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ABSTRACT: Targeted reproductive management (TRM) aims to improve the fertility efficiency of the dairy herd by applying group-level management strategies based on expected reproductive performance. Key to the utility of TRM is the accuracy with which an animal's reproductive performance can be predicted. Automatic milking systems (AMS) allow for the collection of data relating to milk quantity, quality, and robot visit behavior throughout the transition period. In addition to this, auxiliary data sources, such as rumination and activity monitors, as well as historical cow-level data, are often readily available. The utility of this data for the prediction of fertility has not been previously explored. The first objective of this study was to assess the accuracy with which the likelihood of expression of estrus between 22 and 65 DIM and conception to first insemination between 22 and 80 DIM could be predicted using data collected by AMS from 1 to 21 DIM. Our second objective was to assess the change in model performance following the addition of 2 auxiliary data sources. Using data derived solely from the AMS (RBT dataset) a binary random forest classification model was constructed for both outcomes of interest. The performance of these models was compared with models constructed using AMS data in conjunction with 2 auxiliary sources (RBT+ dataset). Expression of estrus was classified with an area under the receiver operator curve (AUC-ROC) of 0.6 and 0.65, conception to first insemination with an AUC-ROC of 0.56 and 0.62 for the RBT and RBT+ datasets, respectively. No statistically significant improvement in classification accuracy was achieved by the addition of auxiliary data sources. This is the first study to report the utility of data collected by AMS for the prediction of reproductive performance. Though the performance described is comparable with previously reported models, their utility for the implementation of TRM is limited by poor classification accuracy within key subgroups. Of note within this study is the failure of the addition of auxiliary data sources to increase the accuracy of prediction over models built using AMS data alone. We discuss the advantages and limitations the integration of additional data sources imposes on model training and deployment and suggest alternative methods to improve performance while preserving model parsimony.

ABSTRACT: Neonatal calves are relatively susceptible to heat loss, and previous research suggests that reduced environmental temperatures are associated with reduced average daily gain (ADG) during the preweaning phase. Current methods of mitigating negative effects of colder environmental conditions include the use of calf jackets and the provision of supplementary heat sources; however, previous research is limited. The aim of this study was to evaluate the effect of calf jackets and 1-kW heat lamps on the growth rates of preweaning calves and evaluate associations between environmental temperature and ADG using a Bayesian approach to incorporate both current and previous data. Seventy-nine calves from a single British dairy farm were randomly allocated at birth to 1 of the following 4 groups: no jacket and no heat lamp, heat lamp but no jacket, jacket but no heat lamp, or both heat lamp and jacket between January and April of 2021. Calves were weighed at both birth and at approximately 21 d of age. Temperature was recorded both inside and outside of the calf building, and in pens both with and without heat lamps using data loggers. To explore the effect of treatment group and environmental temperature on ADG, a fixed effects model was fitted over 1,000 bootstrap samples. The effect of environmental temperature on ADG was further explored within a Bayesian framework that used temperature and ADG data for 484 calves from 16 farms available from a previous trial as prior information. Calves housed under a 1-kW heat lamp had an increased ADG of 0.09 kg/d (95% bootstrap confidence interval: −0.02 to 0.20 kg/d), and no effect of jacket or interactions between jacket and heat lamp were found. A significant positive association was identified between the mean environmental temperature of the calf building and ADG, with a 1°C increase in temperature being associated with a 0.03 kg/d increase in ADG (95% bootstrap confidence interval: 0.01 to 0.04 kg/d). Associations between environmental temperature and ADG were further evaluated within a Bayesian framework, and posterior estimates were 0.014 kg/d of ADG per 1°C increase (95% credible interval: 0.009 to 0.021 kg/d). This study demonstrated that a 1-kW heat lamp was effective in increasing ADG in calves, and no significant effect of calf jacket on ADG was found. A significant, positive effect of increased pen temperature on calf ADG was identified in this study and was reinforced when including prior information from previous research within a Bayesian framework.

