Disorder predispositions and protections of Labrador Retrievers in the UK

Abstract 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

Health-related welfare prioritisation of canine disorders using electronic health records in primary care practice in the UK.

BACKGROUND: Evidence-based comparison of the disorder-specific welfare burdens of major canine conditions could better inform targeting of stakeholder resources, to maximise improvement of health-related welfare in UK dogs. Population-level disease related welfare impact offers a quantitative, welfare-centred framework for objective disorder prioritisation, but practical applications have been limited to date due to sparse reliable evidence on disorder-specific prevalence, severity and duration across the canine disease spectrum. The VetCompass™ Programme collects de-identified electronic health record data from dogs attending primary-care clinics UK-wide, and is well placed to fill these information gaps. RESULTS: The eight common, breed-related conditions assessed were anal sac disorder, conjunctivitis, dental disease, dermatitis, overweight/obese, lipoma, osteoarthritis and otitis externa. Annual period prevalence estimates (based on confirming 250 cases from total potential cases identified from denominator population of 455, 557 dogs) were highest for dental disorder (9.6%), overweight/obese (5.7%) and anal sac disorder (4.5%). Dental disorder (76% of study year), osteoarthritis (82%), and overweight/obese (70%) had highest annual duration scores. Osteoarthritis (scoring 13/21), otitis externa (11/21) and dermatitis demonstrated (10/21) highest overall severity scores. Dental disorder (2.47/3.00 summative score), osteoarthritis (2.24/3.00) and overweight/obese (1.67/3.00) had highest VetCompass Welfare Impact scores overall. DISCUSSION: Of the eight common, breed-related disorders assessed, dental disorder, osteoarthritis and overweight/obese demonstrated particular welfare impact, based on combinations of high prevalence, duration and severity. Future work could extend this methodology to cover a wider range of disorders. CONCLUSIONS: Dental disorders, osteoarthritis and overweight/obese have emerged as priority areas for health-related welfare improvement in the UK dog population. This study demonstrated applicability of a standardised methodology to assess the relative health-related welfare impact across a range of canine disorders using VetCompass clinical data

Post-exercise management of exertional hyperthermia in dogs participating in dog sport (canicross) events in the UK

Exercise is a common trigger of heat-related illness (HRI) events in dogs, accounting for 74% of canine HRI cases treated under primary veterinary care in the United Kingdom. However, few empirical studies have evaluated the effectiveness of differing cooling methods for dogs with exertional hyperthermia or HRI. This study aimed to prospectively evaluate effects of ambient conditions and post-exercise management practices (cooling methods and vehicular confinement) on the post-exercise temperature change of dogs participating in UK canicross events. Canine temperature was recorded at three intervals post-exercise: as close as possible to 0- (immediately post-exercise), 5-, and 15-min post-exercise. Ambient conditions and post-exercise management were recorded for 115 cooling profiles from 52 dogs. In 28/115 (24.4%) profiles, the dog's temperature increased during the first 5-min post-exercise. Overall, 68/115 (59.1%) profiles included passive cooling (stood or walked outside), 35 (30.4%) active cooling (cold-water immersion or application of a cooling coat), and 12 (10.4%) involved no cooling and were immediately housed in vehicles. No dogs developed hypothermia during the study and no adverse effects were observed from any cooling method. In hyperthermic dogs, overall post-exercise body temperature change was significantly negatively associated (i.e. the dogs cooled more) with 0-min post-exercise body temperature (β = −0.93, p &lt; 0.001), and not being housed in a vehicle (β = −0.43, p = 0.013). This study provides evidence cold-water immersion (in water at 0.1–15.0 °C) can be used to effectively and safely cool dogs with exertional hyperthermia. Progressive temperature increases in many dogs - even after exercise has terminated - supports the message to “cool first, transport second” when managing dogs with HRI. When transporting dogs post-exercise or with HRI even after active cooling, care should be taken to cool the vehicle before entry and promote air movement around the dog during transport to facilitate ongoing cooling and prevent worsening of hyperthermia during travel.</p

Veterinary drug therapies used for undesirable behaviours in UK dogs under primary veterinary care

