Polyherbal therapy in management of renal failure in dogs
Bibliographic record
Abstract
The fastest growing urbanisation, environmental contamination, improper feeding practises and the indiscriminate use of certain antibacterial, non-steroidal anti-inflammatory, analgesic and anti-cancer therapeutic drugs have made renal failure as the third most common cause of death in dogs, which affects 2-5% of dogs. Therefore, early diagnosis of the disease can enable an early application of favourable therapeutic interventions to decelerate the disease progression and thus enhance the quality of life. Thus, the objective of the study was to document clinico-epidemiological findings in dogs with renal failure. Sixty dogs found suffering from renal failure, out of which, 36 dogs were randomly selected and divided into two broad groups of infectious and non-infectious origin. These groups were then further sub-divided into 3 treatment groups containing 6 animals in each group and were treated with 3 distinct polyherbal combinations in addition to conventional medication to compare their effectiveness. Following therapy, the treatment efficacy has been analysed based on the lessening of severity of clinical signs and normalisation of the renal function values. In the current investigation, maximum dogs reported were in Stage IV, followed by Stage III, II & I. The prevalence recorded shows most commonly affected dogs belong to age group of 8-10 years (35%) with a higher prevalence of renal failure in males (60%). Breed-wise prevalence study reported Labrador Retriever (35%) was the most commonly affected dog breed. Most common symptoms were inappetence, vomiting, polyuria, polydipsia, weight loss, urine incontinence, dehydration, halitosis, haematuria and oral ulceration. Post treatment with the polyherbal therapy, 12 out of 18 (66.67%) and 9 out of 18 (50%) dogs recovered in infectious and non-infectious group, respectively. In treatment groups, the survivability rate was highest in Group 2 (75%), followed by 50% survivability in Group 1 & Group 3 each. Thus, it was concluded that the efficacy of Group 2 was higher than Group 1 & 3 in terms of survivability.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".