Effects of 12-Week Home-based Resistance Training on Peripheral Muscle Oxygenation in Children With Congenital Heart Disease: A CHAMPS Study
Bibliographic record
Abstract
Background A hallmark feature of children with congenital heart disease (CHD) is exercise intolerance. Whether a home-based resistance training intervention improves muscle oxygenation (as measured by tissue oxygenation index, TOI) and exercise tolerance ( V ˙ O 2 reserve) during aerobic exercise in children with CHD compared with healthy children is unknown. Methods We report findings for 10 children with CHD (female/male: 4/6; mean ± standard deviation age: 13 ± 1 years) and 9 healthy controls (female/male: 5/4; age: 12 ± 3 years). Children with CHD completed a 12-week home-based exercise programme in addition to 6 in-person sessions. Exercise tolerance was assessed with a peak exercise test. Vastus lateralis TOI was continuously sampled during the peak V ˙ O 2 test via near-infrared spectroscopy. Results There was a medium effect (Cohen's d = 0.67) of exercise training on lowering TOI at peak exercise (pre: 30 ± 16 %total labile signal vs post: 20 ± 13 % total labile signal; P = 0.099). Exercise training had a small effect (Cohen's d = 0.23) on increasing V ˙ O 2 reserve by 1.6 mL/kg/min (pre: 27.2 ± 5.7 mL/kg/min vs post: 29.4 ± 8.8 mL/kg/min; P = 0.382). There was also a small effect (Cohen's d = 0.27) of exercise on peak heart rate (pre: 175 ± 23 beats/min vs post: 169 ± 21 beats/min; P = 0.18). TOI, V ˙ O 2 reserve, and heart rate were generally lower than healthy control participants. Conclusions Our findings indicate that home-based resistance training may enhance skeletal muscle oxygen extraction (lower TOI) and subsequently V ˙ O 2 reserve in children with CHD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".