Interclinician agreement on the recognition of selected respiratory clinical signs in dogs and cats with abnormal breathing patterns

Autor: M. Domínguez-Ruiz, Aida I. Vientós-Plotts, K. Le Boedec, D. Silverstein, Megan Grobman, Carol R. Reinero
Rok vydání: 2021
Předmět:
Zdroj: Veterinary journal (London, England : 1997). 277
ISSN: 1532-2971
Popis: In humans, classification of abnormal breathing patterns (ABP) and recognition of ancillary respiratory signs are difficult, as reflected by poor-to-moderate interclinician agreement. The aims of this study were to assess interclinician agreement for respiratory sign recognition in dogs and cats and evaluate the influence of clinical experience on agreement. Dogs and cats with ABP were recruited from three hospitals. Included animals were evaluated by three clinicians at each hospital before therapeutic intervention. Consensual definitions for each respiratory clinical sign were provided to all clinicians. Interclinician agreement was measured via Fleiss' kappa and intraclass correlation coefficient statistics. Influence of clinical experience on interobserver agreement was studied via mixed-effects logistic regression. One-hundred and fifteen dogs and 49 cats with ABP were recruited. Out of 12 clinical signs evaluated, only stertor (kappa, 0.80), stridor (kappa, 0.64), attenuation of heart/lung sounds (kappa, 0.60), and goose honking (kappa, 0.84) in dogs, and stertor (kappa, 0.65) and open-mouth breathing (kappa, 0.75) in cats, were considered sufficiently reliable among clinicians. Agreement on respiratory rate estimation was good in both species (intraclass correlation coefficient, 0.75). The greater the difference in clinical experience between two clinicians, the lower the odds of agreement between the two clinicians' respiratory physical examination findings. Interclinician agreement was demonstrated to be poor for recognition of most respiratory clinical signs in dogs and cats. Teaching and clinical experience acquisition should be encouraged to improve respiratory clinical sign recognition.
Databáze: OpenAIRE