Use of two- and three-dimensional echocardiography for assessment of the left ventricular outflow tract and aortic orifice areas in dogs
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVES: In clinical practice, dogs are screened for subaortic stenosis (SAS) using two-dimensional (2DE) and Doppler echocardiography. There is no accepted antemortem diagnostic criterion to distinguish between mild SAS and unaffected, therefore additional means of evaluating the left ventricular outflow tract (LVOT) and aorta may be desirable. This study sought to determine and compare LVOT and aortic orifice areas using 2DE and three-dimensional echocardiography (3DE) in apparently healthy dogs of various breeds and somatotypes. ANIMALS, MATERIALS, AND METHODS: Sixty-nine healthy, privately-owned dogs. The LVOT and aortic orifice areas were determined using 2DE aortic valve (AV) diameter-derived area; the continuity equation (CE); and 3DE planimetry of the LVOT, AV, sinus of Valsalva, and sinotubular junction. Orifice areas were indexed to body surface area (BSA). RESULTS: ; P<0.001). There was poor agreement between the effective area calculated using the CE and the anatomic areas calculated using 2DE AV diameter and 3DE planimetry. The area calculated using the CE was less than all other calculations of area. Interobserver and intraobserver repeatability and reproducibility for 3DE planimetry were excellent. CONCLUSIONS: Methods for determining aortic orifice areas in dogs are not interchangeable, and this must be taken into account if these methods are investigated in the evaluation of dogs with SAS in the future.
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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 | 0.002 |
| 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) | 0.000 | 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".