Sonographic Evaluation of Liver Hemodynamic Indices in Overweight and Obese Dogs
Bibliographic record
Abstract
BACKGROUND: Hepatic circulatory disturbances have been associated with obesity and fatty liver in humans. In the veterinary literature, however, there is limited information regarding the effects of different body condition scores (BCS) on liver hemodynamic indices in dogs. OBJECTIVES: To investigate the influence of BCS on liver hemodynamic indices. ANIMALS: Fifty-three client-owned dogs of various breeds were included. METHODS: Prospective observational study. Dogs were divided into 3 BCS groups using a 5-point scale: G1 - 12 ideal dogs, G2 - 21 overweight dogs, G3 - 20 obese dogs. Mean portal velocity (MPV), portal blood flow volume (PBFV), portal congestion index (PCI), hepatic artery resistivity index (HARI), and hepatic vein (HV) spectral wave were obtained by pulsed Doppler sonography. Alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), and alanine aminotransferase (ALT) activities were determined. Liver enzymes activities and liver hemodynamic indices were compared among groups. RESULTS: Obese dogs had lower MPV, higher percentage of abnormal hepatic vein spectral wave and higher median ALP activity than did ideal dogs (P < 0.05). Overweight and obese dogs had lower PBFV than ideal dogs (P < 0.01). Overweight dogs had higher median GGT activity than ideal dogs (P < 0.05). No difference was observed for PCI, HARI and median ALT activity among the groups. CONCLUSIONS AND CLINICAL IMPORTANCE: Obesity was associated with changes in portal vein indices and in HV spectral wave. These changes were accompanied by significant differences in some liver enzymes activities and could be a sign of early liver disease.
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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".