Early Milk Total and Differential Cell Counts as a Diagnostic Tool to Improve Antimicrobial Therapy Protocols
Articolo
Data di Pubblicazione:
2023
Citazione:
Early Milk Total and Differential Cell Counts as a Diagnostic Tool to Improve Antimicrobial Therapy Protocols / A. Zecconi, F. Zaghen, G. Meroni, V. Sora, P.A. Martino, G. Laterza, L. Zanini. - In: ANIMALS. - ISSN 2076-2615. - 13:7(2023 Mar), pp. 1143.1-1143.11. [10.3390/ani13071143]
Abstract:
Mastitis is a major cause of antimicrobial treatments either during lactation or at drying off.
From a One Health perspective, there should be a balance between the risk of IMI that may impair
cow health and welfare and the reduction of antimicrobial usage to decrease antimicrobial resistance,
as may happen when applying selective dry-cow therapy. This reduction may be achieved by an
early and accurate diagnosis followed by prudent and rationale therapeutical protocols. This study
aims to assess the accuracy of PLCC (neutrophils + lymphocyte count/mL) in identifying cows at risk
of having IMI due to major pathogens (S.aureus, Str.agalactiae, Str.uberis, and Str.dysgalactiae), and to
simulate the impact of this early diagnosis on the potential number of treatments using a decision-tree
model. The results of this study showed that PLCC had an overall accuracy of 77.6%. The results of
the decision-tree model based on data from the 12 participating herds, with an overall prevalence
of major pathogens of 1.5%, showed a potential decrease in the number of treatments of about 30%
(from 3.4% to 2.5%) when PLCC in early lactation (days 5–16) was used to identify cows at risk for
major pathogens compared with using SCC at the first milk test (days 17–43). The study confirmed
that it is possible to improve animal health and reduce the risk of antimicrobial use through early IMI
detection based on PLCC and applying a rationale and prudent antimicrobial protocol.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
mastitis; antimicrobial resistance; One Health; early diagnosis; differential cell count; dry-cow therap
Elenco autori:
A. Zecconi, F. Zaghen, G. Meroni, V. Sora, P.A. Martino, G. Laterza, L. Zanini
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