Outcomes of Concurrent Prophylactic Mastectomy and Oophorectomy, Compared to Mastectomy and Hysterectomy, in Hereditary Breast and Gynecologic Cancer: A National Surgical Quality Improvement Program Database Analysis
Bibliographic record
Abstract
Objective: The aim of this research was to assess outcomes of concurrent prophylactic mastectomy and oophorectomy, compared to prophylactic mastectomy and hysterectomy, in patients with hereditary breast and gynecologic cancers. Materials and Methods: This retrospective cohort study of perioperative outcomes used the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database. Of 4673 women undergoing prophylactic mastectomy in the dataset, 82 (1.75%) had concurrent mastectomy and oophorectomy, while 46 (0.98%) had concurrent mastectomy and hysterectomy. Concurrent mastectomy and oophorectomy was compared with concurrent mastectomy and hysterectomy, for outcomes of prophylactic procedures. Results: There were 82 cases of concurrent mastectomy and oophorectomy and 46 cases of concurrent mastectomy and hysterectomy. No significant differences in age (mean ± standard deviation: 46.37 ± 9.00 versus 44.00 ± 8.66 years), normal body mass index (45.12% versus 45.65%), nonsmoking status (82.93% versus. 89.13%), diabetes (3.66% versus 0.00%), classified American Society of Anesthesiologists I (17.07% versus 26.09%), and preoperative hematocrit (38.39 ± 3.51 versus 37.05 ± 6.69) were found. Concurrent mastectomy and hysterectomy were more likely to be inpatient surgeries (86.96% versus. 69.51%; p < 0.05), compared to concurrent mastectomy and oophorectomy. There were no significant differences in rates of surgical-site infections, sepsis, wound disruptions, pelvic visceral injury, intraoperative and postoperative transfusions, and reoperations. Conclusions: Surgical outcomes are similar when comparing concurrent mastectomy and hysterectomy to mastectomy and oophorectomy. The NSQIP data suggest either strategy does not increase surgical and medical complications perioperatively. (J GYNECOL SURG 38:148)
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".