Diastolic Doppler flow and tissue Doppler velocities during, and in recovery from, low-intensity supine exercise
Bibliographic record
Abstract
Recent studies have reported evidence of both a short-term and a more sustained reduction in left ventricular diastolic function after prolonged strenuous exercise. Interpretation of this data is confounded by alterations in heart rate (HR) post-exercise. The purpose of this study was to investigate the association between HR and diastolic function during recovery from supine exercise, and to reassess the impact of increasing HR on early diastolic flow and tissue velocities during supine exercise. Repeat echocardiograms in 16 young, trained, volunteers were obtained at rest (50 +/- 6 beats.min-1), during steady-state supine cycling at HR of 60, 80, and 100 beats.min-1, and then during supine recovery at HR of 80 and 60 beats.min-1. Doppler flow velocities and tissue Doppler myocardial annular velocities were recorded in early (E and E', respectively) and late diastole (A and A', respectively). The ratios E/A, E'/A', and E/E' were calculated. Data were compared via analyses of variance (ANOVA; exercise) and t tests (recovery). Peak E, A, E', and A' all increased in line with HR during exercise (p < 0.05) although relatively greater changes in A and A' resulted in a significant decline in E/A and E'/A' with increasing HR (p < 0.05). During recovery E, A, E', and A' all declined from peak values during exercise (p < 0.05). At 80 beats.min-1, flow and tissue Doppler data were still elevated above resting values and only A was significantly reduced compared with assessments made at the same HR during exercise. Diastolic flow and tissue velocities tended to increase (during supine exercise) and return to baseline (during recovery from exercise) in line with changes in HR. The interpretation of diastolic functional indices measured after physical exertion should be made in light of the present data.
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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) | 0.001 | 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".