Evidence map›Paper›PMID 23716291›Full record

Trial reportLa Radiologia medica2013

Learning curve in multidetector CT coronary angiography (MDCT-CA).

Roberto Malagò, Andrea Pezzato, Camilla Barbiani, Michela Tezza, Giuseppe Sala, Ugolino Alfonsi, Roberto Pozzi Mucelli

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in La Radiologia medica, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Roberto MalagòIstituto di Radiologia, Azienda Ospedaliero Universitaria Integrata di Verona, Policlinico G.B. Rossi, P.le L.A. Scuro 10, 37134, Verona, Italy, rmalag@sirm.org.
Andrea Pezzato
Camilla Barbiani
Michela Tezza
Giuseppe Sala
Ugolino Alfonsi
Roberto Pozzi Mucelli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCoronary angiography using multidetector computed tomography (MDCT-CA) is a recent technique for the nonivasive study of coronary arteries. This study assessed the diagnostic accuracy of coronary artery stenosis evaluation obtained by three readers at different levels of training or at different points of the learning curve proposed by the international guidelines. MATERIALS AND

methodsThree radiologists in training with different levels of experience in MDCT-CA scored 50 cases at various time points of the learning curve: baseline, 4 weeks, 8 weeks and 6 months. The trainee radiologists evaluated the degree of stenosis on each coronary segment, and overall accuracy was calculated on a per-segment, pervessel and per-patient basis.

resultsAll readers improved analysis accuracy per segment (range, 73-90%); sensitivity reached 45% per segment, 84% per vessel and 93% per patient; specificity was 99% per segment and vessel and 98% per patient. Positive and negative predictive values increased to 94% and 92%, respectively.

conclusionsAlthough all readers improved in diagnostic performance with growing experience with MDCT-CA, a longer training period may be necessary to achieve adequate levels of expertise in MDCT-CA to be able to perform as independent readers.

Indexed as

Clinical CompetenceCoronary AngiographyCoronary Artery BypassCoronary StenosisFemaleHumansLearning CurveMaleMiddle AgedMultidetector Computed TomographyPatient SelectionPredictive Value of TestsSensitivity and SpecificityStentsVascular Patency

Identifiers

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.