Anaphylaxis cases presenting to primary care paramedics in Quebec
Bibliographic record
Abstract
Data on anaphylaxis cases in pre-hospital settings is limited. As part of the Cross Canada Anaphylaxis Registry (C-CARE), we assessed anaphylaxis cases managed by paramedics in Outaouais, Quebec. A software program was developed to prospectively record demographic and clinical characteristics as well as management of cases meeting the definition of the anaphylaxis. Univariate and multivariate logistic regressions were compared to assess factors associated with severity of reactions and epinephrine use. Among 33,788 ambulance calls of which 23,486 required transport, 104 anaphylaxis cases were identified (anaphylaxis rate of 0.31% [95%CI, 0.25%, 0.37%] among all ambulance calls and 0.44% [95%CI, 0.36%, 0.54%] among those requiring transport). The median age was 46.8 years and 41.3% were males. The common triggers included food (32.7% [95%CI, 24.0%, 42.7%]), drugs (24.0% [16.4%, 33.6%]), and venom (17.3% [10.8%, 26.2%]). Among all reactions, 37.5% (95%CI, 28.4%, 47.6%) were severe. Epinephrine was not administered in 35.6% (95%CI, 26.6%, 45.6%) of all cases. Males were more likely to have severe reactions (Odds ratio [OR]: 2.50 [95%CI, 1.03, 6.01]). Venom-induced reactions and severe anaphylaxis were more likely to be managed with epinephrine (OR: 6.9 [95%CI, 1.3, 35.3] and 4.2 [95%CI, 1.5, 12.0], respectively). This is the first prospective study evaluating anaphylaxis managed by paramedics. Anaphylaxis accounts for a substantial proportion of the cases managed by paramedics in Outaouais, Quebec and exceeds prior reports of the proportion of Quebec emergency room visits attributed to anaphylaxis. Although guidelines recommend prompt use of epinephrine for all cases of anaphylaxis, more than a third of cases did not receive epinephrine. It is crucial to develop educational programs targeting paramedics to promote the use of epinephrine in all cases of anaphylaxis regardless of the specific trigger.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".