ABSTRACT: Previous research has identified key factors associated with improved average daily gain (ADG) in preweaning dairy calves and these factors have been combined to create a web app–based calf health plan (www.nottingham.ac.uk/herdhealthtoolkit). A randomized controlled trial was conducted to determine the effect of implementing this evidence-based calf health plan on both productivity and health outcomes for calves reared on British dairy farms. Sixty dairy farms were randomized by location (North, South, and Midlands) to either receive the plan at the beginning (INT) or after the end of the trial (CON) and recorded birth and weaning weights by weigh tape, and cases of morbidity and mortality. Calf records were returned for 3,593 calves from 45 farms (21 CON, 24 INT), with 1,760 calves from 43 farms having 2 weights recorded >40 d apart for ADG calculations, with 1,871 calves from 43 farms born >90 d before the end of the trial for morbidity and mortality calculations. Associations between both intervention group and the number of interventions in place with ADG were analyzed using linear regression models. Morbidity and mortality rates were analyzed using beta regression models. Mean ADG was 0.78 kg/d, ranging from 0.33 to 1.13 kg/d, with mean rates of 20.12% (0–96.55%), 16.40% (0–95.24%), and 4.28% (0–18.75%) for diarrhea, pneumonia, and mortality. The INT farms were undertaking a greater number of interventions (9.9) by the end of the trial than CON farms (7.6). Mean farm ADG was higher for calves on INT farms than CON farms for both male beef (MB, +0.22 kg/d) and dairy heifer (DH, +0.03 kg/d) calves. The MB calves on INT farms had significantly increased mean ADG (0.12 kg/d, 95% confidence interval: 0.02–0.22) compared with CON farms. No significant differences were observed between intervention groups for morbidity or mortality. Implementing one additional intervention from the plan, regardless of intervention group, was associated with improvements in mean ADG for DH calves of 0.01 kg/d (0.01, 0–0.03) and MB calves of 0.02 kg/d (0.00–0.04). Model predictions suggest that a farm with the highest number of interventions in place (15) compared with farms with the lowest number of interventions in place (4) would expect an improvement in growth rates from 0.65 to 0.81 kg/d for MB, from 0.73 to 0.88 kg/d for DH, a decrease in mortality rates from 10.9% to 2.8% in MB, and a decrease in diarrhea rates from 42.1% to 15.1% in DH. The calf health plan tested in this study represents a useful tool to aid veterinarians and farmers in the implementation of effective management interventions likely to improve the growth rates, health, and welfare of preweaning calves on dairy farms.

Waste from dairy production is one of the largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs) in many parts of the world. However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with > 99 % reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for measurement and control of AMR, and that actions to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

PurposeTauopathy and transactive response DNA binding protein 43 (TDP-43) proteinopathy are associated with neurodegenerative diseases. These proteinopathies are difficult to detect in vivo. This study examined if spectral-domain optical coherence tomography (SD-OCT) can differentiate in vivo the difference in peripapillary retinal nerve fibre layer (pRNFL) thickness and macular retinal thickness between participants with presumed tauopathy (progressive supranuclear palsy) and those with presumed TDP-43 proteinopathy (amyotrophic lateral sclerosis and semantic variant primary progressive aphasia).Study designProspective, multi-centre, observational study.Materials and methodspRNFL and macular SD-OCT images were acquired in both eyes of each participant using Heidelberg Spectralis SD-OCT. Global and pRNFL thickness in 6 sectors were analyzed, as well as macular thickness in a central 1 mm diameter zone and 4 surrounding sectors. Linear mixed model methods adjusting for baseline differences between groups were used to compare the two groups with respect to pRNFL and macular thickness.ResultsA significant difference was found in mean pRNFL thickness between groups, with the TDP-43 group (n = 28 eyes) having a significantly thinner pRNFL in the temporal sector than the tauopathy group (n = 9 eyes; mean difference = 15.46 μm, SE = 6.98, p = 0.046), which was not significant after adjusting for multiple comparisons. No other significant differences were found between groups for pRNFL or macular thickness.ConclusionThe finding that the temporal pRNFL in the TDP-43 group was on average 15.46 μm thinner could potentially have clinical significance. Future work with larger sample sizes, longitudinal studies, and at the level of retinal sublayers will help to determine the utility of SD-OCT to differentiate between these two proteinopathies.

