Prevalence of Echocardiographic Evidence of Trace Mitral and Aortic Valve Regurgitation in 50 Clinically Healthy, Young Adult Labrador Retrievers without Heart Murmur
Bibliographic record
Abstract
Background-Though physiologic regurgitation of the right-sided cardiac valves is well recognized in dogs and other mammals, the prevalence of trace insufficiency of the mitral and aortic valves in clinically healthy, young adult dogs is unknown. Methods-In this observational cross-sectional study, 50 clinically healthy, young adult Labrador retrievers without an audible heart murmur were enrolled. All dogs were bred and owned by a single organization. Cardiac screening was requested for all dogs that were intended for breeding. These dogs underwent a cardiac auscultation and transthoracic echocardiography by a veterinary cardiology specialist. If mitral or aortic valve regurgitation was noticed, the jet size was subjectively assessed on color Doppler echocardiography. Pedigree analysis was performed to reveal a possible hereditary background of mitral valve regurgitation. Results-The prevalence of trivial mitral valve regurgitation was 52% with no significant predisposition to gender ( p = 0.86) or haircoat color ( p = 0.68). The prevalence of aortic valve regurgitation was 4%. Pedigree analysis for mitral valve regurgitation showed familial clustering, suggesting a hereditary background of the trait. Conclusions-The prevalence of silent trace mitral valve regurgitation in young adult Labrador retrievers was high. Because the regurgitant jet was trivial in all dogs, it is probably physiologic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".