Decreased left ventricular distensibility in response to postural change in older patients with heart failure and preserved ejection fraction
Bibliographic record
Abstract
Most elderly persons with heart failure have a preserved left ventricular (LV) ejection fraction (HFPEF). The pathophysiology of this disorder is not well understood, and there are conflicting data regarding the role of decreased LV distensibility. To assess LV distensibility over a range of preload conditions while minimizing the large, confounding changes in contractility, afterload, and heart rate characteristic of exercise, we measured LV end-diastolic volume (EDV), stroke volume (SV), and cardiac output (CO) using two-dimensional echocardiography in 48 elderly (mean age, 69 yr) HFPEF patients and 25 healthy age-matched controls during quiet supine rest, 45 degrees head-up tilt (HUT), and 45 degrees head-down tilt (HDT). As a result, when compared with controls, HFPEF patients had reduced percent changes in EDV (-7 +/- 2 vs. -17 +/- 2%; P = 0.003), SV (-7 +/- 3 vs. -27 +/- 2%; P = 0.003), and CO (-6 +/- 4 vs. -34 +/- 4%; P = 0.001) during the transition from supine to HUT. HFPEF also had reduced percent changes in EDV (8 +/- 2 vs. 15 +/- 2%; P = 0.02), SV (11 +/- 3 vs. 21 +/- 3%; P = 0.002), and CO (1 +/- 4 vs. 12 +/- 4%; P = 0.04) during the transition from HUT to HDT. In conclusion, HFNEF patients have reduced LV distensibility in response to postural change, resulting in blunted EDV, SV, and CO. This provides further support for the hypothesis that a blunted Frank-Starling mechanism may contribute to the pathophysiology of HFPEF.
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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) | 0.001 | 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".