Evidence map›Paper›PMID 39518542›Full record

ArticleJournal of clinical medicine2024

Total Mesorectal Excision with New Robotic Platforms: A Scoping Review.

Francesco Marchegiani, Carlo Alberto Schena, Gaia Santambrogio, Emilio Paolo Emma, Ivan Tsimailo, Nicola de'Angelis

Abstract readScoping Review
In one paragraph

Article in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Guideline
  2. 2025 Delphi consensus on robotic ventral mesh rectopexy.International journal of colorectal disease · 2025
    Guideline
  3. Article
  4. Review
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

6 authors.

Francesco MarchegianiUnit of Colorectal and Digestive Surgery, DIGEST Department, Beaujon University Hospital, AP-HP, University of Paris Cité, 92110 Clichy, France.
Carlo Alberto SchenaUnit of Robotic and Minimally Invasive Digestive Surgery, Department of Surgery, Ferrara University Hospital, 44124 Ferrara, Italy.ORCID 0000-0003-1136-1103
Gaia SantambrogioUnit of Colorectal and Digestive Surgery, DIGEST Department, Beaujon University Hospital, AP-HP, University of Paris Cité, 92110 Clichy, France.ORCID 0000-0003-0474-4018
Emilio Paolo EmmaUnit of Colorectal and Digestive Surgery, DIGEST Department, Beaujon University Hospital, AP-HP, University of Paris Cité, 92110 Clichy, France.
Ivan TsimailoUnit of Colorectal and Digestive Surgery, DIGEST Department, Beaujon University Hospital, AP-HP, University of Paris Cité, 92110 Clichy, France.
Nicola de'AngelisUnit of Robotic and Minimally Invasive Digestive Surgery, Department of Surgery, Ferrara University Hospital, 44124 Ferrara, Italy.ORCID 0000-0002-1211-4916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal surgery is one of the specialties that have significantly benefited from the adoption of robotic technology. Over 20 years since the first robotic rectal resection, the Intuitive Surgical Da Vinci system remains the predominant platform. The introduction of new robotic systems into the market has enabled the first documented total mesorectal excision (TME) using alternative platforms. This scoping review aimed to assess the role and adoption of these emerging robotic systems in performing TME for rectal cancer surgery.

Indexed as

abdominoperineal resectionintersphincteric resectionrectal anterior resectionrectal cancerroboticsrobotic surgeryTaTMEtotal mesorectal excision

Identifiers

PMID39518542
PMCPMC11546395

What OpenQuestion holds

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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.