Volume kinetics of crystalloid and colloid solutions administered to healthy anesthetized cats
Bibliographic record
Abstract
This prospective experimental study evaluated the disposition of a crystalloid and a colloid solution in 10 healthy cats under general anesthesia. Each cat was randomly assigned to receive either 20 mL/kg of a balanced isotonic crystalloid solution (PLA) or 5 mL/kg of 6% tetrastarch 130/0.4 solution (T-HES), administered over 15 minutes, in a 2-period, 2-treatment crossover design. Blood samples were collected, and urine output was measured during a 3-hour experimental period. Plasma dilution was calculated using serial hemoglobin concentrations and red blood cell count. Volume kinetics (distribution and elimination) of each fluid were determined using non-linear mixed effects pharmacokinetic modeling software. Data from a previous study with a similar methodology in healthy conscious cats were included in the population kinetic analysis, revealing anesthesia as a significant covariate for k21 (peripheral-to-central intercompartmental rate constant) for PLA and k10 (dilution-dependent first-order elimination rate constant) for T-HES. Cumulative urine output under general anesthesia was approximately 3.5 times lower for PLA and 2.5 times lower for T-HES compared to conscious cats. Overall, our data suggest that the elimination of PLA and T-HES is markedly reduced, and a bolus of PLA produces a short period of plasma expansion with the potential to cause significant peripheral fluid accumulation in cats during general anesthesia.
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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 | 0.002 |
| 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 | 0.001 | 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".