Effect of Dexamethasone on Resting Blood Lactate Concentrations in Horses
Bibliographic record
Abstract
BACKGROUND: Blood lactate concentration is a marker of tissue perfusion and helps guide therapeutic interventions in critically ill horses. In both humans and dogs, administration of corticosteroids can increase blood lactate concentration, leading to type B hyperlactatemia. This effect could be a consequence of the impact of corticosteroids on glucose metabolism. OBJECTIVES: To investigate the effects of daily IM dexamethasone administration on blood lactate and glucose concentrations in horses. ANIMALS: Nine healthy adult horses. METHODS: A randomized, blinded, controlled, cross-over study design was used. Horses were randomly assigned to 1 of 2 groups, either receiving 0.05 mg/kg of dexamethasone IM or an equivalent volume of saline, daily for 7 days. Blood was collected to determine lactate and glucose concentrations at baseline, 2 hours after the daily injections and 24 hours after the last injection. RESULTS: Dexamethasone treatment had a statistically significant effect on lactate (P = .006) and glucose (P = .033) concentrations. The least squares mean lactate concentration was 0.93 mmol/L (95% CI: 0.87-0.99) in the dexamethasone group compared to 0.71 mmol/L (95% CI: 0.70-0.73) for the saline group. A positive relationship between blood lactate and glucose concentrations was identified, with a 0.07 mmol/L (95% CI: 0.05-0.09) increase in lactate concentration per unit increase in glucose (P < .0001) concentration. CONCLUSIONS AND CLINICAL IMPORTANCE: Dexamethasone induces statistically significant increases in blood lactate and glucose concentrations in healthy horses. Awareness of the potential for corticosteroids to induce type B hyperlactatemia might be important in the management of critically ill horses receiving dexamethasone.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".