Effect of dalteparin administration on thrombin generation kinetics in healthy dogs
Bibliographic record
Abstract
Background Dalteparin is used to prevent thrombotic complications in dogs. Measurement of anti‐factor Xa (anti‐FXa) activity is currently used for monitoring therapy, but remains a nonfunctional test. The calibrated automated thrombogram ( CAT ) could be a suitable approach for functional monitoring. Objectives We hypothesized that the CAT will detect decreased endogenous thrombin potential ( ETP ) in healthy dogs receiving dalteparin. Methods Twenty‐four healthy adult Beagles were randomly allocated to 4 equal groups. A single subcutaneous ( SC ) dose of 50 U/kg, 100 U/kg, or 150 U/kg of dalteparin was given. Platelet‐poor plasma ( PPP ) was collected over a 24‐hour period and evaluated by thrombin generation (TG) via CAT , anti‐FXa activity, and APTT . Analysis was performed with a repeated‐measures general linear mixed model, and the treated groups were compared to a placebo group. Results Time, dose, and time–dose interaction significantly affected ETP ( P < .0001 for all effects), peak ( P < .0001 for all effects), rate index ( P < .0006 for all effects), and anti‐ FX a activity ( P < .0001 for all effects). No significant time trend was detected in the control group. Dogs receiving the 100 U/kg dalteparin SC injection showed the most homogeneous response of ETP inhibition among treated groups. The % inhibition of ETP from baseline increased nonlinearly as a function of anti‐ FX a activity ( r 2 = .8186). Conclusions The CAT assay can be employed to measure the effects of dalteparin at different doses in healthy dogs, showing sensitivity to time‐ and dose‐dependent changes in ETP and other TG variables. Further investigation of the CAT as a tool for monitoring low molecular weight heparin therapy in dogs is warranted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".