Outcome and quality of life in a prospective cohort of the first 100 robotic surgeries for endometrial cancer, with focus on elderly patients.
Bibliographic record
Abstract
OBJECTIVE: Evaluation of surgical outcomes, including quality of life, in patients with endometrial cancer in the early phase of implementation of a robotic surgery program, comparing elderly with younger patients. METHODS: Prospective evaluation of perioperative data and a postoperative quality-of-life survey of the first 100 robotic surgeries for endometrial cancer performed in the Division of Gynecologic Oncology at a tertiary cancer center. Women were divided in 2 groups based on age, allowing comparison of outcomes between the elderly (≥70 years) and younger groups (<70 years). RESULTS: Of the first 100 patients, 41 were elderly (mean age, 78 years). The elderly group had significantly higher number of comorbidities and more advanced disease when compared with the younger women. Despite this, elderly women had similar mean operative times (252 vs 243 minutes), mean console times (171 vs 175 minutes), and mean blood loss (83 vs 81 mL) as compared with the younger group. Conversion rate to minilaparotomy was 6%, all of which were performed at the end of surgery for the removal of enlarged uteri that could not be delivered vaginally. The overall perioperative complication rates were not statistically different between the age groups. Median hospital stay tended to be longer for the elderly women (2 vs 1 day) but was not statistically significant. The postoperative quality-of-life assessment revealed that patients young and old alike were highly satisfied with the procedure. CONCLUSIONS: Prospective evaluation indicates that even in the early phases of implementation of a robotic surgical program for endometrial cancer, the procedure seems safe and confers an excellent quality of life for elderly patients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".