Evidence map›Paper›PMID 35432752›Full record

ArticleWorld journal of diabetes2022

Higher risk of type 2 diabetes in young women with polycystic ovary syndrome: A 10-year retrospective cohort study.

Wan-Ting Liao, Jing-Yang Huang, Ming-Tsung Lee, Yu-Cih Yang, Chun-Chi Wu

Open access · diamondAbstract read
In one paragraph

Article in World journal of diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Wan-Ting LiaoInstitute of Medicine, Chung-Shan Medical University, Taichung 402, Taiwan.
Jing-Yang HuangResearch Center for Health Data Science, Chung Shan Medical University Hospital, Taichung 402, Taiwan.
Ming-Tsung LeeNational Center for Geriatrics and Welfare Research, National Health Research Institutes, Yunlin 632, Taiwan.
Yu-Cih YangClinical Trial Research Center, China Medical University Hospital, Taichung 404, Taiwan.
Chun-Chi WuInstitute of Medicine, Chung-Shan Medical University, Taichung 402, Taiwan. daniel@csmu.edu.tw.
Chung Shan Medical University · TWNational Health Research Institutes · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolycystic ovary syndrome (PCOS) is a common disorder in women of reproductive age. Over the last few decades, research studies have revealed that PCOS is strongly associated with metabolic disorders, including metabolic syndrome, obesity, insulin resistance and prediabetes. Clinical observation has shown that women with PCOS are expected to have an increased risk of developing type 2 diabetes (T2DM) in the future.

aimTo assess the hazard ratio (HR) of T2DM between women with/without PCOS.

methodsThis population-based, retrospective cohort study evaluated data retrieved from the National Health Insurance Research Database. The subjects were women with PCOS (

resultsOur study found that, during a 10-year follow-up period, the overall incidence of T2DM was 6.25 per 1000 person-years in the PCOS group compared with 1.49 in the control group. After adjustment for potential confounding variables, the overall incidence of T2DM was higher in the PCOS group

conclusionThese findings highlight the importance of prompting a more aggressive treatment to prevent diabetes in women diagnosed with PCOS at a young age, and, in contrast, the lessened importance of this type of intervention in women diagnosed with PCOS at a late reproductive age.

Indexed as

DiabetesHazard ratioIncidencePolycystic ovary syndromePopulation-based cohort study

Identifiers

PMID35432752
PMCPMC8984565
OpenAlexW4220775201

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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.