Adaptation of Left Ventricular Twist Mechanics in Exercise-Trained Children Is Only Evident after the Adolescent Growth Spurt
Bibliographic record
Abstract
BACKGROUND: The extent of structural cardiac remodeling in response to endurance training is maturity dependent. In adults, this structural adaptation is often associated with the adaptation of left ventricular (LV) twist mechanics. For example, an increase in LV twist often follows an expansion in end-diastolic volume, whereas a reduction in twist may follow a thickening of the LV walls. While structural cardiac remodeling has been shown to be more prominent post-peak height velocity (PHV), it remains to be determined how this maturation-dependent structural remodeling influences LV twist. Therefore, we aimed to (1) compare LV twist mechanics between trained and untrained children pre- and post-PHV and (2) investigate how LV structural variables relate to LV twist mechanics pre- and post-PHV. METHODS: Left ventricular function and morphology were assessed (echocardiography) in endurance-trained and untrained boys (n = 38 and n = 28, respectively) and girls (n = 39 and n = 34, respectively). Participants were categorized as either pre- or post-PHV using maturity offset to estimate somatic maturation. RESULTS: Pre-PHV, there were no differences in LV twist or torsion between trained and untrained boys (twist: P = .630; torsion: P = .382) or girls (twist: P = .502; torsion: P = .316), and LV twist mechanics were not related with any LV structural variables (P > .05). Post-PHV, LV twist was lower in trained versus untrained boys (P = .004), with torsion lower in trained groups, irrespective of sex (boys: P < .001; girls: P = .017). Moreover, LV torsion was inversely related to LV mass (boys: r = -0.55, P = .001; girls: r = -0.46, P = .003) and end-diastolic volume (boys: r = -0.64, P < .001; girls: r = -0.36, P = .025) in both sexes. CONCLUSIONS: A difference in LV twist mechanics between endurance-trained and untrained cohorts is only apparent post-PHV, where structural and functional remodeling were related.
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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".