Evidence map›Paper›PMID 39198828›Full record

ArticleBMC medical education2024

Web-based objective and structured assessment of point-of-care lung ultrasound skills in resource-limited settings.

Veronique Suttels, Ines Chichignoud, Prudence Ablo Wachinou, Jacques Daniel Du Toit, Pierre-André Mans, Juan Manuel Blanco, Gildas Agodokpessi, Thomas Brahier, Mary-Anne Hartley, Elena Garcia and 1 more

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Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Observational
  3. Observational
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

11 authors.

Veronique Suttels *Department of Infectious diseases, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland. veronique.suttels@chuv.ch.
Ines Chichignoud *Department of Infectious diseases, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland.
Prudence Ablo WachinouNational Teaching Hospital for Tuberculosis and Respiratory Diseases (CNHU-PPC), Cotonou, Benin.
Jacques Daniel Du ToitMRCWits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Pierre-André MansDepartment of Family Medicine, Cecilia Makiwane Hospital, East London, South Africa.
Juan Manuel BlancoDepartment of Epidemiology and Health Systems, Centre for Primary Care and Public Health (Unisanté), University of Lausanne, 10 Route de La Corniche, 1010, Lausanne, Switzerland.
Gildas AgodokpessiNational Teaching Hospital for Tuberculosis and Respiratory Diseases (CNHU-PPC), Cotonou, Benin.
Thomas BrahierDepartment of Infectious diseases, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland.
Mary-Anne HartleyIntelligent Global Health Research Group, Swiss Institute of Technology (EPFL), 1015, Lausanne, Switzerland.
Elena GarciaEmergency department, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland.
Noémie Boillat-BlancoDepartment of Infectious diseases, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObjective assessment of skills after training is essential for safe implementation of lung point-of-care ultrasound (POCUS). In low-and middle-income countries (LMIC) there is a need for assessment tools without onsite experts to scale up POCUS access. Our objective is to develop a web-based assessment tool and evaluate trainees across different countries and at different time points after initial lung POCUS training.

methodsWe adapted the objective and validated lung ultrasound score (LUS-OSAUS) to a web-based tool with quiz and practical skills test. Trainees were evaluated after a short (4-day) standardized lung POCUS training and were classified in distinct groups according to (i) their geographical location (Benin vs. South-Africa) and (ii) time elapsed since training (Benin 0 months vs. Benin 6 months). The Benin 6 months group had minimal continuous education. Skills test images were read by two blinded experts. We report the overall success rates and then compare these rates based on location and timing since training, using the Fischer's exact test.

resultsA total of 35 out of 43 participants completed the online LUS-OSAUS quiz and skills test. The overall success rate was 0.84 (95%CI 0.80-0.88), with lower success rates for "correct depth" 0.54 (0.37-0.71), "correct assessment of pleura" 0.63 (0.45-0.79) and "conclusion" 0.71 (0.54-0.85). There were no differences based on location, with respective rates of 0.86 (0.80-0.92) and 0.83 (0.75-0.91) (p-value = 0.125) for Benin and South Africa at 0 months, respectively. Similarly, there were no differences according to timing with success rates of 0.86 (0.80-0.92) and 0.82 (0.72-0.93) (p-value = 0.563) for Benin at 0 months and 6 months, respectively.

conclusionWeb-based objective and structured assessment of lung POCUS skills in LMIC following a short-standardized training is feasible and has a good overall success rate with consistent results across regions and up to 6 months after training given minimal continuous education. Overall, technical and POCUS-based clinical conclusion skills are the most difficult to acquire.

Indexed as

Clinical CompetenceDeveloping CountriesLungPoint-of-Care SystemsUltrasonographyEducational MeasurementHumansInternetResource-Limited SettingsSouth AfricaLow- and middle- income countriesLung POCUSLUS-OSAUSTraining, quality control

Identifiers

PMID39198828
PMCPMC11360711

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Registered trials

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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.