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Record W4406000674 · doi:10.1038/s41598-024-84807-0

Use of the Da Vinci SP surgical system in robot-assisted nipple-sparing mastectomy: a single-center, retrospective study

2025· article· en· W4406000674 on OpenAlexfundno aff
Sae Byul Lee, Jisun Kim, Il Yong Chung, Hee Jeong Kim, Jong Won Lee, Byung Ho Son, Beom Seok Ko

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsnot available
FundersIntuitiveIntuitive Surgical
KeywordsMedicineInterquartile rangeSurgeryPerioperativeMastectomyBreast reconstructionDa Vinci Surgical SystemSingle CenterBreast cancerStage (stratigraphy)Retrospective cohort studyRobotic surgeryCancerInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.268
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2025
Admission routes1
Has abstractyes

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