Diagnostic evaluation and cardiopulmonary exercise test findings in young athletes with persistent symptoms following COVID-19
Bibliographic record
Abstract
Objectives Persistent or late-onset cardiopulmonary symptoms following COVID-19 may occur in athletes despite a benign initial course. We examined the yield of cardiac evaluation, including cardiopulmonary exercise testing (CPET), in athletes with cardiopulmonary symptoms after COVID-19, compared CPETs in these athletes and those without COVID-19 and evaluated longitudinal changes in CPET with improvement in symptoms. Methods This prospective cohort study evaluated young (18–35 years old) athletes referred for cardiopulmonary symptoms that were present>28 days from COVID-19 diagnosis. CPET findings in post-COVID athletes were compared with a matched reference group of healthy athletes without COVID-19. Post-COVID athletes underwent repeat CPET between 3 and 6 months after initial evaluation. Results Twenty-one consecutive post-COVID athletes with cardiopulmonary symptoms (21.9±3.9 years old, 43% female) were evaluated 3.0±2.1 months after diagnosis. No athlete had active inflammatory heart disease. CPET reproduced presenting symptoms in 86%. Compared with reference athletes (n=42), there was similar peak VO2but a higher prevalence of abnormal spirometry (42%) and low breathing reserve (42%). Thirteen athletes (62%) completed longitudinal follow-up (4.8±1.9 months). The majority (69%) had reduction in cardiopulmonary symptoms, accompanied by improvement in peak VO2and oxygen pulse, and reduction in resting and peak heart rate (all p<0.05). Conclusion Despite a high burden of cardiopulmonary symptoms after COVID-19, no athlete had active inflammatory heart disease. CPET was clinically useful to reproduce symptoms with either normal testing or identification of abnormal spirometry as a potential therapeutic target. Improvement in post-COVID symptoms was accompanied by improvements in CPET parameters.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".