Low central venous oxygen saturation is associated with increased mortality in critically ill dogs
Bibliographic record
Abstract
OBJECTIVES: To investigate relationships between central venous oxygen saturation (ScvO(2)) and survival to hospital discharge in dogs. Central venous oxygen saturation is an accessible measure of the balance between systemic oxygen delivery and consumption. METHODS: Prospective observational cohort study, enrolling 126 client-owned dogs with central venous catheters. Central venous oxygen saturation was measured over the 24 hours following intensive care unit admission. Poor outcome was defined as death or euthanasia performed for moribund status. Regression analysis identified independent predictors of non-survival and physiologic parameters associated with central venous oxygen saturation. Area under the receiver operator curve analysis identified a cut-off point of central venous oxygen saturation, below which central venous oxygen saturation decrease was associated with increased mortality risk. RESULTS: Mortality risk was 30·9%. Low central venous oxygen saturation was associated with poor outcome (P<0·05). Area under the receiver operator curve analysis selected a central venous oxygen saturation of 68% as the point below which a fall in central venous oxygen saturation was associated with increased mortality risk. For each 10% drop in central venous oxygen saturation below 68%, odds of non-survival increased by 2·66 times (P=0·0002, 95% confidence interval of odds ratio=1·45 to 4·85). Central venous oxygen saturation was equivalent to lactate in predicting non-survival. Predictors of central venous oxygen saturation (packed cell volume, mean arterial blood pressure, fever, % arterial haemoglobin saturation as measured by pulse oximeter) were consistent with hypothesised physiologic mechanisms. CLINICAL SIGNIFICANCE: Central venous oxygen saturation was a strong mortality predictor. Further work is needed to determine if therapy targeting central venous oxygen saturation can reduce mortality in canine intensive care unit patients.
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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) | 0.000 | 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) | 0.001 | 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".