Evidence map›Paper›PMID 32582511›Full record

ArticleInternational cancer conference journal2020

Combined robotic and cystoscopic surgery for rectal cancer invading urinary bladder.

Kenji Kawada, Takashi Kobayashi, Rei Mizuno, Saori Goto, Yoshiharu Sakai

Open access · greenAbstract read
In one paragraph

Article in International cancer conference journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Kenji KawadaDepartment of Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin, Kawara-cho, Sakyo-ku, Kyoto, 606-8507 Japan.
Takashi KobayashiDepartment of Urology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Rei MizunoDepartment of Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin, Kawara-cho, Sakyo-ku, Kyoto, 606-8507 Japan.
Saori GotoDepartment of Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin, Kawara-cho, Sakyo-ku, Kyoto, 606-8507 Japan.
Yoshiharu SakaiDepartment of Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin, Kawara-cho, Sakyo-ku, Kyoto, 606-8507 Japan.
Kyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the application of laparoscopic rectal surgery has been widely accepted by accumulated evidence, it remains technically difficult in some cases of obesity, narrow male pelvis, bulky tumors, or involvement of adjacent organs. After robotic rectal surgery has been covered by the health insurance system in Japan since April 2018, we have employed robotic rectal surgery for an increasing number of cases by taking advantages of its 3D vision and wrist function. When a colorectal cancer involves the urinary bladder, the surgical treatment of choice is an anterior resection with en bloc (partial or total) bladder resection, depending on the site and extent of bladder involvement. In the attached video, robotic surgery was conducted with the aid of intraoperative cystoscopy, which resulted in curative resection with negative margin. Given that the robotic system provides excellent stability and dexterity for bladder reconstruction, the robotic approach can be technically suitable for locally advanced T4 colorectal cancer with urinary involvement.

Indexed as

Intraoperative cystoscopyRectal cancer invading urinary bladderRobot-assisted rectal surgery

Identifiers

PMID32582511
PMCPMC7297884
OpenAlexW3014109415

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.