Bibliographic record
Abstract
Volume infusions are one of the commonest clinical interventions in critically ill patients yet the relationship of volume to cardiac output is not well understood. Blood volume has a stressed and unstressed component but only the stressed component determines flow. It is usually about 30 % of total volume. Stressed volume is relatively constant under steady state conditions. It creates an elastic recoil pressure that is an important factor in the generation of blood flow. The heart creates circulatory flow by lowering the right atrial pressure and allowing the recoil pressure in veins and venules to drain blood back to the heart. The heart then puts the volume back into the systemic circulation so that stroke return equals stroke volume. The heart cannot pump out more volume than comes back. Changes in cardiac output without changes in stressed volume occur because of changes in arterial and venous resistances which redistribute blood volume and change pressure gradients throughout the vasculature. Stressed volume also can be increased by decreasing vascular capacitance, which means recruiting unstressed volume into stressed volume. This is the equivalent of an auto-transfusion. It is worth noting that during exercise in normal young males, cardiac output can increase five-fold with only small changes in stressed blood volume. The mechanical characteristics of the cardiac chambers and the circulation thus ultimately determine the relationship between volume and cardiac output and are the subject of this review.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".