Evaluation of a novel dipotassium phosphate bolus for treatment of metabolic disorders in dairy cattle
Notice bibliographique
Résumé
A dipotassium phosphate bolus (K Phos-Boost) has been developed to treat both hypophosphatemia and hypokalemia, as the clinical signs of both conditions are similar and occur in the early post-partum period. The objective of this research was to evaluate the efficacy and application of the bolus for prevention and treatment of metabolic diseases that are common in dairy production systems. Study 1 (Pharmacokinetic study) : Healthy post-partum cows were either untreated or received two K Phos-Boost boluses at times 0, 24, and 48 h. Blood was taken at t = 0, 2-, 4-, 6-, 8-, 10-, 24-, and 52-h post-treatment for analysis of total serum minerals. There was an increase in serum phosphorous to normal levels within 2 h of treatment with the bolus, but control cows remained hypophosphatemic. Serum potassium was significantly elevated 2 h after bolus administration relative to control, while calcium, magnesium, sodium, and chloride levels were not affected by the K Phos-Boost bolus. Study 2 (Downer Cow Treatment) : K Phos-Boost boluses were provided to cows that were unresponsive to intravenous calcium therapy and had been unable to stand for over 24 h (“downer cows”). Most cows (16 of 19) treated with two boluses were standing without assistance between 1 and 24 h after treatment and the serum phosphorous was increased to normal levels in five of five tested animals. Study 3 (Ketosis Treatment) : cows with clinical ketosis were provided with propylene glycol and K Phos-Boost boluses ( n = 29) or only propylene glycol ( n = 23). Cows treated with the K Phos-Boost bolus showed a more rapid recovery by increased milk production (3.9 kg/day) and rumination rate (97 min/day). Study 4 (Health Promotion) : cows in herds with >40% post-partum hypophosphatemia received K Phos-Boost boluses ( n = 130) or no treatment ( n = 146) following calving. There was a trend for treated 2 nd -lactation animals to have higher milk production after 30 DIM (49.1 vs. 46.2 kg/day; P = 0.09). There were no significant differences between control and bolus treated animals in the incidence of subclinical ketosis, post-calving total health events, or culling rates. The K Phos-Boost bolus is a novel product and has the potential to treat and prevent several important metabolic diseases in dairy cattle. The studies described in this paper are early investigations and further research should be conducted to demonstrate the applications of a dipotassium phosphate bolus in dairy cows.
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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 | 0,002 |
| 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 ».