Evidence map›Paper›PMID 23008740›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2012

Chinese herbal medicine paratherapy for Parkinson's disease: a meta-analysis of 19 randomized controlled trials.

Yan Wang, Cheng-Long Xie, Lin Lu, Deng-Lei Fu, Guo-Qing Zheng

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 7 pooled it
0.8field-weighted citation impact, top 27% 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

13 citing papers in PubMed, 7 syntheses or guidelines pooled it, 22 citations in OpenAlex.

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  8. Frontiers in neuroscience · 2022
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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.

Yan WangThe Center of Neurology and Rehabilitation, The Second Affiliated Hospital of Wenzhou Medical College, Wenzhou 325027, China.
Cheng-Long Xie
Lin Lu
Deng-Lei Fu
Guo-Qing Zheng
Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder that needs long-term levodopa administration and can result in progressive deterioration of body functions, daily activities and participation. The objective of this meta-analysis evaluates the clinical efficacy and safety of Chinese herbal medicine (CHM) as an adjunct therapy for PD patients. Methodological issues include a systematic literature search between 1950 and April 2011 to identify randomized trials involving CHM adjuvant therapy versus western conventional treatment. The outcome measures assessed were the reduction in scores of Unified Parkinson's Disease Rating Scale (UPDRS) and adverse effects. 19 trials involving 1371 participants were included in the meta-analysis. As compared to western conventional treatment, CHM adjuvant therapy resulted in greater improvement in UPDRS I, II, III, IV scores, and UPDRS I-IV total scores (P < 0.001). Adverse effects were reported in 9 studies. The side effects in CHM adjuvant therapy group were generally less than or lighter than the conventional treatment group. In conclusion, CHM adjuvant therapy may potentially alleviate symptoms of PD and generally appeared to be safe and well tolerated by PD patients. However, well-designed, randomized, placebo-controlled clinical trials are still needed due to the generally low methodological quality of the included studies.

Identifiers

PMID23008740
PMCPMC3447405
OpenAlexW1964619935

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.