Evidence map›Paper›PMID 28840013›Full record

ReviewJournal of thoracic disease2017

Training and certification in endobronchial ultrasound-guided transbronchial needle aspiration.

Therese Maria Henriette Naur, Lars Konge, Leizl Joy Nayahangan, Paul Frost Clementsen

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  4. Review
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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

4 authors.

Therese Maria Henriette NaurCopenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, University of Copenhagen and the Capital Region of Denmark, Copenhagen, Denmark.
Lars KongeCopenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, University of Copenhagen and the Capital Region of Denmark, Copenhagen, Denmark.
Leizl Joy NayahanganCopenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, University of Copenhagen and the Capital Region of Denmark, Copenhagen, Denmark.
Paul Frost ClementsenCopenhagen Academy for Medical Education and Simulation (CAMES), Rigshospitalet, University of Copenhagen and the Capital Region of Denmark, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) plays a key role in the staging of lung cancer, which is crucial for allocation to surgical treatment. EBUS-TBNA is a complicated procedure and simulation-based training is helpful in the first part of the long learning curve prior to performing the procedure on actual patients. New trainees should follow a structured training programme consisting of training on simulators to proficiency as assessed with a validated test followed by supervised practice on patients. The simulation-based training is superior to the traditional apprenticeship model and is recommended in the newest guidelines. EBUS-TBNA and oesophageal ultrasound-guided fine needle aspiration (EUS-FNA or EUS-B-FNA) are complementary to each other and the combined techniques are superior to either technique alone. It is logical to learn and to perform the two techniques in combination, however, for lung cancer staging solely EBUS-TBNA simulators exist, but hopefully in the future simulation-based training in EUS will be possible.

Indexed as

cancer stagingeducationendobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA)lung cancerSimulation training

Identifiers

PMID28840013
PMCPMC5542957

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.