Genetic and phenotypic analysis of elbow dysplasia in four large Swedish dog breeds
Bibliographic record
Abstract
Elbow dysplasia (ED) is a common hereditary disease in dogs. Elbow dysplasia develops during the critical growth period between 4-12 months of age in large breed dogs and causes pain and lameness in the front limbs. In worst case it can lead to euthanasia. Therefore, a control programme (implemented different years for different breeds) through the Swedish Kennel Club is applied for ED to improve the health of affected breeds. However, few studies have investigated the association between screening results and clinical symptoms. The aim of this thesis was therefore to investigate if the screening results are well associated with the clinical symptoms. Furthermore, this thesis will investigate how many individuals with severe clinical symptoms that do not undergo the official screening in the control programme at the age of 12 months or older. \nFour breeds with high prevalence of ED were included in the study; Rottweilers, German Shepherd dogs, Labrador retrievers and Golden retrievers. Data from the official ED screening programme from the Swedish Kennel Club (SKK) database, as well as data from elbow related insurance claims from the insurance company Agria. Approximately 54 000 dogs had an official screening results, and 574 observations also had insurance claims for elbow related issues. \nResults showed that most of the dogs with an insurance claim were younger than the official screening age of 12 months. It was also shown that dogs with insurance claims generally had higher scores for ED compared with the general screened population. However, there was a high proportion of dogs with a normal screening result (ED score = 0) that still had an insurance claim, which was unexpected. The heritability for ED was between 0.13-0.20. Males, compared to females, had higher regression coefficients for inbreeding coefficient, weight at screening and age at screening related to ED. \nThe conclusions are that the screening results seem to be a valuable indication of later ED-related clinical issues. However, a larger proportion of dogs than expected with an insurance claim had an official screening score of 0 (normal). The diagnosis fragmented coronoid process (FCP) had highest frequency in those dogs. Perhaps a second projection in the screening program could be beneficial in finding these cases. Also, the current routine control used today could perhaps be improved by including regressions nested within sex, litter effect and panellist. \nThe results from this thesis should be interpreted carefully since the number of observations were few. Also, there was no guarantee that animals not included in the merged data were healthy since they could have been insured in another insurance company. However, Agria has the largest market share among all the insurance companies for pets. Moreover, more research is needed with a more complete data to validate the results from this thesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".