Comparison of peak flow velocity through the left ventricular outflow tract and effective orifice area indexed to body surface area in Golden Retriever puppies to predict development of subaortic stenosis in adult dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the usefulness of Doppler-derived peak flow velocity through the left ventricular outflow tract (LVOT Vmax) and effective orifice area indexed to body surface area (EOAi) in puppies to predict development of subaortic stenosis (SAS) in the same dogs as adults. DESIGN: Prospective, longitudinal, observational study. ANIMALS: 38 Golden Retrievers. PROCEDURES: Cardiac auscultation and echocardiography were performed on 2- to 6-month-old puppies, then repeated at 12 to 18 months. Subaortic stenosis was diagnosed when LVOT Vmax was ≥ 2.3 m/s in adult dogs with left basilar systolic murmurs. RESULTS: All puppies with EOAi < 1.46 cm(2)/m(2) had SAS as adults. All adults with EOAi < 1.29 cm(2)/m(2) had SAS. An LVOT Vmax > 2.3 m/s in puppyhood was 63% sensitive and 100% specific for SAS in adulthood. In puppies, LVOT Vmax was more strongly associated with a future diagnosis of SAS (area under the curve [AUC], 0.89) than was EOAi (AUC, 0.80). In puppies, the combination of LVOT Vmax and EOAi yielded slightly higher sensitivity (69%) and specificity (100%) for adult SAS than did LVOT Vmax alone. In unaffected and affected dogs, LVOT Vmax increased significantly from puppyhood to adulthood but EOAi did not. CONCLUSIONS AND CLINICAL RELEVANCE: In Golden Retriever puppies, LVOT Vmax > 2.3 m/s and EOAi < 1.46 cm(2)/m(2) were both associated with a diagnosis of SAS at adulthood. The combination of these 2 criteria may result in higher sensitivity for SAS screening. Unlike LVOT Vmax, EOAi did not change during growth in either unaffected Golden Retrievers or those with SAS.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".