Evaluation of inter-rater agreement of the clinical signs used to diagnose bovine respiratory disease in individually housed veal calves
Notice bibliographique
Résumé
In dairy calves raised for veal, typical clinical signs of bovine respiratory disease (BRD) are ocular discharge, nasal discharge, ear droop or head tilt, abnormal respiration, cough, and increased rectal temperature. Despite the existence of several clinical scoring systems, there are few studies on the variability of human recognition of individual BRD clinical signs. The objective of this study was therefore to assess the inter-rater agreement of BRD clinical signs in veal calves. We hypothesized that BRD clinical signs were not detected equally between veterinarians, technicians, and producers of the veal industry and that some clinical signs have higher inter-rater agreement than others. During 2017-2018, we prospectively recorded 524 videos of physical examinations of random veal calves from 48 different batches in Québec, Canada. A researcher, not involved in the inter-rater assessment, classified each video as presence/absence of each BRD clinical sign except rectal temperature. For each of the 5 clinical signs, 15 videos with and 15 videos without the clinical signs were randomly selected to avoid kappa paradoxes. Those 30 videos were then presented in a random order to experienced raters of BRD in veal calves: 6 veterinarians, 6 technicians, and 6 producers. The raters assessed the clinical signs using scores based on the Wisconsin and California scoring system with modifications (0 = absent, 1 = mild, 2 = moderate, 3 = severe for nasal discharge, ocular discharge, and ear droop or head tilt; and 0 = absent, 1 = moderate, 2 = severe for abnormal respiration and induced cough). We used median percentage agreement (Pa), median Cohen's kappa (κ), and Gwet's agreement coefficient 1 (AC1) to assess inter-rater agreement. The effect of scale combination was also tested to determine the optimal combination (4-scale 0/1/2/3 vs. 3-scale 0/1/2 vs. 2-scale 0/1,2,3; 0,1/2,3; or 0/1,2). The differences of inter-rater agreement between veterinarians, technicians, and producers were estimated by a Wilcoxon rank-sum test. The 2-scale combination (0,1/2,3 or 0/1,2) had the highest inter-rater agreement for all clinical signs. With this combination, induced cough was the clinical sign with the highest inter-rater agreement (Pa = 0.93; κ = 0.79; AC1 = 0.87) and abnormal respiration was the sign with the lowest inter-rater agreement (Pa = 0.77; κ = 0.20; AC1 = 0.74). According to Pa and AC1 values, the 2-scale inter-rater agreement of the 5 clinical signs was good (value > 0.6). According to κ, only ear droop or head tilt and induced cough had a substantial 2-scale inter-rater agreement (κ > 0.6). In general, the 2-scale inter-rater agreement was better among veterinarians than among technicians and producers, except for the ear droop/head tilt, where agreement was better among producers. We concluded that with severity scores assessed on a scale of 2 (0,1/2,3 or 0/1,2), the inter-rater agreement of BRD clinical signs was variable according to the sign in veal calves. BRD clinical signs were not detected equally between veterinarians, technicians, and producers of the veal industry. Future research could determine if this discrepancy could be improved by standardization training.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,051 | 0,084 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».