Low dose prophylaxis and antifibrinolytics: Options to consider with proven benefits for persons with haemophilia
Bibliographic record
Abstract
INTRODUCTION: Prophylaxis has become standard of care for persons with severe phenotype haemophilia (PWsH). However, 'standard prophylaxis' with either factor or non-factor therapies (emicizumab) is prohibitively expensive for much of the world. We sought to evaluate whether haemophilia care can be provided at a lower cost yet achieve good results using Lower dose/Lower frequency prophylaxis (LDP) and with increasing use of antifibrinolytics (Tranexamic acid and Epsilon amino caproic acid). METHODS: We identified 12 studies that collectively included 335 PWsH using LDP. Additionally, we undertook a literature search regarding the benefits of antifibrinolytics in haemophilia care. RESULTS: Identified studies show that LDP is far superior to no prophylaxis (On demand [OD] therapy) resulting in significant patient benefits. Patients on LDP showed (in comparison to patients OD) on average: 72% less total bleeds; 75% less joint bleeds; 91% less days lost from school; 77% less hospital admission days; and improved quality of life measures. These benefits come at similar or only slightly higher (< 2-fold greater) costs than OD therapy. Antifibrinolytics are effective adjunctive agents in managing bleeds (oral, nasal, intracranial, possibly other) and providing haemostasis for surgeries (particularly oral surgeries). Antifibrinolytics can substitute for more expensive factor concentrates or can reduce the use of such concentrates. There is evidence to show that antifibrinolytics may be used in conjunction with factor concentrates/emicizumab for more effective/less costly prophylaxis. CONCLUSIONS: The use of LDP along with appropriate and increased use of antifibrinolytics offers less resourced countries good options for managing patients with haemophilia.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".