Comprehensive clinical, hematobiochemical, urinary, and ultrasonographic profiling of canine chronic kidney disease: A multimodal diagnostic evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chronic kidney disease (CKD) is a progressive and irreversible condition frequently encountered in canine practice. This study aimed to determine the prevalence of CKD in dogs and to evaluate the associated clinical signs and hematological, biochemical, urinary, and ultrasonographic alterations. A total of 3, 180 dogs presented to the Veterinary Clinical Complex, Khanapara, were screened over a six-month period, and 40 were confirmed with CKD, yielding an overall prevalence of 1.25%. Labrador Retrievers, male dogs, and animals aged >6-10 years showed the highest prevalence. The most common clinical signs included inappetence, vomiting, polyuria, polydipsia, diarrhoea, oral lesions, weight loss, and lethargy. Hematological evaluation revealed a significant increase in WBC count, while reductions in RBC, Hb, and Hct values were non-significant. Biochemical analysis demonstrated markedly elevated serum creatinine, BUN, phosphorus, and potassium, accompanied by decreased albumin and chloride levels. Urinalysis showed amber to deep amber urine, presence of crystals, RBCs, WBCs, epithelial cells, and an increased UPC ratio, indicating proteinuria. Ultrasonographic findings included heightened renal echogenicity, loss of corticomedullary distinction, and changes in renal size, all suggestive of chronic renal pathology. Overall, the study highlights the importance of a multimodal diagnostic approach combining clinical assessment with hematological, biochemical, urinary, and imaging evaluations for the early detection and accurate staging of CKD in dogs.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it