Evidence map›Paper›PMID 30510937›Full record

ReviewWorld journal of clinical cases2018

The assessment of endosonographers in training.

Per Hedenström, Riadh Sadik

Abstract readReview
In one paragraph

Review in World journal of clinical cases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. The Role of Endoscopic Ultrasound for Esophageal Varices.Diagnostics (Basel, Switzerland) · 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

2 authors.

Per HedenströmDivision of Gastroenterology, Department of Medicine, Sahlgrenska University Hospital, Gothenburg 41345, Sweden. per.hedenstrom@vgregion.se.
Riadh SadikDivision of Gastroenterology, Department of Medicine, Sahlgrenska University Hospital, Gothenburg 41345, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endosonography (EUS) has an estimated long learning curve including the acquisition of both technical and cognitive skills. Trainees in EUS must learn to master intraprocedural steps such as echoendoscope handling and ultrasonographic imaging with the interpretation of normal anatomy and any pathology. In addition, there is a need to understand the periprocedural parts of the EUS-examination such as the indications and contraindications for EUS and potential adverse events that could occur post-EUS. However, the learning process and progress vary widely among endosonographers in training. Consequently, the performance of a certain number of supervised procedures during training does not automatically guarantee adequate competence in EUS. Instead, the assessment of EUS-competence should preferably be performed by the use of an assessment tool developed specifically for the evaluation of endosonographers in training. Such a tool, covering all the different steps of the EUS-procedure, would better depict the individual learning curve and better reflect the true competence of each trainee. This mini-review will address the issue of clinical education in EUS with respect to the evaluation of endosonographers in training. The aim of the article is to provide an informative overview of the topic. The relevant literature of the field will be reviewed and discussed. The current knowledge on how to assess the skills and competence of endosonographers in training is presented in detail.

Indexed as

AssessmentClinical competenceEducationEducationalEndosonographyFine-needle aspirationLearning curveQuality indicators

Identifiers

PMID30510937
PMCPMC6264995

What OpenQuestion holds

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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.