Case study: Evaluating quarter and composite milk sampling for detection of subclinical intramammary infections in dairy cattle
Notice bibliographique
Résumé
Our objective was to evaluate a 200,000 cells/mL somatic cell count (SCC) cut-point on both the quarter and composite level to determine its effectiveness at identifying subclinical mastitis infections in one commercial dairy herd in Central New York. Milk samples from 107 Holstein cows were used for analysis. All cows were eligible for enrollment provided they had 4 working udder quarters, were >14 and <365 d in milk, and had no clinical mastitis event or treatment with intramammary antibiotics ≤14 d prior to d of sampling. A total of 428 quarter and 107 composite samples from 34 primiparous and 73 multiparous animals were analyzed for total SCC and aerobic culture. Performance of SCC for identification of subclinically infected animals was evaluated against the gold standard aerobic culture. Sensitivities for a 200,000 cells/mL cut-point on both the quarter and composite basis were 28.6%, and specificities were 91.5% and 87.3% on the quarter and composite basis, respectively. Receiver operating characteristic (ROC) curves determined on a quarter basis found the cut-point that optimized the sensitivity and specificity of a positive culture was 32,000 cells/mL, with a sensitivity of 76.2%, a specificity of 62.4%, and an area under the curve (AUC) of 0.73. The ROC curve cut-point that optimized the sensitivity and specificity for the composite samples was 75,000 cells/mL, with a sensitivity of 57.1%, a specificity of 78.9%, and an AUC of 0.67. A large proportion of culture positive primiparous cows (38%) had low SCC (median of 101,000 cells/mL on the quarter and 80,000 cells/mL on the composite level), and therefore, when multiparous cows were examined separately, the cut-point that optimized sensitivity and specificity on the quarter basis increased to 645,000 cells/mL with a corresponding sensitivity of 34.8%, specificity of 97.5%, and AUC of 0.65. On the composite basis, the cut-point based on multiparous cows only was 152,000 cells/mL, with a corresponding sensitivity of 60.0%, and specificity of 82.0%, and an AUC of 0.65. Our data indicate that the 200,000 cells/mL cut-point was inefficient in identifying subclinically infected animals, regardless of whether quarter or composite sampling was used. The low prevalence of subclinical infections as well as the large proportion of minor pathogens, especially in primiparous animals, contributed to this inefficiency. This case study provides evidence that, with continued improvement upon mastitis control and reduction in major mastitis pathogens, blanket cut-points may no longer provide the same diagnostic usefulness as they once did.
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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 | 0,001 | 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 | 0,000 |
| 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 ».