Coagulation parameters predictive of polycystic ovary syndrome

Sun, Qiang; Yang, Yan; Peng, Xuenan; Zhang, Yunyan; Gao, Yuan; Wang, Fang; Zhang, Yang; Feng, Wenhuan; Yang, Wenzhuo; Kang, Xiaomin

doi:10.1016/j.ejogrb.2019.06.018

Cited by 14 publications

(13 citation statements)

References 17 publications

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“…It is reported that PCOS subjects show marked platelet dysfunction [ 2 ] and decreased plasma fibrinolytic activity, resulting in a prothrombotic state [ 3 ]. In addition, coagulation variables such as thrombin-activatable fibrinolysis inhibitor, plasminogen activator inhibitor-1 (PAI-1), D-dimer, Antithrombin and thrombomodulin have been reported to be elevated in PCOS compared to control subjects [ 4 ], and the functional coagulation tests including prothrombin time, thrombin time and fibrin degradation products may be predictive of PCOS [ 5 ]. This suggests that PCOS women have a propensity to a hypercoagulable state; therefore, to determine whether this was the case in a cohort of PCOS women, and whether there was an association with vitamin D status, this study was undertaken.…”

Section: To the Editormentioning

confidence: 99%

Vitamin D association with coagulation factors in polycystic ovary syndrome is dependent upon body mass index

et al. 2021

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Section: To the Editormentioning

confidence: 99%

Vitamin D association with coagulation factors in polycystic ovary syndrome is dependent upon body mass index

et al. 2021

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“…Age and novelty seeking as well as age and reward dependence have negative correlation(r:-0.33, p:0.018; r:-0.295, p:0.037, respectively). "Coagulation parameters predictive of polycystic ovary syndrome" [13], which proposed there were 181 patients having PCOS (selected according to Rotterdam criteria) and 301 controls were selected. Data from the coagulation assays, glucose tolerance test, and insulin release test were then collected from all study subjects.…”

Section: Fig 1 Polycystic and Normal Ovary[4]mentioning

confidence: 99%

Genetic Clustering for Polycystic Ovary Syndrome Detection in Women of Reproductive Age

Thakare,

Lele

2020

IJEAT

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Now a days, hormonal disorder causing Polycystic Ovary Syndrome (PCOS) is been observed in most of the women of reproductive age. PCOS causes enlarged ovaries with small cysts on the outer edges. Women with PCOS may have irregularity in menstrual periods or excess male hormone (androgen) levels. The ovaries may develop numerous small collections of follicles (cysts) and fail to regularly release eggs. Symptoms of PCOS include irregular periods, excess androgen, polycystic ovaries, abnormal Body Mass Index, disturbed levels of hormones (Luteinizing Hormone, Follicle-stimulating Hormone, Dehydroepiandros-terone), poor insulin resistance. There is a need to design and develop an optimized system to analyze the sonogram in correlation with the physical symptoms for detection of PCOS at early stage which may result in proper treatment and reduced health loss. This article presents work-in-progress of our proposed research on Intelligent System to detect PCOS. The performance analysis of various Machine learning algorithms like Artificial Neural Network, K-nearest Neighbor and Linear Regression to detect PCOS is presented. Whereas, optimized Genetic Clustering for optimization of classification results is proposed. Basic Genetic Algorithm (GA)and other hybrid GA's will be used for comparing the optimal results. The classification results are optimized with 89% accuracy

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“…PCOS can be recognized as well as metabolic disease due to the increased prevalence of type 2 DM, cardiovascular disease and hypertension in PCOS patients [2]. Some coagulation markers have been found to be elevated in PCOS versus to controls and the coagulation parameters including prothrombin time, thrombin time and fibrin degradation products may be predictive of PCOS [3]. Recent studies in women with PCOS reported that plasminogen activator inhibitor-1 (PAI-1) which is one of the potent inhibitor of fibrinolysis are increased in level in both normal weight and overweight/obese women with PCOS compared with controls with matched body mass index (BMI) [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Investigation of plasminogen activator inhibitor-1 (PAI-1) levels in patients diagnosed with polycystic ovary syndrome

Bağlı¹,

Küçük

2021

Aegean J Obstet Gynecol

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Objective:The aim of this study was to investigate the plasma levels of plasminogen activator inhibitor -1 (PAI-1) known as a potent inhibitor of fibrinolysis in women with polycystic ovary syndrome (PCOS) and compare with health controls. Methods: Forty women with PCOS diagnosed using 2003 revised Rotterdam criteria and 40 healthy women who attended to Adnan Menderes University Department of Obstetrics and Gynecology between July-October 2013 were recruited to this prospective study. We noted all participant’s demographic features, calculated body mass index (BMI), waist hip ratio (WHR), and measured blood pressures. We performed modified Ferriman-Gallwey Score (mFGS) and calculated Luteinizing hormone (LH)/Follicle stimulating hormone (FSH) ratio and homeostatic model assessment insulin resistance (HOMA-IR) of participants. PAI-1 levels were measured by using the Human PAI-1 Elisa test. We used the student T test and Mann-Whitney U test as statistical methods. A p-value less than 0.05 was considered statistically significant. Results: We found PAI-1 levels, fasting insulin levels, HOMA-IR index, BMI significantly higher in the PCOS group compared with the control group. Mean age of the participants was found lower in the PCOS group. Between the groups we found no statistically significant differences in terms of the LH/FSH ratio, fasting glucose, dehydroepiandrosterone and testosterone levels.

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Coagulation parameters predictive of polycystic ovary syndrome

Cited by 14 publications

References 17 publications

Vitamin D association with coagulation factors in polycystic ovary syndrome is dependent upon body mass index

Vitamin D association with coagulation factors in polycystic ovary syndrome is dependent upon body mass index

Genetic Clustering for Polycystic Ovary Syndrome Detection in Women of Reproductive Age

Investigation of plasminogen activator inhibitor-1 (PAI-1) levels in patients diagnosed with polycystic ovary syndrome

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