Ventral cervical versus bilateral lateral approach for extirpation of mandibular and medial retropharyngeal lymph nodes in dogs
Bibliographic record
Abstract
OBJECTIVE: To compare ventral cervical and bilateral lateral incisions for extirpation of mandibular and medial retropharyngeal lymph nodes in dogs. STUDY DESIGN: Prospective randomized, crossover controlled cadaver trial. SAMPLE POPULATION: Eight veterinarians with advanced surgical training. METHODS: Study participants were randomized to perform both techniques on paired cadavers. Time to extirpation of the first and last lymph node, length of incisions, and complications were recorded for both techniques. Participants were asked to rate satisfaction with their ability to identify local anatomy and lymph nodes as well as overall preferred technique by using a 10-point numerical rating scale. RESULTS: The total length of skin incised for the bilateral lateral approach exceeded that of the ventral cervical approach by 52.1 mm (mean, P < .001). The surgical time for removal of all 4 lymph nodes did not differ between the 2 approaches. The bilateral lateral approach was preferred by 62.5% (5/8) of participants for visualization of mandibular lymph nodes, and the ventral cervical approach was preferred by 87.5% (7/8) of participants for visualization of local anatomy. Overall, 62.5% (5/8) preferred the ventral cervical approach and 37.5% (3/8) preferred the bilateral lateral approach. CONCLUSION: The ventral cervical approach was preferred by participants for its perceived superior visualization of local anatomy and access to lymph nodes for removal. This approach also resulted in an overall shorter incision length. CLINICAL SIGNIFICANCE: A ventral cervical or bilateral lateral approach allows successful removal of the medial mandibular and retropharyngeal lymph nodes in dogs, and surgical approach may be selected according to individual preference.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".