Inhibitor treatment in haemophilias A and B: summary statement for the 2006 international consensus conference
Bibliographic record
Abstract
Participants in an international conference on the management of haemophilia patients with inhibitors developed a jointly authored summary of the findings and conclusions of the conference. Current knowledge of the genetic and immunologic mechanisms underlying inhibitor development was briefly summarized. Concerning the purported treatment-related risk factors, conference participants commented on the limitations of the available evidence and the need for more rigorous prospective research in a fully genotyped population. Other clinical considerations discussed included the unproved utility of routine surveillance, the need for assay standardization, the management of acute bleeding and approaches to joint disease prophylaxis and immune tolerance induction (ITI). A number of issues were identified as needing further investigation in larger prospective studies, ideally through international cooperation. Such studies should enroll cohorts that have been scrupulously defined in terms of mutation status and treatment exposure. Finally, conference participants urged their colleagues to participate in the currently ongoing international trials of ITI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".