Reported Exercise-Related Respiratory Symptoms and Exercise-Induced Bronchoconstriction in Asthmatic Children
Bibliographic record
Abstract
BACKGROUND: Unlimited physical activity is one of the key issues of asthma control and management. We investigated how reliable reported exercise-related respiratory symptoms (ERRS) are in predicting exercise-induced bronchoconstriction (EIB) in asthmatic children. METHODS: In this prospective study, 179 asthmatic children aged 7 - 15 years were asked for specific questions on respiratory symptoms related to exercise and allocated into two groups according to whether they complained about symptoms. Group I (n = 134) consisted of children answering "yes" to one or more of the questions and group II (n = 45) consisted of children answering "no" to all of the questions. RESULTS: Sixty-four of 179 children showed a positive exercise challenge test (ECT). There was no difference in the frequency of a positive test between children in group I (n = 48) and group II (n = 12) (P = 0.47). The sensitivity of a positive report for ERRS to predict a positive ECT was only 37%, with a specificity of 0.72. CONCLUSION: According to current guidelines, the report or lack of ERRS has direct consequences on treatment decisions. However, the history of ERRS did not predict EIB and one-third of asthmatic children without complaints of ERRS developed EIB during the ECT. This raises the question of the need for objective measures of bronchial hyperresponsiveness (BHR) in pediatric asthma management.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".