Use of serum hyaluronic acid as a biomarker of endothelial glycocalyx degradation in dogs with septic peritonitis
Bibliographic record
Abstract
OBJECTIVE: To describe daily changes in serum concentrations of hyaluronic acid (HA), a biomarker of endothelial glycocalyx degradation, in dogs with septic peritonitis and to determine whether relationships exist among serum concentrations of HA and biomarkers of inflammation and patient fluid status. ANIMALS: 8 client-owned dogs. PROCEDURES: Serum samples that had been collected for a previous study and stored at -80°C were used. Blood samples were collected at admission and daily thereafter during hospitalization and were analyzed for concentrations of HA and interleukins 6, 8, and 10. Patient data including acute patient physiologic and laboratory evaluation score, type and amount of fluids administered daily, and daily CBC and lactate concentration results were recorded. To determine the significant predictors of HA concentration, a general linear mixed model for repeated measures was developed. RESULTS: All dogs survived to discharge. Concentrations of HA ranged from 18 to 1,050 ng/mL (interquartile [25th to 75th percentile] range, 49 to 119 ng/mL) throughout hospitalization. Interleukin-6 concentration was a significant predictor of HA concentration as was total administered daily fluid volume when accounting for interleukin-6 concentration. When fluid volume was analyzed independent of inflammatory status, fluid volume was not a significant predictor. Concentrations of HA did not significantly change over time but tended to increase on day 2 or 3 of hospitalization. CONCLUSIONS AND CLINICAL RELEVANCE: Results supported the theory that inflammation is associated with endothelial glycocalyx degradation. Dogs recovering from septic peritonitis may become more susceptible to further endothelial glycocalyx damage as increasing fluid volumes are administered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".