Seasonality and other risk factors for fleas infestations in domestic dogs and cats.

Fleas in the genus Ctenocephalides are the most clinically important parasitic arthropods of dogs and cats worldwide yet risk factors that might increase the risk of infestation in small animals remains unclear. Here we developed a supervised text mining approach analysing key aspects of flea epidemiology using electronic health records from domestic cats and dogs seen at a sentinel network of 191 voluntary veterinary practices across Great Britain between March 2014 and July 2020. Our methods identified fleas as likely to have been present during 22,276 of 1,902,016 cat consultations (1.17%) and 12,168 of 4,844,850 dog consultations (0.25%). Multivariable logistic regression modelling found that animals originating from areas of least deprivation were associated with 50% reductions in odds of veterinary-recorded flea infestation compared to the most deprived regions in England. Age of the animal was significantly associated with flea presentation in both cats and dogs, with cases peaking before animals reached 12 months. Cases were recorded through each study years, peaking between July and October, with fluctuations between each year. Our findings can be used towards healthcare messaging for veterinary practitioners and owners.

Factors Associated with Prescription of Antimicrobial Drugs for Dogs and Cats, United Kingdom, 2014-2016.

Antimicrobial stewardship is a cornerstone of efforts to curtail antimicrobial resistance. To determine factors potentially influencing likelihood of prescribing antimicrobials for animals, we analyzed electronic health records for unwell dogs (n = 155,732 unique dogs, 281,543 consultations) and cats (n = 69,236 unique cats, 111,139 consultations) voluntarily contributed by 173 UK veterinary practices. Using multivariable mixed effects logistic regression, we found that factors associated with decreased odds of systemic antimicrobial prescription were client decisions focused on preventive health: vaccination (dogs, odds ratio [OR] 0.93, 95% CI, 0.90-0.95; cats, OR 0.92, 95% CI 0.89-0.95), insurance (dogs, OR 0.87, 95% CI 0.84-0.90; cats, OR 0.82, 95% CI 0.79-0.86), neutering of dogs (OR 0.90, 95% CI 0.88-0.92), and practices accredited by the Royal College of Veterinary Surgeons (OR 0.79, 95% 95% CI 0.68-0.92). This large multicenter companion animal study demonstrates the potential of preventive healthcare and client engagement to encourage responsible antimicrobial drug use.

Demographics of dogs, cats, and rabbits attending veterinary practices in Great Britain as recorded in their electronic health records.

BACKGROUND: Understanding the distribution and determinants of disease in animal populations must be underpinned by knowledge of animal demographics. For companion animals, these data have been difficult to collect because of the distributed nature of the companion animal veterinary industry. Here we describe key demographic features of a large veterinary-visiting pet population in Great Britain as recorded in electronic health records, and explore the association between a range of animal's characteristics and socioeconomic factors. RESULTS: Electronic health records were captured by the Small Animal Veterinary Surveillance Network (SAVSNET), from 143 practices (329 sites) in Great Britain. Mixed logistic regression models were used to assess the association between socioeconomic factors and species and breed ownership, and preventative health care interventions. Dogs made up 64.8% of the veterinary-visiting population, with cats, rabbits and other species making up 30.3, 2.0 and 1.6% respectively. Compared to cats, dogs and rabbits were more likely to be purebred and younger. Neutering was more common in cats (77.0%) compared to dogs (57.1%) and rabbits (45.8%). The insurance and microchipping relative frequency was highest in dogs (27.9 and 53.1%, respectively). Dogs in the veterinary-visiting population belonging to owners living in least-deprived areas of Great Britain were more likely to be purebred, neutered, insured and microchipped. The same association was found for cats in England and for certain parameters in Wales and Scotland. CONCLUSIONS: The differences we observed within these populations are likely to impact on the clinical diseases observed within individual veterinary practices that care for them. Based on this descriptive study, there is an indication that the population structures of companion animals co-vary with human and environmental factors such as the predicted socioeconomic level linked to the owner's address. This 'co-demographic' information suggests that further studies of the relationship between human demographics and pet ownership are warranted.

