Un‐United Medial Epicondyle of the Humerus: Radiographic Prevalence and Association with Elbow Osteoarthritis in a Cohort of Labrador Retrievers
Bibliographic record
Abstract
OBJECTIVE: To longitudinally characterize the radiographic appearance of un-united medial epicondyle (UME) of the humerus, evaluate UME association with osteoarthritis (OA) and consider its relevance to the elbow dysplasia complex. STUDY DESIGN: Longitudinal cohort study. ANIMALS: Labrador retrievers (n=48) from 7 litters. METHODS: Forty-eight same-sex littermates were paired for this lifetime feeding study. One of each pair was control-fed; the pair mate was fed 25% less than the control each day. Elbows of 46 surviving dogs were radiographed at ages 6 and 8 years, and/or at end-of-life (EOL). Elbow histopathology was done EOL, although UME lesions were not evaluated histologically. RESULTS: Seven dogs (15%) had UME, representing 5 litters; 4 were control-fed, 3 diet-restricted. Six (86%) dogs had unilateral lesions; 1 was bilateral. UME was evident on craniocaudal (CrCd) radiographic projections by 8 years in all dogs. UME was detected in only 1 elbow by mediolateral radiographic projection. Elbow OA frequency in UME affected dogs was not significantly different from the remaining study population. Histopathologic lesions were bilateral in dogs with unilateral UME. CONCLUSIONS: UME may be more common than previously thought. Most cases were unilateral and diet restriction had no effect on frequency. The CrCd view was critical for diagnosis. Elbow OA was not directly associated with UME. CLINICAL RELEVANCE: Infrequent diagnosis of UME could result from infrequent radiography and use of only the flexed lateral radiographic projection required by the Orthopedic Foundation for Animals for elbow screening. Like hip evaluations, screening for UME should be continued for life, until genetics are better understood. Lack of association between UME and elbow OA suggests that UME is not likely a component of elbow dysplasia.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".