Predictors of diarrhea, mortality, and weight gain in male dairy calves
Notice bibliographique
Résumé
The objective of this prospective cohort study was to determine the effect of an abnormal fecal consistency score on weight gain and mortality in male Holstein calves and to identify risk factors associated with the occurrence of an abnormal fecal consistency score. This study enrolled 2,616 calves entering a calf-raising facility in Ontario, Canada, between January 2018 and December 2020. Fecal consistency scores were assigned twice daily for the first 28 d following arrival, where a score of 2, indicating runny consistency, and 3, indicating watery consistency, were classified as diarrhea. Severe diarrhea was classified by a score of 3. Serum total protein was measured upon arrival and the source of the calf (i.e., whether the calf came from a drover, local farm, or auction) was recorded. Body weight measurements were also collected at arrival and at 14, 56, and 77 d after arrival. Calf mortality and disease treatment during the first 77 d were recorded. On average, calves had diarrhea for 16% (4.51 d) of the first 28 d under observation, and severe diarrhea for 7% (1.87 d) of the 28 d under observation. Using a repeated measures linear regression model, we found the proportion of days with diarrhea significantly decreased weight gain at 14, 56, and 77 d following arrival. An increased proportion of days with diarrhea increased the risk of mortality, which was determined using a Cox proportional hazards model. We also found, using 2 Cox proportional hazards models, that a higher proportion of days with an abnormal fecal score increased the hazard of antibiotic treatment. With respect to factors associated with the occurrence of abnormal fecal consistency, we found that arrival weight and the source of calves were statistically significant predictors. Specifically, for every additional kilogram of body weight at arrival, the proportion of days with diarrhea decreased by 7%. With respect to source, calves from drovers had a higher proportion of days with diarrhea compared with those sourced directly from local dairy farms. Our results highlight the substantial influence the presence of abnormal fecal consistency has on short-term weight gain, mortality risk, and morbidity risk. We also demonstrate that diarrhea occurrence can be predicted using body weight at arrival and calf source. Further research should evaluate longer-term effects of diarrhea and better understand the effect of arrival weight on neonatal calf disease risk.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».