Pharmacologic treatment of anaphylaxis: can the evidence base be strengthened?
Bibliographic record
Abstract
PURPOSE OF REVIEW: To evaluate the evidence base for the pharmacologic treatment of anaphylaxis. RECENT FINDINGS: In this review, we focus on four classes of medications (the alpha/beta-agonist epinephrine (adrenaline), H1-antihistamines, H2-antihistamines, and glucocorticoids) that are used in healthcare settings for the initial treatment of anaphylaxis. Epinephrine and many H1-antihistamines and glucocorticoids were introduced before the era of randomized controlled trials and before the era of evidence-based medicine. In anaphylaxis, no randomized controlled trials that are free from methodological problems and meet current standards have been performed with these medications, or with H2-antihistamines. The evidence base for epinephrine injection is stronger than the evidence base for use of other medications in anaphylaxis. Guidelines unanimously recommend prompt injection of epinephrine as the life-saving first-line medication in anaphylaxis; however, they differ in their recommendations for H1-antihistamines, H2-antihistamines, and glucocorticoids. Epinephrine is the only medication that is universally available for anaphylaxis treatment in healthcare settings worldwide. Paradoxically, it is underused in anaphylaxis treatment. SUMMARY: For ethical reasons, there should never be a placebo-controlled trial of epinephrine in anaphylaxis. We discuss why the possibility of conducting randomized placebo-controlled trials with H1-antihistamines, H2-antihistamines, and particularly with glucocorticoids in anaphylaxis should be considered in order to improve the evidence base for treatment and guide clinical decision-making. We also describe the precautions that will be needed if randomized controlled trials are conducted in anaphylaxis.
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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 | 0.027 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".