Marked improvements in cardiac function in postmenopausal women exposed to blood withdrawal plus endurance training
Bibliographic record
Abstract
The cardiac phenotype of a substantial fraction of the population, i.e., mature women, is mainly unresponsive to endurance training (ET), the most effective intervention to improve cardiorespiratory fitness. This study assessed whether a novel intervention comprising additional haemodynamic stimuli may overcome the generalized limitations to modify the cardiac phenotype of middle-aged and older women. Fifteen healthy postmenopausal women (52-75 yr) were recruited. Transthoracic echocardiography and central haemodynamics were assessed during incremental cycle ergometry (i) in baseline conditions, (ii) after standard (10%) blood withdrawal and (iii) subsequent 8-week ET. Main outcomes such as left ventricular (LV) function and structure and blood volume (BV) were determined. Phlebotomy induced a 0.5 ± 0.1 l reduction of BV, which was re-established after ET. Decrements in LV end-systolic volume (-27%) and increments in LV ejection fraction (+8%) during exercise as well as improved E/A ratio were detected after ET compared with baseline. In parallel, ET induced a 10% increment in LV mass without a concomitant increase in LV size. In conclusion, postmenopausal women exhibit large improvements in cardiac systolic and diastolic functions along with LV concentric remodelling in response to the sequenced combination of blood withdrawal and ET.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".