Bradykinin-induced angioedema in the emergency department
Bibliographic record
Abstract
BACKGROUND: Acute airway angioedema commonly occurs through two distinct mechanisms: histamine- and bradykinin-dependent. Although they respond to distinct treatments, these two potentially life-threatening states present similarly. Poor recognition of the bradykinin-dependent pathway leads to treatment errors in the emergency department (ED), despite the availability of multiple pharmacologic options for hereditary angioedema (HAE) and other forms of bradykinin-induced angioedema. Here, we consider the pathophysiology and clinical features of bradykinin-induced angioedema, and we present a systematic literature review exploring the effectiveness of the available therapies for managing such cases. METHODS: PubMed searches using 'emergency', 'bradykinin' and various therapeutic product names identified studies reporting the efficacy of treatments for bradykinin-induced angioedema in the ED setting. In all, 22 studies met prespecified criteria and are analysed here. FINDINGS: Whereas histamine-induced angioedema has a faster onset and often presents with urticaria, bradykinin-induced angioedema is slower in onset, with greater incidence of abdominal symptoms. Acute airway angioedema in the ED should initially be treated with anaphylactic protocols, focusing on airway management and treatment with epinephrine, antihistamine and systemic steroids. Bradykinin-induced angioedema should be considered if this standard treatment is not effective, despite proper dosing and regard of beta-adrenergic blockade. Therapeutics currently approved for HAE appear as promising options for this and other forms of bradykinin-induced angioedema encountered in the ED. CONCLUSION: Diagnostic algorithms of bradykinin-induced angioedema should be followed in the ED, with early use of approved therapies to improve patient outcomes.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".