Evidence map›Paper›PMID 39980043›Full record

ReviewJournal of ovarian research2025

Physiopathology of polycystic ovary syndrome in endocrinology, metabolism and inflammation.

Pingping Su, Chao Chen, Yun Sun

Abstract readReview
In one paragraph

Review in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 5 pooled it
–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

70 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

10 more citing papers are in PubMed but not listed here.

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.

Pingping SuWenzhou Graduate Joint Training Base, Zhejiang Chinese Medical University, Hangzhou, China.
Chao ChenDepartment of Traditional Chinese Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Yun SunDepartment of Gynecology, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, China. sunyun7304@outlook.com.

Funding

China International Medical Foundation Z-2014-08-2309-3Wenzhou Major Science and Technology Innovation Projects ZY2022014
6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder characterized by elevated androgen levels, ovarian cysts, and impaired ovulation in females. This condition is closely linked with various reproductive health issues and has significant impacts on endocrine and metabolic pathways. Patients with PCOS commonly exhibit hyperandrogenaemia and insulin resistance, leading to complications such as acne, hirsutism, weight fluctuations, and metabolic disturbances, as well as an increased risk for type 2 diabetes, cardiovascular disease, and endometrial cancer. Although extensive research has identified several mechanistic aspects of PCOS, a thorough understanding of its pathophysiology remains incomplete. This review aims to provide a detailed analysis of the physiological and pathological aspects of PCOS, covering endocrine, metabolic, and inflammatory dimensions, to better elucidate its etiological framework.

Indexed as

InflammationPolycystic Ovary SyndromeFemaleHumansHyperandrogenismInsulin ResistanceEndocrinologyInflammationMetabolismPhysiopathologyPolycystic ovary syndrome

Identifiers

PMID39980043
PMCPMC11841159

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.