Bibliographic record
Abstract
The use of pulmonary artery catheters has diminished, so that other technologies are emerging. Central venous oxygen saturation measurement (ScvO₂) as a surrogate for mixed venous oxygen saturation measurement (SvO₂) is simple and clinically accessible. To maximize the clinical utility of ScvO₂ (or SvO₂) measurement, it is useful to review what the measurement means in a physiologic context,how the measurement is made, important limitations, and how this measurement may be helpful in common clinical scenarios. Compared with cardiac output measurement, SvO₂ is more directly related to tissue oxygenation. Furthermore,when tissue oxygenation is a clinical concern, SvO₂ is less prone to error compared with cardiac output, where small measurement errors may lead to larger errors in interpreting adequacy of oxygen delivery. ScvO₂ should be measured from the tip of a central venous catheter placed close to, or within, the right atrium to reduce measurement error. Correct clinical interpretation of SvO₂, or its properly measured ScvO₂ surrogate, can be used to (1) estimate cardiac output using the Fick equation, (2) better understand whether a patient's oxygen delivery is adequate to meet their oxygen demands, (3) help guide clinical practice, particularly when resuscitating patients using validated early goal directed therapy treatment protocols, (4) understand and treat arterial hypoxemia, and (5) rapidly estimate shunt fraction (venous admixture).
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".