Hereditary angioedema due to C1 inhibitor deficiency: real-world experience from the Icatibant Outcome Survey in Spain
Bibliographic record
Abstract
BACKGROUND: receptor antagonist indicated for the acute treatment of hereditary angioedema (HAE) attacks. Our goal was to assess disease characteristics and icatibant treatment outcomes in patients with HAE due to C1 inhibitor deficiency (HAE type 1 or 2 (HAE-1/2)) from Spain relative to other countries participating in IOS. METHODS: Descriptive retrospective analyses of data are reported from 10 centers in Spain vs 51 centers in 12 other participating countries (July 2009 to January 2019). RESULTS: No meaningful differences were identified between patients in Spain (n = 119) and patients across other countries (n = 907) regarding median age at symptom onset (15.0 vs 12.0 years) or diagnosis (22.3 vs 20.5 years). Overall HAE attack rates (total attacks/total years of follow-up) were 2.66 in Spain and 1.46 across other countries. Patients in Spain reported fewer severe/very severe HAE attacks before treatment (41.0% vs 45.9%; P < 0.0001) and, for icatibant-treated attacks, longer median time to treatment (2.9 vs 1.0 h), time to attack resolution (18.0 vs 5.5 h), and total attack duration (24.6 vs 8.0 h). Use of androgens for long-term prophylaxis was higher in Spain (51.2% vs 26.7%). CONCLUSION: Patients with HAE-1/2 in Spain reported fewer severe/very severe attacks, administered icatibant later, and had longer-lasting attacks than did patients across other countries in IOS. These differences may indicate varying disease management practices (e.g., delayed icatibant treatment) and reporting. Efforts to raise awareness on the benefits of early on-demand treatment may be warranted. TRIAL REGISTRATION: NCT01034969.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".