Glucose metabolism in five septic neonatal foals
Bibliographic record
Abstract
Abstract Objective:Glucose metabolism is often deranged in septic animals. Bacteremia and sepsis are common in foals and clinical experience suggests that glucose metabolism is abnormal in some of these animals. The purpose of this study was to provide initial estimates of rates of glucose appearance, disappearance, and metabolic clearance rate in septic foals. Series Summary:Rates of glucose entry, and exit from blood were determined by use of infusion of isotopically labeled glucose in 5 foals with confirmed sepsis. Serum concentrations of glucose, insulin, glucagon, and cortisol were measured concurrent with measurement of rates of glucose turnover. Median glucose turnover rate was 24 μmol/kg/min (range 17–53 μmol/kg/min), and median glucose metabolic clearance rate was 3.2 mL/kg/min (range 1.7–6.7 mL/kg/min). Median concentration of serum immunoreactive insulin was 55 pmol/L (range 36–190 pmol/L), median serum immunoreactive glucagon was 65 pmol/L (range 19–120 pmol/L), and median serum cortisol was 207 nmol/L (range 100–333 nmol/L). New or unique information provided:These data, although limited in scope and by the lack of data in healthy foals, demonstrate the magnitude and variation in glucose appearance, disappearance, and metabolic clearance rate in septic foals, provide an estimate of rates of glucose utilization in sick foals, and will be useful in guiding future studies of energy metabolism in healthy and ill foals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".