A prospective cohort study of early‐pregnancy risk factors for gestational diabetes in polycystic ovarian syndrome

Li, Guanghui; Huang, Wenyu; Zhang, Li; Tian, Zhihong; Zheng, Wei; Wang, Teng; Zhang, Ting; Zhang, Weiyuan

doi:10.1002/dmrr.3003

Cited by 20 publications

(22 citation statements)

References 62 publications

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“…Although some studies have shown otherwise 37 , the incidence of GDM, pregnancy-related hypertension and neonatal hypoglycemia is higher in women with PCOS diagnosed [38][39][40] . Glucose, lipid and androgen metabolism disorders are known to be important risk factors in the development of GDM in women with PCOS 41 . Because of this close relationship, PCO appearance in patients with GDM is thought to be between 41 and 52% ratio 42 .…”

Section: Resultsmentioning

confidence: 99%

Is Gestational Diabetes Mellitus Associated with the Metabolic Syndrome?

Yıldırım¹,

Bülbül²,

Özerkan³

et al. 2019

Kafkas J Med Sci

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Section: Resultsmentioning

confidence: 99%

Is Gestational Diabetes Mellitus Associated with the Metabolic Syndrome?

Yıldırım¹,

Bülbül²,

Özerkan³

et al. 2019

Kafkas J Med Sci

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“…In addition, SHBG is implicated in several pregnant complications. Firstly, SHBG is a marker in predicting GDM in PCOS subjects 18 . Moreover, a previous prospective study reports that SHBG is an independent risk factor for PCOS women who had preeclampsia (PE) 19 .…”

Section: Discussionmentioning

confidence: 99%

High Baseline SHBG, as an Independent Predictor, Was Associated With High Ovulation: a Secondary Analysis of PCOSAct

Chang

et al. 2021

Preprint

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Background: Sex hormone-binding globulin (SHBG) is related to several human systems such as reproductive system and endocrine system. SHBG binds to testosterone and estradiol, therefore we explored ethe role of SHBG on reproductive process. Methods: We carried out secondary analysis of Polycystic Ovary Syndrome and Acupuncture Clinical Trail (PCOSAct) at 21 sites in China, comprising a total of 1000 women with PCOS. A total of 954 women with baseline homocysteine (HCY) were included in the study. Results: Multivariate analysis of predictors of ovulation showed that age, body mass index (BMI), estradiol (E2), total testosterone (T) and SHBG are predictors of ovulation (P=0.0211, 0.0011, 0.0211, 0.0029, 0.0434) whereas luteinizing hormone (LH) to follicle-stimulating hormone (FSH) ratio is negatively correlated with ovulation (P=0.0539). A multivariate logistic regression model (MLRM) of all baseline serum parameters showed the strongest predictive ability for ovulation, followed by MLRM without SHBG. In addition to treatment, baseline SHBG was the strongest single predictor for ovulation. Patients in higher SHBG quartile showed significantly higher ovulation rate (HR=1.138; 95%CI [1.054,1.229], P=0.0009). Notably, significance was observed after adjustment for testosterone (HR=1.139, 95%CI [1.055,1.229], P=0.0009). However, quartiles of T, free testosterone (FT) and E2 all showed no correlation with ovulation. Kaplan-Meier curves showed that high SHBG is positively correlated with high ovulation, conception and pregnancy rates. Conclusions: Higher baseline SHBG is associated with higher ovulation rate and is an independent predictive marker.Trial registration: ClinicalTrials.gov (No. NCT01573858). Registered 10 April 2012, https://clinicaltrials.gov/ct2/show/NCT01573858?cond=NCT01573858&draw=2&rank=1.

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“…Women with PCOS and GDM were more likely to have impaired fasting blood glucose or impaired glucose tolerance at 18 months post-delivery compared with women that only exhibited GDM (29). Furthermore, hyperandrogenism with accompanying anovulation is one of the main features of PCOS and a previous study has demonstrated that patients with PCOS had lower levels of free androgen and sex hormone-binding globulin (SHBG) compared with patients without GDM (30). A previous study also demonstrated that obese women with PCOS and low SHBG levels were more likely to develop GDM compared with those with high SHBG levels (31).…”

Section: Discussionmentioning

confidence: 99%

A mid‑pregnancy risk prediction model for gestational diabetes mellitus based on the maternal status in combination with ultrasound and serological findings

et al. 2020

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to their diagnostic results at 24-28 weeks of pregnancy. Univariate analysis was performed to investigate the significance of the maternal clinical parameters for GDM diagnosis and a GDM prediction model was established using stepwise regression analysis. The predictive value of the model was evaluated using a Homer-Lemeshow goodness-of-fit test and a receiver operating characteristic curve (ROC). The model demonstrated that age, pre-pregnancy body mass index, a family history of diabetes mellitus, polycystic ovary syndrome, a history of GDM, high systolic pressures, glycosylated hemoglobin levels, triglyceride levels, total cholesterol levels, low-density lipoprotein cholesterol levels, serum hypersensitive C-reactive protein, increased subcutaneous fat thickness and visceral fat thickness were all correlated with an increased GDM risk (all P<0.01). The area under the curve value was 0.911 (95% CI, 0.893-0.930). Overall, the results indicated that the current model, which included ultrasound and serological data, may be a more effective predictor of GDM compared with other single predictor models. In conclusion, the present study developed a tool to determine the risk of GDM in pregnant women during the second trimester. This prediction model, based on various risk factors, demonstrated a high predictive value for the GDM occurrence in pregnant women in China and may prove useful in guiding future clinical practice.

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A prospective cohort study of early‐pregnancy risk factors for gestational diabetes in polycystic ovarian syndrome

Cited by 20 publications

References 62 publications

Is Gestational Diabetes Mellitus Associated with the Metabolic Syndrome?

Is Gestational Diabetes Mellitus Associated with the Metabolic Syndrome?

High Baseline SHBG, as an Independent Predictor, Was Associated With High Ovulation: a Secondary Analysis of PCOSAct

A mid‑pregnancy risk prediction model for gestational diabetes mellitus based on the maternal status in combination with ultrasound and serological findings

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