The influence of maturation on exercise-induced cardiac remodelling and haematological adaptation
Bibliographic record
Abstract
Cardiovascular and haematological adaptations to endurance training facilitate greater maximal oxygen consumption, and such adaptations maybe augmented following puberty. Therefore, we compared left ventricular (LV) morphology (echocardiography), blood volume, haemoglobin (Hb) mass (CO-rebreathe) and in endurance-trained and untrained boys (n = 42, age = 9.0-17.1 years, = 61.6±7.2 mL∙kg∙min, and n = 31, age = 8.0-17.7 years, O2max = 46.5±6.1 mL∙kg∙min, respectively) and girls (n = 45, age = 8.2-17.0 years, O2max = 51.4±5.7 mL∙kg∙min and n = 36, age = 8.0-17.6 years, O2max = 39.8±5.7 mL∙kg∙min, respectively). Pubertal stage was estimated via maturity offset, with participants classified as pre- or post-peak height velocity (PHV). Pre-PHV, only a larger LV end-diastolic volume/lean body mass (EDV/LBM) for trained boys (+0.28 mL∙kgLBM, P = 0.007) and a higher Hb mass/LBM for trained girls (+1.65 g∙kgLBM, P = 0.007) were evident compared to untrained controls. Post-PHV, LV mass/LBM (boys:+0.50 g∙kgLBM, P = 0.0003; girls:+0.35 g∙kgLBM, P = 0.003), EDV/LBM (boys:+0.35 mL∙kgLBM, P<0.0001; girls:+0.31 mL∙kgLBM, P = 0.0004), blood volume/LBM (boys:+12.47 mL∙kgLBM, P = 0.004; girls:+13.48 mL∙kgLBM, P = 0.0002.) and Hb mass/LBM (boys:+1.29 g∙kgLBM, P = 0.015; girls:+1.47 g∙kgLBM, P = 0.002) were all greater in trained vs. untrained groups. Pre-PHV, EDV (R2adj = 0.224, P = 0.001) in boys, and Hb mass and interventricular septal thickness (R2adj = 0.317, P = 0.002) in girls partially accounted for the variance in O2max. Post-PHV, stronger predictive models were evident via the inclusion of LV wall thickness and EDV in boys (R2adj = 0.608, P<0.0001), and posterior wall thickness and Hb mass in girls (R2adj = 0.490, P<0.0001). In conclusion, cardiovascular adaptation to exercise training is more pronounced post-PHV, with evidence for a greater role of central components for oxygen delivery.
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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) | 0.002 | 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".