Evidence map›Paper›PMID 40766070›Full record

SynthesisFrontiers in medicine2025

Factors contributing to the delayed diagnosis of endometriosis-a systematic review and meta-analysis.

Wenwei Li, Huiyan Feng, Qingjian Ye

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
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  9. Review
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

3 authors.

Wenwei LiDepartment of Gynaecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Huiyan FengDepartment of Gynaecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Qingjian YeDepartment of Gynaecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Endometriosis is a prevalent gynecological disorder that is estimated to affect approximately 10% of women of childbearing age globally. However, the condition remains significantly under-or misrecognized, and the mean time to diagnosis is several years. These delays result in increased symptom severity, diminished quality of life, and adverse long-term reproductive outcomes. Therefore, the aim of this systematic review and meta-analysis was to estimate the sources of diagnostic delay and their effects. Methods: The articles were retrieved from PubMed, Cochrane, and Google Scholar databases after performing a rigorous literature search. The initial search yielded 2,348 records, and 10 articles were included in the final analysis. Causes of diagnostic delay were classified under patient, physician, and systems attributes. Random-effects analysis was used to estimate the overall SMDs with 95% confidence intervals (CIs). For the primary Results: Patient-related factors demonstrated a significant pooled effect size (SMD: 1.94, 95% CI: 1.62-2.27, Conclusion: The results indicate that diagnostic delays in endometriosis are a function of multiple factors, with key contributions from patient and provider-related barriers. To close these gaps, targeted interventions such as public education to combat symptom normalization and stigmatization, more comprehensive provider training, and streamlined diagnostic pathways are needed. Future research can evaluate system-level changes and non-invasive diagnostic tools to reduce systemic delays further.

Indexed as

diagnostic delayendometriosishealthcare disparitiesmeta-analysismisdiagnosispatient-related factorsprovider-related factorssystematic review

Identifiers

PMID40766070
PMCPMC12321876

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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.