Short-term Training Effects on Left Ventricular Diastolic Function and Oxygen Uptake in Older and Younger Men
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of plasma volume change with short-term training and diuresis on left ventricular diastolic filling and exercise oxygen uptake (VO(2)) in older versus younger men. METHODS: Eleven older (68 +/- 5 y) physically active (maximal oxygen uptake [VO(2max)] = 25.9 +/- 3.6 mL. kg-1. min-1) and 10 younger sedentary males (24 +/- 5 y, VO(2max) 40.5 +/- 5.0 mL. kg-1. min-1) were randomly assigned to 5 consecutive days of (1) 1 h/d high intensity stationary cycling (EXER); (2) 100 mg/d spironolactone (DIUR); and (3) exercise and diuretic (EXDI). Each treatment was separated by a 21-day washout. Doppler echocardiographic indices of left ventricular diastolic filling including peak early and atrial transmitral flow velocity and isovolumic relaxation time; percent change in plasma volume; submaximal VO(2) kinetics; and VO(2max) were determined at baseline and 48 hours after each treatment. RESULTS: Plasma volume was increased more in the young following EXER (8.92 +/- 7.6 vs. 6.2%, P = 0.038) and decreased more in the older group following DIUR (-11.5% vs. -3.54 +/- 9.0, P < 0.001). There was no significant difference between groups after EXDI. Significant changes in peak early flow velocity with EXER in older subjects were not reflected in any other changes in left ventricular diastolic filling across conditions. No changes in left ventricular diastolic filling were observed in the young group with any condition. VO(2max) and VO(2) kinetics were unchanged under all conditions from baseline in both groups. CONCLUSIONS: These results suggest that exercise VO(2) responses either at maximal or submaximal workrates are not limited by alterations in left ventricular pump function in physically fit older adults.
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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 | 0.000 |
| 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".