Epidemiological Valuation of Renal Diseases in Dogs in and Around Guwahati Region of Assam, India
Bibliographic record
Abstract
Renal disease is one of the most common and fatal condition occurring in dogs. Only few reports are available on the prevalence of renal diseases in dogs in India in general and in Assam in particular. The present study was intended to report the prevalence of renal diseases in dogs registered at Veterinary Clinical Complex, Guwahati, Assam over a period of 5 years. The study was conducted on all the dogs registered at veterinary clinical complex, college of veterinary science, Khanapara from January 2018 to December 2022. The dogs were screened for renal diseases on the basis of patient’s history, clinical signs and symptoms; and were confirmed for renal diseases on the basis of haemato-biochemical analysis, urinalysis and diagnostic study (imaging techniques like radiography and ultrasonography). The overall prevalence of renal disorder in dogs was found to be 2.74%. The breed-wise occurrence of renal disorder was found to be highest in Labrador retriever (29.71%) followed by non-descript breed (17.22%). The sex-wise occurrence was found to be higher in males (60.08%) than female dogs (39.92 %). Highest occurrence of renal disease was observed in the age group of greater than 6-10 Years (31.74%) followed by age group of greater than 3-6 Years (26.38%). The present study evaluated the prevalence of renal diseases in dogs in and around Guwahati region. The highest occurrence of renal disorder was observed in Labrador dogs while English pointer is the least affected one amongst all the breeds. The occurrence of renal disorder in dogs was found be increased with the advancement of age. Male dogs are more prone to renal disorder compared to female dogs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".