Left Ventricular Diastolic Filling and Cardiovascular Functional Capacity in Older Men
Bibliographic record
Abstract
We investigated anaerobic threshold (< theta(L)) gas exchange kinetics and maximal oxygen uptake (VO2,max) among older men with reduced left ventricular end-diastolic filling (LVDF). Ten men (mean age, 73 years) with LVDF impairment and low fitness, but without other cardiovascular dysfunction were studied. Treatments compared to control included: 5 days, high intensity exercise training protocol; 5 days, calcium channel blockade (240 mg verapamil); 21 days, detraining/washout; and 5 days, combined treatments. Results indicated no changes in resting left ventricular systolic function with any treatment. Significant resting diastolic function changes included increased early:late flow velocity (control, 0.87; training, 1.28; verapamil, 1.32), and a decreased isovolumic relaxation time (control, 0.10 s; training, 0.08 s; verapamil, 0.08 s). The combined treatments were not additive. Sub-threshold oxygen uptake kinetics (tauVO2, s) were significantly faster following either training or verapamil (tauVO2,control, 62+/-12; tauVO2,training, 44+/-9; tauVO2,verapamil, 48+/-10) and combined treatments (tauVO2, 41+/- 8). V O2,max (ml kg(-1) min(-1)) was significantly increased (control, 21.8+/-2.2; training, 27.3+/-2.2; verapamil, 25.2+/-3.4; combined treatments, 26.9+/-2.3). Increasing ventricular preload with either exercise training or calcium channel blockade was coincident with faster tauVO2 and increased VO2,max.
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 | 0.001 |
| 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".