Left atrial phasic function interacts to support left ventricular filling during exercise in healthy athletes
Bibliographic record
Abstract
We studied the contribution of phasic left atrial (LA) function to left ventricular (LV) filling during exercise. We hypothesized that reduced LV filling time at moderate-intensity exercise limits LA passive emptying and increases LA active emptying. Twenty endurance-trained males (55 ± 6 yr) were studied at rest and during light- (∼100 beats/min) and moderate-intensity (∼130 beats/min) exercise. Two-dimensional and Doppler echocardiography were used to assess phasic volumes and diastolic function. LV end-diastolic volume increased from rest to light exercise (54 ± 6 to 58 ± 5 ml/m(2), P < 0.01) and from light to moderate exercise (58 ± 5 to 62 ± 6 ml/m(2), P < 0.01). LA maximal volume increased from rest to light exercise (26 ± 4 to 30 ± 5 ml/m(2), P < 0.01) related to atrioventricular plane displacement (r = 0.55, P < 0.005), without further change at moderate exercise. LA passive emptying increased at light exercise (9 ± 2 to 13 ± 3 ml/m(2), P < 0.01) and then returned to baseline at moderate exercise, whereas LA active emptying increased appreciably only at moderate exercise (6 ± 2 to 14 ± 3 ml/m(2), P < 0.01). Thus, the total atrial emptying volume did not increase beyond light exercise, and the increase in LV filling at moderate exercise could be attributed primarily to an increase in the conduit flow volume (19 ± 3 to 25 ± 5 ml/m(2), P < 0.01). LA filling increases during exercise in relation to augmented LV longitudinal contraction. Conduit flow increases progressively with exercise in athletes, although this is driven by LV properties rather than intrinsic LA function. The pump function of the LA augments only at moderate exercise due to a reduced diastolic filling time and the Frank-Starling mechanism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".