Dilemmas on emicizumab in children with haemophilia A: A survey of strategies from PedNet centres
Bibliographic record
Abstract
INTRODUCTION: Haemophilia A care has changed with the introduction of emicizumab. Experience on the youngest children is still scarce and clinical practice varies between haemophilia treatment centres. AIM: We aimed to assess the current clinical practice on emicizumab prophylaxis within PedNet, a collaborative research platform for paediatricians treating children with haemophilia. METHODS: An electronic survey was sent to all PedNet members (n = 32) between October 2022 and February 2023. The survey included questions on the availability of emicizumab, on the practice of initiating prophylaxis in previously untreated or minimally treated patients (PUPs or MTPs) and emicizumab use in patients with or without inhibitors. RESULTS: All but four centres (28/32; 88%) responded. Emicizumab was available in clinical practice in 25/28 centres (89%), and in 3/28 for selected patients only (e.g. with inhibitors). Emicizumab was the preferred choice for prophylaxis in PUPs or MTPs in 20/25 centres; most (85%) started emicizumab prophylaxis before 1 year of age (30% before 6 months of age) and without concomitant FVIII (16/20; 80%). After the loading dose, 13/28 centres administered the recommended dosing, while the others adjusted the interval of injections to give whole vials. In inhibitor patients, the use of emicizumab during ITI was common, with low-dose ITI being the preferred protocol. CONCLUSION: Most centres choose to initiate prophylaxis with emicizumab before 12 months of age and without concomitant FVIII. In inhibitor patients, ITI is mostly given in addition to emicizumab, but there was no common practice on how to proceed after successful ITI.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".