Evidence map›Paper›PMID 40427324›Full record

ArticleAnimals : an open access journal from MDPI2025

Assessment of Computed Tomography as a Diagnostic Tool for Upper Respiratory Tract Disorders in Sheep.

Enrique Castells, Pablo Quílez, Aurora Ortín, Sergio Villanueva-Saz, Marta Ruiz de Arcaute, María Climent, Marcelo De Las Heras, Héctor Ruiz, Teresa Navarro, Delia Lacasta

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

10 authors.

Enrique CastellsCentro Clínico Veterinario de Zaragoza, Madre Genoveva Torres Morales, 8, 50006 Zaragoza, Spain.
Pablo QuílezDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0009-0003-9757-3840
Aurora OrtínDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-0313-5926
Sergio Villanueva-SazDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0001-6209-4282
Marta Ruiz de ArcauteDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-7655-2472
María ClimentRuminant Clinical Service, Veterinary Faculty, University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-0606-0763
Marcelo De Las HerasDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0003-3792-287X
Héctor RuizDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-8474-2831
Teresa NavarroDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-4557-6033
Delia LacastaDepartment of Animal Pathology, Veterinary Faculty, Instituto Agroalimentario de Aragón-IA2 (Universidad de Zaragoza-CITA), University of Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain.ORCID 0000-0002-7822-6646

Funding

Aragon Government (AR15_23R) and the European Social Fund. AR15_23R
6 · The paper itself

Abstract

Upper respiratory tract diseases are a major concern in sheep, causing economic losses and affecting animal welfare. Accurate diagnosis is crucial for effective treatment and prevention. This case-based study assessed the use of computed tomography for diagnosing these diseases in sheep. Thirty-three sheep showing clinical signs of one or more upper respiratory tract diseases underwent computed tomography scans, which were compared to clinical diagnoses and postmortem examinations. Results showed that clinical diagnosis matched the postmortem findings in 26 of 38 cases, while computed tomography diagnosis matched in 36 of 38 diagnosed conditions, demonstrating higher accuracy. Computed tomography provided detailed anatomical reconstructions of the respiratory tract, allowing precise detection of lesions, identification of their origin or content, and clear visualisation of surrounding structures. Despite limitations such as high costs, risks related to general anaesthesia, and radiation exposure, its accuracy makes it a valuable tool for managing these diseases. The creation of extensive databases on common diseases affecting sheep could improve the accessibility and effectiveness of computed tomography in veterinary clinics.

Indexed as

computed tomographydiagnostic imagingsheepupper respiratory tract diseases

Identifiers

PMID40427324
PMCPMC12108525

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.