The relevance of MRI findings in joints of persons with haemophilia: Insights from the last decade
Bibliographic record
Abstract
osteochondral abnormalities, outcome assessment, subclinical bleeding Most bleeding episodes in persons with haemophilia (PwH) occur in the large synovial joints (elbows, knees, and ankles).Recurrent joint bleeding eventually leads to irreversible haemophilic arthropathy, which causes pain, reduced functionality, and thus reduced quality of life.Prophylactic treatment prevents most bleeding episodes.1 Even in the absence of clinically overt joint bleeding, long-term progression to arthropathy is observed.Subclinical bleeding and inflammation are therefore thought to contribute to the development of arthropathy.2-4 Detection of these subclinical processes is becoming increasingly important in the prevention of arthropathy in PwH as overt spontaneous joint bleeding is almost completely avoided by prophylaxis with new (non-factor) replacement therapies.5 Magnetic resonance imaging (MRI) is considered the gold standard for evaluation of early blood-induced joint changes in PwH.In 2005, the International Prophylaxis Study Group (IPSG) published compatible scales for progressive and additive MRI assessment based on the Denver MRI score and the European MRI score.6 These scores were combined in a comprehensive scoring scheme in 2012.7 Based on an appraisal of the original IPSG MRI scale, 8 the score is now updated to the IPSG MRI Scale version 2.0 by Lundin and colleagues.9 To provide more insight on the clinical relevance of MRI findings, we provide an overview of research on the clinical relevance of MRI findings evaluated by IPSG MRI Scale version 2.0.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".