The asthma‐rhinitis multimorbidity is associated with IgE polysensitization in adolescents and adults
Bibliographic record
Abstract
BACKGROUND: Children with multimorbid asthma and rhinitis show IgE polysensitization to several allergen sources. This association remains poorly studied in adolescents and adults using defined allergen molecules. We investigated IgE sensitization patterns towards a broad panel of aeroallergen components in adults and adolescents with a focus on individuals with asthma and rhinitis multimorbidity. METHODS: IgE reactivity to 64 micro-arrayed aeroallergen molecules was determined with the MeDALL-chip in samples from the French EGEA study (n = 840, age = 40.7 ± 17.1) and the Swedish population-based birth cohort BAMSE (n = 786, age = 16 ± 0.26). The age- and sex-adjusted associations between the number of IgE-reactive allergen molecules (≥0.3 ISU) and the asthma-rhinitis phenotypes were assessed using a negative binomial model. RESULTS: Groups representing 4 phenotypes were identified: no asthma-no rhinitis (A-R-; 30% in EGEA and 54% in BAMSE), asthma alone (A+R-; 11% and 8%), rhinitis alone (A-R+; 15% and 24%) and asthma-rhinitis (A+R+; 44% and 14%). The numbers of IgE-reactive aeroallergen molecules significantly differed between phenotypes (median in A-R-, A+R-, A-R+ and A+R+: 0, 1, 2 and 7 in EGEA and 0, 0, 3 and 5 in BAMSE). As compared to A-R- subjects, the adjusted ratio of the mean number of IgE-reactive molecules was higher in A+R+ than in A+R- or A-R+ (10.0, 5.4 and 5.0 in EGEA and 7.2, 0.7 and 4.8 in BAMSE). CONCLUSION: The A+R+ phenotype combined the sensitization pattern of both the A-R+ and A+R- phenotypes. This multimorbid polysensitized phenotype seems to be generalizable to various ages and allergenic environments and may be associated with specific mechanisms.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".