The effect of myxomatous mitral valve disease severity on packed cell volume in dogs
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to examine whether associations between disease severity and packed cell volume exist in dogs with myxomatous mitral valve disease. MATERIALS AND METHODS: Data were selected from 289 dogs that had been examined at a research clinic (2004-2017) on multiple occasions (n=1465). American College of Veterinary Internal Medicine stage and echocardiographic measurements were entered in separate multivariable linear mixed effects models with packed cell volume as the dependent variable. Age, breed, sex, weight and blood urea nitrogen concentrations were additionally tested in these analyses to control for patient characteristics. RESULTS: Packed cell volume (% whole blood) in stages B1 and B2 (B1: 42.62 ±0.27, P=0.001; B2: 41.77± 0.42, P < 0.001) was lower than stage A (44.57 ±0.53). In stage C, packed cell volume was greater than both preclinical stages (C: 43.84 ±0.46). When the administration of loop diuretics was included in statistical models, packed cell volume was inversely related to normalised left ventricular internal diameters (β: -2.37; 95% confidence intervals: -3.49, -1.25; P < 0.001). CLINICAL SIGNIFICANCE: Dogs with myxomatous mitral valve disease may develop reductions in packed cell volume as their disease progresses. Although this finding was statistically significant at a population level, it should be noted that the differences described are relatively small. This, along with other causes of variation in packed cell volume, means that changes would be challenging to appreciate within individual patients. Plasma volume depletion following diuretic administration may explain why findings differed in stage C.
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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 | 0.003 |
| 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 | 0.001 | 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".