Evidence map›Paper›PMID 32899026›Full record

ArticleMedicine2020

Salvia miltiorrhiza improves Alzheimer's disease: A protocol for systematic review and meta-analysis.

Ying Guo, Xing Dong, Renyan Zhang, Yanmei Zhong, Peng Yang, San Ying 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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Experimental and therapeutic medicine · 2023
    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.

Ying GuoSchool of Basic Medical Sciences.
Xing DongSchool of Basic Medical Sciences.
Renyan ZhangSchool of Basic Medical Sciences.
Yanmei ZhongSchool of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine.
Peng YangSchool of Basic Medical Sciences.
San Ying ZhangInnovative Institute of Chinese Medicine and Pharmacy of Chengdu University of Traditional Chinese Medicine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is an age-related neurodegenerative disease that is slowly becoming a global problem. Salvia miltiorrhiza (SM) has a history of thousands of years of use in China. In recent years, SM has been reported to have the effect of improving Alzheimer's disease. However, there is no systematic review of its efficacy and safety yet. Therefore, we propose a systematic review to evaluate the efficacy and safety of SM for AD patients.

methodsSix databases will be searched: China National Knowledge Infrastructure (CNKI), China Biological Medicine (CBM), China Scientific Journals Database (CSJD), Wanfang database, PubMed, and EMBASE. The information is searched from January 2010 to July 2020. Languages are limited to English and Chinese. The primary outcomes include changes in the Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) and Activities of Daily Living scale (ADL). Additional outcomes include clinical effective rate and adverse event rate. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system will be used to assess the strength of the evidence.

resultsThis systematic review will evaluate the efficacy and safety of SM in the treatment of Alzheimer's disease.

conclusionThis systematic review provides evidence as to whether SM is effective and safe for Alzheimer's disease patients. SYSTEMATIC REVIEW REGISTRATION: INPLASY202070066.

Indexed as

Salvia miltiorrhizaAlzheimer DiseaseDrugs, Chinese HerbalHumansMeta-Analysis as TopicSystematic Reviews as TopicDrugs, Chinese Herbal

Identifiers

PMID32899026
PMCPMC7478559

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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.