Skeletal muscle abnormalities and exercise intolerance in older patients with heart failure and preserved ejection fraction
Bibliographic record
Abstract
Heart failure (HF) with preserved ejection fraction (HFPEF) is the most common form of HF in older persons. The primary chronic symptom in HFPEF is severe exercise intolerance, and its pathophysiology is poorly understood. To determine whether skeletal muscle abnormalities contribute to their severely reduced peak exercise O2 consumption (Vo2), we examined 22 older HFPEF patients (70 ± 7 yr) compared with 43 age-matched healthy control (HC) subjects using needle biopsy of the vastus lateralis muscle and cardiopulmonary exercise testing to assess muscle fiber type distribution and capillarity and peak Vo2. In HFPEF versus HC patients, peak Vo2 (14.7 ± 2.1 vs. 22.9 ± 6.6 ml·kg(-1)·min(-1), P < 0.001) and 6-min walk distance (454 ± 72 vs. 573 ± 71 m, P < 0.001) were reduced. In HFPEF versus HC patients, the percentage of type I fibers (39.0 ± 11.4% vs. 53.7 ± 12.4%, P < 0.001), type I-to-type II fiber ratio (0.72 ± 0.39 vs. 1.36 ± 0.85, P = 0.001), and capillary-to-fiber ratio (1.35 ± 0.32 vs. 2.53 ± 1.37, P = 0.006) were reduced, whereas the percentage of type II fibers was greater (61 ± 11.4% vs. 46.3 ± 12.4%, P < 0.001). In univariate analyses, the percentage of type I fibers (r = 0.39, P = 0.003), type I-to-type II fiber ratio (r = 0.33, P = 0.02), and capillary-to-fiber ratio (r = 0.59, P < 0.0001) were positively related to peak Vo2. In multivariate analyses, type I fibers and the capillary-to-fiber ratio remained significantly related to peak Vo2. We conclude that older HFPEF patients have significant abnormalities in skeletal muscle, characterized by a shift in muscle fiber type distribution with reduced type I oxidative muscle fibers and a reduced capillary-to-fiber ratio, and these may contribute to their severe exercise intolerance. This suggests potential new therapeutic targets in this difficult to treat disorder.
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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 | 0.001 | 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".