MOLECULAR MECHANISMS OF INHIBITOR DEVELOPMENT IN HEMOPHILIA
Bibliographic record
Abstract
The development of neutralizing antibodies in hemophilia is a serious complication of factor replacement therapy. These antibodies, also known as "inhibitors", significantly increase morbidity within the hemophilia population and lower the quality of life for these patients. People with severe hemophilia A have an overall 25-40% lifetime risk of inhibitor development, compared to that of 5-15% lifetime risk in those with moderate/mild hemophilia A. The risk is lower in hemophilia B population (about 1-5%) and occurrence of inhibitors is almost only seen in patients with severe hemophilia B. The understanding of the pathophysiological mechanism leading to the development of inhibitors in patients with hemophilia has improved considerably over the last 2 decades. Identification of early biomarkers which predict inhibitor development in previously untreated patients with hemophilia will assist in risk identification and possible early intervention strategies. In this review, we aim to summarize the molecular mechanisms of inhibitor development in hemophilia and to identify potential areas in need of further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".