Explainable text-tabular models for predicting mortality risk in companion animals.

As interest in using machine learning models to support clinical decision-making increases, explainability is an unequivocal priority for clinicians, researchers and regulators to comprehend and trust their results. With many clinical datasets containing a range of modalities, from the free-text of clinician notes to structured tabular data entries, there is a need for frameworks capable of providing comprehensive explanation values across diverse modalities. Here, we present a multimodal masking framework to extend the reach of SHapley Additive exPlanations (SHAP) to text and tabular datasets to identify risk factors for companion animal mortality in first-opinion veterinary electronic health records (EHRs) from across the United Kingdom. The framework is designed to treat each modality consistently, ensuring uniform and consistent treatment of features and thereby fostering predictability in unimodal and multimodal contexts. We present five multimodality approaches, with the best-performing method utilising PetBERT, a language model pre-trained on a veterinary dataset. Utilising our framework, we shed light for the first time on the reasons each model makes its decision and identify the inclination of PetBERT towards a more pronounced engagement with free-text narratives compared to BERT-base's predominant emphasis on tabular data. The investigation also explores the important features on a more granular level, identifying distinct words and phrases that substantially influenced an animal's life status prediction. PetBERT showcased a heightened ability to grasp phrases associated with veterinary clinical nomenclature, signalling the productivity of additional pre-training of language models.

Evaluating ChatGPT text mining of clinical records for companion animal obesity monitoring.

BACKGROUND: Veterinary clinical narratives remain a largely untapped resource for addressing complex diseases. Here we compare the ability of a large language model (ChatGPT) and a previously developed regular expression (RegexT) to identify overweight body condition scores (BCS) in veterinary narratives pertaining to companion animals. METHODS: BCS values were extracted from 4415 anonymised clinical narratives using either RegexT or by appending the narrative to a prompt sent to ChatGPT, prompting the model to return the BCS information. Data were manually reviewed for comparison. RESULTS: The precision of RegexT was higher (100%, 95% confidence interval [CI] 94.81%-100%) than that of ChatGPT (89.3%, 95% CI 82.75%-93.64%). However, the recall of ChatGPT (100%, 95% CI 96.18%-100%) was considerably higher than that of RegexT (72.6%, 95% CI 63.92%-79.94%). LIMITATIONS: Prior anonymisation and subtle prompt engineering are needed to improve ChatGPT output. CONCLUSIONS: Large language models create diverse opportunities and, while complex, present an intuitive interface to information. However, they require careful implementation to avoid unpredictable errors.

Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words.

The development of natural language processing techniques for deriving useful information from unstructured clinical narratives is a fast-paced and rapidly evolving area of machine learning research. Large volumes of veterinary clinical narratives now exist curated by projects such as the Small Animal Veterinary Surveillance Network (SAVSNET) and VetCompass, and the application of such techniques to these datasets is already (and will continue to) improve our understanding of disease and disease patterns within veterinary medicine. In part one of this two part article series, we discuss the importance of understanding the lexical structure of clinical records and discuss the use of basic tools for filtering records based on key words and more complex rule based pattern matching approaches. We discuss the strengths and weaknesses of these approaches highlighting the on-going potential value in using these "traditional" approaches but ultimately recognizing that these approaches constrain how effectively information retrieval can be automated. This sets the scene for the introduction of machine-learning methodologies and the plethora of opportunities for automation of information extraction these present which is discussed in part two of the series.

Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014-2021.

