Training effects on peripheral muscle oxygenation and performance in children with congenital heart diseases
Bibliographic record
Abstract
We investigated the effect of training on peripheral muscular performance and oxygenation during exercise and recovery in children with congenital heart diseases (CHD). Eighteen patients with CHD aged 12 to 15 years were randomly assigned into either an individualized 12-week aerobic cycling training group (TG) or a control group (CG). Maximal voluntary contraction (MVC) and endurance at 50% MVC (time to exhaustion, T(lim)) of the knee extensors were measured before and after training. During the 50% MVC exercise and recovery, near-infrared spectroscopy (NIRS) was used to assess the fall in muscle oxygenation, i.e., deoxygenation ([Formula: see text]) of the vastus lateralis, the mean rate of decrease in muscle oxygenation, the half time of recovery (T(1/2R)), and the recovery speed to maximal oxygenation (R(S)). There was no effect of time on any parameter in the CG. After training, significant improvements were observed in TG for MVC (101.6 ± 14.0 vs. 120.2 ± 19.4 N·m, p < 0.01) and T(lim) (66.2 ± 22.6 vs. 86.0 ± 23.0 s, p< 0.01). Increased oxygenation (0.20 ± 0.13 vs. 0.15 ± 0.07 a.u., p < 0.01) and faster mean rate of decrease in muscle oxygenation were also shown after training in TG (1.22 ± 0.45 vs. 1.71 ± 0.78%·s(-1), p < 0.001). Moreover, a shorter recovery time was observed in TG after training for T(1/2R) (27.2 ± 6.1 vs. 20.8 ± 4.2 s, p < 0.01) and R(S) (63.1 ± 18.4 vs. 50.3 ± 11.4 s, p < 0.01). A significant relationship between the change in [Formula: see text] and both MVC (r = 0.95, p < 0.001) and T(lim) (r = 0.90, p < 0.001) in TG was observed. We concluded that exercise training improves peripheral muscular function by enhancing strength and endurance performance in children with CHD. This improvement was associated with increased oxygenation of peripheral muscles and faster recovery.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".