Evidence map›Paper›PMID 39019640›Full record

ArticleBMJ open2024

Robotic pancreaticoduodenectomy in patients with overweight or obesity: a meta-analysis protocol.

Wenxiao Yang, Hai Zeng, Yueling Jin

Abstract read
In one paragraph

Article in BMJ open, 2024. 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

3 authors.

Wenxiao YangBusiness School, University of Shanghai for Science & Technology, Shanghai, China.
Hai ZengThe First Affiliated Hospital of Jinan University, Guangzhou, China.
Yueling JinShanghai Science and Technology Museum, Shanghai, China jinyuel@sstm.org.cn.ORCID 0000-0003-1691-9217

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe prevalence of overweight or obesity among patients undergoing pancreaticoduodenectomy is on the rise. The utilisation of robotic assistance has the potential to enhance the feasibility of performing minimally invasive pancreaticoduodenectomy in this particular group of patients who are at a higher risk. The objective of this meta-analysis is to assess the safety and effectiveness of robotic pancreaticoduodenectomy in individuals with overweight or obesity. METHODS AND ANALYSIS: This investigation will systematically search for randomised controlled trials (RCTs) and non-randomised comparative studies that compare robotic pancreaticoduodenectomy with open or laparoscopic pancreaticoduodenectomy in patients with overweight or obesity, using PubMed, Embase and the Cochrane Library databases. The methodological quality of studies will be evaluated using the Cochrane risk of bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. RevMan software (V.5.4.1) will be used for statistical analysis. The OR and weighted mean differences will be calculated separately for dichotomous and continuous data. The selection of a fixed-effects or random-effects model will depend on the level of heterogeneity observed among the included studies. ETHICS AND DISSEMINATION: This study will be conducted based on data in the published literature from publicly available databases. Therefore, ethics approval is not applicable. The results will be disseminated in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023462321.

Indexed as

ObesityOverweightPancreaticoduodenectomyRobotic Surgical ProceduresHumansLaparoscopyMeta-Analysis as TopicResearch DesignMeta-AnalysisObesityPancreatic diseasePancreatic surgery

Identifiers

PMID39019640
PMCPMC11284876

What OpenQuestion holds

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LicenceCC BY-NC
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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.