Evidence map›Paper›PMID 40003031›Full record

ArticleAnimals : an open access journal from MDPI2025

Retrospective Evaluation of Subpleural Consolidations Using Lung Ultrasound in 634 Dogs and 347 Cats.

Katarzyna Kraszewska, Michał Gajewski, Søren Boysen, Natalia Buda

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2025. 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.

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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

4 authors.

Katarzyna KraszewskaVetcardia Veterinary Clinic, Kijowska 11, 03-743 Warsaw, Poland.ORCID 0000-0001-8326-0817
Michał GajewskiVetcardia Veterinary Clinic, Kijowska 11, 03-743 Warsaw, Poland.ORCID 0009-0009-0856-6977
Søren BoysenFaculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada.ORCID 0000-0002-0936-4834
Natalia BudaSimulation Laboratory of Endoscopic and Minimally Invasive Techniques, Medical University of Gdansk, 80-210 Gdańsk, Poland.ORCID 0000-0002-9356-2736

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman literature describes vascular patterns in various types of lung consolidations; however, these changes have not been analyzed in dogs and cats. This retrospective analysis of medical records aimed to describe vascular patterns observed in the airless subpleural lung tissue of dogs and cats and to compare these patterns to various lung consolidations and clinical diagnoses according to parenchymal and vascular criteria described in human literature. ANIMALS: This study included 347 cats and 634 dogs.

methodsThis was a retrospective study encompassing medical records obtained between 2018 and 2023. Lung ultrasound was performed in dogs and cats and cases with different sonographically identified airless subpleural lung tissue were selected. Airless subpleural lung tissue was categorized into five types of consolidations: shred, nodule, wedge sign, mass, and tissue sign. Further classification was based on the parenchymal criteria, the presence or absence of bronchograms and the vascular patterns identified within these regions. Bronchograms were classified as air bronchograms (dynamic and/or static), fluid bronchograms, mixed fluid and air bronchograms, and/or absence of bronchograms. Vascular patterns were classified as tree-like, residual, chaotic, " CONCLUSIONS AND CLINICAL IMPORTANCE: It is possible to identify and characterize airless subpleural lung tissue in cats and dogs based on the parenchymal and vascular characteristics.

Indexed as

bronchogramcolor Dopplerconsolidationvascularity

Identifiers

PMID40003031
PMCPMC11851566

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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.