Understanding veterinary practitioners' decision-making process: implications for veterinary medical education

Understanding how veterinary practitioners make clinical decisions, and how they use scientific information to inform their decisions, is important to optimize animal care, client satisfaction, and veterinary education. We aimed to develop an understanding of private practitioners' process of decision making. On the basis of a grounded-theory qualitative approach, we conducted a telephone survey and semi-structured face-to-face interviews. We identified a decision-making framework consisting of two possible processes to make decisions, five steps in the management of a clinical case, and three influencing factors. To inform their decision, veterinary surgeons rarely take the evidence-based medicine (EBM) approach. They consult first-opinion colleagues, specialists, laboratories, and the Internet rather than scientific databases and peer-reviewed literature, mainly because of limited time. Most interviewees suggested the development of educational interventions to better develop decision-making skills in veterinary schools. Adequate information and EBM tools are needed to optimize the time spent in query and assessment of scientific information, and practitioners need to be trained in their use.     

The impact of badger removal on the control of tuberculosis in cattle herds in Ireland

In Ireland, the herd prevalence of bovine tuberculosis has remained stable for several decades, and in common with several other countries, progress towards eradication has stalled. There is evidence in support of the potential role of infected badgers (Meles meles, a protected species) in bovine tuberculosis in Ireland and Britain. However, this evidence on its own has not been sufficient to prove disease causation. Field trials are likely to offer the best opportunity to define this role. Building on the earlier East Offaly project, our objectives were to assess the impact of badger removal on the control of tuberculosis in cattle herds in Ireland.

The study was conducted from September 1997 to August 2002 in matched removal and reference areas (average area of 245.1 km²) in four counties: Cork, Donegal, Kilkenny and Monaghan. Badger removal was intensive and proactive throughout the study period in the removal areas, but reactive (in response to severe tuberculosis outbreaks in cattle) in the reference areas. Removal intensity in the removal and reference areas during the first 2 years of the study averaged 0.57 and 0.07 badgers/km²/year, respectively.

The outcome of interest was restriction of cattle herds due to confirmed tuberculosis, where tuberculous lesions were detected in one or more animals. Data were analysed using logistic regression (modelling the probability of a confirmed herd restriction) and survival analysis (modelling time to a confirmed herd restriction).

During the study period, there was a significant difference between the removal and reference areas in all four counties in both the probability of and the time to a confirmed herd restriction due to tuberculosis. In the final year of the study, the odds of a confirmed herd restriction in the removal (as compared to the reference areas) were 0.25 in Cork, 0.04 in Donegal, 0.26 in Kilkenny and 0.43 in Monaghan. Further, the hazard ratios (removal over reference) ranged from 0.4 to 0.04 (a 60–96% decrease in the rate at which herds were becoming the subject of a confirmed restriction).     

Development of an enzyme-linked immunosorbent assay for the detection of dicamba

A competitive indirect enzyme-linked immunosorbent assay (CI-ELISA) was developed to quantitate the herbicide dicamba (3,6-dichloro-2-methoxybenzoic acid) in water. The CI-ELISA has a detection limit of 2.3 microg L(-1) and a linear working range of 10--10000 microg L(-1) with an IC(50) value of 195 microg L(-1). The dicamba polyclonal antisera did not cross-react with a number of other herbicides tested but did cross-react with a dicamba metabolite, 5-hydroxydicamba, and structurally related chlorobenzoic acids. The assay was used to estimate quantitatively dicamba concentrations in water samples. Water samples were analyzed directly, and no sample preparation was required. To improve detection limits, a C(18) (reversed phase) column concentration step was devised prior to analysis, and the detection limits were increased by at least by 10-fold. After the sample preconcentration, the detection limit, IC(50), and linear working range were 0.23, 19.5, and 5-200 microg L(-1), respectively. The CI-ELISA estimations in water correlated well with those from gas chromatography-mass spectrometry (GC-MS) analysis (r(2) = 0.9991). This assay contributes to reducing laboratory costs associated with the conventional GC-MS residue analysis techniques for the quantitation of dicamba in water.     

The effect of ivermectin treatment of late pregnant dairy cows in south-west Victoria on subsequent milk production and reproductive performance

SUMMARY A total of 498 dairy cows in 5 predominantly pasture-fed herds were allocated to pairs. One cow in each pair was treated with a single dose of ivermectin during the dry period. Treated and untreated cows were managed as a single group throughout the trial. Most cows calved between 45 and 115 days after treatment. When data from all herds were pooled, treated cows produced an extra 74 L of milk over the first 100 days of the subsequent lactation (95% confidence interval 20 to 128). Means were greater among treated groups relative to untreated groups in all 5 herds. However, when analysed individually, differences were statistically significant (P < 0.05) in 1 herd only. Over the complete lactation, mean milk volume for treated cows was 86 L greater than for untreated cows (95% confidence interval of difference -57 to 229; P = 0.24). Untreated cows produced 2473 L and 5883 L for the first 100 days of lactation and for the complete lactation, respectively. Milk production responses to treatment did not vary significantly with parity, body condition score, previous production index, calving date category or with plasma pepsinogen concentration or faecal egg count at the time of treatment. Faecal egg counts and plasma pepsinogen concentrations were low at the start of the study. The interval from calving to conception was 4.8 days less in treated cows (95% confidence interval 1.2 to 8.2) relative to untreated cows when data from all 5 herds were pooled. Differences within individual herds were not statistically significant.     

Age‐related morphometric changes of the tidemark in the ovine stifle

Though the ovine stifle is commonly used to study osteoarthritis, there is limited information about the age‐related morphometric changes of the tidemark. The objective of this study was to document the number of tidemarks in the stifle of research sheep without clinical signs of osteoarthritis and of various ages (n = 80). Articular cartilage of the medial and lateral tibial condyles and of the medial and lateral femoral condyles was assessed by histology: (a) to count the number of tidemark; and (b) to assess the OARSI (Osteoarthritis Research Society International) score for structural changes of cartilage. The number of tidemarks varied between anatomical regions, respectively, from 4.2 in the medial femoral condyle to 5.0 in the lateral tibial condyle. The axial part showed a significant higher number of tidemarks than the abaxial part, for all regions except the medial tibial condyle. Whilst the tidemark count strongly correlated with age (Spearman's correlation coefficient = 0.70; 95% confidence interval (95% CI): 0.67–0.73; p < 0.0001), the OARSI score was weakly correlated with age in our cohort of sheep (Spearman's correlation coefficient = 0.25; 95% CI: 0.19–0.30; p < 0.0001). Interestingly, no tidemark was seen in the three animals aged 6 months. Our data indicate that the number of tidemarks increases with age and vary with anatomical region. The regional variation also revealed a higher number of tidemarks in the tibia than in the femur. This could be attributed to the local variation in cartilage response to strain and to the difference in chondrocyte biology and density.