Evidence map›Paper›PMID 23974524›Full record

ArticleIntensive care medicine2014

Determination of the learning curve for ultrasound-guided jugular central venous catheter placement.

Ba-Vinh Nguyen, Gwenael Prat, Jean-Louis Vincent, Emmanuel Nowak, Nicolas Bizien, Jean-Marie Tonnelier, Anne Renault, Mehdi Ould-Ahmed, Jean-Michel Boles, Erwan L'Her

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Article in Intensive care medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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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

32 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ba-Vinh NguyenRéanimation Médicale, CHRU de La Cavale Blanche, Bvd Tanguy-Prigent, 29609, Brest Cedex, France, bavinh@free.fr.
Gwenael Prat
Jean-Louis Vincent
Emmanuel Nowak
Nicolas Bizien
Jean-Marie Tonnelier
Anne Renault
Mehdi Ould-Ahmed
Jean-Michel Boles
Erwan L'Her

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUse of ultrasound (US) when introducing central venous catheters (CVC) may improve success rates, reduce the number of needle punctures, and decrease complication rates, but has been hampered by supposed difficulty in learning how to perform the technique. This study describes the learning curve for US-guided jugular CVC placement after a training program.

methodsAfter an initial slide presentation and a video, intensivists who had not previously used US for CVC placement were evaluated qualitatively for US set up (score S1) and technical skills (score S2). Quantitative measures included durations of different components of the procedure (T1, time from entry of the US into the patient's room to sterile dressing of the intensivist; T2, time needed for sterile drapes, venous line preparation, and sterile sheath placement; T3, time from skin puncture to venous flashback; T4, time from guide insertion to dressing; T(tot), total duration of the procedure); number of skin punctures; and a difficulty score allocated by the intensivist.

resultsWe performed 150 evaluations of 30 intensivists: 50% had no prior experience of CVC placement and 50% no prior US experience. Maximal S1 and S2 scores were obtained with the fourth and eighth placement procedures, respectively. T1 and T2 did not change with ongoing training (5 and 8 min, respectively), but T3 and T4 decreased, from 5 min (first procedure) to less than 1 min (seventh procedure), and from 10 min (first procedure) to 7 min (sixth procedure), respectively. T(tot) decreased from 34 to 21 min at the eighth procedure. The number of skin punctures and the difficulty score decreased rapidly with the number of evaluations.

conclusionsOur study demonstrates that skills in US-guided CVC placement can easily be acquired with training.

Indexed as

Catheterization, Central VenousEducational MeasurementFemaleFranceHumansInservice TrainingIntensive Care UnitsJugular VeinsLearning CurveMaleMedical Staff, HospitalMiddle AgedUltrasonicsUltrasonography, InterventionalWorkforce

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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.