Veterinary echocardiographers’ preferences for image selection, timing, and caliper placement for left atrial two-dimensional size assessment in dogs: the BENEFIT project
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVES: This study aimed to investigate veterinary echocardiographers' preferences for assessing left atrial (LA) size in dogs using linear two-dimensional echocardiography, focusing on image selection, timing, caliper placement, and thresholds used for LA enlargement. A secondary aim was to explore the impact of experience and training on echocardiographers' linear two-dimensional measurements of LA size in dogs. ANIMALS, MATERIALS AND METHODS: A global online study was conducted, asking veterinary echocardiographers to measure LA size using static echocardiographic images. RESULTS: A total of 533 echocardiographers (63% non-specialists and 37% specialists, of which 43% were cardiology board certified) completed the study. Most echocardiographers (86%, n = 459/533) used a right parasternal short-axis (RPSAX) view for LA and aortic (Ao) measurements. Of these, 57% (n = 261/459) favored the same image angulation for performing measurements and 76% (n = 351/459) timed measurements at end-systole/early-diastole. Caliper placement near pulmonary venous inlets impacted their LA dimension measurements the most. Thirty-nine percent (n = 207/533) used right parasternal long-axis (RPLAX) views. The upper limit for LA enlargement varied across all commonly used methods. Training and experience level influenced interobserver variation for LA dimension measurements obtained from a RPLAX four-chamber view, but not from a RPSAX view. STUDY LIMITATIONS: Static images may not reflect real-time clinical settings or allow precise identification of anatomical structures. CONCLUSIONS: The RPSAX view was most favored for LA size assessment in dogs, but variations existed in image selection, timing, caliper placement, and threshold used for LA enlargement. Training and experience level influenced interobserver variation in LA dimension measurements obtained from a RPLAX four-chamber view.
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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 | 0.006 | 0.014 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".