Effect of Pimobendan on Case Fatality Rate in Doberman Pinschers with Congestive Heart Failure Caused by Dilated Cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Despite traditional therapy of a diuretic, angiotensin converting enzyme inhibitor, digoxin, or a combination of these drugs, survival of dogs with dilated cardiomyopathy (DCM) is low. Pimobendan, an inodilator, has both inotropic and balanced peripheral vasodilatory properties. HYPOTHESIS: Pimobendan when added to conventional therapy will improve morbidity and reduce case fatality rate in Doberman Pinschers with congestive heart failure (CHF) caused by DCM. ANIMALS: Sixteen Doberman Pinschers in CHF caused by DCM. METHODS: A prospective randomized, double-blind, placebo-controlled study with treatment failure as the primary and quality of life (QoL) indices as secondary outcome variables. Therapy consisted of furosemide (per os [PO] as required) and benazepril hydrochloride (0.5 mg/kg PO q12h) and dogs were randomized in pairs and by sex to receive pimobendan (0.25 mg/kg PO q12h) or placebo (1 tablet PO q12h). RESULTS: Pimobendan-treated dogs had a significant improvement in time to treatment failure (pimobendan median, 130.5 days; placebo median, 14 days; P= .002; risk ratio = 0.35, P= .003, lower 5% confidence limit = 0.13, upper 95% confidence limit = 0.71). Number and rate of dogs reaching treatment failure in the placebo group precluded the analysis of QoL. CONCLUSIONS AND CLINICAL IMPORTANCE: Pimobendan should be used as a first-line therapeutic in Doberman Pinschers for the treatment of CHF caused by DCM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".