BACKGROUND: Ticks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored epidemiological and geo-referenced data from > 7 million electronic health records (EHRs) from cats and dogs collected by the Small Animal Veterinary Surveillance Network (SAVSNET) in Great Britain (GB) between 2014 and 2021 to assess the factors affecting tick attachment in an individual and at a spatiotemporal level. METHODS: EHRs in which ticks were mentioned were identified by text mining; domain experts confirmed those with ticks on the animal. Tick presence/absence records were overlaid with a spatiotemporal series of climate, environment, anthropogenic and host distribution factors to produce a spatiotemporal regression matrix. An ensemble machine learning spatiotemporal model was used to fine-tune hyperparameters for Random Forest, Gradient-boosted Trees and Generalized Linear Model regression algorithms, which were then used to produce a final ensemble meta-learner to predict the probability of tick attachment across GB at a monthly interval and averaged long-term through 2014-2021 at a spatial resolution of 1 km. Individual host factors associated with tick attachment were also assessed by conditional logistic regression on a matched case-control dataset. RESULTS: In total, 11,741 consultations were identified in which a tick was recorded. The frequency of tick records was low (0.16% EHRs), suggesting an underestimation of risk. That said, increased odds for tick attachment in cats and dogs were associated with younger adult ages, longer coat length, crossbreeds and unclassified breeds. In cats, males and entire animals had significantly increased odds of recorded tick attachment. The key variables controlling the spatiotemporal risk for tick attachment were climatic (precipitation and temperature) and vegetation type (Enhanced Vegetation Index). Suitable areas for tick attachment were predicted across GB, especially in forests and grassland areas, mainly during summer, particularly in June. CONCLUSIONS: Our results can inform targeted health messages to owners and veterinary practitioners, identifying those animals, seasons and areas of higher risk for tick attachment and allowing for more tailored prophylaxis to reduce tick burden, inappropriate parasiticide treatment and potentially TBDs in companion animals and humans. Sentinel networks like SAVSNET represent a novel complementary data source to improve our understanding of tick attachment risk for companion animals and as a proxy of risk to humans.

PetBERT: automated ICD-11 syndromic disease coding for outbreak detection in first opinion veterinary electronic health records.

Effective public health surveillance requires consistent monitoring of disease signals such that researchers and decision-makers can react dynamically to changes in disease occurrence. However, whilst surveillance initiatives exist in production animal veterinary medicine, comparable frameworks for companion animals are lacking. First-opinion veterinary electronic health records (EHRs) have the potential to reveal disease signals and often represent the initial reporting of clinical syndromes in animals presenting for medical attention, highlighting their possible significance in early disease detection. Yet despite their availability, there are limitations surrounding their free text-based nature, inhibiting the ability for national-level mortality and morbidity statistics to occur. This paper presents PetBERT, a large language model trained on over 500 million words from 5.1 million EHRs across the UK. PetBERT-ICD is the additional training of PetBERT as a multi-label classifier for the automated coding of veterinary clinical EHRs with the International Classification of Disease 11 framework, achieving F1 scores exceeding 83% across 20 disease codings with minimal annotations. PetBERT-ICD effectively identifies disease outbreaks, outperforming current clinician-assigned point-of-care labelling strategies up to 3 weeks earlier. The potential for PetBERT-ICD to enhance disease surveillance in veterinary medicine represents a promising avenue for advancing animal health and improving public health outcomes.

Dogs with cropped ears in the UK: A population-based study using electronic health records.

BACKGROUND: Ear cropping for cosmetic purposes was made illegal in the UK in 2006. Despite this, a lack of import regulations and celebrity and media influences mean cropped dogs are increasingly reported. METHODS: The demographics, temporal trends and patient-level associated factors for dogs with cropped ears were evaluated in a large sentinel population of dogs visiting UK veterinary practices. RESULTS: A total of 132 dogs with cropped ears were identified, with rates peaking in 2021. In 84 cases (63.6%), there was evidence of importation, most commonly from countries where cropping is also illegal, including Romania, Hungary, Bulgaria, Serbia, Spain, Poland and Ireland. American Bulldogs, Dobermanns, Italian Mastiffs (Cane Corso), Bulldogs and Mastiffs were all significantly overrepresented. Affected dogs were more likely to be unneutered (odds ratio 11.04, 95% confidence interval 5.84-20.90). LIMITATIONS: The study likely underestimates true levels of ear cropping. Identified cases are from a sentinel network of veterinary practices, and as such may not be representative of the wider UK population. CONCLUSION: These data suggest a need to educate owners and veterinary surgeons about the welfare and legal implications of ear cropping. The data presented can inform future targeted policies in veterinary practices and at a governmental level.

