Long‐term biological variability and the generation of a new reference interval for plasma N‐terminal pro‐B‐type natriuretic peptide in Labrador retrievers
Bibliographic record
Abstract
OBJECTIVES: First, to investigate the biological variability of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in healthy Labrador retrievers and compare this with current laboratory recommendations for dilated cardiomyopathy screening. Second, to calculate a breed-specific reference interval and validate it in a retrospective cohort. MATERIALS AND METHODS: Plasma NT-proBNP was measured in 51 clinically healthy Labrador retrievers at 0, 2, 4, 6 and 8 weeks. Coefficient of variation for individual dogs over time, the coefficient of variation for the group at each time point and the index of individuality were calculated. A reference interval was derived and tested on a clinical dataset available from four UK cardiology referral centres. RESULTS: Median NT-proBNP was 865 pmol/L (315 to 2064 pmol/L). Mean individual coefficient of variation was 19% (95% CI: 16 to 21%) and group coefficient of variation was 43% (95% CI: 41 to 46%), with index of individuality at 0.44. The breed-specific reference interval was 275 to 2100 pmol/L. In the validation group, 93% of NT-proBNP measurements from healthy dogs were within the reference interval. NT-proBNP measurements exceeded the reference interval in 82% of dogs with dilated cardiomyopathy. The upper bound of the reference interval (2100 pmol/L) had a positive predictive value of 90% and a negative predictive value of 87% for identification of dilated cardiomyopathy in this population. CLINICAL SIGNIFICANCE: Breed-specific reference intervals might improve the diagnostic accuracy of NT-proBNP measurement. Applying the currently recommended general cut-off value to Labradors is likely to result in frequent false positives and diagnosis would be improved by application of the new breed-specific reference interval calculated here.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".