Undesirable behaviours (UBs) in dogs are common and important issues with serious potential welfare consequences for both the dogs and their owners. This study aimed to investigate the usage of drug therapy for UBs in dogs and assess demographic risk factors for drug-prescribed UBs within the dog population under primary-care veterinary care in the UK in 2013. Dogs receiving drug therapy for UB were identified through the retrospective analysis of anonymised electronic patient records in VetCompass™. Risk factor analysis used multivariable logistic regression modelling. The study population comprised 103,597 dogs under veterinary care in the UK during 2013. There were 413 drug-prescribed UBs recorded among 404 dogs. The prevalence of dogs with at least one UB event treated with a drug in 2013 was 0.4%. Multivariable modelling identified 3 breeds with increased odds of drug-prescribed UB compared with crossbred dogs: Toy Poodle (OR 2.75), Tibetan Terrier (OR 2.68) and Shih-tzu (OR 1.95). Increasing age was associated with increased odds of drug-prescribed UB, with dogs ≥ 12 years showing 3.1 times the odds compared with dogs < 3 years. Neutered males (OR 1.82) and entire males (OR 1.50) had increased odds compared with entire females. The relatively low prevalence of dogs with at least one UB event that was treated with a drug in 2013 could suggest that opportunities for useful psychopharmaceutical intervention in UBs may be being missed in first opinion veterinary practice. While bodyweight was not a significant factor, the 3 individual breeds at higher odds of an UB treated with a behaviour modifying drug all have a relatively low average bodyweight. The current results also support previous research of a male predisposition to UBs and it is possible that this higher risk resulted in the increased likelihood of being prescribed a behaviour modifying drug, regardless of neuter status

Clinical management of lipomas in dogs under primary care in the UK

Lipomas are relatively common and biologically benign masses of mesenchymal origin consisting of adipocytes. This study reports benchmark data on the clinical management and outcomes of lipomas in dogs under UK primary veterinary care. The study used a cross-sectional analysis of cohort clinical data from dogs that were under veterinary care at practices participating within VetCompass from January 1, 2013 to December 31, 2013. Descriptive and analytic statistics characterised the clinical management and outcomes following presumptive lipoma diagnosis. The study included 2765 lipoma cases from 384 284 dogs under UK veterinary care during 2013. Diagnostics included fine needle aspirate in 1119 (40.5 per cent) cases, biopsy in 215 (7.8 per cent) cases and diagnostic imaging in 11 (0.4 per cent) cases. Overall, 525 (19.0 per cent) cases were managed surgically. Of the surgical cases, 307 (58.5 per cent) solely had mass removal whilst 218 (41.5 per cent) included another procedure during the same surgical episode. A surgical drain was placed during surgery in 90 (17.1 per cent) cases. Wound breakdown was reported in 14 (2.7 per cent) surgical procedures. Wound infection followed surgery in 11 (2.1 per cent) dogs. The findings provide veterinarians with an evidence base that benchmarks how lipoma cases are currently managed in the UK, but these results do not necessarily reflect optimal management or best practice

Time-dependent ARMA modeling of genomic sequences

<p>Abstract</p> <p>Background</p> <p>Over the past decade, many investigators have used sophisticated time series tools for the analysis of genomic sequences. Specifically, the correlation of the nucleotide chain has been studied by examining the properties of the power spectrum. The main limitation of the power spectrum is that it is restricted to stationary time series. However, it has been observed over the past decade that genomic sequences exhibit non-stationary statistical behavior. Standard statistical tests have been used to verify that the genomic sequences are indeed not stationary. More recent analysis of genomic data has relied on time-varying power spectral methods to capture the statistical characteristics of genomic sequences. Techniques such as the evolutionary spectrum and evolutionary periodogram have been successful in extracting the time-varying correlation structure. The main difficulty in using time-varying spectral methods is that they are extremely unstable. Large deviations in the correlation structure results from very minor perturbations in the genomic data and experimental procedure. A fundamental new approach is needed in order to provide a stable platform for the non-stationary statistical analysis of genomic sequences.</p> <p>Results</p> <p>In this paper, we propose to model non-stationary genomic sequences by a time-dependent autoregressive moving average (TD-ARMA) process. The model is based on a classical ARMA process whose coefficients are allowed to vary with time. A series expansion of the time-varying coefficients is used to form a generalized Yule-Walker-type system of equations. A recursive least-squares algorithm is subsequently used to estimate the time-dependent coefficients of the model. The non-stationary parameters estimated are used as a basis for statistical inference and biophysical interpretation of genomic data. In particular, we rely on the TD-ARMA model of genomic sequences to investigate the statistical properties and differentiate between coding and non-coding regions in the nucleotide chain. Specifically, we define a quantitative measure of randomness to assess how far a process deviates from white noise. Our simulation results on various gene sequences show that both the coding and non-coding regions are non-random. However, coding sequences are "whiter" than non-coding sequences as attested by a higher index of randomness.</p> <p>Conclusion</p> <p>We demonstrate that the proposed TD-ARMA model can be used to provide a stable time series tool for the analysis of non-stationary genomic sequences. The estimated time-varying coefficients are used to define an index of randomness, in order to assess the statistical correlations in coding and non-coding DNA sequences. It turns out that the statistical differences between coding and non-coding sequences are more subtle than previously thought using stationary analysis tools: Both coding and non-coding sequences exhibit statistical correlations, with the coding regions being "whiter" than the non-coding regions. These results corroborate the evolutionary periodogram analysis of genomic sequences and revoke the stationary analysis' conclusion that coding DNA behaves like random sequences.</p