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Sommaire

Pain during hysterosalpingography

Douleur de l'hystérosalpingographie

1. Systematic Reviews and Meta-Analysis

1.1. Generic Acupuncture

Fang 2026 Fang SH, Yu PS, Lee BO, Chen CJ. Non-pharmacological interventions for reducing pain and anxiety in women experiencing infertility undergoing hysterosalpingography: A systematic review without meta-analysis. Eur J Integr Med. 2026;82:102609. https://doi.org/10.1016/j.eujim.2025.102609

IntroductionHysterosalpingography (HSG) is a common diagnostic procedure for infertility but often causes pain and anxiety. Non-pharmacological interventions offer potential alternatives to pharmacological pain management.
MethodsA systematic review followed PRISMA 2020 guidelines where a search strategy was applied to extract articles from included databases: PubMed, CINAHL Plus with Full Text, Cochrane Library, EMBASE, DynaMed, Clinical Key, MEDLINE, and Airiti Library, published before December 2024. The Cochrane RoB (Risk of Bias) 2.0 tool was used to assess the risk of bias, and the GRADE (Grading of Recommendations Assessment, Development and Evaluation) criteria were applied to evaluate study evidence.
ResultsEight randomized controlled trials (RCTs) met the inclusion criteria, covering educational counseling, virtual reality (VR), music therapy, mobile-assisted education (MAEC), and acupoint warming therapy. Educational counseling improved patient preparedness and reduced pain, technology-assisted interventions diverted attention, and acupoint warming therapy with music provided dual physiological and psychological benefits. It was also observed that anxiety was reduced in three related articles although study quality varied, with some limitations in blinding and sample size.
ConclusionNon-pharmacological interventions reduced pain (low certainty) and anxiety (very low certainty) during hysterosalpingography. Concerns remain about the methodological quality, small sample sizes, heterogeneity in the interventions, and for anxiety outcomes, inconsistent effects. Further high-quality studies are needed to determine the optimal application, refine implementation, and support evidence-based application.