A blinded randomised controlled trial to determine the effect of enteric coating on enzyme treatment for canine exocrine pancreatic efficiency.

BACKGROUND: Enzyme treatment is the mainstay for management of exocrine pancreatic insufficiency (EPI) in dogs. 'Enteric-coated' preparations have been developed to protect the enzyme from degradation in the stomach, but their efficacy has not been critically evaluated. The hypothesis of the current study was that enteric coating would have no effect on the efficacy of pancreatic enzyme treatment for dogs with EPI.Thirty-eight client-owned dogs with naturally occurring EPI were included in this multicentre, blinded, randomised controlled trial. Dogs received either an enteric-coated enzyme preparation (test treatment) or an identical preparation without the enteric coating (control treatment) over a period of 56 days. RESULTS: There were no significant differences in either signalment or cobalamin status (where cobalamin deficient or not) between the dogs on the test and control treatments. Body weight and body condition score increased in both groups during the trial (P<0.001) but the magnitude of increase was greater for the test treatment compared with the control treatment (P<0.001). By day 56, mean body weight increase was 17% (95% confidence interval 11-23%) in the test treatment group and 9% (95% confidence interval 4-15%) in the control treatment group. The dose of enzyme required increased over time (P<0.001) but there was no significant difference between treatments at any time point (P=0.225). Clinical disease severity score decreased over time for both groups (P=0.011) and no difference was noted between groups (P=0.869). No significant adverse effects were reported, for either treatment, for the duration of the trial. CONCLUSIONS: Enteric coating a pancreatic enzyme treatment improves response in canine EPI.

Acute kidney injury manifesting as renal tubular acidosis with proximal and distal renal tubular dysfunction in a dog with acute pancreatitis.

OBJECTIVE: To describe the clinical presentation and management of a critically ill dog with profound renal tubular acidosis (RTA) with proximal and distal renal tubular dysfunction. CASE SUMMARY: A 3-year-old neutered female Border Terrier was presented with frequent regurgitation resulting from acute pancreatitis with severe ileus. Venous acid-base analysis and complete urinalysis confirmed the presence of normal anion gap metabolic acidosis with inappropriately alkaline urine (pH 8), consistent with distal RTA. Urinalysis, urine amino acids, and urinary fractional excretion of electrolytes revealed glycosuria (with normoglycemia), aminoaciduria, and increased fractional excretion of sodium, calcium, and phosphate consistent with generalized proximal renal tubulopathy or Fanconi syndrome. The dog responded well to supportive care and alkaline therapy and made a complete recovery. NEW OR UNIQUE INFORMATION PROVIDED: To the authors' knowledge, this is the first description of RTA with proximal and distal renal tubular dysfunction in the veterinary literature. Furthermore, the authors hypothesize that the transient RTA was a manifestation of acute kidney injury secondary to acute pancreatitis, the first report of this in the literature.

Incidence of alimentary and respiratory disease in brachycephalic dogs presenting to primary care veterinary practices participating in the SAVSNET project.

BACKGROUND: Brachycephalic dogs clinically affected by brachycephalic obstructive airway syndrome have been shown to have a high incidence of gastrointestinal disease, with French Bulldogs (FBD) identified as a particularly affected breed. METHODS: Clinical records of 750 brachycephalic dogs attending over 500 practices participating in the small animal veterinary surveillance network (SAVSNET) project were analysed in this cohort study to determine the incidence of alimentary and respiratory disease within FBD, Bulldogs (BD) and Pugs attending primary care veterinary practice. Electronic clinical records were studied for treatment or acknowledgement of specific clinical signs that could be attributed to different anatomical locations. Disease of the different anatomical locations was marked as either being present or not present which allowed for statistical analysis. RESULTS: Significant differences in the incidence of oesophageal (p = 0.006), gastric (p = 0.001) and intestinal (p = 0.001) diseases were present among the breeds studied. FBD had significantly increased odds ratios of having oesophageal (2.0, 2.2), gastric (2.4, 1.5) and intestinal (1.7, 1.5) diseases relative to Pugs and BD, respectively. Pugs had significantly increased odds ratios of having upper respiratory tract disease relative to BD (1.9). CONCLUSION: The results show the incidence of gastrointestinal disease and upper respiratory tract disease is significantly different between the brachycephalic breeds studied. Furthermore, the general population of FBD has the highest incidence of gastrointestinal disease.