Pain is a significant welfare concern within the dairy industry. Recognizing and managing pain are important factors for safeguarding animal welfare. A questionnaire was sent via post to Irish dairy farmers and large animal veterinarians to assess attitudes to pain and the use of non-steroidal anti-inflammatory drugs (NSAIDs) in pasture-based dairy cows. The questionnaire could also be completed online. A total of 1,002 surveys were received from dairy farmers and 116 from livestock veterinarians. Veterinarians and farmers generally perceived the same conditions and procedures as the most painful. However, farmers scored surgical procedures significantly higher than veterinarians, and veterinarians scored lameness-related conditions, mastitis (clots in milk only) and hock hair loss significantly higher than farmers. Higher pain scores for conditions and procedures given by dairy farmers and veterinarians were associated with increased NSAID use. However, the use of NSAIDs was low, relative to the pain score, for Burdizzo castration (farmers and veterinarians), white line separation (farmers and veterinarians) and abscess (veterinarians), mastitis with clots in milk only (farmers) and calving with no assistance (farmers). Veterinarians who graduated less recently had significantly lower odds of using NSAIDs, and farmers that completed the survey online, had a larger herd size, completed education up to level four or five (as opposed to level three) and those who seemed to have less knowledge on analgesics, had significantly lower odds of using NSAIDs. Empathy was not found to be associated with NSAID use and no correlation was found between pain and empathy scores. Veterinarians perceived cost as more of a barrier than farmers did; therefore, NSAIDs should be offered more readily. For those working with dairy cows, there is a need to continue education on the benefits of analgesia, especially for conditions and procedures that have low NSAID use relative to pain score. The habituation of humans to pain in animals needs to be prevented to enable pain to be recognized and managed appropriately. Pain scores can be used as a benchmark for veterinarians and farmers to determine how their perception of pain compares to others, and see how this may influence their NSAID use.

Despite the wide application of the magnetic resonance imaging (MRI) technique, there are no widely used standards on naming and describing MRI sequences. The absence of consistent naming conventions presents a major challenge in automating image processing since most MRI software require a priori knowledge of the type of the MRI sequences to be processed. This issue becomes increasingly critical with the current efforts toward open-sharing of MRI data in the neuroscience community. This manuscript reports an MRI sequence detection method using imaging metadata and a supervised machine learning technique. Three datasets from the Brain Center for Ontario Data Exploration (Brain-CODE) data platform, each involving MRI data from multiple research institutes, are used to build and test our model. The preliminary results show that a random forest model can be trained to accurately identify MRI sequence types, and to recognize MRI scans that do not belong to any of the known sequence types. Therefore the proposed approach can be used to automate processing of MRI data that involves a large number of variations in sequence names, and to help standardize sequence naming in ongoing data collections. This study highlights the potential of the machine learning approaches in helping manage health data.

Research suggests that many sheep farmers continue to carry out traditional antibiotic use practices despite new 'good practice' recommendations. The aim of this study was to group farmers depending on their attitudes around antibiotic use and antibiotic resistance, and determine the behaviours that are associated with the farmers in these groups. In 2017, a flock health survey was sent to British sheep farmers. K-means cluster analysis was used to identify groups of farmers with similar attitudes towards antibiotic use and resistance. A multivariable logistic regression model was built to determine the associations between farmers' past behaviours and their antibiotic attitude group. There were 461 responses. Two groups of farmers were identified based on their antibiotic attitudes. Cluster 1 were defined as the "discordant" group who had positive views of using antibiotics prophylactically and negative views of reducing antibiotic use. Cluster 2 were defined as the "concordant" group who were positive about reducing antibiotic use and had negative views about using antibiotics prophylactically. Using antibiotics in all lambs (OR = 2.689, CI = 1.571, 4.603), using antibiotics in all ewes (OR = 3.388, CI = 1.318, 8.706), always trimming diseased feet over the past three years (OR = 2.487, CI = 1.459, 4.238), not using a computer to record information over the past three years (OR = 1.996, CI = 1.179, 3.381), not changing worming practices over the past three years (OR = 1.879, CI = 1.144, 3.087), and farmers' perceptions that their sheep flock did not make a financial loss in the past three years (OR = 2.088, CI = 1.079, 4.040) were significantly associated with belonging to the discordant group. Talking to their veterinarian about antibiotic use or the frequency of veterinary visits were not associated with antibiotic attitude group. These results suggest that farmers who had attitudes relating to antibiotic use that did not align with current recommendations carried out more traditional practices, which were strengthened by their positive perceptions of profitability.

