Association of transition cow health with pregnancy per artificial insemination and pregnancy loss in Holstein cows submitted to a Double-Ovsynch protocol for first service
Notice bibliographique
Résumé
This observational study was conducted to evaluate the effect of transition cow health on pregnancy per artificial insemination (P/AI) and pregnancy loss (PL) in cows submitted to a Double-Ovsynch protocol (DO) for first service. Lactating Holstein cows (n = 15,041) from one commercial dairy farm in northern Germany between January 2015 to December 2021 were enrolled into a modified Double-Ovsynch protocol (GnRH, 7 d later PGF 2α , 3 d later GnRH, 7 d later GnRH, 7 d later PGF 2α , 24 h later PGF 2α , 32 h later GnRH, and 16 to 18 h later timed artificial insemination) for first service at 72 ± 3 d in milk. Pregnancy was diagnosed at 32 and 60 d post-AI via transrectal ultrasonography. Pregnancy loss was defined as the proportion of cows diagnosed pregnant 32 d post-artificial insemination that were diagnosed nonpregnant 60 d post-artificial insemination. Health-related events (i.e., milk fever [MF], hyperketonemia [KET], retained fetal membranes [RFM], metritis, mastitis, left displaced abomasum [LDA]) were assessed by farm personnel using standard operating procedures. Multivariable logistic regression was used for testing potential associations between transition cow health event occurrence and outcome variables, including P/AI and PL. Three separate models were built for cows in first lactation, second lactation, and ≥third lactation. Overall, 20.0% (885/4,430), 34.9% (1,391/3,989), and 53.9% (3,570/6,622) of cows had at least one transition cow health event for first, second, and ≥third lactations, respectively. The most prevalent transition cow health event for first-lactation cows was metritis (10.7%; [473/4,430]), whereas second-lactation cows suffered mostly from mastitis (16.6%; [664/3,989] and KET (16.6%; [661/3,989]), and cows with ≥third lactations were mostly affected by KET (33.2%; [2,198/6,622]). We observed a negative association between inflammatory disorders (i.e., RFM, metritis, mastitis) and P/AI in all cows irrespective of parity. Metabolic disorders (i.e., MF, KET, LDA) were negatively associated with P/AI only in multiparous cows. Irrespective of parity, only uterine diseases (i.e., RFM, metritis) were significantly associated with PL. These results show that enrolling cows into a fertility protocol, such as DO, cannot overcome the carryover effects of inflammatory and metabolic disorders on P/AI and PL and highlight the importance of optimizing transition cow health as a prerequisite for achieving high fertility in a DO protocol.
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 | 0,001 | 0,002 |
| 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) | 0,001 | 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 ».