A comparison of radical vaginal hysterectomy combined with extraperitoneal or laparoscopic pelvic lymphadenectomy in the treatment of cervical cancer.
Bibliographic record
Abstract
BACKGROUND: The use of radical vaginal hysterectomy in the treatment of cervical cancer is associated with lower morbidity and a similar cure rate when compared with the abdominal approach. The present study reports a case series of radical vaginal hysterectomy followed by extraperitoneal (Mitra) or video-laparoscopic (VLP) lymphadenectomy, with comparison of the 2 techniques. METHODS: Twenty-five patients with cervical carcinoma (stages IA1 to IIA) were submitted to radical vaginal hysterectomy and extraperitoneal or laparoscopic lymphadenectomy. RESULTS: The Mitra technique was used in 17 cases, and VLP was used in 8. Seventeen patients presented minor postoperative complications. The number of resected lymph nodes was similar with both techniques (median of 14 with VLP vs. 21 with Mitra) (P = 0.215). The duration of surgery in the VLP group (mean, 339 minutes) was shorter than that of the Mitra group (mean, 421 minutes) (P = 0.015). CONCLUSIONS: The results obtained with both techniques are similar to those reported in the literature. The duration of extraperitoneal lymphadenectomy was longer than that of VLP lymphadenectomy. There were no differences between the 2 techniques concerning the number of resected lymph nodes and hospital stay.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".