Abstract 500: Basal Peripheral Arterial Blood Flow Increases Concomitantly with Decreased Cardiopulmonary Reserve and Biomarkers Activation in Patients with Heart Failure and Preserved Ejection Fraction
Bibliographic record
Abstract
Background The underlying pathophysiology of heart failure with preserved ejection fraction (HFpEF) remains poorly understood. Changes in peripheral arterial function concomitantly with the evaluation of cardiopulmonary reserve and biomarkers related to wall stress, extra-cellular matrix turnover (ECM), subclinical inflammation and oxidative stress have not been investigated in patients with HFpEF nor compared with age-matched healthy volunteers (HV). We hypothesized that patients with HFpEF would have impairments in cardiac reserve with reduced peripheral arterial function associated with broad-spectrum biomarkers activation. Methods Eighteen male and female HFpEF patients (aged 70 ± 9 yr) NYHA class II and III were recruited. Data from patients were compared with those from 14 age and sex matched HV. A maximal exercise testing with gas exchange analysis was completed on a treadmill using a RAMP protocol and heart rate recovery (HRR) was measured at 1 and 2 minutes following exercise. Peripheral arterial function was assessed using near infrared radionuclide plethysmography. Biomarkers included BNP, NT-proBNP, hsCRP, TBARS, 8-epi-prostaglandin F2α, MMP 1, 2, 9 and TIMP 1, 2, 3, 4) were analyzed. Results Selected data are presented in the Table 1 and 2. Conclusions Compared to healthy volunteers, patients with HFpEF demonstrated a significant decrease in aerobic capacity but an increase in basal peripheral arterial blood flow, subclinical inflammation and oxidative stress. The increase in resting arterial blood flow may be a compensatory mechanism for the decrease in cardiac reserve and the pro-inflammatory/oxidant milieu in these patients.
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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 | 0.000 |
| 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) | 0.005 | 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".