Hypothyroidism in a geriatric labrador retriever: Clinical diagnosis and therapeutic management
Bibliographic record
Abstract
Canine hypothyroidism is a commonly reported endocrine disorder, particularly in aging, large-breed dogs, resulting from inadequate secretion of thyroid hormones and leading to metabolic, dermatological, and systemic alterations. This case report describes hypothyroidism (serum T3 level: 0.52 ng/ml) in a 10-year-old Labrador Retriever presented with lethargy, progressive weight gain, and chronic dermatological abnormalities. Diagnosis was established based on clinical signs, supportive hematobiochemical findings, and decreased serum total thyroxine concentration. The treatment protocol included oral levothyroxine at a dose of 22 µg/kg body weight, fexofenadine hydrochloride at 4 mg/kg, ketoconazole at 5 mg/kg, along with supportive therapy comprising LivFit syrup (15 ml twice daily) and GlowCoat syrup (15 ml twice daily). Topical management involved bathing with Nuforce NF Pet shampoo twice weekly for one month, followed by Keramed Vet shampoo once weekly. Therapy was continued for a total duration of six months. Marked clinical improvement was observed within three months of treatment, with significant resolution of lethargy and skin lesions. After six months of therapy, serum thyroxine levels increased to 0.79 ng/ml, following which antifungal therapy and nutritional supplements were gradually discontinued. This report highlights the importance of considering hypothyroidism as a differential diagnosis in geriatric dogs presenting with nonspecific clinical signs and chronic dermatological conditions, and emphasizes the effectiveness of appropriate hormone replacement and supportive therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".