Evidence map›Paper›PMID 40330667›Full record

ReviewJSLS : Journal of the Society of Laparoendoscopic Surgeons

Optimizing Robotic Surgical Assistance: Shorten the Learning Curve for Urologic Oncology Cases.

Lixian Zhu, Dan Xia, Shuo Wang, Sunyi Ye

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in JSLS : Journal of the Society of Laparoendoscopic Surgeons. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lixian ZhuDepartment of Thyroid Disease Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. (Dr. Lixian).
Dan XiaDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. (Drs. Dan, Shuo, and Ye).
Shuo WangDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. (Drs. Dan, Shuo, and Ye).
Sunyi YeDepartment of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. (Drs. Dan, Shuo, and Ye).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: While robotic surgery platforms are widely used, there is a dearth of literature on robotic assistants. This study aims to provide a comprehensive understanding of the role and functions of a valuable assistant in robotic surgery. Methods: The first author has garnered over 10 years of experience as an assistant at a high-volume urological center, where more than 10,000 robotic operations have been performed. This paper delves into the specific intricacies of how an assistant collaborates with the chief surgeon. Results: The assistant's primary responsibilities encompass ensuring the precise placement of trocars to facilitate the chief surgeon's manipulation of the robot and assisting in the optimal exposure of the surgical area according to the chief surgeon's requirements. Conclusions: The assistant assumes a pivotal role in robot-assisted surgery, necessitating a profound understanding of the chief surgeon's intentions and the ability to effectively expose the operative field.

Indexed as

Learning CurveRobotic Surgical ProceduresUrologic NeoplasmsUrologic Surgical ProceduresHumansAssistantPartial nephrectomyRadical cystectomyRadical prostatectomyRobotic surgery

Identifiers

PMID40330667
PMCPMC12054619

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.