Inhibitor development in haemophilia according to concentrate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Inhibitor development represents the most serious side effect of haemophilia treatment. Any difference in risk of inhibitor formation depending on the product used might be of clinical relevance. It was this study's objective to assess inhibitor development according to clotting factor concentrate in severe haemophilia A and B. The European Haemophilia Safety Surveillance (EUHASS) was set up as a study monitoring adverse events overall and according to concentrate. Since October 2008, inhibitors were reported at least quarterly. Number of treated patients was reported annually, specifying the number of patients completing 50 exposure days (Previously Untreated Patients, PUPs) without inhibitor development. Cumulative incidence, incidence rates and 95 % confidence intervals (CI) were calculated. Data from October 1, 2008 to December 31, 2012 were analysed for 68 centres that validated their data. Inhibitors developed in 108/417 (26 %; CI 22-30 %) PUPs with severe haemophilia A and 5/72 (7 %; CI 2-16%) PUPs with severe haemophilia B. For Previously Treated Patients (PTPs), 26 inhibitors developed in 17,667 treatment years [0.15/100 treatment years; CI 0.10-0.22) for severe haemophilia A and 1/2836 (0.04/100; (CI 0.00-0.20) for severe haemophilia B. Differences between plasma-derived and recombinant concentrates, or among the different recombinant FVIII concentrates were investigated. In conclusion, while confirming the expected rates of inhibitors in PUPs and PTPs, no class or brand related differences were observed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it