Radiographic findings in dogs with 360 degrees gastric dilatation and volvulus
Bibliographic record
Abstract
Gastric dilatation and volvulus (GDV) is a life-threatening emergency that requires urgent intervention. Radiographic features associated with 360-GDV in dogs have not been investigated. The aim of this retrospective observational study is to describe radiographic features and clinical variables in dogs affected with 360-GDV and to report agreement rates between different radiologists. We also report the sensitivity and specificity of radiographs to diagnose 360-GDV in dogs. Confirmed 360-GDV cases were retrieved, and the radiographic findings were compared with dogs presenting with gastric dilatation (GD) and 180-GDV. Images were reviewed and graded by three blinded board-certified radiologists. A total of 16 dogs with confirmed 360-GDV were identified. The median age was 10 years old (2-13 years). The sensitivity for detection of 360-GDV ranged between 43.7% and 50%, and the specificity between 84.6% and 92.1%. Interobserver agreement on final diagnosis was substantial (Kappa = 0.623; 0.487-0.760, 95% CI). The highest agreement rate was in cases of 180-GDV (87%), followed by the GD cases (72%) and 360-GDV (46%). Severe esophageal distension and absence of small intestinal dilation were the only radiographic features specifically associated with 360-GDV. A similar pyloric position was found between GD and 360-GDV. Additional radiographic variables that could help differentiate GD from 360-GDV include the degree of gastric distension and the peritoneal serosal contrast. Two cases with 360-GDV were misdiagnosed by the three radiologists as GD. In conclusion, radiographically, 360-GDV cases can reassemble GD and vice versa. Radiologists and clinicians should be aware of the low sensitivity of radiographs for the detection of 360-GDV.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".