Impact of aerobic training periodisation on global and regional right ventricular strain in coronary heart disease
Bibliographic record
Abstract
Linear aerobic training periodisation (LP) is recommended for patients with coronary heart disease (CHD). However, the effects of training periodisation on the right heart mechanics in patients with CHD have never been examined. This study aimed to explore the effects of LP and non-linear periodisation (NLP) on right heart mechanics. We prospectively randomised CHD patients to 12 weeks of aerobic training with LP or NLP. While there was a weekly increase in energy expenditure with LP, there was a steeper increase during the first 3 weeks, followed by a decrease in the fourth week with NLP. Echocardiography was performed at baseline and after the training period to assess the right ventricular free wall (RVFW) and right atrial strain. Thirty patients with CHD were included (NLP, n = 16; LP, n = 14). The traditional right and left heart parameters showed no significant time effects. There was a decrease of RVFW strain with time in both groups (+1.3 ± 0.9% with NLP, and +1.5 ± 0.8% with LP; p = 0.033). Mid-ventricular RVFW strain changed significantly with time (+2.0 ± 1.3% with NLP, and from +2.3 ± 1.2% with LP; p = 0.025). There was no time effect on the right atrial strain. In stable CHD patients, LP and NLP resulted in right ventricular strain decrements with a segment-specific pattern. This study was registered at ClinicalTrials.gov (identifier number: NCT03414996). Novelty: In stable coronary heart disease patients, both linear and non-linear aerobic training periodisation programs result in right ventricular strain decrements with time, particularly in the mid-ventricular segment. Traditional right and left heart parameters and right atrial strain showed no significant time effect in both 12 weeks aerobic training periodisation programs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".