PSXI-35 Evaluation of biomarkers N-terminal pro-B-type natriuretic peptide and troponin-I in healthy Labrador retrievers and Labrador retrievers with subclinical dilated cardiomyopathy
Bibliographic record
Abstract
Abstract Cardiovascular disease in dogs may have minimal outward signs in the beginning stages, but early detection and intervention are vital to help affected dogs live longer and have better quality of life. N-terminal pro-B-type natriuretic peptide (NT-proBNP) and troponin-I are two biomarkers that show promise for detection of cardiovascular disease at a research level, but a deeper understanding is necessary to bring them into the forefront for diagnostic purposes. The aim of this research was to present values of NT-proBNP and troponin-I in healthy Labrador retrievers and in Labrador retrievers with subclinical dilated cardiomyopathy (subDCM). 55 intact Labrador retrievers (27m/28f) were selected based on good clinical health, with no prior evidence of cardiovascular disease. All dogs were maintained on the same standard kennel diet prior to testing. Each dog had plasma collected for NT-proBNP analysis (Cardiopet; Idexx) and serum collected for troponin-I analysis (Immulite; UC Davis Vet Lab). Each dog then had an echocardiogram performed by an experienced sonographer which was reviewed by a boarded veterinary cardiologist. Out of 55 adult Labrador retrievers, 46 (24m/22f) were classified as normal and 9 (3m/6f) were classified as having occult subDCM. Normal Labrador retrievers had a significantly lower mean NT-proBNP of 695 ± 432 pmol/L compared to subDCM Labrador retrievers with a mean of 1144 ± 546 pmol/L (P = 0.009). Normal Labrador retrievers had a lower mean troponin-I of 0.07 ± 0.04ng/mL compared to subDCM Labrador retrievers with a mean of 0.1 ± 0.07ng/mL, trending towards significance (P = 0.08). In summary, healthy Labrador retrievers had significantly lower NT-proBNP compared to Labrador retrievers affected with subclinical dilated cardiomyopathy.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".