Clinical findings associated with N-terminal pro-B-type natriuretic peptide measurement in dogs and cats attending first opinion veterinary practices.

BACKGROUND: Clinical findings associated with N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurement in dogs and cats in primary practice, and their relevance to published measurement indications, have not been described. METHODS: Using electronic health record data collected by the Small Animal Veterinary Surveillance Network, appointments in which NT-proBNP was measured were identified using keyword-based text filtering. For these appointments, clinical findings were manually identified from each patient's clinical narrative (CN) and their frequencies described. RESULTS: CNs of 3510 appointments (357 dogs and 257 cats) from 99practices were evaluated. The most frequently recorded clinical findings in dogs were: heart murmur (n = 147, 41.2% (95% confidence interval (CI) = 36.1%-46.3%), coughing (n = 83, 23.2% (95% CI = 18.8%-27.6%)) and panting (n = 58, 16.2% (95% CI = 12.4%-20.0%)) and in cats: heart murmur (n = 143, 55.6% (95% CI = 49.5%-61.7%)), suspected thromboembolism (n = 88, 34.2% (95% CI = 28.4%-40.0%)) and weight loss (n = 53, 20.6% (95% CI = 15.7%-25.5%)). Dyspnoea and tachypnoea were infrequently reported in dogs (n = 29, 8.1% (95% CI = 5.3%-10.9%) and n = 21, 5.9% (95% CI = 3.5%-8.3%), respectively) and cats (n = 26, 10.1% (95% CI = 6.4%-13.8%) and n = 36, 14.0% (95% CI = 9.8%-18.2%), respectively). CONCLUSION: Clinical findings referable to cardiac disease were recorded contemporaneously with NT-proBNP measurement and suggested both published and other indications (coughing (in dogs and cats), and serial measurements and thromboembolism (in cats)) for testing.

UK veterinary professionals' perceptions and experiences of adverse drug reaction reporting.

BACKGROUND: Spontaneous reporting of suspected adverse drug reactions (ADRs) is the cornerstone of pharmacovigilance. Despite this, it is believed that there is significant under-reporting in the veterinary setting. Low reporting rates delay marketing authorisation holders (MAHs) and regulators taking mitigating action in the case of safety concerns. METHOD: We designed a survey to explore the perceptions, attitudes and experiences of UK veterinary professionals towards ADR reporting. The survey was advertised widely through conventional and social media and at several conferences. RESULTS: In total, 260 respondents completed the survey, including 210 veterinary surgeons, 49 veterinary nurses and one suitably qualified person. Respondents generally understood the need to report ADRs. The main barrier to reporting was the suspected ADR being well known, and the most popular potential facilitator identified was the ability to report via the practice management system. Facilitation via education in the form of a pharmacovigilance themed continuing professional development event was particularly popular among veterinary nurses, who reported time as being less of a barrier to reporting than their veterinary surgeon counterparts. CONCLUSIONS: Our findings suggest that technological interventions to facilitate reporting and empowerment of veterinary nurses to report through a tailored training event should be explored further.

Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs.

