Evidence map›Paper›PMID 37510973›Full record

ArticleJournal of clinical medicine2023

Robotic Total Mesorectal Excision for Low Rectal Cancer: A Narrative Review and Description of the Technique.

Giampaolo Formisano, Luca Ferraro, Adelona Salaj, Simona Giuratrabocchetta, Gaetano Piccolo, Giulia Di Raimondo, Paolo Pietro Bianchi

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Giampaolo FormisanoDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.
Luca FerraroDepartment of General Surgery, Asst Santi Paolo e Carlo, 20142 Milan, Italy.ORCID 0000-0002-9666-5634
Adelona SalajDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.
Simona GiuratrabocchettaDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.
Gaetano PiccoloDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.
Giulia Di RaimondoDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.
Paolo Pietro BianchiDepartment of Surgery, Asst Santi Paolo e Carlo, Dipartimento di Scienze della Salute, University of Milan, 20122 Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic surgery may offer significant advantages for treating extraperitoneal rectal cancer. Although laparoscopy has been shown to be safe and effective, laparoscopic total mesorectal excision (TME) remains technically challenging and is still performed in selected centers. Robotic anterior resection (RAR) may overcome the drawback of conventional laparoscopy, providing high-quality surgery with favorable oncological outcomes. Moreover, recent data show how RAR offers clinical and oncological benefits when affording difficult TMEs, such as low and advanced rectal tumors, in terms of complication rate, specimen quality, recurrence rate, and survival. This series aims to review the most recent and relevant literature, reporting mid- and long-term oncological outcomes and focusing on minimally invasive RAR for low rectal cancer.

Indexed as

long-term outcomesrectal cancerrobotic anterior resectiontotal mesorectal excision

Identifiers

PMID37510973
PMCPMC10381747

What OpenQuestion holds

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Registered trials

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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.