The Effect of High-Intensity Rowing and Combined Strength and Endurance Training on Left Ventricular Systolic Function and Morphology
Bibliographic record
Abstract
Combined strength and endurance training may result in alterations in left ventricular (LV) systolic function and morphology, however, the acute effect of high-intensity rowing exercise and concurrent training-induced adaptations on LV systolic function are not well known. The purpose of this investigation was to assess LV systolic function before and after a simulated 2000-m rowing race on a Concept II rowing ergometer and evaluate these adaptations following 10 weeks of concurrent strength and endurance training. Furthermore, resting LV morphology was assessed prior to and following the 10-week training program. Ten male subjects underwent two-dimensional echocardiograms at rest, immediately following (95 +/- 27 s), as well as 5 and 45 minutes after, a simulated 2000-m rowing race. These measurements were also made before and after 10 weeks of training. Irrespective of testing time, performance of a 2000-m rowing race resulted in an increase in fractional area change (0.51 +/- 0.06 vs. 0.63 +/- 0.09; p < 0.05) due to an increase in LV contractility. Concurrent strength and endurance training resulted in an increase in the resting LV diastolic cavity area (20.64 +/- 2.59 vs. 22.82 +/- 2.17 cm (2); p < 0.05), end systolic myocardial area (23.27 +/- 4.86 vs. 24.56 +/- 4.00 cm (2); p < 0.05) and LV mass (179.07 +/- 46.91 g vs. 210.46 +/- 51.13 g; p < 0.05). These findings suggest that the acute increase in LV systolic function following a simulated 2000-m rowing race was due to heightened LV contractile reserve. Further, 10 weeks of combined strength and endurance training resulted in an increase in resting LV diastolic cavity size, wall thickness and mass.
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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) | 0.001 | 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".