Evidence map›Paper›PMID 39046468›Full record

ArticleArchives of gynecology and obstetrics2025

Feasibility evaluation of the Versius surgical system: robot-assisted hysterectomy for benign and malignant gynaecological lesions.

Pawel Sadlecki, Malgorzata Walentowicz-Sadlecka

Abstract read
In one paragraph

Article in Archives of gynecology and obstetrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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

2 authors.

Pawel SadleckiMedical Department, University of Science and Technology, Bydgoszcz, Poland. sadleckip@gmail.com.ORCID 0000-0001-8355-2553
Malgorzata Walentowicz-SadleckaMedical Department, University of Science and Technology, Bydgoszcz, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe application of minimally invasive surgery allows for radical and precise removal of the gynaecological lesion while simultaneously reducing the side effects and complications associated with surgical treatment. This paper aims to share our direct experience with the implementation of the CMR Versius robotic platform in the treatment of benign and malignant gynaecological lesions.

methodsThis study included patients who underwent hysterectomy in the Department of Obstetrics, Gynaecology, and Gynaecologic Oncology at the Regional Polyclinical Hospital in Grudziadz, Poland. A total of 50 patients were included in the study: 29 underwent laparoscopic surgery and 21 underwent robot-assisted surgery using the CMR Versius system.

resultsIt was found that in the case of non-radical hysterectomy, the duration of surgery differed significantly (96.5 vs. 134.6 min, p < 0.01) in the groups of patients undergoing laparoscopic and robotic surgery. There were also no statistically significant differences in loss of blood parameters, rate of complications and conversions to other type of surgery after the laparoscopic and robotic surgeries. Both groups did not differ significantly in terms of hospitalisation time after surgery.

conclusionVersius CMR surgical robot assistance provides safe and effective support for MIS procedures in gynaecology.

Indexed as

Genital Neoplasms, FemaleHysterectomyRobotic Surgical ProceduresAdultAgedFeasibility StudiesFemaleHumansLaparoscopyLength of StayMiddle AgedOperative TimeCMR VersiusMinimally invasive surgeryRobotic assisted hysterectomyRobotic assisted radical hysterectomy

Identifiers

PMID39046468
PMCPMC11890229

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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.