Pericardial fat is adversely related to cardio-mechanical interaction in heart failure with preserved ejection fraction: implications for exercise intolerance
Bibliographic record
Abstract
Abstract Background Exercise intolerance is the primary manifestation in heart failure with preserved ejection fraction (HFpEF); however, the pathophysiologic mechanism(s) remains incompletely understood. Excess cardiac adiposity may physically constrain the myocardium, resulting in adverse Cardio-Mechanical Interaction (i.e., greater left ventricular eccentricity); a phenomenon only expected to worsen during exercise, with increased respiratory excursion and hemodynamic load. Evidence for this hypothesis, however, remains limited to a small number of observations, from a single group, made only under resting conditions using transthoracic echocardiography. Purpose To evaluate the relationship between pericardial fat and cardio-mechanical interaction in HFpEF at rest and during exercise using high resolution cardiac magnetic resonance imaging (cMRI). Methods We performed real-time (ungated), free-breathing cinematic imaging of the left ventricular (LV) short axis in 11 individuals with HFpEF (4M/7F, BMI: 36±6, age: 69±4 years). Imaging was performed at rest and during dynamic leg exercise (30 Watts) using an MRI-compatible ergometer (Ergospect, Austria). Epicardial and paracardial fat area were measured using high resolution cine images in the horizontal long axis imaging plane, with epicardial fat defined as the adipose tissue within the pericardium and paracardial fat defined as the adipose tissue outside of the pericardium (Figure 1A); the sum of which defined pericardial fat area. The LV eccentricity index was calculated as the ratio of LV short axis diameter parallel to the septum (anteroposterior dimension, AP) to the LV short axis diameter perpendicular to the septum (septolateral dimension, SL, Figure 1A) at mid-ventricular level, during inspiration at end-diastole. Results At rest, adverse cardio-mechanical interaction (i.e., AP/SL >1.0) was observed in 5 of the 11 cases. In those with adverse cardio-mechanical interaction both epicardial and paracardial fat area were significantly higher, resulting in greater pericardial fat area (Figure 1B). While epicardial fat area was not related to LV eccentricity index (R2=0.19, P=0.18), we observed a strong correlation between paracardial fat area and LV eccentricity index (R2=0.93, P<0.01), and pericardial fat area and LV eccentricity index (R2=0.86, P<0.01, Figure 1C). In contrast to our hypothesis, however, supine exercise did not exacerbate cardio-mechanical interaction, with LV eccentricity index remaining elevated in 4 of the 5 original cases, improving the fifth case (1.1 to 0.9, rest to exercise). Conclusions Taken together, these data extend prior reports of adverse cardio-mechanical interaction in HFpEF, showing greater contribution from paracardial fat versus epicardial fat. Future studies are needed to examine cardio-mechanical interaction during upright exercise in HFpEF patients. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): National Institutes of Health
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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) | 0.002 | 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".