Low prevalence of inhibitor antibodies in the Canadian haemophilia population
Bibliographic record
Abstract
Annual reporting of inhibitors to factors (FVIII) and IX (FIX) to the Canadian Haemophilia Registry has suggested a lower prevalence than that published in the literature. We performed a prospective study to determine the prevalence of patients with inhibitors directed against either FVIII or FIX. Patients with inhibitors were classified as: (i) inhibitor test positive; (ii) inhibitor test negative but on immune tolerance induction (ITI); (iii) inhibitor test negative but bypass treatment recommended; or (iv) inhibitor resolved. One year later, the cohort was re-classified. The prevalence of inhibitors on 1 May, 2007 was 3.3% for haemophilia A, 0.6% for haemophilia B and 8.9% and 2.1% for severe haemophilia A and B. One year later 17 individuals gained and 11 individuals lost inhibitor status (10 of these with ITI). This study suggests that the prevalence of inhibitors in our population is lower than that was previously published. We hypothesize that this is primarily due to the increased use of ITI, but other factors may be the unselected nature of the cohort and the restriction of the study to one date thereby conforming as close as practical to the definition of prevalence rather than incidence. The classification system used in this study was easy for clinics to apply and was important in defining the population with inhibitors.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".