A key goal of disease surveillance is to identify outbreaks of known or novel diseases in a timely manner. Such an outbreak occurred in the UK associated with acute vomiting in dogs between December 2019 and March 2020. We tracked this outbreak using the clinical free text component of anonymised electronic health records (EHRs) collected from a sentinel network of participating veterinary practices. We sourced the free text (narrative) component of each EHR supplemented with one of 10 practitioner-derived main presenting complaints (MPCs), with the 'gastroenteric' MPC identifying cases involved in the disease outbreak. Such clinician-derived annotation systems can suffer from poor compliance requiring retrospective, often manual, coding, thereby limiting real-time usability, especially where an outbreak of a novel disease might not present clinically as a currently recognised syndrome or MPC. Here, we investigate the use of an unsupervised method of EHR annotation using latent Dirichlet allocation topic-modelling to identify topics inherent within the clinical narrative component of EHRs. The model comprised 30 topics which were used to annotate EHRs spanning the natural disease outbreak and investigate whether any given topic might mirror the outbreak time-course. Narratives were annotated using the Gensim Library LdaModel module for the topic best representing the text within them. Counts for narratives labelled with one of the topics significantly matched the disease outbreak based on the practitioner-derived 'gastroenteric' MPC (Spearman correlation 0.978); no other topics showed a similar time course. Using artificially injected outbreaks, it was possible to see other topics that would match other MPCs including respiratory disease. The underlying topics were readily evaluated using simple word-cloud representations and using a freely available package (LDAVis) providing rapid insight into the clinical basis of each topic. This work clearly shows that unsupervised record annotation using topic modelling linked to simple text visualisations can provide an easily interrogable method to identify and characterise outbreaks and other anomalies of known and previously un-characterised diseases based on changes in clinical narratives.

A virtual biobank for companion animals: A parvovirus pilot study.

BACKGROUND: There is a lack of national population data concerning infectious disease in companion animals. Here, we piloted the feasibility of linking diagnostic laboratories, population surveillance and modern sequencing approaches to extract targeted diagnostic samples from laboratories before they were discarded, as a novel route to better understand national epidemiology of major small animal pathogens. METHODS: Samples tested for canine or feline parvovirus were requested from a national veterinary diagnostic laboratory and analysed by Sanger or next generation sequencing. Samples were linked to electronic health data held in the SAVSNET database. RESULTS: Sequences obtained from positive samples, together with associated metadata, provided new insights into the recent geographical distribution of parvovirus strains in circulation in the United Kingdom (UK). CONCLUSIONS: This collaboration with industry represents a 'National Virtual Biobank' that can rapidly be called on, to efficiently add new layers of epidemiological information of relevance to animal, and potentially human, population health.

A randomised controlled trial to reduce highest priority critically important antimicrobial prescription in companion animals.

Robust evidence supporting strategies for companion animal antimicrobial stewardship is limited, despite frequent prescription of highest priority critically important antimicrobials (HPCIA). Here we describe a randomised controlled trial where electronic prescription data were utilised (August 2018-January 2019) to identify above average HPCIA-prescribing practices (n = 60), which were randomly assigned into a control group (CG) and two intervention groups. In March 2019, the light intervention group (LIG) and heavy intervention group (HIG) were notified of their above average status, and were provided with educational material (LIG, HIG), in-depth benchmarking (HIG), and follow-up meetings (HIG). Following notification, follow-up monitoring lasted for eight months (April-November 2019; post-intervention period) for all intervention groups, though HIG practices were able to access further support (i.e., follow-up meetings) for the first six of these months if requested. Post-intervention, in the HIG a 23.5% and 39.0% reduction in canine (0.5% of total consultations, 95% confidence interval, 0.4-0.6, P = 0.04) and feline (4.4%, 3.4-5.3, P < 0.001) HPCIA-prescribing consultations was observed, compared to the CG (dogs: 0.6%, 0.5-0.8; cats: 7.4%, 6.0-8.7). The LIG was associated with a 16.7% reduction in feline HPCIA prescription (6.1% of total consultations, 5.3-7.0, P = 0.03). Therefore, in this trial we have demonstrated effective strategies for reducing veterinary HPCIA prescription.

Gastric mucosal pathology in Belgian Shepherd dogs with and without clinical signs of gastric disease.

