Evidence map›Paper›PMID 39355987›Full record

ArticleVeterinary surgery : VS2025

Comparison of remote and in-person respiratory function grading of brachycephalic dogs.

Zong H Peng, Kathleen M Ham, Jane Ladlow, Carrie Stefaniak, Nicholas D Jeffery, Kelley M Thieman Mankin

Abstract readComparative Study
In one paragraph

Article in Veterinary surgery : VS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zong H PengDepartment of Small Animal Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.
Kathleen M HamDepartment of Small Animal Clinical Sciences, University of Florida, Gainesville, Florida, USA.
Jane LadlowDepartment of Veterinary Medicine, University of Cambridge, Cambridge, Cambridgeshire, UK.
Carrie StefaniakSunrise Veterinary Services, Reedsburg, Wisconsin, USA.
Nicholas D JefferyDepartment of Small Animal Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.
Kelley M Thieman MankinDepartment of Small Animal Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.ORCID https://orcid.org/0000-0002-5618-1600

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the reliability of respiratory function grading (RFG) scores assigned in-person and remotely via video and electronic stethoscope recordings, evaluated by novice and expert graders. STUDY

designProspective study. SAMPLE POPULATION: Fifty-seven brachycephalic dogs.

methodsDogs were evaluated in person by expert graders and RFG scores were assigned. Audio and video recordings were made during the in-person evaluations. Four expert and four novice graders evaluated the recordings and assigned an RFG score to each dog. Agreement between in-person and remote RFG scores was assessed using Cohen's kappa statistic. Interobserver reliability was assessed using Fleiss' kappa statistic.

resultsThe median RFG score from the in-person assessment was 1 (range, 0-3). Distribution of RFG scores included 12 grade 0 scores, 19 grade 1 scores, 25 grade 2 scores, and 1 grade 3 score. The raw percentage agreements between remote and in-person scores were 68.4%, 59.6%, 64.9%, and 61.4% for the four experts, and 52.6%, 64.9%, 50.9%, and 42.1% for the four novices. Reliability between remote and in-person RFG scores was poor to moderate both for the experts (Cohen's kappa: .48, .37, .46, .41) and novices (Cohen's kappa: .28, .47, .28, .21). Interobserver reliability was moderate among the experts (Fleiss' kappa: .59) and poor among the novices (Fleiss' kappa: .39).

conclusionRemote RFG scores had poor to moderate interassessment and interobserver reliability. Novice evaluators performed worse than experts for remote or in-person RFG evaluations. CLINICAL SIGNIFICANCE: Remote RFG, as measured in this study, is not reliable for assigning RFG scores. Modifications could be made to remote evaluation to improve reliability. Based upon the performance of novice evaluators, training of evaluators is justified.

Indexed as

CraniosynostosesDog DiseasesRespiratory Function TestsAnimalsDogsFemaleMaleObserver VariationProspective StudiesReproducibility of ResultsVideo Recording

Identifiers

PMID39355987
PMCPMC11947300

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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.