Myocardial compression and recoil as determinants of coronary blood flow
Bibliographic record
Abstract
Coronary blood flow is conventionally analysed as a continuous flow of blood through a tube with the input of energy in the epicardial coronary arteries and the principal resistance to flow in the arterioles and the small arteries. This model has been studied in detail and is accepted by all expert groups. However, this essay argues that this model is valid but incomplete. Coronary blood flow is not continuous. Coronary blood flow is phasic and asynchronous. During systole, at rest, there is no forward flow to the left ventricle in the epicardial coronary arteries. But there is forward flow in systole in the coronary veins. The blood forced during systole into the coronary veins is expelled from the coronary microcirculation by myocardial contraction and represents the compressible volume of the coronary microcirculation. During diastole, inflow of blood from the epicardial coronary artery begins abruptly, accelerated by myocardial recoil, refilling the compressible volume of the coronary microcirculation, and then flowing through the coronary vein. Accordingly, the hydrostatic energy in the epicardial coronary artery is not the only energy propelling blood through the coronary circulation. Myocardial compression and recoil also contribute. Disorders of myocardial compression and myocardial recoil in diastole should be considered in the differential diagnosis of disorders of the microcirculation. Thus, reduced coronary flow reserve in heart failure with preserved ejection fraction might be a consequence, rather than a cause, of myocardial dysfunction.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".