Technical note: Validation of an automated in-line milk progesterone analysis system to diagnose pregnancy in dairy cattle
Notice bibliographique
Résumé
The in-line milk analysis system (IMAS) is an automated biosensor technology that samples and quantifies milk progesterone concentrations (P4c) at frequent intervals starting early postpartum until pregnancy. The objective was to validate the use of pregnancy notifications (PregN) generated by an IMAS based on P4c profiles after artificial insemination (AI) to determine pregnancy and nonpregnancy status in dairy cows. Records of 1,821 AI events from 715 Holstein cows that had milk P4c (ng/mL) measured every 2.2 ± 1.9 d (mean ± standard deviation) between 24.5 ± 8.2 and 173.4 ± 49.3 d in milk through a real-time IMAS (Herd Navigator, DeLaval International, Tumba, Sweden) were evaluated. Based on variations in adjusted milk P4c (< vs. ≥ the 5.0 ng/mL threshold), the system determined the sampling frequency, onset and cessation of luteal phases, and pregnancy. If a luteal phase initiated (P4c increased to ≥5.0 ng/mL) after AI and remained uninterrupted, a PregN was generated starting at (mean ± standard deviation) 31.0 ± 4.3 d until 53.4 ± 7.9 d after AI, when sampling stopped, unless a decline in P4c (to <5.0 ng/mL) occurred indicating nonpregnancy and imminent estrus. The assessment of IMAS PregN at 4 weekly intervals was tested, and a confirmed calving occurrence between 262 and 296 d after AI, with no other subsequent AI recorded, was the gold standard for pregnancy. In total, 14.1 (256/1,821), 41.0 (746/1,821), and 50.7% (924/1,821) of AI events were followed by a decline in P4c before 19, 23, and 30 d after AI, respectively. Frequency of the last 3 sampling events preceding P4c decline was greater if P4c decline occurred between 18 and 25 d after AI (1.4 ± 0.5 samples per day) compared with before 17 or beyond 26 d after AI (1.0 ± 0.5 samples per day). At 30 ± 3 (27 to 33) d after AI, PregN occurred in 46.8% (853/1,821) of AI events, of which 15.2% (130/853) had a decline in P4c between 30 and 55 d after AI and 17.1% (146/853) was later confirmed nonpregnant based on the gold standard. A total of 40.7% (742/1,821) of AI events was confirmed pregnant by the gold standard, which was no different than the proportion of PregN at 51 ± 3 (48 to 54) d (40.9%; 744/1,821). At any time point between 27 and 54 d after AI, sensitivity and negative predictive values for PregN were greater than 95.0 and 96.0%, respectively, whereas specificity values were less than 90.0% for PregN before 40 d but greater than 94.0% for PregN beyond 41 d after AI. In conclusion, IMAS is able to diagnose pregnancy based on P4c profiles with high precision and determine early nonpregnancy based on the spontaneous cessation of the luteal phase. However, for accuracy greater than 95.0%, pregnancy declaration based on IMAS notifications alone should occur no earlier than 41 d after AI.
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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 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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 ».