Evaluation of an automated milk leukocyte differential test and the California Mastitis Test for detecting intramammary infection in early- and late-lactation quarters and cows
Notice bibliographique
Résumé
Study objectives were to (1) describe the diagnostic test characteristics of an automated milk leukocyte differential (MLD) test and the California Mastitis Test (CMT) to identify intramammary infection (IMI) in early- (EL) and late-lactation (LL) quarters and cows when using 3 different approaches to define IMI from milk culture, and (2) describe the repeatability of MLD test results at both the quarter and cow level. Eighty-six EL and 90 LL Holstein cows were sampled from 3 Midwest herds. Quarter milk samples were collected for a cow-side CMT test, milk culture, and MLD testing. Quarter IMI status was defined by 3 methods: culture of a single milk sample, culture of duplicate samples with parallel interpretation, and culture of duplicate samples with serial interpretation. The MLD testing was completed in duplicate within 8 h of sample collection; MLD results (positive/negative) were reported at each possible threshold setting (1-18 for EL; 1-12 for LL) and CMT results (positive/negative) were reported at each possible cut-points (trace, ≥1, ≥2, or 3). We created 2 × 2 tables to compare MLD and CMT results to milk culture, at both the quarter and cow level, when using each of 3 different definitions of IMI as the referent test. Paired MLD test results were compared with evaluate repeatability. The MLD test showed excellent repeatability. The choice of definition of IMI from milk culture had minor effects on estimates of MLD and CMT test characteristics. For EL samples, when interpreting MLD and CMT results at the quarter level, and regardless of the referent test used, both tests had low sensitivity (MLD = 11.7-39.1%; CMT = 0-52.2%) but good to very good specificity (MLD = 82.1-95.2%; CMT = 68.1-100%), depending on the cut-point used. Sensitivity improved slightly if diagnosis was interpreted at the cow level (MLD = 25.6-56.4%; CMT = 0-72.2%), though specificity generally declined (MLD = 61.8-100%; CMT = 25.0-100%) depending on the cut-point used. For LL samples, when interpreted at the quarter level, both tests had variable sensitivity (MLD = 46.6-84.8%; CMT = 9.6-72.7%) and variable specificity (MLD = 59.2-79.8%; CMT = 52.5-97.3%), depending on the cut-point used. Test sensitivity improved if interpreted at the cow level (MLD = 59.6-86.4%; CMT = 19.1-86.4%), though specificity declined (MLD = 32.4-56.8%; CMT = 14.3-92.3%). Producers considering adopting either test for LL or EL screening programs will need to carefully consider the goals and priorities of the program (e.g., whether to prioritize test sensitivity or specificity) when deciding on the level of interpretation (quarter or cow) and when selecting the optimal cut-point for interpreting test results. Additional validation studies and large randomized field studies will be needed to evaluate the effect of adopting either test in selective dry cow therapy or fresh cow screening programs on udder health, antibiotic use, and economics.
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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 | 0,005 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 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 ».