Evidence map›Paper›PMID 37174950›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Polycystic Ovary Syndrome: Pathophysiology and Controversies in Diagnosis.

Duaa Fahs, Dima Salloum, Mona Nasrallah, Ghina Ghazeeri

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
12.0field-weighted citation impact, top 1% of its field
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

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

4 authors at 1 institution in 1 country.

Duaa FahsDepartment of Obstetrics and Gynecology, Faculty of Medicine, American University of Beirut Medical Center, Beirut P.O. Box 113-6044, Lebanon.
Dima SalloumDepartment of Obstetrics and Gynecology, Faculty of Medicine, American University of Beirut Medical Center, Beirut P.O. Box 113-6044, Lebanon.
Mona NasrallahDivision of Endocrinology and Metabolism, Faculty of Medicine, American University of Beirut Medical Center, Beirut P.O. Box 113-6044, Lebanon.ORCID 0000-0001-7382-8835
Ghina GhazeeriDepartment of Obstetrics and Gynecology, Faculty of Medicine, American University of Beirut Medical Center, Beirut P.O. Box 113-6044, Lebanon.
American University of Beirut Medical Center · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a complex and heterogeneous disorder that commonly affects women in the reproductive age group. The disorder has features that propose a blend of functional reproductive disorders, such as anovulation and hyperandrogenism, and metabolic disorders, such as hyperglycemia, hypertension, and obesity in women. Until today, the three implemented groups of criteria for the diagnosis of PCOS are from the National Institutes of Health (NIH) in the 1990s, Rotterdam 2003, and the Androgen Excess Polycystic Ovary Syndrome 2009 criteria. Currently, the most widely utilized criteria are the 2003 Rotterdam criteria, which validate the diagnosis of PCOS with the incidence of two out of the three criteria: hyperandrogenism (clinical and/or biochemical), irregular cycles, and polycystic ovary morphology. Currently, the anti-Müllerian hormone in serum is introduced as a substitute for the follicular count and is controversially emerging as an official polycystic ovarian morphology/PCOS marker. In adolescents, the two crucial factors for PCOS diagnosis are hyperandrogenism and irregular cycles. Recently, artificial intelligence, specifically machine learning, is being introduced as a promising diagnostic and predictive tool for PCOS with minimal to zero error that would help in clinical decisions regarding early management and treatment. Throughout this review, we focused on the pathophysiology, clinical features, and diagnostic challenges in females with PCOS.

Indexed as

diagnostic criteriapathophysiologypolycystic ovary syndrome

Identifiers

PMID37174950
PMCPMC10177792
OpenAlexW4367183320

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.