Total bacterial counts (TBC) and coliform counts (CC) were estimated for 328 colostrum samples from 56 British dairy farms. Samples collected directly from cows' teats had lower mean TBC (32,079) and CC (21) than those collected from both colostrum collection buckets (TBC: 327,879, CC: 13,294) and feeding equipment (TBC: 439,438, CC: 17,859). Mixed effects models were built using an automated backwards stepwise process in conjunction with repeated bootstrap sampling to provide robust estimates of both effect size and 95% bootstrap confidence intervals (BCI) as well as an estimate of the reproducibility of a variable effect within a target population (stability). Colostrum collected using parlor (2.06 log cfu/ml, 95% BCI: 0.35–3.71) or robot (3.38 log cfu/ml, 95% BCI: 1.29–5.80) milking systems, and samples collected from feeding equipment (2.36 log cfu/ml, 95% BCI: 0.77–5.45) were associated with higher TBC than those collected from the teat, suggesting interventions to reduce bacterial contamination should focus on the hygiene of collection and feeding equipment. The use of hot water to clean feeding equipment (−2.54 log cfu/ml, 95% BCI: −3.76 to −1.74) was associated with reductions in TBC, and the use of peracetic acid (−2.04 log cfu/ml, 95% BCI: −3.49 to −0.56) or hypochlorite (−1.60 log cfu/ml, 95% BCI: −3.01 to 0.27) to clean collection equipment was associated with reductions in TBC compared with water. Cleaning collection equipment less frequently than every use (1.75 log cfu/ml, 95% BCI: 1.30–2.49) was associated with increased TBC, the use of pre-milking teat disinfection prior to colostrum collection (−1.85 log cfu/ml, 95% BCI: −3.39 to 2.23) and the pasteurization of colostrum (−3.79 log cfu/ml, 95% BCI: −5.87 to −2.93) were associated with reduced TBC. Colostrum collection protocols should include the cleaning of colostrum collection and feeding equipment after every use with hot water as opposed to cold water, and hypochlorite or peracetic acid as opposed to water or parlor wash. Cows' teats should be prepared with a pre-milking teat disinfectant and wiped with a clean, dry paper towel prior to colostrum collection, and colostrum should be pasteurized where possible.

Antibiotic resistance is one of the most serious public health risks facing humanity. The overuse of antibiotics in the treatment of infectious disease have been identified as sources of the global threat of antibiotic resistance. This paper examines how farmers perceive and manage risks associated with overuse of antibiotics. Specifically, the paper examines the role of habitus and risk in determining farmers' decisions to adopt national antibiotic reduction targets set by members of the Responsible Use of Medicines in Agriculture Alliance's Targets Task Force. Semi-structured interviews were conducted with 34 sheep and beef farmers in England and Wales. Farmers presented four scripts which illuminated reasons for limited adoption of the targets. The scripts presented the farmers as “good farmers” facing an emerging threat to their ontological security. Scripts suggested that they engaged in preventative measures but deflected responsibility for reducing antibiotic resistance to veterinarians and poorly run farms. This research provides valuable insights for policy makers and highlight the benefits of including social science research to support effective implementation.

Abstract Introduction We propose a minimum data set framework for the acquisition and analysis of retinal images for the development of retinal Alzheimer's disease (AD) biomarkers. Our goal is to describe methodology that will increase concordance across laboratories, so that the broader research community is able to cross‐validate findings in parallel, accumulate large databases with normative data across the cognitive aging spectrum, and progress the application of this technology from the discovery stage to the validation stage in the search for sensitive and specific retinal biomarkers in AD. Methods The proposed minimum data set framework is based on the Atlas of Retinal Imaging Study (ARIAS), an ongoing, longitudinal, multi‐site observational cohort study. However, the ARIAS protocol has been edited and refined with the expertise of all co‐authors, representing 16 institutions, and research groups from three countries, as a first step to address a pressing need identified by experts in neuroscience, neurology, optometry, and ophthalmology at the Retinal Imaging in Alzheimer's Disease (RIAD) conference, convened by the Alzheimer's Association and held in Washington, DC, in May 2019. Results Our framework delineates specific imaging protocols and methods of analysis for imaging structural changes in retinal neuronal layers, with optional add‐on procedures of fundus autofluorescence to examine beta‐amyloid accumulation and optical coherence tomography angiography to examine AD‐related changes in the retinal vasculature. Discussion This minimum data set represents a first step toward the standardization of retinal imaging data acquisition and analysis in cognitive aging and AD. A standardized approach is essential to move from discovery to validation, and to examine which retinal AD biomarkers may be more sensitive and specific for the different stages of the disease severity spectrum. This approach has worked for other biomarkers in the AD field, such as magnetic resonance imaging; amyloid positron emission tomography; and, more recently, blood proteomics. Potential context of use for retinal AD biomarkers is discussed.

