Indication and Method of Frozen Section in Vaginal Radical Trachelectomy
Bibliographic record
Abstract
Vaginal radical trachelectomy (VRT) is a fertility-sparing surgical technique used as an alternative to radical hysterectomy in early stage cervical carcinoma. With the advent of VRT, preoperative evaluation of the surgical margin has become imperative, because if the tumor is found within 5 mm of the endocervical margin, additional surgical resection is required. In a study published earlier from our center, we came to the conclusion that a frozen section should be conducted only when a cancerous lesion is grossly visible, and that it could be omitted in normal-looking specimens or VRT with nonspecific lesions. Since then, 53 VRT have been performed in our center, and frozen sections were conducted according to these recommendations. Fifteen VRT were grossly normal, 24 had a nonspecific lesion and 14 showed a grossly visible lesion. Final margins were satisfactory on all 15 grossly normal specimens. Of the 24 VRT with nonspecific lesions, 2 cases for which no frozen section was performed had unsatisfactory final margins (<5 mm). Of the 14 VRT with grossly visible lesions, 3 cases were inadequately evaluated by frozen section due to sampling errors, which led to unsatisfactory final margin assessment. These results confirm that a frozen section can be omitted on normal looking VRT specimens, but contrary to results published earlier, we recommend that a frozen section be performed on all VRT with nonspecific lesions. As for VRT with a grossly visible lesion, frozen section evaluation is still warranted, and we recommend increasing the sampling to improve the adequacy of frozen sections.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".