Height and weight trajectories are associated with submaximal and maximal exercise capacity in children with congenital heart defects
Bibliographic record
Abstract
Abstract Children with congenital heart defects (CHD) are often short/lightweight relative to peers. Limited growth, particularly height, may reflect energy deficits impacting physical activity. Latent class analyses of growth from birth and Bruce treadmill exercise data retrospectively identified for height, weight, and body mass index z-scores growth trajectories. Linear regression models examined exercise parameters by growth trajectory, adjusting for age/sex/CHD severity. A total of 213 children with CHD (39% female, 12.1 ± 2.9 years) achieved 85.8 ± 10.1% of the predicted peak heart rate. Peak heart rate among children whose height was consistently below average (class 1) was 15.2 ± 4.9 beats/min lower than children with other height trajectories. These children also attained a lower percentage of predicted peak heart rate. Children whose weight (p = 0.03) or body mass index (p < 0.001) z-score increased throughout childhood had significantly lower exercise duration (mean difference 1–2 min) than children whose growth trajectories were stable or declined. Children with above-average weight or an increasing body mass index also used a higher percentage of their heart rate reserve at each submaximal exercise stage. A very low height z-score trajectory is associated with decreased exercise capacity that may increase the risk for morbidities associated with a sedentary lifestyle. Future studies should examine potential mechanisms for the observed height deficits, such as an inadequate energy supply that could impact physical activity participation, congestive heart failure, cyanosis, pubertal stage, supplemental feeding history, or familial growth patterns. Prospective studies examining growth in relation to objective measures of daily physical activity are required.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".