Chronic Lymphocytic Leukaemia (CLL) is associated with immune suppression and susceptibility to infection. CD8+ T cell numbers are increased and demonstrate elevated expression of PD-1 and impaired function. The mechanisms driving these features of exhaustion are uncertain but are likely to include chronic immune recognition of tumor and/or infectious agents. We investigated the number, phenotype and function of total and virus-specific CD8+ T cells in 65 patients with CLL and 14 patients undergoing long-term ibrutinib therapy (median 21 months). Ibrutinib substantially reduced the number of both CD3+ T cells and CD8+ T cells. Importantly, this was associated with a reduction in PD-1 expression on CD8+ T cells (median 28 vs. 24%; p = 0.042) and 3.5 fold increase in cytokine production following mitogen stimulation. The influence of ibrutinib on antigen-specific CD8+ T cell function was assessed by HLA-peptide tetramers and revealed increased IFNγ and TNFα cytokine responses following stimulation with CMV or EBV peptides together with a 55% reduction in the frequency of “inflated” virus-specific CD8+ T cells. These findings reveal that long-term ibrutinib therapy is associated with substantial reversal of T cell exhaustion in B-CLL and is likely to contribute to the reduced infection risk seen in association with this agent.

As a quality improvement tool, clinical audit has been extensively described in the medical literature. There is scant literature on the use of clinical audit in the farm animal veterinary setting. This study describes the process and feasibility of prospective and retrospective data collection for farm animal clinical audit performed at three different farm animal practices in the United Kingdom. Retrospective clinical audit was difficult in all three practices due to barriers in establishing diagnosis and patient identity from clinical records. Prospective data collection proved feasible but depended on adequate case accrual and practitioner engagement. The decision to conduct clinical audit retrospectively or prospectively will depend on the topic to audit, the availability of data and the wishes of the team members involved. Further work is required looking at the use of clinical coding and alternatives to using practice management software to improve retrospective data availability for clinical audit.

BackgroundWithout an effective vaccine, as was the case early in the 2014-2016 Ebola Outbreak in West Africa, disease control depends entirely on interrupting transmission through early disease detection and prompt patient isolation. Lateral Flow Immunoassays (LFI) are a potential supplement to centralized reference laboratory testing for the early diagnosis of Ebola Virus Disease (EVD). The goal of this study was to assess the performance of commercially available simple and rapid antigen detection LFIs, submitted for review to the WHO via the Emergency Use Assessment and Listing procedure. The study was performed in an Ebola Treatment Centre laboratory involved in EVD testing in Sierra Leone. In light of the current Ebola outbreak in May 2018 in the Democratic Republic of Congo, which highlights the lack of clarity in the global health community about appropriate Ebola diagnostics, our findings are increasingly critical.MethodsA cross-sectional study was conducted to assess comparative performance of four LFIs for detecting EVD. LFIs were assessed against the same 328 plasma samples and 100 whole EDTA blood samples, using the altona RealStar Filovirus Screen real-time RT-PCR as the bench mark assay. The performance of the Public Health England (PHE) in-house Zaire ebolavirus-specific real time RT-PCR Trombley assay was concurrently assessed. Statistical analysis using generalized estimating equations was conducted to compare LFI performance.FindingsSensitivity and specificity varied between the LFIs, with specificity found to be significantly higher for whole EDTA blood samples compared to plasma samples in at least 2 LFIs (P≤0.003). Using the altona RT-PCR assay as the bench mark, sensitivities on plasma samples ranged from 79.53% (101/127, 95% CI: 71.46-86.17%) for the DEDIATEST EBOLA (SD Biosensor) to 98.43% (125/127, 95% CI: 94.43-99.81%) for the One step Ebola test (Intec). Specificities ranged from 80.20% (158/197, 95% CI: 74.07-88.60%) for plasma samples using the ReEBOV Antigen test Kit (Corgenix) to 100.00% (98/98, 95% CI: 96.31-100.00%) for whole blood samples using the DEDIATEST EBOLA (SD Biosensor) and SD Ebola Zaire Ag (SD Biosensor). Results also showed the Trombley RT-PCR assay had a lower limit of detection than the altona assay, with some LFIs having higher sensitivity than the altona assay when the Trombley assay was the bench mark.InterpretationAll of the tested EVD LFIs may be considered suitable for use in an outbreak situation (i.e. rule out testing in communities), although they had variable performance characteristics, with none possessing both high sensitivity and specificity. The non-commercial Trombley Zaire ebolavirus RT-PCR assay warrants further investigation, as it appeared more sensitive than the current gold standard, the altona Filovirus Screen RT-PCR assay.

