ArticleBMC women's health2026
How common are pelvic venous disorders in patients with unexplained chronic pelvic pain: a prospective cross-sectional study.
Article in BMC women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveChronicpelvic pain is a multifactorial condition that significantly impacts women’s quality of life. Pelvic venous disorders (PeVD) are increasingly recognized as a potential contributor to chronic pelvic pain and are related to pelvic venous insufficiency. This study aims to investigate the proportion of CPP patients with sonographic venous congestion patterns consistent with PeVD in women with chronic pelvic pain and to evaluate its clinical and ultrasonographic features. MATERIALS AND
methodsIn this prospective study, 83 women diagnosed with chronic pelvic pain and meeting the inclusion criteria were evaluated. Demographic and ultrasonographic data were recorded. All participants underwent ultrasonographic assessment for venous parameters associated with pelvic venous disorders. Patients were stratified according to ovarian vein diameter (≥ 6 mm vs. < 6 mm) for comparative analysis. Statistical analyses included the Shapiro–Wilk test, Student’s t-test, chi-square test, and logistic regression. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of ultrasonographic parameters. A p-value < 0.05 was considered significant.
resultsAmong all women presenting with chronic pelvic pain, 11.7% exhibited sonographic venous congestion patterns consistent with PeVD. When the analysis was restricted to the final cohort of women with isolated chronic pelvic pain, ovarian vein dilatation (≥ 6 mm) was observed in 54.2% of patients. Other ultrasonographic findings, including coiled tubular veins, low velocity venous flow in the ovarian vein (< 3 cm/s), and myometrial arcuate veins were associated with sonographic venous congestion patterns, with tortuous tubular veins showing the strongest discriminative performance. Additionally, antidepressant use was more frequent in patients with venous congestion, reflecting a higher symptom burden and healthcare utilization in this subgroup.
conclusionPelvic venous disorders appear to be a potential and possibly under-recognized contributor to chronic pelvic pain. Ultrasonography is a valuable, non-invasive tool for identifying pelvic venous disorders. In addition to ovarian vein dilation, coiled veins, reduced flow velocity, and myometrial arcuate veins may serve as supportive imaging features. Further large-scale studies are needed to better define the role of pelvic venous disorders in the context of chronic pelvic pain.
trial registrationNot applicable.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.