Evidence map›Paper›PMID 41415097›Full record

ReviewAmerican journal of translational research2025

Acupuncture-induced pain relief and anti-inflammatory effects in chronic pelvic inflammatory disease: a systematic review and meta-analysis.

Ran Wei, Zuozhen Huang

Abstract readReview
In one paragraph

Review in American journal of translational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Ran WeiCollege of Ancient Chinese Studies, Beijing University of Chinese Medicine Beijing 100029, China.
Zuozhen HuangCollege of Ancient Chinese Studies, Beijing University of Chinese Medicine Beijing 100029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo systematically evaluate the effects of acupuncture and moxibustion on pain relief, inflammatory biomarkers, and reproductive outcomes in patients with chronic pelvic inflammatory disease (CPID).

methodA systematic search was conducted in PubMed, Embase, Cochrane Library, CNKI, and Wanfang for studies published between January 2010 and December 2023. Randomized controlled trials (RCTs) comparing acupuncture with sham/conventional control interventions in CPID patients were included. The primary outcomes included pain intensity (visual analog scale, VAS), inflammatory biomarkers (C-reactive protein [CRP], interleukin-6 [IL-6], tumor necrosis factor alpha [TNF-α]), and CPID specific indicators (fallopian tube patency and pelvic mass regression). Data were analyzed using a random-effects model (RevMan 5.3/Stata 16).

resultThirteen RCTs involving 658 patients were included. Acupuncture significantly reduced pain intensity (standardized mean deviation [SMD]=-1.42, 95% confidence interval [CI]: -1.66 to -1.18), CRP (SMD=-3.89), IL-6 (SMD=-5.00), TNF-α (SMD=0.60) (all P<0.001). CPID-specific outcomes were improved, with higher rates of fallopian tube patency (hazard ratio [RR] =1.35) and pelvic mass regression (RR=1.44; both P<0.01). Moreover, acupuncture improved quality of life (SMD=0.55, P<0.0001), increased pregnancy rate (RR=1.32), and reduced recurrence rates (RR=0.68; both P<0.05). Electroacupuncture combined with herbal medicine (≥8 weeks) showed the most pronounced therapeutic benefits.

conclusionElectroacupuncture combined with herbal medicine significantly alleviates pelvic pain, reduces systemic inflammation, and enhances reproductive outcomes in patients with CPID.

Indexed as

Acupuncture and moxibustionanti-inflammatorychronic pelvic inflammatory diseasepain reliefpelvic mass regressionsmooth fallopian tubes

Identifiers

PMID41415097
PMCPMC12709353

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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.