Evidence map›Paper›PMID 29285610›Full record

ArticleWorld journal of surgery2018

A Pilot Study for a Better Visibility in the 3D Laparoscopic Right Colectomy Surgery.

Lei Gu, Pei-Lin Liu, Hong Zhou, Qing Xu

Abstract read
PubMed Publisher
In one paragraph

Article in World journal of surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Lei GuDepartment of Gastrointestinal Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, People's Republic of China.
Pei-Lin LiuSchool of Electronic Information and Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Hong ZhouDepartment of Gastrointestinal Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, People's Republic of China.
Qing XuDepartment of Gastrointestinal Surgery, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, People's Republic of China. renjixuqing@163.com.

Funding

Renji hospital clinical research innovation fund PYXJS16-007
6 · The paper itself

Abstract

objectiveThe aim of this study was to investigate the feasibility of digital defog technique in 3D laparoscopic surgery for right colon cancer.

methodsFifty patients with right colon cancer were divided into digital defogging group and control group. The intraoperative image clarity, the surgeon's anxiety, the time of operation and the time of fog nursing were compared.

resultsThe clarity of the video screen of the digital defogging group was significantly higher than that of the control group, and the degree of anxiety was significantly lower than that of the control group. The operative time was (136.4 ± 30.4) min in the digital defogging group, the operation time of the control group was (168.7 ± 32.7) min, and the difference was statistically significant (P < 0.05). The time of dehumidification was (4.8 ± 1.3) min in the digital defogging group and (16.3 ± 4.6) min in the control group, and the difference was statistically significant (P < 0.05).

conclusionDigital defogging technology in the 3D laparoscopic right colon cancer surgery significantly improves the clarity of video images, reduces the surgeon due to screen clarity caused by anxiety, reduces the operation of right colon cancer time and reduces the time to fog care.

Indexed as

AdultAgedColectomyColonic NeoplasmsFemaleHumansLaparoscopyMaleMiddle AgedOperative TimePilot Projects

Identifiers

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.