Comparison and interobserver reliability between a visual analog scale and the Wisconsin Calf Health Scoring Chart for detection of respiratory disease in dairy calves.

Respiratory disease is an ongoing challenge for calves in the dairy sector with a relatively high prevalence and impact on welfare and economics. Applying scoring protocols for detecting respiratory disease requires that they are easily implemented, consistent between observers and fast to use in daily management. This study was conducted in one Danish dairy farm from September 2020 through January 2021. The study included 126 heifer calves enrolled in the age of 17 to 24 d. All calves were observed every second day for a period of 46 d. At each visit all calves were scored with a new visual analog scale (VAS) and the Wisconsin Calf Health Scoring Chart (WCHSC). We calculated agreement between the 2 scoring systems based on conditional probability to score higher or lower than a cutoff in the VAS compared with a specified cutoff in WCHSC used as reference test. A generalized mixed effects regression model was developed to estimate the prevalence of respiratory disease and the overall agreement between the 2 scoring systems. The overall agreement between the VAS and WCHSC was 89.6%. The second part of the study assessed interobserver reliability between 2 experienced observers and between an experienced observer and veterinary students. The interobserver reliability was calculated by intraclass correlation coefficient and was 0.58 between experienced observers and was 0.34 between an experienced observer and veterinary students indicating a moderate to poor reliability between the observers. It was possible to use VAS as an alternative clinical scoring method, which primarily focuses on the general condition of the individual calf rather than specific categories of clinical signs. Our study set up lacked a comparison to other diagnostic tools i.e., thoracic ultrasound to confirm the findings which should be considered in future studies when exploring VAS as a screening tool for detection of respiratory disease in dairy calves.

Retrospective cohort study of management procedures associated with dairy herd-level eradication of Streptococcus agalactiae in the Danish surveillance program.

The aim of this observational retrospective cohort study was to identify management procedures that are associated with herd-level eradication of Streptococcus agalactiae in dairy herds. The objective was to compare herds that recovered from Strep. agalactiae with herds that remained infected with Strep. agalactiae on the basis of specific management procedures. Data from the Danish surveillance program for Strep. agalactiae, where all milk delivering dairy herds are tested yearly, were used to identify study herds. One hundred ninety-six herds that were classified in the program as infected with Strep. agalactiae, in both January 2013 and January 2014, were identified as study herds. These were followed until January 2017. One hundred forty-four herds remained infected every year until January 2017. Forty-six herds recovered from Strep. agalactiae after January 2014 (were tested negative continuously after January 2015, January 2016, or January 2017 and remained noninfected in the program from recovery until January 2017). Herd characteristics and management procedures were obtained through the Danish Cattle Database. Herd characteristics included herd size, yield, milking system, and bulk milk somatic cell count (SCC). Management procedures included the proportion of cows culled within 100 d after calving due to mastitis, the extent of diagnoses relative to the extent of mastitis treatments, the proportion of cows treated for mastitis during lactation, the proportion of cows treated for mastitis early in lactation, the proportion of cows treated at dry-off, and the median length of the dry period for cows receiving dry cow treatment. All variables were calculated on herd level. Multivariable logistic regression was used to analyze the association between herd infection status and management procedures. A higher proportion of culling due to mastitis within 100 d from calving was associated with a higher probability of herd-level recovery from Strep. agalactiae in herds with conventional milking system. For example, herds with conventional milking, a bulk milk SCC of 260,000 cells/mL, and 10% early culling due to mastitis had a recovery probability of 0.13, whereas similar herds with 20% early culling due to mastitis had a recovery probability of 0.15. A higher proportion of mastitis treatments within 250 d postcalving was associated with a higher probability of herd-level recovery for herds with a relatively high bulk milk SCC. For example, herds with conventional milking, a bulk milk SCC of 260,000 cells/mL, and 10% lactational mastitis treatments had a recovery probability of 0.12, whereas similar herds with 20% lactational mastitis treatments had a recovery probability of 0.15. Herds with a low bulk milk SCC (<220,000 cells/mL) combined with a low proportion of lactational treatments (<0.2) had a relatively high probability of herd-level recovery (>0.2). Additional variables, including the proportion of dry cow treatments, were not associated with herd-level recovery from Strep. agalactiae.

Economic value of information from an alert system on physiological imbalance in fresh cows.

