Hypercoagulability and ACTH-Dependent Hyperadrenocorticism in Dogs
Bibliographic record
Abstract
BACKGROUND: Dogs with hyperadrenocorticism are at risk of thromboembolic disease, which might be caused by an underlying hypercoagulable state. HYPOTHESIS/OBJECTIVES: To assess hemostatic function in dogs with ACTH-dependent hyperadrenocorticism (ADHAC) before and after treatment. ANIMALS: Nineteen dogs with ADHAC and 40 normal dogs. METHODS: Prospective, observational study. Dogs with ADHAC were recruited from the referral hospital patient population; normal dogs were recruited from staff and students at the study's institution. Hemostasis was assessed before and at 3 and 6 months after treatment with trilostane (T0, T3, T6) by kaolin-activated thrombelastography with platelet mapping (TEG-PM), prothrombin time, activated partial thromboplastin time, fibrinogen concentration, and antithrombin activity (AT). RESULTS: Dogs with ADHAC had statistically significantly increased α-angle (P < .01) and maximum amplitude (MA)(thrombin) (P < .01) on TEG-PM, and significantly decreased κ (P < .005) at T0, T3, and T6. Platelet count (P < .001) and fibrinogen concentration (P < .001), but not AT activity, were increased in dogs with ADHAC at T0, T3, and T6. CONCLUSIONS AND CLINICAL IMPORTANCE: Dogs with ADHAC have thrombelastographic evidence of hypercoagulability and remained hypercoagulable during treatment. AT deficiency does not appear to be involved in the pathogenesis of hypercoagulability in this population.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".