Platelet‐activating factor acetylhydrolase is a biomarker of severe anaphylaxis in children
Bibliographic record
Abstract
BACKGROUND: There is limited ability to predict the severity of allergic reactions in children. Data derived predominantly from adults have implicated the platelet-activating factor pathway as a potential contributor to severe anaphylaxis. In this study, we sought to prospectively assess involvement of key components of the platelet-activating factor pathway in pediatric patients with anaphylaxis. METHODS: Forty-six pediatric patients (<18 years) presenting with acute anaphylaxis were assessed. Anaphylaxis severity was graded and serum anaphylaxis markers were measured acutely and in 36 children who returned for follow-up >4 weeks after their acute presentation. These markers were compared with pediatric laboratory reference sera. RESULTS: Severe anaphylaxis was experienced by 12/46 (26%) and mild-moderate anaphylaxis in 34/46 (74%) children. Platelet-activating factor acetylhydrolase (PAF-AH) activity was inversely associated with severe anaphylaxis: 9/12 children with severe anaphylaxis had reduced PAF-AH activity as compared with 14/34 with mild-moderate anaphylaxis (p < .05). Furthermore, 3/3 children who required intensive care had markedly reduced mean PAF-AH (nmol/ml/min) (13.73, 95%CI: 7.42-20.03) versus 20/23 who required ward/emergency department care (17.81, 95%CI: 16.80-18.83; p < .05). In children with anaphylaxis, PAF-AH during acute anaphylaxis was unchanged relative to the child's basal levels (mean, 17.26, 95%CI: 16.10-18.42 vs 17.50, 95%CI: 16.21-18.78, p = .63) and was lower than healthy pediatric controls (mean 19.21; 95%CI:18.21-20.21; p < .05). CONCLUSION: Decreased serum PAF-AH activity is a biomarker of severe anaphylaxis. Levels of this enzyme do not change from basal levels during acute anaphylaxis. Our results show that PAF-AH is a biomarker of anaphylaxis severity in children. This key regulatory enzyme may modulate susceptibility to severe anaphylaxis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.005 | 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 teacher head, 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".