Evaluation of the effect of fresh-frozen plasma transfusion on circulating hyaluronic acid concentration in critically ill dogs: a pilot study
Bibliographic record
Abstract
OBJECTIVE: To describe changes in circulating hyaluronic acid (HA) concentration, a biomarker of endothelial glycocalyx degradation, after administration of fresh-frozen plasma (FFP) in critically ill dogs. ANIMALS: 12 client-owned dogs receiving an FFP transfusion due to underlying disease. METHODS: Plasma samples were collected for HA concentration measurement pre-FFP transfusion (T0) and 10 minutes (T10) and 90 minutes (T90) following completion of FFP transfusion of a minimum volume of 7 mL/kg. Hyaluronic acid was also measured in the transfused FFP units following in-house validation of a commercial HA assay on citrate phosphate dextrose-anticoagulated plasma. Potential associations of the difference between pre-FFP and post-FFP HA plasma concentrations with the volume of FFP transfused, the cumulative volume of IV fluids administered during the study period, and the HA concentration in the transfused unit were explored. RESULTS: Concentrations of HA were not significantly different between pre- and post-FFP transfusion measurements. The volume of FFP transfused, the cumulative volume of other IV fluids administered during the study time, and the concentration of HA in the FFP units had no significant effect on the change in HA concentration following FFP transfusion in this study. CLINICAL RELEVANCE: This pilot study did not demonstrate an association between FFP administration and changes in plasma HA concentration. The results of this study may serve to help design future research. A commercial assay was validated to measure HA in citrate phosphate dextrose-anticoagulated plasma.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".