Serial Exercise Testing in Children With Known or Suspected Congenital and Acquired Heart Disease: A Narrative Review and Survey of Current Practice
Bibliographic record
Abstract
BACKGROUND: Exercise parameters can be altered in children with congenital heart disease or acquired heart disease compared with children with normal hearts. Exercise testing has proven a useful tool to predict patient outcomes and even the need for reintervention in several cardiovascular disease processes. There are established guidelines for serial exercise stress testing in adults with congenital heart disease, but corollary guidelines do not exist for the pediatric population. METHODS AND RESULTS: A narrative literature review was completed. Evidence was ranked by a 4-point scale as outlined by the American College of Sports Medicine evidence categories. A survey was sent to experts in pediatric exercise physiology across the country regarding their current testing practices for 26 unique congenital heart disease or known or suspected acquired heart disease lesions. Survey questions were related to the frequency of testing, the age at which exercise testing is started, and if the frequency of testing is altered by a patient presenting with symptoms. Our literature search yielded 122 relevant studies pertaining to exercise stress testing in pediatric heart disease. We received 59 responses to our survey from 33 unique institutions in the United States and Canada. CONCLUSIONS: Twenty-one summaries were provided regarding exercise stress testing in pediatric patients with heart disease. Multicentered or national stress testing registries may allow for adequate sample sizes of rare pediatric diseases to allow for development of improved guidelines regarding the type and timing of stress testing.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".