Use of the Da Vinci SP surgical system in robot-assisted nipple-sparing mastectomy: a single-center, retrospective study
Bibliographic record
Abstract
We investigated the safety and performance of the Da Vinci SP single-port robot (SP robot) in nipple-sparing mastectomy (NSM) with immediate reconstruction. Medical records of 60 women aged ≥ 19 years who had undergone SP robot-assisted unilateral or bilateral NSM with immediate reconstruction between October 2020 and August 2021 were retrospectively analyzed. Stage I (31, 47.1%) was the most common pathological tumor-node-metastasis stage, followed by stages II (22, 33.3%), 0 (7, 10.6%), and III (4, 6.0%). The median total duration of NSM performed by a breast surgeon and reconstruction performed by a plastic surgeon was 154.0 min (interquartile range [IQR], 130.5-206.0 min) and 133.0 min (IQR, 80.0-255.0 min), respectively. The median length of hospitalization was 5.5 days (IQR, 3.0-9.0 days). Conversion to robotic multiport or open surgery was not required in any case. The median duration to drain removal was 5.0 days (IQR, 4.0-6.0 days). Recurrence of cancer within 6 months was not observed in any patient. SP robot-assisted NSM with immediate reconstruction was performed successfully in all patients without conversion to open surgery or the incidence of significant perioperative complications, indicating its precision and ability to minimize the size of the surgical incision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".