Early Detection of Allergy Symptoms in Children and Adolescents, Characteristics of Possible Pathogens, Pre-Treatment Prevention Measures (in Poland)
Bibliographic record
Abstract
Background: The purpose of this study was to investigate the main allergens and signs of the onset of allergic diseases and explore methods of prevention that do not include medicines. Methods: Non-parametric statistical methods were used. A retrospective study was conducted, which included 270 case histories. The average age of the patients was 19 (12.5; 40.1) years, 127 (47%) were men and 143 (53%) were women. Clinical diagnoses, early symptoms, allergen spectrum, and treatment recommendations provided by doctors were analyzed. It was established that the early signs of allergic rhinitis and rhinoconjunctivitis are nasal congestion, runny nose, and lacrimation, and the onset of atopic dermatitis is -characterized by dry and itchy skin. Results: Allergy to triggers from one group was present in 136 (50.4%) patients, irritants from two groups – in 95 (35.2%) patients, and irritants from three groups – in 39 (14.4%) patients. Polish doctors advised patients to limit their exposure to allergens but did not give recommendations for concrete actions. Conclusion: The results of the study can be used to help in the identification of the most common symptoms of allergic diseases and allergens, which is vital for the early diagnosis of this pathology by clinicians.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".