Tackling nasal symptoms in athletes: moving towards personalized medicine
Bibliographic record
Abstract
Adequate nasal breathing is indispensable for athletes and nasal symptoms have been shown to inter-fere with their subjective feeling of comfortable breathing and quality of life. Nasal symptoms are caused by either structural abnormalities or mucosal pathology. Structural pathologies are managed differently from mucosal disease and therefore adequate diagnosis is of utmost importance in athletes in order to choose the correct treatment option for the individual. Literature suggests that nasal symp-toms are more prevalent in athletes compared to the general population and certain sport environments might even trigger the development of symptoms. Given the high demands of respiratory function in athletes, insight into triggering factors is of high importance for disease prevention. Also, it has been suggested that athletes are more neglectful to their symptoms and hence remain undertreated, meaning that special attention should be paid to education of athletes and their caregivers. This review aims at giving an overview of nasal physiology in exercise as well as the possible types of nasal pathology. Additionally, diagnostic and treatment options are discussed and we focus on un-met needs for the management and prevention of these symptoms in athletes within the concept of precision medicine.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".