Prospective Evaluation of NT-proBNP Assay to Detect Occult Dilated Cardiomyopathy and Predict Survival in Doberman Pinschers
Bibliographic record
Abstract
BACKGROUND: Occult (asymptomatic) dilated cardiomyopathy (ODCM) is highly prevalent in Doberman Pinschers. HYPOTHESIS/OBJECTIVES: Assess ability of NT-proBNP assay to detect ODCM and predict death. ANIMALS: 155 asymptomatic Dobermans presenting for ODCM screening. METHODS: Echocardiography, 24-hour Holter, and NT-proBNP assay were performed prospectively. Diagnosis was based on increased left ventricular end-systolic dimension, >50 ventricular premature complexes (VPCs), or both on Holter. Utility was evaluated using receiver-operating characteristic curves. Effect of age, weight, sex, disease status, VPCs, and NT-proBNP on survival was analyzed using Kaplan-Meier and Cox-proportional hazard analysis. RESULTS: Seventy-three (47.1%) Dobermans were diagnosed with ODCM, including 31, 17, and 25 that met Holter, echocardiographic, or both criteria, respectively. Sensitivity of NT-proBNP > 457 pmol/L to detect these groups was 45.2, 76.5, and 96.0%, respectively. Combination of NT-proBNP and Holter to detect ODCM yielded sensitivity of 94.5%, specificity of 87.8%, and accuracy of 91.0%. Follow-up data were available for 78 Dobermans. The median survival time of Dobermans with > 50 VPCs (469 days), NT-proBNP > 900 pmol/L (284 days), or ODCM (474 days) was significantly (P < .0001) shorter than those with < 50 VPCs (1743 days), NT-proBNP < 900 pmol/L (1743 days), or without disease (1743 days). NT-proBNP concentration and disease status were independently predictive of all-cause mortality. CONCLUSIONS AND CLINICAL IMPORTANCE: The combination of NT-proBNP assay and Holter detected ODCM with high accuracy. NT-proBNP and disease status were independently associated with survival. NT-proBNP assay identified Dobermans with high probability of increased LVIDs consistent with ODCM, and can facilitate pursuit of confirmatory diagnostic testing, such as echocardiography, in suspected Dobermans.
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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 | 0.001 | 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".