Evidence map›Paper›PMID 37511638›Full record

ArticleJournal of personalized medicine2023

Are Graduate Medical Trainees Prepared for the Personalized Genomic Medicine Revolution? Trainee Perspectives at One Institution.

Elizabeth L Kudron, Kimberly M Deininger, Christina L Aquilante

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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  5. 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 at 2 institutions in 1 country.

Elizabeth L KudronDepartment of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO 80045, USA.ORCID 0009-0007-4066-4978
Kimberly M DeiningerDepartment of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO 80045, USA.
Christina L AquilanteColorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
University of Colorado Anschutz Medical Campus · USUniversity of Montana · US

Funding

Department of Medicine, University of Colorado School of Medicine Program for Academic Clinician Educators (PACE) Grant; no associated grant number
6 · The paper itself

Abstract

Although the use of genomics to inform clinical care is increasing, clinicians feel underprepared to integrate personalized medicine (PM) into care decisions. The educational needs of physician residents and fellows, also known as graduate medical trainees (GMTs), have been overlooked. We administered an anonymous, web-based survey to all GMTs participating in training programs affiliated with our institution to evaluate their knowledge, skills, and attitudes toward PM. Of the 1190 GMTs contacted, 319 (26.8%) returned surveys. Most (88.4%) respondents reported receiving PM education in the past. Although the respondents agreed that knowledge of disease genetics (80.9%) or pharmacogenetics (87.1%) would likely lead to improved clinical outcomes, only 33.2% of the respondents felt sufficiently informed about PM. The respondents who had received PM education in residency and/or fellowship had significantly higher self-reported knowledge, ability, awareness, and adoption of PM than those who had not received this education (

Indexed as

fellowsgeneticsgraduate medical trainingmedical educationmedical schoolpersonalized medicinepharmacogeneticsresidents

Identifiers

PMID37511638
PMCPMC10381337
OpenAlexW4381616988

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.