An MRI scale for assessment of haemophilic arthropathy from the International Prophylaxis Study Group
Bibliographic record
Abstract
Evaluation of prophylactic treatment of haemophilia requires sensitive methods. To design and test a new magnetic resonance imaging (MRI) scale for haemophilic arthropathy, two scales of a combined MRI scoring scheme were merged into a single scale which includes soft tissue and osteochondral subscores. Sixty-one joint MRI's of 46 patients with haemophilia were evaluated by four radiologists using the new and older scales. Forty-six of the joints were evaluated using two X-ray scales. For all MRI scores, interreader agreement and correlations with X-ray scores and lifetime number of haemarthroses were analysed. The interreader agreement intraclass correlation coefficient was 0.82, 0.89 and 0.88 for the soft tissue and osteochondral subscores and the total score, as evaluated according to the new MRI scale, compared to 0.80 and 0.89 as for the older scales. The total score and osteochondral subscore according to the new scale, as well as scores according to the older scales were correlated (P < 0.01) with number of haemarthroses (Spearman correlation 0.35-0.68) and with the X-ray scores (Spearman correlation 0.40-0.76), but no correlation (P > 0.05) was found between the soft tissue subscore of the new MRI scale and the X-ray scores. The new MRI scale is simpler to apply than the older and has similar reader reliability and correlation with lifetime number of haemarthroses, and by separating soft tissue and osteochondral changes it gives additional information. The new scale is useful for analyses of early and moderate stages of arthropathy, and may help to evaluate prophylactic haemophilia treatment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".