Evidence map›Paper›PMID 30557963›Full record

ArticleMedicine2018

Acupuncture for hyperlipidemia: Protocol for a systematic review and meta-analysis.

Qinyan Peng, Xiaobin Yao, Jiexiang Xiang, Yuanping Wang, Xinmei Lin

Open access · goldAbstract 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. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  8. Review
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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 at 1 institution in 1 country.

Qinyan PengGuangzhou University of Chinese Medicine, Guangzhou, China.
Xiaobin Yao
Jiexiang Xiang
Yuanping Wang
Xinmei Lin
Guangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperlipidemia is a major risk factor for cardiovascular and cerebrovascular diseases. Acupuncture has been widely applied in the treatment of hyperlipidemia. But its efficacy has not been evaluated scientifically and systematically. Therefore, we provide a protocol of systematic evaluation to assess the effectiveness and safety of acupuncture treatment on patient with hyperlipidemia.

methodsWe will search the following databases electronically, including 3 English literature databases (i.e., PubMed, Embase, and Cochrane Library) and 4 Chinese literature databases (i.e., Chinese Biological and Medical database, China National Knowledge Infrastructure, VIP, and Wanfang Database). We will also search randomized-controlled trials about acupuncture treatment for hyperlipidemia and the search time limit is from its establishment to October 2018. The primary outcome is lipid-lowering efficacy. Secondary outcomes are total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol levels. We will use RevMan V.5.3 software as well to compute the data synthesis carefully when a meta-analysis is allowed.

resultsThis study will provide a high-quality synthesis to assess the effectiveness and safety of acupuncture treatment on patient with hyperlipidemia.

conclusionThe conclusion of our systematic review will provide evidence to judge whether acupuncture is an effective intervention for patient with hyperlipidemia.

Indexed as

Acupuncture TherapyChinaHumansHyperlipidemiasLipidsMeta-Analysis as TopicSystematic Reviews as TopicTreatment OutcomeLipids

Identifiers

PMID30557963
PMCPMC6319778
OpenAlexW2905468688

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.