Temporal changes in clinical and radiographic variables in dogs with preclinical myxomatous mitral valve disease: The EPIC study
Bibliographic record
Abstract
BACKGROUND: The Evaluation of pimobendan in dogs with cardiomegaly caused by preclinical myxomatous mitral valve disease (EPIC) study monitored dogs with myxomatous mitral valve disease (MMVD) as they developed congestive heart failure (CHF). OBJECTIVES: To describe the changes in clinical and radiographic variables occurring as dogs with MMVD and cardiomegaly develop CHF, compared to similar dogs that do not develop CHF. ANIMALS: One hundred and thirty-five, and 73 dogs that did or did not develop CHF, respectively. MATERIALS AND METHODS: The following variables were evaluated in 2 groups of dogs (dogs that did or did not develop CHF): Heart rate (HR), clinic respiratory rate (RR), home-measured resting respiratory rate (RRR), rectal temperature (RT), body weight (BW), and vertebral heart sum (VHS). Absolute value and rate of change of each variable were calculated for each day a dog was in study. Daily means were calculated and plotted against time. The onset of CHF or last visit before leaving the study were set as reference time points. RESULTS: The most extreme values and rate of change occurred in variables immediately before onset of CHF. Vertebral heart sum increased earliest. Heart rate, RR, and RRR also increased. Rectal temperature and BW decreased. Increases in RR and RRR were most extreme and occurred immediately before CHF. CONCLUSIONS AND CLINICAL IMPORTANCE: Dogs with MMVD and cardiomegaly experience increases in HR, RR, RRR, and VHS, and decreases in BW and RT as they develop CHF. The variables with highest absolute change and rate of change were RR and RRR. These findings reinforce the value of RR and RRR as indicators of impending or incipient CHF.
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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".