Evidence map›Paper›PMID 32769901›Full record

ArticleMedicine2020

Effect of early enteral nutrition support for the management of acute severe pancreatitis: A protocol of systematic review.

Yong-Bo Guo, Yan Liu, Jing Ma, Ying Cai, Xiao-Ming Jiang, Hong Zhang

Abstract read
In one paragraph

Article in Medicine, 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
–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

1 citing paper in PubMed.

  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

6 authors.

Yong-Bo GuoDepartment of Critical Care Medicine, The Affiliated Hongqi Hospital of Mudanjiang Medical University.
Yan LiuDepartment of Critical Care Medicine, The Affiliated Hongqi Hospital of Mudanjiang Medical University.
Jing MaDepartment of Critical Care Medicine, The Affiliated Hongqi Hospital of Mudanjiang Medical University.
Ying CaiDepartment of Critical Care Medicine, First Affiliated Hospital of Mudanjiang Medical University, Mudanjiang.
Xiao-Ming JiangDepartment of Critical Care Medicine, Beijing Mentougou District Hospital, Beijing, China.
Hong ZhangDepartment of Critical Care Medicine, The Affiliated Hongqi Hospital of Mudanjiang Medical University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to assess the effect of early enteral nutrition support (EENS) for the management of acute severe pancreatitis (ASP).

methodsThis study will search Cochrane Library, PUBMED, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Allied and Complementary Medicine Database, CNKI, and WANGFANG from their inception to the present without language limitations. In addition, this study will also search clinical trial registry and reference lists of included trials. Eligible comparators will be standard care, medications, and any other interventions. Two authors will independently scan all citations, titles/abstracts, and full-text studies. The study methodological quality will be appraised using Cochrane risk of bias tool. If it is possible, we will pool out data and perform meta-analysis. Strength of evidence for each main outcome will be evaluated using the Grading of Recommendations Assessment, Development, and Evaluation.

resultsThis study will summarize the most recent evidence to assess the effect of EENS for the management of ASP.

conclusionThe findings of this study will help to determine whether EENS is effective for patients with ASP. STUDY REGISTRATION: INPLASY202070009.

Indexed as

Disease ManagementEnteral NutritionHumansNutritional SupportPancreatitisSystematic Reviews as Topic

Identifiers

PMID32769901
PMCPMC7593012

What OpenQuestion holds

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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.