Plasma Big Endothelin-1, Atrial Natriuretic Peptide, Aldosterone, and Norepinephrine Concentrations in Normal Doberman Pinschers and Doberman Pinschers with Dilated Cardiomyopathy
Bibliographic record
Abstract
Abstract Background: Dilated Cardiomyopathy (DCM) results in progressive myocardial and circulatory dysfunction causing activation of a number of neurohormonal systems, including the endothelin (ET) system, which is only beginning to be described in clinical veterinary medicine. Measurement of these circulating neurohormones possesses potential utility in the diagnosis, staging, and assessment of prognosis in cardiac disease. Hypothesis: We hypothesized that plasma big ET-1, norepinephrine (NE), aldosterone, and atrial natriuretic peptide (ANP) concentrations in normal Dobermans would differ from those in Dobermans with DCM, and that concentrations of these hormones would be associated with time to congestive heart failure (CHF) or death. Animals: Thirty client-owned Dobermans (10 each of normal, occult DCM, and overt DCM) were included in the study. Methods: Dogs underwent an echocardiogram, ECG, and blood sample collection. Neurohormones were measured by high-pressure liquid chromatography (NE) or commercial assays. Results: Dogs with occult DCM had significantly higher ANP concentrations compared with normal dogs (least squares means [95% confidence interval, CI]: occult female 53.7 pg/mL [40.2–71.7] versus normal female 31.6 pg/mL [24.8–40.3], P= .026; occult male 86.1 pg/mL [64.7–115] versus normal male 12.1 pg/mL [5.1–28.7], P= .011). Dogs with overt DCM had significantly higher concentrations of all neurohormones compared with the normal group. Furthermore, increasing big ET-1 (risk ratio [RR] 2.7, CI 1.3–8.6, P= .01) and NE concentrations (RR 3.9, CI 1.1–18.1, P= .03) over 1 month were associated with a shorter survival time. Conclusions and Clinical Importance: High ANP concentrations can identify dogs with advanced occult DCM. Increasing big ET-1 or NE concentrations over time can be useful predictors of poor prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".