Cohort-level disease prediction using aggregate biomarker data measured at dry-off in transition dairy cattle: A proof-of-concept study

Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level

A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS ≥ 3 and losing ≤ 0.5 (OR: 0.07-0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22-0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574-0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.

Weather conditions associated with death attributed to bovine respiratory disease complex in high-risk auction market-sourced male beef calves

OBJECTIVE

To evaluate associations between weather conditions and management factors with the incidence of death attributable to bovine respiratory disease complex (BRDC) in high-risk auction-sourced beef calves.

ANIMALS

Cohorts (n = 3,339) of male beef calves (545,866) purchased by 1 large cattle feeding operation from 216 locations and transported to 1 of 89 feeding locations (backgrounding location or feedlot) with similar management protocols.

PROCEDURES

Associations between weather conditions and management factors on the day of purchase (day P) and during the first week at the feeding location and cumulative BRDC mortality incidence within the first 60 days on feed were estimated in a mixed-effects negative binomial regression model.

RESULTS

Significant factors in the final model were weaning status; degree of commingling; body weight; transport distance; season; precipitation, mean wind speed, and maximum environmental temperature on day P; environmental temperature range in the first week after arrival at the feeding location; and interactions between distance and wind speed and between body weight and maximum environmental temperature. Precipitation and wind speed on day P were associated with lower cumulative BRDC mortality incidence, but wind speed was associated only among calves transported long distances (≥ 1,082.4 km). Higher mean maximum temperature on day P increased the incidence of cumulative mortality among calves with low body weights (< 275.5 kg).

CONCLUSIONS AND CLINICAL RELEVANCE

Several weather conditions on day P and during the first week after arrival were associated with incidence of BRDC mortality. The results may have implications for health- and economic-risk management, especially for high-risk calves and calves that are transported long distances.

Rumination time around dry-off relative to the development of diseases in early-lactation cows

Monitoring rumination time (RT) around the time of calving is an effective way of identifying cows at risk of disease in early lactation. However, this only allows for the identification of cows a few days before the onset of clinical signs; thus, effective preventive measures cannot be implemented. Recent research has suggested that biomarkers of immune and metabolic function measured at dry-off (DO) can predict higher disease risk in early lactation. Nevertheless, the extent to which RT around DO is associated with early-lactation disease risk remains unexplored. Thus, the objective of this study was to compare RT in the weeks before and after DO between cows that did and did not experience health disorders in early lactation. For this, we conducted an observational retrospective cohort study utilizing the records available from a large commercial dairy herd in which RT is recorded daily using an automated system. Daily RT from -7 to +14 d relative to DO from 2,258 DO cycles and their respective health records in the first 60 d in milk were used. Differences in RT between animals with and without a disease history were tested with the Student t-test with Bonferroni adjustment. Mixed linear regression analyses were performed to assess differences in RT around DO and the association of RT with the occurrence of mastitis, metritis, retained placenta, hyperketonemia, lameness, hypocalcemia, pneumonia, and displaced abomasum. Rumination time decreased abruptly at DO and remained lower for 3 to 4 d compared with the days before DO. On average, cows affected by hyperketonemia and lameness ruminated 9.83 ± 6.40 and 15.00 ± 6.08 min/d less than unaffected cows, respectively. Cows that developed lameness in the first 60 d in milk showed reduced RT from 1 to 3 d following DO compared with cows that were not diagnosed with lameness in early lactation. However, RT around DO was not associated with the occurrence of the other health disorders studied here. Our results demonstrate that DO is a stressful event for dairy cows resulting in decreased RT for several days. Furthermore, the association between RT around DO and some early-lactation diseases suggests that RT could be a useful tool to identify at-risk cows early enough to allow for preventive interventions. Further studies should investigate the diagnostic utility of incorporating RT data early in the dry period in the disease prediction algorithms of rumination sensors.

Serum retinol, β-carotene, and α-tocopherol as biomarkers for disease risk and milk production in periparturient dairy cows

The effectiveness of using serum vitamin concentrations as biomarkers to predict diseases in dairy cows during the periparturient period is not well known. The objective of this study was to evaluate the association between serum β-carotene, retinol, and α-tocopherol concentrations and periparturient cow diseases in commercial dairies. We measured serum concentrations of these vitamin-active compounds at dry-off and during close-up (approximately 3 wk before calving) and early lactation (approximately 7 d post-calving), and we examined their association with clinical diseases in the first 30 d in milk. Diseases were diagnosed by trained personnel and recorded using database software. Blood samples were taken from 353 cows from 5 different farms over a 3-yr period. Blood samples were analyzed for β-carotene, retinol, α-tocopherol, and cholesterol. We built separate mixed logistic regression models for each disease outcome: hyperketonuria, lameness, mastitis, uterine diseases (retained placenta or metritis), and an aggregate outcome. For the aggregate outcome, a cow was considered positive if she had one or more of the following: hyperketonuria, lameness, mastitis, uterine disease, pneumonia, milk fever, or displaced abomasum. Concentrations of all 3 fat-soluble vitamins decreased significantly in early lactation relative to the 2 prepartum sampling times. Serum retinol concentrations at close-up and early lactation were negatively associated with odds of developing postpartum hyperketonuria. At early lactation, cows with uterine disease had lower serum retinol concentrations than cows without uterine disease. Similarly, lower serum retinol concentrations were associated with greater odds of having any one disease in the aggregate outcome. First-test 305-d mature-equivalent milk yield was positively correlated with increased serum α-tocopherol and negatively correlated with β-carotene concentrations. This study demonstrates the potential for serum β-carotene, retinol, and α-tocopherol to serve as biomarkers for disease risk.

Recent advances and future directions for uterine diseases diagnosis, pathogenesis, and management in dairy cows

Researchers, veterinarians, and farmers' pursuit of a consistent diagnosis, treatment, and prevention of uterine diseases remains challenging. The diagnosis and treatment of metritis is inconsistent, a concerning situation when considered the global threat of antimicrobial resistance dissemination. Endometritis is an insidious disease absent on routine health programs in many dairy farms and from pharmaceutical therapeutics arsenal in places like the US market. Conversely, a multitude of studies advanced the understanding of how uterine diseases compromise oocyte, follicle, and embryo development, and the uterine environment having long-lasting effects on fertility. The field of uterine disease microbiome also experienced tremendous progress and created opportunities for the development of novel preventives to improve the management of uterine diseases. Activity monitors, biomarkers, genomic selection, and machine learning predictive models are other innovative developments that have been explored in recent years to help mitigate the negative impacts of uterine diseases. Albeit novel tools such as vaccines for metritis, immune modulators, probiotics, genomic selection, and selective antimicrobial therapy are promising, further research is warranted to implement these technologies in a systematic and cost-effective manner.