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Record W3089111349 · doi:10.1097/md.0000000000022286

Moxibustion for the treatment of diabetic peripheral neuropathy

2020· review· en· W3089111349 on OpenAlexaboutno aff
Yu‐Meng Tan, Jun Hu, Bing Pang, Lijuan Du, Yanan Yang, Qing Pang, Meizhen Zhang, Qian Wu, Yi Zhang, Qing Ni

Bibliographic record

VenueMedicine · 2020
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsnot available
FundersCapital Health Research and Development of Special Fund
KeywordsMedicineConfidence intervalMoxibustionRandomized controlled trialPeripheral neuropathyPlaceboNerve conduction velocityRelative riskInternal medicineMeta-analysisCommon peroneal nervePhysical therapySurgeryAcupunctureDiabetes mellitusAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: At present, the effect of western-medicine (WM) therapy to treat diabetic peripheral neuropathy (DPN) is limited. Moxibustion is a representative external treatment in traditional Chinese medicine that has been beneficial to DPN. We aim to systematically assess the efficacy and safety of moxibustion in treating DPN, following PRISMA guidelines. METHODS: Eight electronic databases were searched to acquire information on eligible trials published from inception to June 1, 2019. We included randomized controlled trials (RCTs) applying moxibustion therapy with a minimum of 14-days treatment duration for DPN patients compared with placebo, no intervention, or conventional WM interventions. The primary outcomes in our study include the sensory-nerve conduction velocity (SNCV) and motor-nerve conduction velocity (MNCV). We used the Cochrane Collaboration Risk of Bias tool to assess the methodological quality of eligible RCTs. Statistical analyses were conducted using Review Manager 5.3. Risk ratios (RR) and mean differences (MD) were calculated with a 95% confidence interval (CI). The χ test was applied to assess the heterogeneity. RESULTS: In total, 11 RCTs were included that involved 927 DPN patients. Compared with the control group, there was an increase in median MNCV (MD = 6.26, 95% CI 2.64-9.89, Z = 3.39, P = .0007) and peroneal MNCV (MD = 6.45, 95% CI 5.30-7.61, P < .00001). There was also an increase in median SNCV (MD = 6.64, 95% CI 3.25-10.03, P = .0001) and peroneal SNCV (MD = 3. 57, 95% CI 2.06-5.09, Z = 4.63, P < .00001) in the treatment groups. The treatment groups receiving moxibustion therapy indicated a more significant improvement in total effectiveness rate (RR = 0.25, 95% CI 0.18-0.37, Z = 7.16, P < .00001). Toronto Clinical Scoring System indicated a significant decrease in the treatment groups (MD = -2.12, 95% CI -2.82 to 1.43, P < .00001). Only 1 study reported that treatment groups experienced no adverse reactions. The other 10 studies did not mention adverse events. CONCLUSIONS: Moxibustion therapy may be an effective and safe option for DPN patients but needs to be verified in further rigorous studies.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.084
GPT teacher head0.367
Teacher spread0.283 · 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 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

Citations7
Published2020
Admission routes1
Has abstractyes

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