The Clinical Role of Central Venous Pressure Measurements
Bibliographic record
Abstract
Central venous pressure (CVP) is commonly measured, but its clinical use is still not clear. We argue that the interpretation of the CVP needs to be considered in conjunction with an assessment of cardiac output. The objective of this study was to define an elevated CVP as one in which there is a low probability for cardiac output to increase with a volume infusion through a Starling mechanism by relating the initial CVP (measured relative to a reference point 5 cm below the sternal angle) to the response in cardiac output with volume infusion. The authors studied consecutive patients who had pulmonary artery catheters in place and who had a volume challenge as part of routine management as ordered by the treating physician. To ensure an adequate test of the Starling mechanism, data were included only if the volume infusion increased CVP by > or = 2 mm Hg. Responders were defined a priori as those with an increase in cardiac index > or = 300 and nonresponders as < 300 mL/min/m2. Patients failed to respond to volume infusion at all CVP values, and even 25% of those with CVP < 5 mm Hg were nonresponders. However, when CVP was > 10 mm Hg, physicians prescribed less fluid challenges, and when they did, a positive response was much less likely. Change in blood pressure or changes in urine output with volume infusion correlated poorly with change in cardiac index. A CVP of > 10 mm Hg should be considered high, and the probability of an increase in cardiac output with volume infusion is low. This value is a reasonable upper limit for algorithms for empiric fluid challenges.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".