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Record W4399363721

Meta-Analysis on the Recovery Effect of Acupuncture Combined With Rehabilitation Therapy in Spinal Cord Injury Patients.

2024· article· en· W4399363721 on OpenAlexaboutno aff
Han Su, Binbin Zhou, Xiaofeng Ji, Bolin Li, Xiangyu Yang, Zhenxing Li

Bibliographic record

VenuePubMed · 2024
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsAcupunctureMedicineRehabilitationSpinal cord injuryAcupuncture therapyPhysical medicine and rehabilitationPhysical therapySpinal cordAlternative medicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective: To explore the recovery effect of acupuncture combined with rehabilitation therapy on muscle spasms in patients with spinal cord injury through a systematic review of meta-analysis methods. Methods: Use "acupuncture," "electronic-acupuncture," "spinal cord," "spasm," and "paraplegia" as keywords, CNKI, Google, Wanfang, VIP, sci-hub, Web of Science, PubMed, and other Chinese or English databases were searched. To collect the domestic and foreign research on acupuncture combined with rehabilitation for muscle spasms in patients with spinal cord injury. Preliminary screening was conducted, and data extraction and quality evaluation were carried out on the included literature, including publication time, sample size, treatment methods, recovery effects, etc. According to the literature, the influence of acupuncture combined with rehabilitation therapy on muscle spasms in patients with spinal cord injury and related indices was analyzed. The search period was from January 2018 to June 2023, and the selected research results were tested by RevMan5.3 software and data consolidation for consistency. The methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: A preliminary literature search yielded 172 papers. 53 papers from sci-hub, 71 papers from HowNet, 36 papers from Wanfang, and 12 papers from VIP. Finally, 10 articles that met the criteria were included, including 594 patients. According to different treatment methods, the literature about acupuncture combined with rehabilitation therapy for muscle spasms in patients with spinal cord injury was analyzed for consistency, and data were merged. It was concluded that acupuncture combined with rehabilitation The clinical curative effect of the experimental group of patients is higher than that of the control group MD=5.31, 95%CI (2.94, 7.81), Z=5.64, P < .001; the clinical effective rate of the experimental group is higher than that of the control group. The improvement of the clinical spasticity index (CSI) score index of the patients in the experimental group was better than that of the control group MD = -3.09, 95%CI (-4.51, -1.67), Z =4.28, P < .001; the MAS score of the patients in the experimental group The improvement was better than that of the control group MD =-0.76, 95%CI (-1.16, -0.38), Z=8.13, P < .001; the improvement of Barthel index (BI) in the experimental group was better than that of the control group MD=9.81, 95%CI (7.84,11.71), Z=12.71, P < .001; no adverse events were reported in the experimental group and the control group. Conclusion: This study shows that acupuncture and rehabilitation are more effective than other therapeutic methods in the treatment of muscle spasms after spinal cord injury, and more randomized controlled trials are needed to verify this in the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.042
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.054
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.348
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

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