Colour Doppler ultrasonography and sclerosing therapy in diagnosis and treatment of tendinopathy in horses—a research model for human medicine
Bibliographic record
Abstract
Sclerosing therapy has in recent studies showed promising results in patients with clinically and ultrasonographically diagnosed tendinosis in Achilles and patellar tendons. The aim of this investigation was to study the presence of intratendinous colour Doppler (CD) flow in horses with clinically diagnosed chronic tendinopathy and to test if experience from human studies could be extrapolated to horses. Special interest was focused on the treatment with sclerosing therapy and whether we could obtain the same successful peroperative findings as in humans. Four horses with clinically diagnosed unilateral chronic tendinosis in the forelimbs were examinated with both grey-scale ultrasonography (US) and CD. The horses were to be euthanised according to standard procedure is such cases. The US findings were used for guidance of sclerosing therapy. All horses showed abnormal findings on US, especially intratendinous neovascularisation in the affected limb but not in the contralateral limb. The CD findings had the same appearance as seen in human Achilles tendons with chronic tendinopathy. In all cases the intratendinous neovascularisation was successfully "shut down" peroperatively. The horses showed no signs of discomfort or worsening of symptoms during the short follow-up period after the procedure. The results indicate that the promising results from human medicine might be transferred to treatment of horses with chronic tendinopathy. In the future it will hopefully be possible to use the model from overused tendons in the horse to determine the best treatment of overuse injuries in humans as well. The animal model will allow experimental studies including substantial tissue sampling for mechanical and molecular biological analysis.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".