Evidence map›Paper›PMID 34772730›Full record

ArticleBMJ open respiratory research2021

Lung ultrasound volume sweep imaging for respiratory illness: a new horizon in expanding imaging access.

Thomas J Marini, Justin M Weis, Timothy M Baran, Jonah Kan, Steven Meng, Alex Yeo, Yu T Zhao, Robert Ambrosini, Sean Cleary, Deborah Rubens and 6 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open respiratory research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

12 citing papers in PubMed, 23 citations in OpenAlex.

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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

16 authors at 5 institutions in 2 countries.

Thomas J MariniDepartment of Imaging Sciences, URMC, Rochester, NY, USA rochesterradiology2021@gmail.com.ORCID 0000-0002-1529-5097
Justin M WeisDepartment of Medicine, URMC, Rochester, NY, USA.
Timothy M BaranDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Jonah KanUniversity of Rochester School of Medicine and Dentistry, URMC, Rochester, NY, USA.
Steven MengUniversity of Rochester School of Medicine and Dentistry, URMC, Rochester, NY, USA.
Alex YeoDepartment of Medicine, Boston University Medical Center, Boston, MA, USA.
Yu T ZhaoDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Robert AmbrosiniDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Sean ClearyDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Deborah RubensDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Mitchell ChessDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
Benjamin CastanedaDepartmento de Ingeniería, Pontificia Universidad Católica del Perú, Lima, Peru.
Ann DozierDepartment of Public Health Sciences, URMC, Rochester, NY, USA.
Timothy O'ConnorDepartment of Emergency Medicine, URMC, Rochester, NY, USA.
Brian GarraMedical Imaging Ministries of the Americas, Clermont, FL, USA.
Katherine Kaproth-JoslinDepartment of Imaging Sciences, URMC, Rochester, NY, USA.
University of Rochester Medical Center · USUniversity of Rochester · USBoston University · USGlobal Ministries · USPontificia Universidad Católica del Perú · PE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRespiratory illness is a leading cause of morbidity in adults and the number one cause of mortality in children, yet billions of people lack access to medical imaging to assist in its diagnosis. Although ultrasound is highly sensitive and specific for respiratory illness such as pneumonia, its deployment is limited by a lack of sonographers. As a solution, we tested a standardised lung ultrasound volume sweep imaging (VSI) protocol based solely on external body landmarks performed by individuals without prior ultrasound experience after brief training. Each step in the VSI protocol is saved as a video clip for later interpretation by a specialist.

methodsDyspneic hospitalised patients were scanned by ultrasound naive operators after 2 hours of training using the lung ultrasound VSI protocol. Separate blinded readers interpreted both lung ultrasound VSI examinations and standard of care chest radiographs to ascertain the diagnostic value of lung VSI considering chest X-ray as the reference standard. Comparison to clinical diagnosis as documented in the medical record and CT (when available) were also performed. Readers offered a final interpretation of normal, abnormal, or indeterminate/borderline for each VSI examination, chest X-ray, and CT.

resultsOperators scanned 102 subjects (0-89 years old) for analysis. Lung VSI showed a sensitivity of 93% and a specificity of 91% for an abnormal chest X-ray and a sensitivity of 100% and a specificity of 93% for a clinical diagnosis of pneumonia. When any cases with an indeterminate rating on chest X-ray or ultrasound were excluded (n=38), VSI lung ultrasound showed 92% agreement with chest X-ray (Cohen's κ 0.83 (0.68 to 0.97, p<0.0001)). Among cases with CT (n=21), when any ultrasound with an indeterminate rating was excluded (n=3), there was 100% agreement with VSI.

conclusionLung VSI performed by previously inexperienced ultrasound operators after brief training showed excellent agreement with chest X-ray and high sensitivity and specificity for a clinical diagnosis of pneumonia. Blinded readers were able to identify other respiratory diseases including pulmonary oedema and pleural effusion. Deployment of lung VSI could benefit the health of the global community.

Indexed as

LungPneumoniaAdolescentAdultAgedAged, 80 and overChildChild, PreschoolHumansInfantInfant, NewbornMiddle AgedSensitivity and SpecificityThoraxUltrasonographyYoung Adultpleural effusionpneumoniapulmonary edemateleultrasoundultrasound

Identifiers

PMID34772730
PMCPMC8593737
OpenAlexW3212601943

What OpenQuestion holds

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LicenceCC BY-NC
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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.