Postexercise heart rate recovery in children: relationship with power output, blood pH, and lactate
Bibliographic record
Abstract
The aim of the present study was to determine whether differences in age-related heart rate recovery (HRR) kinetics were associated with differences in power output, blood lactate concentration ([La]b), and acidosis among children, adolescents, and adults. Ten prepubertal boys (aged 9.6 +/- 0.7 years), 6 pubertal boys (aged 15.2 +/- 0.8 years), and 7 men (aged 20.4 +/- 1.0 years) performed 10 repeated 10-s all-out cycling sprints, interspersed with 5-min passive recovery intervals. Mean power output (MPO) was measured during each sprint, and HRR, [La]b, and acidosis (pHb) were determined immediately after each sprint. Children displayed a shorter time constant of the primary component of HRR than adolescents and adults (17.5 +/- 4.1 vs. 38.0 +/- 5.3 and 36.9 +/- 4.9 s, p < 0.001 for both), but no difference was observed between adolescents and adults (p = 1.00). MPO, [La]b, and pHb were also lower in children compared with the other 2 groups (p < 0.001 for both). When data were pooled, HRR was significantly correlated with MPO (r = 0.48, p < 0.001), [La]b (r = 0.58, p < 0.001), and pHb (r = -0.60, p < 0.001). Covarying for MPO, [La]b, or pHb abolished the between-group differences in HRR (p = 0.42, p = 0.19, and p = 0.16, respectively). Anaerobic glycolytic contribution and power output explained a significant portion of the HRR variance following high-intensity intermittent exercise. The faster HRR kinetic observed in children appears to be related, at least in part, to their lower work rate and inherent lack of anaerobic metabolic capacity.
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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 | 0.002 |
| 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".