, 2022. 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. Article
  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

6 authors.

Javier Padilla-CabelloProgram of Biomedicine, University of Granada Granada, Spain.
Antonio Santisteban-EspejoDepartment of Pathology, Puerta del Mar University Hospital Cadiz, Spain.
Ruben HeradioSchool of Computer Science, Universidad Nacional de Educación a Distancia (UNED) Madrid, Spain.
Manuel J CoboDepartment of Computer Science and Engineering, University of Cadiz Puerto Real, Spain.
Miguel A Martin-PiedraTissue Engineering Group, Department of Histology, University of Granada Granada, Spain.
Jose A Moral-MunozInstitute of Research and Innovation in Biomedical Sciences of The Province of Cadiz (INiBICA) Cadiz, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Translational medicine is an important area of biomedicine, and has significantly facilitated the development of biomedical research. Despite its relevance, there is no consensus on how to evaluate its progress and impact. A systematic review was carried out to identify all the methods to evaluate translational research. Seven methods were found according to the established criteria to analyze their characteristics, advantages, and limitations. They allow us to perform this type of evaluation in different ways. No relevant advantages were found between them; each one presented its specific limitations that need to be considered. Nevertheless, the Triangle of Biomedicine could be considered the most relevant method, concerning the time since its publication and usefulness. In conclusion, there is still a lack of a gold-standard method for evaluating biomedical translational research.

Indexed as

bibliometric analysisbiomedical translational researchmethods for evaluatingresearch evaluationTranslational research

Identifiers

PMID35559386
PMCPMC9091120

What OpenQuestion holds

Textmetadata
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.