Evidence map›Paper›PMID 39055317›Full record

SynthesisFrontiers in neurology2024

Optimal acupuncture methods for lower limb motor dysfunction after stroke: a systematic review and network meta-analysis.

Yaning Liu, Yuqi Tang, Linjia Wang, Pei Yu, Can Wang, Lichuan Zeng, Jing Yuan, Ling Zhao

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
–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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Electroacupuncture combined with nutritional intervention for gastrointestinal cancer-related sarcopenia: a randomized controlled trial using ultrasonographic indices.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Trial
  6. Trial
  7. Article
  8. Review
  9. Review
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

8 authors.

Yaning LiuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Yuqi TangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Linjia WangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Pei YuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Can WangAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Lichuan ZengDepartment of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Jing YuanAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
Ling ZhaoAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The lower limb motor dysfunction caused by stroke is one of the main sequelae affecting patients' ability to live normally in the later period. Acupuncture treatment of limb movement dysfunction after stroke has been recommended by authoritative guidelines for reducing limb spasticity, enhancing limb strength and so on. However, the efficacy of different acupuncture methods in treating lower limb motor dysfunction after stroke remains controversial. Objective: In this paper, network meta-analysis (NMA) was used to prioritize various acupuncture intervention combinations commonly used in clinical practice, try to screen the acupuncture intervention scheme with the highest clinical efficacy and safety, and explore its rationality in guiding clinical practice. Methods: We searched a total of 4,312 studies from 8 databases and 2 clinical trial registries, and selected 43 articles for systematic review. We used pairwise meta-analysis and network meta-analysis to evaluate the efficacy and ranking of various acupuncture interventions. At the same time, the risk of bias, publication bias, and sensitivity of included randomized controlled trials were analyzed. The main outcome indicator was Fugl-Meyer assessment of lower extremity (FMA-LE), and the secondary outcome indicators were Modified Barthel Index (MBI), Berg balance scale (BBS) and Modified Ashworth scale (MAS). Results: A total of 4,134 patients in 43 studies were included. The intervention included 9 acupuncture-related treatments, of which 20.9% were classified as high-risk. Among the four outcome indicators in pairwise meta-analysis, the effect of body acupuncture combined with conventional rehabilitation has the highest comprehensive credibility in terms of efficacy and safety comparing with conventional rehabilitation [SMD = 1.14, 95%CI (0.81, 1.46)], [SMD = 1.35, 95%CI (0.97, 1.72)], [SMD = 1.22, 95%CI (0.39, 2.05)], [SMD = 1.21, 95%CI (0.74, 1.44)]. In addition, multiple intervention methods, for example, warm acupuncture plus rehabilitation treatment for MBI and electroacupuncture plus body acupuncture plus rehabilitation treatment for BBS, may increase certain additional effects on different outcome indicators. Conclusion: This study proves that body acupuncture combined with rehabilitation treatment is the most widely used intervention method with the highest evidence quality in the treatment of lower limb motor dysfunction after stroke. However, for some other acupuncture methods, large samples and high-quality clinical randomized controlled trials are still needed to be fully verified.

Indexed as

acupuncturelower limb dysfunctionnetwork meta-analysisrehabilitationstroke

Identifiers

PMID39055317
PMCPMC11270540

What OpenQuestion holds

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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.