Periodicity, time constants of drainage, and the mechanical determinants of peak cardiac output during exercise
Bibliographic record
Abstract
To analyze mechanical adaptations that must occur in the cardiovascular system to reach the high cardiac outputs known to occur at peak aerobic performance, we adapted a computational model of the circulation by adding a second parallel venous compartment as proposed by August Krogh in 1912. One venous compartment has a large compliance and slow time constant of emptying; it is representative of the splanchnic circulation. The other has a low compliance and fast time constant of emptying and is representative of muscle beds. Fractional distribution between the two compartments is an important determinant of cardiac output. Parameters in the model were based on values from animal and human studies normalized to a 70 kg male. The baseline cardiac output was set at 5 L/min, and we aimed for 25 L/min at peak exercise with a fractional flow to the peripheral-muscle region of 90%. Finally, we added the equivalent of a muscle pump. Adjustments in circuit and cardiac parameters alone increased cardiac output to only 15.6 L/min because volume accumulated in the muscle compartment and limited a higher cardiac output. Addition of muscle contractions decompressed the muscle region and allowed cardiac output to increase to 23.4 L/min. The pulsatility of blood flow imposes important constraints on the adaptations of cardiac and circulatory functions because it fixes the times for filling and emptying. Flow is further limited by the limits of cardiac filling on each beat. Muscle contractions play a key role by decompressing volume that would otherwise accumulate in the muscle vasculature and by decreasing the time for stroke return to the right ventricle. NEW & NOTEWORTHY We used a computational model of the circulation and previous human and animal data to model mechanical changes in the heart and circulation that are needed to reach the known high cardiac output at peak aerobic exercise. Key points are that time constants of drainage of circulatory compartments put limits on peak flow in a pulsatile system. Muscle contractions increase the rate of return to the heart and by doing so prevent accumulation of volume in the muscle compartment and greatly increase circulatory capacity.
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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 | 0.002 |
| 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) | 0.000 | 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".