Efficacy and safety of acupuncture for painful diabetic neuropathy: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Painful diabetic neuropathy (PDN) is a common chronic neurological complication of diabetes mellitus. Medications are often used to relieve pain, but with significant side effects. Acupuncture is now a component of pragmatic and integrative treatment for PDN. An increasing number of relevant randomized controlled trials have been published in recent years, but a comprehensive meta-analysis has not yet been performed. The aim of this paper is to verify the effectiveness and safety of acupuncture for PDN by meta-analysis and trial sequential analysis (TSA). Methods All participants in this study should have had a PDN diagnosis and the trial group was treated with acupuncture. Eight databases, including EMbase, PubMed, Web of science, Cochrane Library, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), Wanfang and Chongqing VIP (CQVIP) were retrieved from inception to 5 April 2023. Meta-analysis was conducted utilizing RevMan 5.3 and Stata 15.0. TSA was performed to assess the adequacy of sample size for the outcomes. Results A total of 36 studies, comprising 2,739 PDN patients, were included. Among them, 1,393 patients were assigned to the trial group and 1,346 patients were treated in the control group. Outcomes covers the primary indicator Total effective rate (RR = 1.42, 95%CI [1.34, 1.52], p < 0.00001), with 21 studies reported, Pain intensity (SMD = −1.27, 95%CI [−1.58, −0.95], p < 0.00001), with 23 studies reported, and other outcomes, including motor nerve conduction velocity (MCV; MD = 3.58, 95%CI [2.77, 4.38], p < 0.00001), sensory nerve conduction velocity (SCV; MD = 3.62, 95%CI [2.75, 4.49], p < 0.00001), Depression score (SMD = −1.02, 95%CI [1.58, 0.46]), Toronto clinical scoring system (TCSS; MD = −2.41, 95%CI [−3.37, −1.45], p < 0.00001), Quality of life (SMD = 1.06, 95%CI [0.66, 1.46]), traditional Chinese medicine (TCM) syndrome score (MD = −4.99, 95%CI [−6.79, −3.18], p < 0.00001), suggesting that acupuncture have an ameliorating effect on PDN in various respect. Egger’s test revealed publication bias for four outcomes. TSA showed that as for Total effective rate, Pain Intensity, MCV and SCV, the number of included studies was sufficient to support the conclusions. Conclusion Acupuncture demonstrates significant effectiveness in improving PDN outcomes, including Total effective rate, Pain intensity, MCV, SCV, Depression score, TCSS, Quality of life, TCM syndrome score. But the Adverse events rate is no different in trail group and control group. The publication bias presented in Total effective rate, Pain intensity, MCV and SCV can be remedied by Trim and filling method. Systematic review registration Prospero, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=477295 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".