Defining phenotypes of wheeze at preschool age: Comparison of episodic vs multitrigger wheeze
Bibliographic record
Abstract
Rationale Wheeze at preschool age includes different disease entities. It has been proposed that episodic wheeze (only with viral infections) and multitrigger wheeze may represent distinct phenotypes. Aim To define clinical and pathological features typical of children with episodic or multitrigger wheeze at preschool age. Methods We studied 55 children undergoing bronchoscopy for clinical indications:11 with episodic wheeze (4;1-6 yrs), 24 with multitrigger wheeze (4;1-6) and 20 controls (4;2-6). Structural and inflammatory changes were assessed in bronchial biopsies by histochemistry and immunohistochemistry. Results Age at onset (1.2;0.5-4 vs 1;0-3.5yrs) and symptom duration (3;1-3.5 vs 2.5;1-6yrs) were similar in children with episodic and multitrigger wheeze. Prevalence of atopy (45%vs 40%) and number of infectious episodes (mean:1/month) were similar in the 2 groups. Children with episodic and those with multitrigger wheeze had similar airway pathology with higher numbers of mast cells (461;100-800 and 441;113-95/mm 2 ) and eosinophils (50;0-586 and 63;0-267/mm 2 ) compared to controls (143;8-650/mm 2 ,p=0.0005 and 9,0-200/mm 2 ,p=0.01). Epithelial loss and BM thickness were also increased in episodic and multitrigger wheezers and correlated with mast cell count (r=0.36,p<0.01 and r=0.40,p<0.01). Pathological and clinical features were not dependent on age or atopic status. Conclusion Children with episodic wheeze at preschool age are indistinguishable from those with multitrigger wheeze in pattern of symptom onset and duration, prevalence of atopy and airway pathology. This suggests that episodic and multitrigger wheezers represent the same disease with different attack predisposition.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".