Treatment of Hereditary Angioedema: items that need to be addressed in practice parameter
Bibliographic record
Abstract
BACKGROUND: Hereditary Angioedema (HAE) is a rare, autosomal dominant (AD) disorder caused by a C1 esterase inhibitor (C1-inh) deficiency or qualitative defect. Treatment of HAE in many parts of the world fall short and certain items need to be addressed in future guidelines. OBJECTIVE: To identify those individuals who should be on long-term prophylaxis for HAE. Additionally, to determine if prodromal symptoms are sensitive and specific enough to start treatment with C-1 INH and possibly other newly approved therapies. Also, to discuss who is appropriate to self-administer medications at home and to discuss training of such patients. METHODS: A literature review (PubMed and Google) was performed and articles published in peer-reviewed journals, which addressed HAE prophylaxis, current HAE treatments, prodromal symptoms of HAE and self-administration of injected home medications were selected, reviewed and summarized. RESULTS: Individuals whom have a significant decrease in QOL or have frequent or severe attacks and who fail or are intolerant to androgens should be considered for long-term prophylaxis with C1INH. Prodromal symptoms are sensitive, but non-specific, and precede acute HAE attacks in the majority of patients. Although the treatment of prodromal symptoms could lead to occasional overtreatment, it could be a viable option for those patients able to adequately predict their attacks. Finally, self-administration, has been shown to be feasible, safe and effective for patients who require IV therapy for multiple other diseases to include, but not limited to, hemophilia. CONCLUSIONS: Prophylactic therapy, treatment at the time of prodromal symptoms and self-administration at home all should allow a reduction in morbidity and mortality associated with HAE.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".