What is the number of lymph nodes required for an "adequate" pelvic lymphadenectomy?
Bibliographic record
Abstract
PURPOSE OF INVESTIGATION: To establish a definition of an adequate number of lymph nodes identified at a pelvic lymphadenectomy through statistical methods. METHODS: We conducted a retrospective study in cervical and endometrial carcinoma patients who underwent radical or staging surgery. The Student's t-test, Pearson's correlation, analysis of variance, and linear regression analysis were used. RESULTS: Five hundred and ninety four-sided pelvic lymphadenectomies were analyzed. The mean (range) number of pelvic lymph nodes identifed was 11.3 (0-42). The 1st, 5th and 10th percentiles were three, five, and six lymph nodes respectively. The number of lymph nodes was higher in the laparoscopic approach compared to laparotomy (11.9 vs 10.6, p < 0.01). CONCLUSIONS: The number of lymph nodes identified at a pelvic lymphadencetomy vary with type of surgery. We propose that using the 1st, 5th or 10th percentile is reasonable for the definition of an adequate number of lymph nodes to be identified at a pelvic lymphadenectomy.
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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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".