Epidemiological findings of ocular dermoid in dogs and cats: 50 cases (2007-2024)
Bibliographic record
Abstract
ABSTRACT: A dermoid is a tissue that resembles normal skin in a non-typical anatomical region. Dermoids can be found in various organs and affect ocular structures in the growth of normal tissue in a non-typical anatomical region. The aim of this study was to describe clinical signs, location, histopathologic findings and breed, age, and sex profile of dogs and cats diagnosed with ocular dermoids in the specialized Veterinary Ophthalmology Service of the Federal University of Rio Grande do Sul. Medical records of dogs and cats diagnosed with ocular dermoids from January 2007 to January 2024 were evaluated. Data regarding age, breed, gender, the affected eye and the location of the dermoid were recorded. In total, 53 eyes of 49 dogs affected with dermoid were included in the study. Of these dogs, 29 (59.18%) were male and 20 (40.82%) were female. Of the total number of dermoids diagnosed, 18 (33.96%) were located in the limbal region, 11 (20.75%) in the corneal region, 11 (20.75%) in the eyelid region, five (9.43%) in the bulbar conjunctiva region, five (9.43%) in the conjunctival and palpebral regions, two (3.77%) in the third eyelid and one (1.89%) in the limbal and corneal regions. The average age of the patients at the time of dermoid diagnosis was 1.17 years. In total, 12 dog breeds were represented, including Shih-Tzu, Labrador, Dachshund, French Bulldog, Pug, Rottweiler, English Cocker Spaniel, Doberman, Fila Brasileiro, Lhasa Apso, German Shepherd and Malinois Shepherd. Furthermore, 15 dogs were of mixed breed. A 4-month-old male mixed-breed cat was diagnosed with a dermoid on the bulbar conjunctiva. It is possible to conclude that ocular dermoids most frequently affect young, mixed-breed dogs and Shih Tzus. They occur mainly unilaterally and especially affect the limbal regions of the cornea and the eyelids. Although rare, ocular dermoids can be diagnosed in cats.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".