Evidence map›Paper›PMID 34442401›Full record

ArticleJournal of personalized medicine2021

Role of Lung Ultrasound in Predicting Clinical Severity and Fatality in COVID-19 Pneumonia.

Ivan Skopljanac, Mirela Pavicic Ivelja, Ognjen Barcot, Ivan Brdar, Kresimir Dolic, Ozren Polasek, Mislav Radic

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  5. Observational
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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

7 authors at 1 institution in 1 country.

Ivan SkopljanacDepartment of Pulmology, University Hospital of Split, 21000 Split, Croatia.ORCID 0000-0003-4479-6947
Mirela Pavicic IveljaDepartment of Infectious Diseases, University Hospital of Split, 21000 Split, Croatia.ORCID 0000-0002-8878-7164
Ognjen BarcotDepartment of Surgery, University Hospital of Split, 21000 Split, Croatia.ORCID 0000-0003-0287-453X
Ivan BrdarDepartment of Internal Emergency Medicine, University Hospital of Split, 21000 Split, Croatia.ORCID 0000-0002-2467-4013
Kresimir DolicDepartment of Diagnostic and Interventional Radiology, University Hospital of Split, 21000 Split, Croatia.
Ozren PolasekSchool of Medicine, University of Split, 21000 Split, Croatia.ORCID 0000-0002-5765-1862
Mislav RadicDivision of Rheumatology and Clinical Immunology, Centre of Excellence for Systemic Sclerosis in Croatia, University Hospital of Split, 21000 Split, Croatia.
University of Split · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung ultrasound (LUS) is a useful imaging method for identifying COVID-19 pneumonia. The aim of this study was to explore the role of LUS in predicting the severity of the disease and fatality in patients with COVID-19.

methodsThis was a single-center, follow-up study, conducted from 1 November 2020, to 22 March 2021. The LUS protocol was based on the assessment of 14 lung zones with a total score up to 42, which was compared to the disease severity and fatality.

resultsA total of 133 patients with COVID-19 pneumonia confirmed by RT-PCR were enrolled, with a median time from hospital admission to lung ultrasound of one day. The LUS score was correlated with clinical severity at hospital admission (Spearman's rho 0.40, 95% CI 0.24 to 0.53,

conclusionsLUS at hospital admission is shown to have a high predictive power of the severity and fatality of COVID-19 pneumonia.

Indexed as

COVID-19lung ultrasoundLUSpneumoniaprognostic

Identifiers

PMID34442401
PMCPMC8399683
OpenAlexW3189760823

What OpenQuestion holds

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LicenceCC BY
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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.