Pediatric Anaphylaxis in the Emergency Department
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to describe the quality of emergency department (ED) care for pediatric patients with anaphylaxis. The secondary objectives were to describe (1) the clinical presentation of pediatric patients with anaphylaxis including the proportion of patients meeting each of the National Institute of Allergy and Infectious Diseases (NIAID) consensus criteria and subcriteria and (2) the Interrater reliability (IRR) for applying the NIAID criteria. METHODS: We conducted a retrospective cross-sectional chart review of patients seen in a pediatric ED during a 2-year period. All charts were reviewed by a trained chart reviewer with 10% abstracted by a second reviewer. Data were analyzed using descriptive statistics including proportions, medians, and interquartile range. Interrater reliability was calculated using Cohen unweighted κ or percent agreement. RESULTS: Of the 250 charts reviewed, 84% (211) met the NIAID criteria for anaphylaxis (IRR, 1.0). Only 68% of patients received epinephrine in the ED or within 3 hours of the ED visit. Adherence was poor and IRR was variable, for measures reflecting documentation of discharge instructions and follow-up with a specialist. The IRR of reviewers for determining which patients met the NIAID criteria overall and for each subcriterion was high. CONCLUSIONS: Our findings highlight a gap between best practice and ED care. In addition, our results suggest that the NIAID criteria can reliably be used to retrospectively identify pediatric patients with anaphylaxis. Accurately identifying cases is a prerequisite for measuring gaps in management and developing interventions to improve care.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".