Effect of time until sample analysis on lactate in dogs with shock
Bibliographic record
Abstract
INTRODUCTION: Lactate concentrations can increase with hypoperfusion in dogs and could be used as a prognostic indicator in sick dogs. In a busy emergency service, sample evaluation could be delayed. However, sample evaluation delays have been shown to cause lactate concentration increases in healthy dogs. In sick dogs, the magnitude of increased lactate is unknown. The goal of this study was to prospectively evaluate the effect of room temperature storage times on lactate measurements in dogs presenting to an emergency service. METHODS: We evaluated the precision and accuracy of the NOVA Lactate Plus, using standard procedures. To assess the impact of time on lactate concentrations in sick dogs, we prospectively enrolled dogs presenting to an emergency service. Lactate concentrations were measured at six time points using samples stored at room temperature. A Friedman test, followed by a Wilcoxon rank test with a Bonferroni correction was used to evaluate time points. RESULTS: of .98, and a mean bias of 0.26 in 50 canine samples. Precision was acceptable, with a percent coefficient of variation of 5.39. Statistically significant increases in lactate concentrations were found at all time points over baseline (P = .008). CONCLUSIONS: In as little as 7.5 minutes, lactate concentrations increased significantly in samples stored at room temperature. Dogs with lower initial lactate concentrations had had higher increases in lactate concentration percentages over 90 minutes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".