Children under 15 kg with food allergy may be at risk of having epinephrine auto-injectors administered into bone
Bibliographic record
Abstract
BACKGROUND: The Epipen® Jr and Allerject® 0.15 mg are currently the most commonly prescribed epinephrine auto-injectors (EAIs) for the management of anaphylaxis in pediatric patients in North America and Canada. To ensure rapid absorption, it should be administered intramuscularly into the anterolateral aspect of the thigh. We examined whether the 12.7-mm needle length of the Epipen® Jr and Allerject® 0.15 mg is adequate for delivering epinephrine intramuscularly in pediatric patients who weighed <15 kg. METHODS: Consecutive pediatric patients with food allergy weighing <15 kg who required an EAI were included. Ultrasounds of the mid-anterolateral thigh were performed under minimal (min) and maximal (max) pressure. Skin-to-muscle depth (STMD) and skin-to-bone depth (STBD) measurements were completed. Baseline characteristics were compared between patients with a STBDmax <12.7 mm vs. ≥12.7 mm. Linear regression including variables such as age, sex, body mass index (BMI) and race was performed. The proportion of patients with a STBDmax <12.7 mm was compared in those weighing <10 kg vs. 10-14.9 kg. RESULTS: One hundred patients were included; 29 (29%) had STBDmax <12.7 mm. Height (p = 0.02) and weight (p = 0.0002) differed significantly between the two groups. Approximately 19% of those weighing 10-14.9 kg and 60% of those <10 kg had a STBDmax <12.7 mm. In the multivariable regression analysis, BMI was found to be a significant predictor of STBDmax. CONCLUSIONS: A large proportion of children <15 kg prescribed an EAI is at risk of having the auto-injector administered into bone. Since alternative EAIs with shorter needle lengths are not currently available, EAIs should be prescribed with appropriate counselling in this population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".