Outcomes associated with different surgical approaches to radical hysterectomy: A systematic review and network meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy and safety of five different approaches to cervical cancer surgery. METHODS: We conducted a systematic search for comparative studies on different radical hysterectomy types for cervical cancer in PubMed, Embase, the Cochrane Library, and Web of Science databases. All included observational studies used survival analyses to compare clinical outcomes of patients undergoing different radical hysterectomy types. All studies were assessed by the Newcastle-Ottawa Scale with scores of at least seven points. We extracted the relevant data and conducted a network meta-analysis to compare clinical outcomes among five surgical approaches. RESULTS: Thirty studies (n = 11 353) were included. Robotic surgery had the lowest blood loss volume and hospitalization duration; open surgery had the shortest operative time. Vaginal assisted laparoscopic surgery was associated with the highest number of resected lymph nodes and lowest rate of perioperative complications. Survival outcomes and tumor recurrence outcomes were similar among the approaches. CONCLUSION: The current approaches to cervical cancer surgery have comparable efficacies.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".