BACKGROUND: Gastric carcinoma (GC) is uncommon in dogs, except in predisposed breeds such as Belgian Shepherd dogs (BSD) of the Tervuren and Groenendael varieties. When GC is diagnosed in dogs it is often late in the disease, resulting in a poorer prognosis. The aim of this prospective clinical study was to investigate possible associations of gastric mucosal pathologies with clinical signs, laboratory test results and GC in BSD. An online survey gathered epidemiological data to generate potential risk factors for vomiting as the predominant gastric clinical sign, and supported patient recruitment for endoscopy. Canine Chronic Enteropathy Clinical Activity Index (CCECAI) score and signs of gastroesophageal reflux (GER) were used to allocate BSD older than five years to either Group A, with signs of gastric disease, or Group B, without signs. Findings in the clinical history, laboratory tests and gastric histopathology of endoscopic biopsies were statistically analysed in search of associations. RESULTS: The online survey included 232 responses. Logistic regression analysis recognized an association of vomiting with gagging, poor appetite and change in attitude. Recruitment for endoscopy included 16 BSD in Group A (mean age 9.1 ± 1.8 years, mean CCECAI = 3.1 ± 2.2 and signs of GER); and 11 in Group B (mean age 9.8 ± 1.4 years, CCECAI = 0, no signs of GER). Seven (25.9%) of the 27 BSD (Group A 4/16, Group B 3/11) had leukopenia. Serum C-reactive protein tended to be increased with more advanced GC (P = 0.063). Frequency of GC, mucosal atrophy, mucous metaplasia, or glandular dysplasia did not differ between groups. GC was frequently diagnosed (6/27), even without clinical signs (2/11). The odds ratio for vomiting (OR = 9.9; P = 0.016) was increased only when glandular dysplasia was present. GC was associated with mucous metaplasia (P = 0.024) and glandular dysplasia (P = 0.006), but not with mucosal atrophy (P = 1). CONCLUSIONS: GC can develop as an occult disease, associated with metaplasia and dysplasia of the gastric mucosa. Suggestive clinical signs, notably vomiting, should warrant timely endoscopy in BSD. Extensive endoscopic screening of asymptomatic dogs remains, however, unrealistic. Therefore, biomarkers of mucosal pathology preceding clinical illness are needed to support an indication for endoscopy and enable early diagnosis of GC.

SARS-CoV-2 neutralising antibodies in Dogs and Cats in the United Kingdom.

Companion animals are susceptible to SARS-CoV-2 infection and sporadic cases of pet infections have occurred in the United Kingdom. Here we present the first large-scale serological survey of SARS-CoV-2 neutralising antibodies in dogs and cats in the UK. Results are reported for 688 sera (454 canine, 234 feline) collected by a large veterinary diagnostic laboratory for routine haematology during three time periods; pre-COVID-19 (January 2020), during the first wave of UK human infections (April-May 2020) and during the second wave of UK human infections (September 2020-February 2021). Both pre-COVID-19 sera and those from the first wave tested negative. However, in sera collected during the second wave, 1.4% (n=4) of dogs and 2.2% (n=2) cats tested positive for neutralising antibodies. The low numbers of animals testing positive suggests pet animals are unlikely to be a major reservoir for human infection in the UK. However, continued surveillance of in-contact susceptible animals should be performed as part of ongoing population health surveillance initiatives.

SARS-CoV-2 neutralising antibodies in dogs and cats in the United Kingdom.

Companion animals are susceptible to SARS-CoV-2 infection and sporadic cases of pet infections have occurred in the United Kingdom. Here we present the first large-scale serological survey of SARS-CoV-2 neutralising antibodies in dogs and cats in the UK. Results are reported for 688 sera (454 canine, 234 feline) collected by a large veterinary diagnostic laboratory for routine haematology during three time periods; pre-COVID-19 (January 2020), during the first wave of UK human infections (April-May 2020) and during the second wave of UK human infections (September 2020-February 2021). Both pre-COVID-19 sera and those from the first wave tested negative. However, in sera collected during the second wave, 1.4% (n â€‹= â€‹4) of dogs and 2.2% (n â€‹= â€‹2) of cats tested positive for neutralising antibodies. The low numbers of animals testing positive suggests pet animals are unlikely to be a major reservoir for human infection in the UK. However, continued surveillance of in-contact susceptible animals should be performed as part of ongoing population health surveillance initiatives.