Epidemiological Assessment of Systemic Hypertension in Dogs
Bibliographic record
Abstract
Systemic hypertension in dogs is a clinically significant condition often associated with underlying diseases. The objective of this study was to assess the prevalence and distribution of hypertension in dogs. A total of 214 dogs (149 males and 65 females, irrespective of age and breed) were surveyed randomly at the Veterinary Clinical Complex, College of Veterinary Science & Animal Husbandry, Nanaji Deshmukh Veterinary Science University, Jabalpur, Madhya Pradesh, India, between May and October 2024. This study comprised of 81 clinically healthy dogs and 133 dogs diagnosed with various systemic co-morbidities. Blood pressure measurements were performed using a Doppler Vet BP machine following ACVIM guidelines (Acierno et al.,2018). Clinical Hypertension (SAP ≥160 mmHg) using Doppler NIBP was recorded in 39 dogs, resulting in an overall prevalence of 18.22%. Secondary hypertension was more common (27.81%) compared to primary hypertension (2.46%), reinforcing the strong association between hypertension and concurrent diseases. Age-wise analysis revealed a higher prevalence in dogs over 8 years (30%), suggesting an age-related predisposition. Male dogs (76.92%) were more frequently affected than females (23.07%). Breed predisposition was observed, with Labrador Retrievers (33.3%) and German Shepherds (23.07%) showing the highest occurrence.
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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 | 0.002 | 0.001 |
| 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".