Gastrointestinal angiodysplasias diagnosed using video capsule endoscopy in 15 dogs
Bibliographic record
Abstract
BACKGROUND: Angiodysplasia (AGD) is rarely diagnosed in dogs with gastrointestinal bleeding (GIB) and is reported in case reports in dogs. OBJECTIVE: Describe signalment, clinical and diagnostic features of dogs with gastrointestinal (GI) AGD diagnosed by video capsule endoscopy (VCE). ANIMALS: Dogs with overt or suspected GIB which underwent VCE. METHODS: Dogs for which a VCE was submitted for overt or suspected GIB from 2016 to 2021 were selected retrospectively. Medical records and full-length VCE recordings where AGDs were initially detected, were reviewed by 2 trained internists. AGD was considered definitive if 2 readers detected it. Signalment, clinical signs, blood work, medications, concurrent diseases, findings of previous conventional endoscopy, and surgical exploration (if applicable) of dogs with AGD were recorded. RESULTS: Definitive AGD was diagnosed in 15 of 291 (5%) dogs (12 males, 3 females). Twelve (80%) had overt GIB, 11 (73%) had hematochezia, and 6 (40%) had microcytic and hypochromic anemia. AGD was missed by conventional endoscopy in 9/9 dogs and exploratory surgery in 3/3 dogs. Thirteen capsules were administered by mouth (1 incomplete study), and 2 via endoscopy directly into the duodenum. AGD was visualized in the stomach of 3 dogs, in the small intestine of 4, and in the colon of 13 dogs. CONCLUSION AND CLINICAL IMPORTANCE: Although rare, AGD should be considered in dogs with suspected GIB after a negative conventional endoscopy or surgical exporation. Video capsuel endoscopy appears to be a sensitive test to identify AGD within the GI tract.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".