Comparison of citrated native and kaolin‐activated samples for thrombelastographic analysis in healthy dogs
Bibliographic record
Abstract
BACKGROUND: Thrombelastographic (TEG) analysis is a test of global hemostasis in veterinary medicine; however, there have been limited comparisons of analysis of citrated native and kaolin-activated samples. OBJECTIVES: The purpose of this study was to determine the variation in TEG variables between citrated native and kaolin-activated whole blood samples and to establish reference intervals for both sample types. METHODS: Citrated whole blood samples were obtained from 40 healthy dogs. Thirty minutes after collection, TEG analysis was performed simultaneously on samples with and without kaolin-activation. Reaction time (R), clotting time (K), angle (α), maximum amplitude (MA), global clot strength (G), and clot lysis at 30 minutes (LY30) were recorded, and the concordance correlation coefficient (ρ(c)) was calculated for each sample type. RESULTS: Significant differences between results obtained for kaolin-activated and native samples were obtained for R (mean difference -1.3 minute, P = .0009), K (-0.7 minute, P = .0003), α (+5.1º, P = .002), MA (+2.4 mm, P = .002), and G (+568 dyn/cm(2), P = .0009). LY30 was not different between methods. There was substantial agreement between methods for G (ρ(c) = .69) and MA (ρ(c) = .65), moderate agreement for R (ρ(c) = .45) and α (ρ(c) = .44), fair agreement for K (ρ(c) = .29), and slight agreement for LY30 (ρ(c) = .04). CONCLUSIONS: The TEG variables were significantly altered by kaolin activation; however, some agreement between sample types suggests a consistent bias. In citrated whole blood activated with kaolin, clot formation time is shortened and the amplitude of the tracing is increased, resulting in a TEG tracing that appears to indicate relative hypercoagulability compared with that obtained using native citrated whole blood samples.
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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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".