Evidence map›Paper›PMID 37488629›Full record

ArticleJournal of ovarian research2023

Characteristics of retinal image associated with premature ovarian insufficiency: a case- control study.

Jiaman Wu, Liya Tan, Yan Ning, Weiqu Yuan, Zuowei Lee, Fei Ma, Erfeng Wang, Yuanyuan Zhuo

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Jiaman Wu *Affiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China.
Liya Tan *Guangzhou University of Chinese Medicine, Guangzhou, China.
Yan NingAffiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China.
Weiqu YuanShenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, China.
Zuowei LeeDivision of Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Fei MaAffiliated Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China.
Erfeng WangGuangzhou University of Chinese Medicine, Guangzhou, China.
Yuanyuan ZhuoShenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, China. qinyuan64@163.com.
Guangzhou University of Chinese Medicine · CNShenzhen Pingle Orthopedic Hospital · CNSouthern Medical University · CNHong Kong Jockey Club · CNShenzhen Maternity and Child Healthcare Hospital · CN

Funding

Guangdong Provincial Administration of Traditional Chinese Medicine 20201294Internal research project of Shenzhen Maternity & Child Healthcare Hospital FYA2018006Sanming Project of Medicine in Shenzhen SZSM201612046the General project of Shenzhen basic research special (Natural Science Foundation) No.JCYJ20210324130001004
6 · The paper itself

Abstract

purposeTo establish an early clinical diagnosis model based on the retinal vascular features associated with POI, supplying a non-invasive way for accurately and early predicted the risk of POI.

methodsA total of 78 women with spontaneous POI and 48 healthy women were recruited from the Affiliated Shenzhen Maternity & Child Healthcare Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis system. Binary logistic regression was used to identify POI cases and develop predictive models.

resultsCompared to the normal group, the POI group had larger central retinal artery equivalent (CRAE) (P = 0.006), central retinal vein equivalent (CRVE) (P = 0.001), index of venules asymmetry (Vasym) (P = 0.000); larger bifurcation angles of arterioles (Aangle) (P = 0.001), bifurcation coefficient of venule (BCV) (P = 0.001) and more obvious arteriovenous nipping (Nipping) (P = 0.005), but lower arteriole-to-venule ratio (AVR) (P = 0.012). In the POI group, the odds ratio (OR) of Vasym was 6.72e-32 (95% C.I. 4.62e-49-9.79e-15, P = 0.000), the OR of BCV was 5.66e-20 (95% C.I. 1.93e-34-.0000, P = 5.66e-20) and the OR of Nipping was 6.65e-06 (95% C.I. 6.33e-10-.0698, P = 0.012). Moreover, the area under the ROC curve for the binary logistic regression with retinal characteristics was 0.8582, and the fitting degree of regression models was 60.48% (Prob > chi-square = 0.6048).

conclusionThis study demonstrated that retinal image analysis can provide useful information for POI identification and certain characteristics may help with early clinical diagnosis of POI.

Indexed as

Menopause, PrematurePrimary Ovarian InsufficiencyCase-Control StudiesChildFemaleHumansImage Processing, Computer-AssistedOdds RatioPregnancyBiostatistics methodEarly clinical diagnosisPremature ovarian insufficiencyRetinal characteristicsRetinal image analysis

Identifiers

PMID37488629
PMCPMC10367310
OpenAlexW4385198477

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