Impact of postpartum health disorders on metabolic status and reproductive performance of lactating dairy cows.

This study evaluated the impact of the presence of diseases within the first 21 days in milk (DIM) in dairy cows on metabolic status after the voluntary waiting period (VWP), conception at first service, infectious disease seroconversion, and the association between metabolic status at first artificial insemination (AI) and conception at first service. Cows were classified as sick (n = 48) or healthy (n = 75) based on diseases within 21 DIM. Blood samples were obtained at first AI (D0), pregnancy diagnosis (D30), and pregnancy confirmation (D60) after the first AI. Samples were analyzed for glucose, cholesterol, aspartate aminotransferase, alanine aminotransferase, non-esterified fatty acids (NEFA), and insulin-like growth factor 1 (IGF-1) using a linear mixed model for repeated measures. An Energetic Metabolic Index (EMI) at AI was calculated, integrating cholesterol, NEFA, and glucose. Logistic regression models were used to predict EMI, conception at first service, and seroconversion to Leptospira spp. and Bovine Viral Diarrhea Virus (BVDV). The presence of diseases did not affect the metabolic status after the VWP (P > 0.05); however, changes in blood metabolites by day were observed (P < 0.001). EMI was not associated with the presence of diseases (P = 0.13). EMI, IGF-1 concentration, and the presence of diseases were significant predictors of conception at first service (P ≤ 0.05). Sick cows were 37 times more likely to seroconvert to BVDV at D60 (P = 0.001). EMI at AI may serve as a valuable biological marker for predicting fertility. Simple summary: This study identifies the association between the presence of diseases within the first 21 days in milk in dairy cows and metabolic status after the voluntary waiting period, conception at first service, and the effect of metabolic status at first artificial insemination on conception. Integrating multiple metabolites into an Energetic Metabolic Index (EMI) may improve the prediction of fertility outcomes by better capturing complex metabolic responses than relying on insufficient single metabolite analyses. EMI and the presence of diseases were significant predictors of conception at first service. The EMI may serve as a potential biological marker for predicting fertility.