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Record W4404866370 · doi:10.3389/fnins.2024.1468331

Efficacy of combination scalp acupuncture for post-stroke cognitive impairment: a systematic review and meta-analysis

2024· review· en· W4404866370 on OpenAlexaboutno aff
Song Li, Anhong Dai, Yihao Zhou, Xu Chen, Yizhou Chen, Li Zhou, Xiaolin Yang, Jing Shi, Yong Qiu

Bibliographic record

VenueFrontiers in Neuroscience · 2024
Typereview
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCognitive impairmentAcupunctureMeta-analysisStroke (engine)MedicineScalpPhysical medicine and rehabilitationSystematic reviewCognitionMEDLINEAlternative medicinePsychiatryInternal medicineDermatologyPathologyEngineering

Abstract

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Objective This systematic review and meta-analysis aimed to evaluate the efficacy of combination scalp acupuncture in treating post-stroke cognitive impairment. Methods A comprehensive search was conducted across eight databases: PubMed, Web of Science, Cochrane Database, Embase, CBM, CNKI, WanFang, and VIP, targeting randomized controlled trials (RCTs) published from the inception of these databases until October 24, 2024. The inclusion criteria focused on RCTs that compared scalp acupuncture with conventional treatments as therapeutic interventions for patients suffering from post-stroke cognitive impairment (PSCI). The effectiveness of these treatments was evaluated using various outcome measures, including the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Loewenstein Occupational Therapy Cognitive Assessment (LOTCA), as well as P300 latency and amplitude, which collectively assess cognitive function. Two independent reviewers conducted a risk of bias (ROB2) assessment, and data analysis was performed using Review Manager (RevMan) version 5.4. Results This analysis included a total of 28 studies involving 1,995 patients. However, according to the standards of the ROB2 tool, most of these studies exhibited various methodological issues. The comprehensive analysis indicates that the efficacy of combined scalp acupuncture in treating post-stroke cognitive impairment (PSCI) is superior to that of single treatments, as evidenced by improvements across multiple scales, including the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Loewenstein Occupational Therapy Cognitive Assessment (LOTCA), P300 latency, and amplitude. Specifically, the overall effective rate was reported as (RR = 1.28, 95% CI: 1.14–1.45, p < 0.0001; I 2 = 51%, random effects model). The mean differences for the various scales were as follows: MoCA (MD = 3.55, 95% CI: 2.68–4.41, I 2 = 93%, random effects model), MMSE (MD = 3.78, 95% CI: 2.83–4.73, I 2 = 94%, random effects model), LOTCA (MD = 9.70, 95% CI: 7.72–11.69, I 2 = 57%, random effects model), P300 latency (MD = −21.83, 95% CI: −26.31 to −17.35, I 2 = 55%, random effects model), and amplitude (MD = 1.05, 95% CI: 0.76–1.34, I 2 = 0%, fixed effects model), demonstrating low, medium, and high levels of heterogeneity, respectively. Notably, one study reported an adverse event related to participant withdrawal during the study. Conclusion Combination scalp acupuncture exhibits superior efficacy compared to single-treatment modalities in patients with post-stroke cognitive impairment (PSCI). However, the higher risk of bias (ROB) in the included trials suggests that the quality of evidence about these assessment results may be compromised. Therefore, there is an urgent need for additional high-quality clinical trials to further validate the efficacy and effectiveness of combined scalp acupuncture in treating PSCI, ultimately enhancing the overall level of evidence. Systematic review registration https://www.crd.york.ac.uk/prospero/ , identifier CRD42024519200.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0110.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.398
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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