Resistance to antimicrobials is one of the biggest challenges worldwide for public health. A key strategy for tackling this is ensuring judicious use of antimicrobials in human and veterinary medicine. Whilst there are many studies in human medicine investigating prescribing behaviour of doctors, there is limited work to understand what factors influence veterinarian prescribing behaviour. Veterinarians often prescribe antimicrobials to sheep and beef farmers in contexts other than at a clinical consultation, and decision-making behind this has not been explored. The aim of this study was to measure, for the first time, the influence of factors from social theories on veterinarians' decision to prescribe antimicrobials to sheep and beef farmers without a clinical consultation, using a factorial survey approach. Respondents were presented with eight vignette scenarios, where a farmer asks for antimicrobials at the veterinary practice. Seven factors, identified from constructs of social theories, were included in the vignettes. Random intercept and random slope models were built to estimate the effects of the vignette factors and vet characteristics on the respondents' willingness to prescribe ratings. A total of 306 surveys were completed. The vignette factors: case type, farmer relationship, other veterinarians in practice, time pressure, habit, willingness to pay, and confidence in the farmer, were significant in the decision to prescribe. Confidence in the farmer was the most influential vignette variable, and was included as a random slope effect. Respondent variables with significant influence on the decision to prescribe were agreeableness personality score, region of veterinary practice, and presence of a small animal department. These influential factors could be considered to target interventions in beef and sheep farm animal veterinary practice for improved antimicrobial stewardship.

Advances in microfluidics and the introduction of isothermal nucleic acid amplification assays have resulted in a range of solutions for nucleic acid amplification tests suited for point of care and field use. However, miniaturisation of instrumentation for such assays has not seen such rapid advances and fluorescence based assays still depend on complex, bulky and expensive optics such as fluorescence microscopes, photomultiplier tubes and sensitive lens assemblies. In this work we demonstrate a robust, low cost platform for isothermal nucleic acid amplification on a microfluidic device. Using easily obtainable materials and commercial off-the-shelf components, we show real time fluorescence detection using a low cost photodiode and operational amplifier without need for lenses. Temperature regulation on the device is achieved using a heater fabricated with standard printed circuit board fabrication methods. These facile construction methods allow fabrications at a cost compatible with widespread deployment to resource poor settings.

Clinical audit is a quality improvement tool used to assess and improve the clinical services provided to patients. This is the first study to investigate the extent to which clinical audit is understood and utilised in farm animal veterinary practice. A cross-sectional study to collect experiences and attitudes of farm animal veterinary surgeons in the UK towards clinical audit was conducted using an online nationwide survey. The survey revealed that whilst just under three-quarters (n = 237/325; 73%) of responding veterinary surgeons had heard of clinical audit, nearly 50% (n = 148/301) had never been involved in a clinical audit of any species. The participants’ knowledge of what a clinical audit was varied substantially, with many respondents reporting not receiving training on clinical audit at the undergraduate or postgraduate level. Respondents that had participated in a clinical audit suggested that protected time away from clinical work was required for the process to be completed successfully. This novel study suggests that clinical audit is undertaken to some extent in farm animal practice and that practitioner perception is that it can bring benefits, but was felt that more resources and support were needed for it to be implemented successfully on a wider scale.

Swim race analysis systems often rely on manual digitization of recorded videos to obtain performance related metrics such as stroke-rate, stroke-length or swim velocity. Using image-processing algorithms, a stroke tagging system has been developed that can be used in competitive swimming environments. Test images from video footage of a women’s 200 m medley race recorded at the 2012 Olympic Games, was segmented into regions of interest (ROI) consisting of individual lanes. Analysis of ROI indicated that the red component of the RGB color map corresponded well with the splash generated by the swimmer. Detected red values from the splash were filtered and a sine-fitting function applied; the frequency of which was used to estimate stroke-rate. Results were compared to manually identified parameters and demonstrated excellent agreement for all four disciplines. Future developments will look to improve the accuracy of the identification of swimmer position allowing swim velocity to be calculated.

The impact of anaemia on patients undergoing aortic valve surgery has not been well studied. We sought to evaluate the effect of anaemia on early outcomes following aortic valve replacement (AVR). Methods: All patients undergoing non-emergent aortic valve surgery (n=2698) with or without other concomitant procedures between 1997 and 2010 were included. Preoperative anaemia was defined as per World Health Organization guidelines as haemoglobin (Hb)