Generic Health‐Related Quality of Life of Children With Severe Peanut or Tree Nut Allergy
Bibliographic record
Abstract
AIM: Food allergies may decrease health-related quality of life. We assessed health-related quality of life in Finnish children at risk of a severe peanut or tree nut allergy and their parents. METHODS: Study included children aged 3-15 years referred to Tampere University Hospital for suspected severe nut allergy. Eligibility criteria included a history of anaphylaxis and/or molecular immunology testing referring for severe peanut and/or tree nut allergy. Health-related quality of life was assessed with generic questionnaires 15D for adults, 16D for teenagers or 17D for children, with scores compared with age group-matched population references. RESULTS: A total of 101 children (mean age 7.7 ± 2.9 years) and parent pairs were enrolled. The mean 16D score for 11 teenagers aged 12-15 years and mean 15D score for 101 parents was similar to reference populations; parental distress was borderline statistically worse (0.890 vs. 0.932, p = 0.013). The mean 17D score for 90 children aged 3-11 years was significantly higher (0.959 vs. 0.938) than in references (p < 0.01). CONCLUSION: Children with a suspected severe peanut or tree nut allergy had a comparable health-related quality of life to the reference population. Distress among their parents seemed to be increased, warranting more focus on parental counselling.
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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 | 0.000 | 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) | 0.002 | 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".