Evidence map›Paper›PMID 33392301›Full record

ArticleFrontiers in veterinary science2020

Usefulness of Chest Ultrasonography in Predicting Diagnosis in Non-emergency Small Animal Patients With Lung Parenchymal and Pleural Disease.

Chung-Hui Lin, Pei-Ying Lo, Man-Cham Lam, Huey-Dong Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2020. 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
0.3field-weighted citation impact, top 37% 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, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. 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

4 authors at 1 institution in 1 country.

Chung-Hui LinNational Taiwan University Veterinary Hospital, National Taiwan University, Taipei, Taiwan.
Pei-Ying LoNational Taiwan University Veterinary Hospital, National Taiwan University, Taipei, Taiwan.
Man-Cham LamNational Taiwan University Veterinary Hospital, National Taiwan University, Taipei, Taiwan.
Huey-Dong WuSection of Respiratory Therapy, Department of Integrated Diagnostics and Therapeutics, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan.
National Taiwan University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chest ultrasonography has become an indispensable tool for pulmonary specialists in human medicine, but its current use in dogs and cats is primarily for emergency. The diagnostic performances of various ultrasonographic features other than comet-tail artifacts are of limited information in veterinary literatures. Therefore, the aims of this retrospective study were to investigate ultrasonographic findings in feline and canine respiratory patients with lung parenchymal and pleural space diseases, and to assess how ultrasonographic features correspond to specific diagnoses. Sixty-five non-emergency cases with radiographically identified lung parenchymal and pleural space abnormalities were included. Medical records and ultrasound video clips were reviewed, and additional follow-up information was subsequently collected. Common findings such as comet-tail artifacts (87.7% of cases), consolidation (84.6%), and thickened/irregular pleura (69.2%) were not distinguishable for a specific diagnosis. The presence of nodular/mass-like lesion (OR = 212,

Indexed as

catchest ultrasonographydognon-invasive clinical assessmentpulmonologyrespiratory disease

Identifiers

PMID33392301
PMCPMC7775533
OpenAlexW3111430060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.