Evidence map›Paper›PMID 31393342›Full record

SynthesisMedicine2019

Pharmacological treatments for patients with irritable bowel syndrome: An umbrella review of systematic reviews and meta-analyses.

Di Qin, Ling Yue, Bin Xue, Min Chen, Tai-Chun Tang, Hui Zheng

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 21% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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 at 1 institution in 1 country.

Di QinThe 3 Hospital/Acupuncture and Tuina School.
Ling YueThe 3 Hospital/Acupuncture and Tuina School.
Bin XueAcupuncture and Rehabilitation Department, Sichuan 2 Hospital of Traditional Chinese Medicine.
Min ChenClinical Medicine College/Teaching Hospital, Chengdu University of Traditional Chinese Medicine, China.
Tai-Chun TangClinical Medicine College/Teaching Hospital, Chengdu University of Traditional Chinese Medicine, China.
Hui ZhengThe 3 Hospital/Acupuncture and Tuina School.
Sichuan Provincial Hospital of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSeveral pharmacological treatments are beneficial for patients with irritable bowel syndrome (IBS), and there are numbers of systematic reviews evaluating the effectiveness of these treatments. However, the overall quality of the evidence has not been quantitatively assessed. The aim of this study is to evaluate the possible biases in the published systematic reviews and determine the treatments with reliable evidence. METHODS AND ANALYSIS: We will perform an umbrella review to identify eligible systematic reviews. A comprehensive literature search will be conducted in MEDLINE, EMBASE, and the Cochrane library for systematic reviews. We will describe the general information such as participants, interventions, outcome measurements, and conclusion. Additionally, the heterogeneity and inconsistency between trials will be assessed by the I statistical test and Cochrane Q test. We will assess risk of bias, and summarize the strength evidence.

conclusionThe umbrella reviews will assess the reliability of the evidence so that doctors and patients can make better medical choices. PROSPERO REGISTRATION NUMBER: CRD42018109597.

Indexed as

Meta-Analysis as TopicSystematic Reviews as TopicHumansIrritable Bowel SyndromeResearch Design

Identifiers

PMID31393342
PMCPMC6709044
OpenAlexW2968828328

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.