Evidence map›Paper›PMID 39325064›Full record

ArticleJournal of robotic surgery2024

Implementation and outcomes in benign gynecological surgery with HUGO™ RAS system 12 months initial experience.

Yael Yagur, Martin A Martino, Mikhail Sarofim, Mohammed Almoqren, Hayley Anderson, Jessica Robertson, Sarah Choi, David Rosen, Danny Chou

Abstract read
In one paragraph

Article in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
–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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Optimizing arm placement in the HugoUpdates in surgery · 2025
    Article
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

9 authors.

Yael YagurSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia. yaelyagur@gmail.com.ORCID http://orcid.org/0000-0002-3560-6374
Martin A MartinoAscension St. Vincent's, Jacksonville, Florida, University of South Florida, Tampa, Florida, USA.
Mikhail SarofimSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
Mohammed AlmoqrenSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
Hayley AndersonSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
Jessica RobertsonSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
Sarah ChoiSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
David RosenSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.
Danny ChouSydney Women's Endosurgery Centre (SWEC), St George Hospital, Kogarah, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We share our experience with the Hugo™ Robotic-Assisted Surgery system in benign gynecological surgeries. We retrospectively analyzed patients who underwent elective robotic surgeries for benign gynecological conditions at our surgical center from February 2023 to February 2024. Data collected included patient demographics, surgery indications, and outcomes. Perioperative data on port-placement time, arm configurations, docking, and console time were documented. Procedural outcome data including troubleshooting and overall satisfaction were also recorded. The primary outcome was perioperative data on port placement, docking time, arm configuration, and console time. The secondary outcome was defined as team satisfaction, system troubleshooting, arm repositioning, and complications graded 3-4 on the Clavien-Dindo Scale. A total of 60 patients underwent procedures for benign gynecological conditions using the Hugo™ RAS over the 12-month study period, primarily for pelvic endometriosis (53%), hysterectomies (27%), and adnexal surgery (10%). The mean port-placement time was 13 min and 41 s. In 31% of cases, low-port placement was used, with arm positioning being asymmetrical in 63% and symmetrical in 37%, demonstrating the system's flexibility in customizing port configurations while optimizing cosmetic outcomes. Docking time averaged 5 min and 51 s, and console time was 1 h and 5 min. Operational challenges included arm tremors and limited workspace for the assistant. This study details our knowledge using the Hugo™ RAS. Learning curves of port placement, arm positioning, docking, and procedure time can be rapidly adapted in a well-trained team. Our experience suggests the technology is still in its learning curve period.

Indexed as

Gynecologic Surgical ProceduresRobotic Surgical ProceduresAdultEndometriosisFemaleHumansHysterectomyMiddle AgedOperative TimeRetrospective StudiesTime FactorsTreatment OutcomeDa VinciDocking timeHugo™Learning curvePort placementRobotic assisted surgery

Identifiers

PMID39325064
PMCPMC11427502

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.