Doppler Echocardiographic Reference Parameters in Healthy Labrador Retriever Dogs
Bibliographic record
Abstract
Thirty-one clinically healthy Labrador retriever dogs of both sexes (18 males and 13 females) were selected for determining Doppler echocardiographic reference values. 2 D and Pulse wave Doppler echocardiography was carried out by using GE Logiq P5 Color Doppler machine.The effect of body weight, age and sex on various doppler echocardiographic parameters were recorded.Twenty four dogs were in body weight range of 20-40 kg and 7 dogs in 40-60 kg range.To study the effect of age on various Doppler echocardiographic measurements, dogs were divided into 4 age groups (1-2, 2-3, 3-5 and >5 years of age).The mitral A wave peak velocity (MA) and ME:MA ratio were significantly (p<0.05)affected by body weight.The pulmonic valve velocity and pulmonic valve pressure were significantly (p<0.05)affected and there was significant negative correlation of pulmonic valve peak velocity (Pulmonary V max) and pulmonary pressure with body weight with r 2 values of 0.160 and 0.120 respectively.Mitral valve (MV) deceleration time was significantly (p<0.05)affected by age.The tricuspid valve deceleration time (TVDecT) was significantly (p≤0.01)higher in dogs > 5 years of age.Tricuspid A velocity was significantly (p≤0.01)higher in 2-3 year age group dogs as compared to dogs belonging to age group 3-5 years and > 5 years of age group.The pulmonic valve velocity and pressure were significantly affected by age.The tricuspid valve TE: TA ratio was significantly (p≤0.05)affected by gender and the ratio was significantly (p≤0.05)higher in males as compared to females. HIGHLIGHTS mThe mitral A wave peak velocity (MA) and ME:MA ratio were significantly (p<0.05)affected by bodyweight.m The tricuspid valve deceleration time (TVDecT) was significantly (p≤0.01)higher in dogs >5 years of age.
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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 | 0.000 | 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) | 0.001 | 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".