Assessment of Diastolic Function by Doppler Echocardiography in Normal Doberman Pinschers and Doberman Pinschers with Dilated Cardiomyopathy
Bibliographic record
Abstract
Abstract Background: Assessment of diastolic function in patients with dilated cardiomyopathy (DCM) has the potential to add valuable information regarding hemodynamics, disease severity, and prognosis. The purpose of this study was to determine transmitral flow (TMF), isovolumic relaxation time (IVRT), pulmonary venous flow (PVF), flow propagation velocity (Vp), and mitral annular velocities by tissue Doppler in Doberman Pinschers with and without DCM. Hypothesis: It was anticipated that normal and DCM Dobermans would differ with respect to these parameters, and that associations with time to congestive heart failure (CHF) or death would be found. Animals: Thirty client-owned Doberman Pinschers (10 each of normal, occult DCM, and overt DCM) were studied. Methods: Each dog underwent echocardiography with or without thoracic radiography (to confirm CHF) for classification as normal or DCM-affected, followed by collection of echocardiographic diastolic parameters. Results: The group with occult DCM exhibited features of pseudonormal TMF, reduced systolic to diastolic PVF ratio, and reduced Vp. Shorter early TMF deceleration time (DTE) was associated with shorter time to CHF or sudden death. The group with overt DCM exhibited restrictive TMF, blunted systolic PVF, and reduced early and late diastolic mitral annular velocities. Conclusions and Clinical Importance: Doberman Pinschers showed evidence of moderate and severe diastolic dysfunction in occult and overt DCM, respectively. Short DTE may be a useful predictor of onset of CHF or sudden death.
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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 | 0.001 |
| 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".