All data are prone to error and require data cleaning prior to analysis. An important example is longitudinal growth data, for which there are no universally agreed standard methods for identifying and removing implausible values and many existing methods have limitations that restrict their usage across different domains. A decision-making algorithm that modified or deleted growth measurements based on a combination of pre-defined cutoffs and logic rules was designed. Five data cleaning methods for growth were tested with and without the addition of the algorithm and applied to five different longitudinal growth datasets: four uncleaned canine weight or height datasets and one pre-cleaned human weight dataset with randomly simulated errors. Prior to the addition of the algorithm, data cleaning based on non-linear mixed effects models was the most effective in all datasets and had on average a minimum of 26.00% higher sensitivity and 0.12% higher specificity than other methods. Data cleaning methods using the algorithm had improved data preservation and were capable of correcting simulated errors according to the gold standard; returning a value to its original state prior to error simulation. The algorithm improved the performance of all data cleaning methods and increased the average sensitivity and specificity of the non-linear mixed effects model method by 7.68% and 0.42% respectively. Using non-linear mixed effects models combined with the algorithm to clean data allows individual growth trajectories to vary from the population by using repeated longitudinal measurements, identifies consecutive errors or those within the first data entry, avoids the requirement for a minimum number of data entries, preserves data where possible by correcting errors rather than deleting them and removes duplications intelligently. This algorithm is broadly applicable to data cleaning anthropometric data in different mammalian species and could be adapted for use in a range of other domains.

The Labrador Retriever is one of the most popular dog breeds worldwide, therefore it is important to have reliable evidence on the general health issues of the breed. Using anonymised veterinary clinical data from the VetCompass Programme, this study aimed to explore the relative risk to common disorders in the Labrador Retriever. The clinical records of a random sample of dogs were reviewed to extract the most definitive diagnoses for all disorders recorded during 2016. A list of disorders was generated, including the 30 most common disorders in Labrador Retrievers and the 30 most common disorders in non-Labrador Retrievers. Multivariable logistic regression was used to report the odds of each of these disorders in 1462 (6.6%) Labrador Retrievers compared with 20,786 (93.4%) non-Labrador Retrievers. At a specific-level of diagnostic precision, after accounting for confounding, Labrador Retrievers had significantly increased odds of 12/35 (34.3%) disorders compared to non-Labrador Retrievers; osteoarthritis (OR 2.83) had the highest odds. Conversely, Labrador Retrievers had reduced odds of 7/35 (20.0%) disorders; patellar luxation (OR 0.18) had the lowest odds. This study provides useful information about breed-specific disorder predispositions and protections, which future research could evaluate further to produce definitive guidance for Labrador Retriever breeders and owners.

Objectives To identify and describe histological and immunohistochemical criteria that may differentiate between skin and lymph node lesions associated with Mycobacterium (M.) bovis and M. microti in a diagnostic pathology setting. Materials and Methods Archived skin and lymph node biopsies of tuberculous lesions were stained with haematoxylin and eosin, Ziehl‐Neelsen and Masson's Trichrome. Immunohistochemistry was performed to detect the expression of calprotectin, CD3 and Pax5. Samples were scored for histological parameters (i.e. granulomas with central necrosis versus small granulomas without central necrosis, percentage necrosis and/or multinucleated giant cells), number of acid‐fast bacilli (bacterial index) and lesion percentage of fibrosis and positive immunohistochemical staining. Results Twenty‐two samples were examined (M. bovis n=11, M. microti n=11). When controlling for age, gender and tissue, feline M. bovis‐associated lesions more often featured large multi‐layered granulomas with central necrosis. Conversely, this presentation was infrequent in feline M. microti‐associated lesions, where small granulomas without central necrosis predominated. The presence of an outer fibrous capsule was variable in both groups, as was the bacterial index. There were no differences in intralesional expression of immunohistochemical markers. Clinical Significance Differences in the histological appearance of skin and lymph node lesions may help to infer feline infection with either M. bovis or M. microti at an earlier stage when investigating these cases, informing clinicians of the potential zoonotic risk. Importantly, cases of tuberculosis can present with numerous acid‐fast bacilli. This implies that a high bacterial index does not infer infection with non‐zoonotic non‐tuberculous mycobacteria.