Consequences of intra‐articular bleeding in haemophilia: science to clinical practice and beyond
Bibliographic record
Abstract
Blood in the joint causes a number of physiological and pathological events that eventually lead to haemophilic arthropathy. Animal models show that blood in the joint induces inflammation that continues long after blood has been cleared. TNF-alpha, IL-1 beta and IL-6 are inflammatory mediators that increase following haemarthrosis in haemophilic mice. Conventional anti-inflammatory drugs have failed to demonstrate a lasting effect in preventing haemophilic arthropathy. A new TNF-alpha antagonist has shown promising results in haemophilic mice. Similarly, the use of cyclo-oxygenase-2 inhibitors may reduce angiogenesis associated with the healing process following bleeding and the associated tissue damage. Animal models are useful for studying the pathophysiology of haemarthropathy, however, when applying results from animals to humans, the differences in matrix turnover rate, thickness of cartilage and joint biomechanics must be kept in mind. In people with haemophilia, there is a variable response to haemarthrosis as demonstrated by magnetic resonance imaging (MRI). Up to 30% of subjects have normal MRI despite having three or more haemarthroses into the same joint. Once bone damage is present, little can be done to restore anatomic integrity. Several molecules, including members of the bone morphogenic protein subfamily, have been injected into bone defects in non-haemophilic subjects with some evidence of benefit. To achieve the primary goal of reducing blood in the joint and the negative sequelae, it is questionable to use ice to treat haemarthrosis. Indeed low temperature is associated with impairment of coagulation enzyme activity and platelet function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".