Higher Cardiorespiratory Fitness in Older Trained Women is Due to Preserved Stroke Volume.
Bibliographic record
Abstract
UNLABELLED: Previous literature has shown that sedentary older women rely on peripheral adaptations to improve cardiorespiratory fitness with endurance training i.e. they show minimal increases in central parameters (cardiac output, Q) in response to endurance training. The purpose of this study therefore was to determine whether endurance trained older women were able to preserve maximal exercise Q and were characterized by a high stroke volume (SV) when compared to physically inactive older women. Trained (n = 7) and untrained (n = 1 0) women attended two maximal and one submaximal laboratory session. Breath-by-breath analysis was conducted using mass spectrometry and Q was assessed using acetylene open circuit inert gas wash-in. Multivariate analysis of variance and paired samples t-tests were used to determine between and within group differences. Trained women had a significantly higher VO2max (37.5 vs. 24.1 ml(-1)·kg·min(-1)) compared to untrained women. There were no differences for peripheral oxygen extraction (VO2/Q) at either submaximal or maximal work rates; however trained women had a significantly higher SV at maximal (119.3 vs. 94.6 ml) exercise compared to untrained women. In both trained and untrained women, SV did not rise significantly between submaximal and maximal exercise. CONCLUSION: Highly fit, endurance trained older women are able to preserve central parameters of VO2max. Peripheral oxygen extraction is similar between older trained and untrained women.
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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) | 0.003 | 0.001 |
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".