Physiological imbalance is an abnormal physiological condition that cannot be directly observed but is assumed to precede subclinical and clinical diseases in the beginning of lactation. Alert systems to detect the physiological imbalance in a cow using Fourier transform mid-infrared spectroscopy in milk have been developed. The objective of this study was to estimate the value of information provided from such system with different indicator accuracies, herd prevalence and prices. A decision tree was created to model the probabilities of detection and associated costs of test outcome, intervention and occurrence of disease. We assumed that the negative effect of physiological imbalance was the development of subclinical ketosis and that this negative effect was prevented by drenching the cows with propylene glycol for 5 days. We simulated the economic impact of subclinical ketosis mediated through physiological imbalance to be $194 per case. The results showed that if the alert system was highly accurate (Se = 0.99/Sp = 0.99), and the prevalence of physiological imbalance was 30 %, the value of information provided from the system is $19 per cow-year. In case the prevalence is 5 % or 50 %, the value of information is $3 and $13, respectively. These estimates for the value do not cover the capital costs and operational costs of the alert system. This study furthermore clearly demonstrated that in order to estimate the value of information correctly, it is important to consider that drenching all cows and not drenching any of the cows are the two relevant alternative options in the absence of the alert system. In conclusion, the decision tree and sensitivity analysis developed in this study show that final economic results are highly variable to the prevalence of physiological imbalance and highest at an intermediate prevalence. Other relevant factors are the costs associated with drenching and the cost associated with treating false positives and not treating false negatives. In addition, this study highlights the benefits of simulation to pinpoint where additional information is needed to further quantify the economic value and required accuracy of an indication-based intervention system.

Predicting physiological imbalance in Holstein dairy cows by three different sets of milk biomarkers.

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, ß-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and "intermediate cows" with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1-50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R2cv) and root mean squared error (RMSEcv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R2cv = 0.40 (95 % CI: 0.29-0.50) at 14 DIM and 0.35 (0.23-0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R2cv = 0.28 (0.24-0.33) vs 0.21 (0.18-0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95 % CI: 0.39-0.68) to 0.65 (0.55-0.75) for MME and 0.51 (0.37-0.65) to 0.68 (0.53-0.81) for FT-MIR. R2cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted.

Effect of automatic cluster flushing on the concentration of Staphylococcus aureus in teat cup liners.

Automatic flushing of milking clusters between milking events is a control measure aimed at reducing transmission of mastitis pathogens from infectious milk to a subsequently milked cow. We evaluated the effect of flushing with cold water and flushing with water containing peracetic acid (PAA) on the concentration of Staphylococcus aureus in teat cup liners. Thirty-two clusters in a swing-over milking parlor (Dairymaster, Causeway, Ireland) were subjected to a simulated milking with S. aureus-contaminated milk. Sixteen clusters were not flushed (controls), whereas 8 clusters were flushed with cold water (966 ± 32 mL) and 8 clusters were flushed with water containing PAA (200 mL/mL). A random teat cup in each cluster was sampled by rinsing with a phosphate buffer. Teat cup samples were cultured on the day following collection on Baird-Parker plates to determine the concentration of S. aureus. In teat cup samples from control clusters, the mean concentration of S. aureus was 2.8 × 105 cfu/mL. The concentration of S. aureus was zero in teat cup samples from clusters flushed with cold water. In teat cup samples from clusters flushed with water containing PAA, the concentration of S. aureus was in general reduced compared with control clusters, but S. aureus was not removed completely. However, the automatic cluster flushing did not function properly when clusters were flushed with water containing PAA; thus, results reflected the effect of inadequate function rather than the effect of adding disinfectant to the flushing water. Before the main study, we conducted a pilot study to evaluate whether teat cup sampling with swabs and sample analysis with quantitative PCR were appropriate methods for the main study. Specifically, we evaluated the effect of swab sample mass on detection of S. aureus by quantitative PCR in the laboratory, Further, we compared PCR and bacterial culture on detection of S. aureus in a suspension following disinfection of the suspension with PAA. We sampled 20 identical S. aureus suspensions for culture and PCR by swabs before and after disinfection with PAA. Swab sample mass was determined by differential weighing and contributed to 46% of the variation observed in detection of S. aureus by PCR. Following disinfection with PAA, S. aureus remained detectable by PCR, although culturability ceased. Based on these results, we sampled teat cups in the main study with a buffer rinse and quantified S. aureus in the samples by bacterial culture. We concluded that automatic cluster flushing with cold water was effective in removing S. aureus from teat cup liners and that addition of PAA was therefore not necessary.

A quantitative screening method to detect rater-introduced bias in clinical ratings.

BACKGROUND: We suggest a 'screening test' to examine large data files with clinical ratings for the occurrence of rater-introduced bias prior to using the data for quantitative analyses. The test is based on a statistical model in which a well-standardized interval-scale outcome (for example, milk yield) is related to clinical ratings (for example, body condition scores) obtained from multiple contexts (for example, dairy herds). FINDINGS: 84,968 calvings from 279 herds, with subsequent body condition scores performed by 117 veterinarians within the first 21 days postpartum were analyzed with a multilevel random coefficient regression model. The model included an independent variable, where body condition score was centered within veterinarian. This is a so-called comparison effect to describe possible rater-introduced bias in the body condition scores. A highly significant comparison effect was found for second and older parities, indicating occurrence of possible rater-introduced bias in this large multi-herd data file. CONCLUSIONS: A within-group centering technique (the comparison effect) appeared to be useful for discriminating between biased and unbiased clinical scores. In some cases, this test for bias should prevent further analysis of the data and divert the focus of study to the calibration of raters or alternative study designs.