Evidence map›Paper›PMID 30508949›Full record

ArticleMedicine2018

Minimally invasive and open gastrectomy for gastric cancer: A protocol for systematic review and network meta-analysis.

Xixiong Wang, Zhiqiang Li, Meizhu Chen, Chenming Wu, Yexiang Fu

Abstract read
In one paragraph

Article in Medicine, 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

5 authors.

Xixiong WangDepartment of Surgical Oncology, Boao Evergrande International Hospital, Qionghai.
Zhiqiang LiDepartment of Gastrointestinal Surgery, Sanya People's Hospital, Sanya, China.
Meizhu ChenDepartment of Gastrointestinal Surgery, Sanya People's Hospital, Sanya, China.
Chenming WuDepartment of Gastrointestinal Surgery, Sanya People's Hospital, Sanya, China.
Yexiang FuDepartment of Gastrointestinal Surgery, Sanya People's Hospital, Sanya, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study is to find the better treatment for gastric cancer by comparing robotic gastrectomy, laparoscopic gastrectomy, and open gastrectomy using Bayesian network meta-analysis.

methodsWe will search PubMed, Embase, and the Cochrane Library for eligible studies published before 1 September 2018. There will be no language restrictions. Randomized clinical trials that compare robotic gastrectomy, laparoscopic gastrectomy, or open gastrectomy for patients with gastric cancer will be included. The risk of bias of included studies will be assessed by the Cochrane Collaboration's tool for assessing risk of bias in randomized trial. The outcomes of the study include operation time, estimated blood loss, time of ambulation, times to first flatus, time of oral intake, hospitalization, and the occurrence of complication. If sufficient data is collected and adequate clinical homogeneity is established among studies, we will conduct pairwise meta-analyses and Bayesian network meta-analyses for all related outcome measures. ETHICS AND DISSEMINATION: The study does not involve human subjects and does not need ethical approval and patient consent. The results of the network meta-analysis will be disseminated in a peer-reviewed journal for publication.

Indexed as

Systematic Reviews as TopicBayes TheoremBlood Loss, SurgicalGastrectomyHumansLaparoscopyLength of StayNetwork Meta-Analysis as TopicOperative TimeOutcome Assessment, Health CareRandomized Controlled Trials as TopicRobotic Surgical ProceduresStomach Neoplasms

Identifiers

PMID30508949
PMCPMC6283097

What OpenQuestion holds

Textmetadata
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.