Chronic idiopathic myopathy in Icelandic horses: A case series
Bibliographic record
Abstract
BACKGROUND: Exertional myopathies are recognised as a cause of poor performance in equines. In Icelandic horses presenting reduced performance and/or multi-limb lameness, no specific myopathy has been identified. OBJECTIVES: To characterise the clinical presentation and histopathological findings in muscle biopsy samples from Icelandic horses demonstrating poor performance. STUDY DESIGN: Case series. METHODS: Phenotypic characteristics, clinical examination and diagnoses of 17 Icelandic horses were studied. All horses had a resting serum creatine kinase (CK) and aspartate transaminase activities measured, and CK activities 4-6 and 24 h post-exercise were measured in some horses. The semimembranosus muscle was biopsied in all horses and used to categorise horses into two groups: those with histopathological evidence of chronic idiopathic myopathy and those with normal biopsy findings. RESULTS: Twelve horses displayed non-specific histological features of muscle degeneration and regeneration consistent with a myopathy. The affected horses had significantly increased CK activities after exercise (median 1637 U/L, IQR 861-2480 U/L) compared with the group with histologically normal muscle (median 234 U/L, IQR 211-457 U/L, p = 0.02). Phenotypic traits, such as tachypnoea, fatigue, stumbling and reluctance to tölt or canter, were present in both groups. MAIN LIMITATIONS: The small sample size and absence of a control group with normal performance. CONCLUSIONS: This case series suggests the presence of a novel myopathy in Icelandic horses. In horses of this breed, exhibiting decreased performance, multi-limb lameness and/or increased serum CK activity at rest or post-exercise, an underlying myopathy should be considered.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".