Hereditary Angioedema With Normal C1 Inhibitor: A Quarter Century of Forward Progress and Persisting Obstacles
Bibliographic record
Abstract
Hereditary angioedema with normal C1 inhibitor (HAE-nl-C1INH) was initially described almost a quarter century ago. Considerable progress toward unraveling the mysteries of this complex disease has been made during the intervening years. The ability to diagnose, classify, and treat HAE-nl-C1INH, however, continues to present daunting clinical challenges. In this article we have attempted to summarize current areas of scientific consensus and provide some insights to assist physicians caring for affected individuals. Coherently describing the field of HAE-nl-C1INH in many ways embodies a precarious balance between assertions anchored by data versus conjecture. In this Rostrum we have tried to encapsulate the numerous scientific developments over the past 25 years into a proposed classification schema intended to facilitate decisions when evaluating patients with recurrent angioedema. Founded on an accurate diagnosis in conjunction with an appreciation of the underlying pathomechanism, targeted patient treatment strategies can be appropriately designed. It is hoped that this approach will lay the groundwork for future advances in our understanding of HAE-nl-C1INH while bringing patients ever closer to the goal of leading a normal life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".