The use of Guyton’s approach to the control of cardiac output for clinical fluid management
Bibliographic record
Abstract
Infusion of fluids is one of the most common medical acts when resuscitating critically ill patients. However, fluids most often are given without consideration of how fluid infusion can actually improve tissue perfusion. Arthur Guyton's analysis of the circulation was based on how cardiac output is determined by the interaction of the factors determining the return of blood to the heart, i.e. venous return, and the factors that determine the output from the heart, i.e. pump function. His theoretical approach can be used to understand what fluids can and cannot do. In his graphical analysis, right atrial pressure (RAP) is at the center of this interaction and thus indicates the status of these two functions. Accordingly, trends in RAP and cardiac output (or a surrogate of cardiac output) can provide important guides for the cause of a hemodynamic deterioration, the potential role of fluids, the limits of their use, and when the fluid is given, the response to therapeutic interventions. Use of the trends in these values provide a physiologically grounded approach to clinical fluid management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".