Evidence map›Paper›PMID 39701598›Full record

ReviewJournal of obesity & metabolic syndrome2024

Obesity and Polycystic Ovary Syndrome.

Jin Ju Kim

Abstract readReview
In one paragraph

Review in Journal of obesity & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

1 author.

Jin Ju KimDepartment of Obstetrics and Gynecology, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea.ORCID https://orcid.org/0000-0003-0879-8208

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The core pathophysiology of polycystic ovary syndrome involves an overproduction of androgens primarily originating from ovarian thecal cells. Two major external triggers promote androgen overproduction in the ovaries: the increased secretion of luteinizing hormone, a consequence of aberrant hypothalamic gonadotropin-releasing hormone secretion dynamics, and compensatory hyperinsulinemia resulting from insulin resistance. Obesity interacts with polycystic ovary syndrome in multiple ways, but a major role of obesity in its pathophysiology is the exacerbation of insulin resistance. Additionally, obesity contributes to polycystic ovary syndrome by facilitating the conversion of precursor hormones to testosterone within adipose cells. Moreover, obesity can lead to relative hyperandrogenemia, which is marked by lower levels of sex hormone binding globulin and increased availability of free testosterone to target tissues. Also, obesity affects the secretion of gonadotropins, resulting in heightened luteinizing hormone secretion or increased sensitivity of thecal cells to luteinizing hormone. Obesity-related insulin resistance might be amplified by alterations in adipokine and inflammatory cytokine production. Ultimately, obesity and polycystic ovary syndrome might share a common genetic predisposition. The cornerstone of managing polycystic ovary syndrome is to address individual symptoms such as hyperandrogenism (hirsutism, acne, and female type boldness), menstrual irregularities, and infertility stemming from anovulation. However, obesity is integral to the pathophysiology of polycystic ovary syndrome and exacerbates all of its features. Therefore, lifestyle modifications aimed at weight reduction should be the primary strategy in overweight or obese women with polycystic ovary syndrome.

Indexed as

AnovulationInsulin resistanceObesityPolycystic ovary syndrome

Identifiers

PMID39701598
PMCPMC11704221

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.