Evidence map›Paper›PMID 25277477›Full record

ArticleSurgical endoscopy2015

Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.

Tomohiro Yamaguchi, Yusuke Kinugasa, Akio Shiomi, Sumito Sato, Yushi Yamakawa, Hiroyasu Kagawa, Hiroyuki Tomioka, Keita Mori

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Article in Surgical endoscopy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 5 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

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

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  5. Learning curve in robotic rectal cancer surgery: current state of affairs.International journal of colorectal disease · 2016
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23 more citing papers are in PubMed but not listed here.

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

8 authors.

Tomohiro YamaguchiDivision of Colon and Rectal Surgery, Shizuoka Cancer Center Hospital, 1007 Shimonagakubo, Nagaizumi-cho, Sunto-gun, Shizuoka, 411-8777, Japan, t.yamaguchi@scchr.jp.
Yusuke Kinugasa
Akio Shiomi
Sumito Sato
Yushi Yamakawa
Hiroyasu Kagawa
Hiroyuki Tomioka
Keita Mori

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single institute.

methodsFrom December 2011 to August 2013, a total of 80 consecutive patients who underwent robotic-assisted surgery for rectal cancer performed by the same surgeon were included in this study. The learning curve was analyzed using the cumulative sum method. This method was used for all 80 cases, taking into account operative time.

resultsOperative procedures included anterior resections in 6 patients, low anterior resections in 46 patients, intersphincteric resections in 22 patients, and abdominoperineal resections in 6 patients. Lateral lymph node dissection was performed in 28 patients. Median operative time was 280 min (range 135-683 min), and median blood loss was 17 mL (range 0-690 mL). No postoperative complications of Clavien-Dindo classification Grade III or IV were encountered. We arranged operative times and calculated cumulative sum values, allowing differentiation of three phases: phase I, Cases 1-25; phase II, Cases 26-50; and phase III, Cases 51-80.

conclusionsOur data suggested three phases of the learning curve in robotic-assisted surgery for rectal cancer. The first 25 cases formed the learning phase.

Indexed as

Learning CurveAdultAgedAged, 80 and overEducation, MedicalFemaleGeneral SurgeryHumansLaparoscopyMaleMiddle AgedOperative TimeRectal NeoplasmsRectumRoboticsSurgeons

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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.