Is there any relationship between exercise-induced laryngeal obstruction (EILO) and bronchial hyperresponsiveness (BHR) in Norwegian olympic athletes?
Bibliographic record
Abstract
Background: Exercise-induced laryngeal obstruction (EILO) and asthma present with similar symptoms, complicating diagnostic work-up. Bronchial hyperresponsiveness (BHR) is a hallmark of asthma. The relationship between EILO and BHR are therefore important to understand but remain underexplored. Athletes exhibit high rates of both conditions, providing a valuable population for study. Objective: To evaluate the prevalence of EILO in elite athletes and assess the association to BHR. Methods: In this retrospective cross-sectional study, Norwegian athletes participating in the Beijing 2008 summer Olympics (n=80: ♀=62, ♂=18) and in the Vancouver 2010 winter Olympics (n=63: ♀=21, ♂=42), are included. EILO was diagnosed using continuous laryngoscopy during exercise (CLE) or immediate post-exercise bronchoscopy, as feasible during exam. BHR was defined as a positive methacholine provocation test (PD20met≤0.8mg). Results: EILO was identified in 19 (13%) athletes, 13 (9 %) females and 6 (4 %) males. BHR was found in 20 (14%) athletes, with no significant association between EILO and BHR (Phi = -0.021). Co-occurrence of both conditions was found in 3 (2%) athletes, i.e. 16 % of those with EILO also had BHR. However, 8 (42%) athletes with EILO reported using asthma medication. Conclusion: EILO and BHR were both common in athletes but appeared to be unrelated. Notably, a large proportion of athletes with EILO used asthma medications, even in the absence of BHR. Healthcare providers should ensure that respiratory symptoms in athletes are properly evaluated using appropriate diagnostic methods.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".