Efficacy of metformin on pregnancy complications in women with polycystic ovary syndrome: a meta-analysis

2015 ◽  
Vol 31 (11) ◽  
pp. 833-839 ◽  
Author(s):  
Li Feng ◽  
Xiao-Fang Lin ◽  
Zhi-Hua Wan ◽  
Dan Hu ◽  
Yu-Kai Du
2019 ◽  
Vol 20 (5) ◽  
pp. 659-674 ◽  
Author(s):  
Mahnaz Bahri Khomami ◽  
Anju E. Joham ◽  
Jacqueline A. Boyle ◽  
Terhi Piltonen ◽  
Michael Silagy ◽  
...  

JGH Open ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 434-445
Author(s):  
Mohamed Shengir ◽  
Tianyan Chen ◽  
Elena Guadagno ◽  
Agnihotram V Ramanakumar ◽  
Peter Ghali ◽  
...  

2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110317
Author(s):  
Chenyun Miao ◽  
Qingge Guo ◽  
Xiaojie Fang ◽  
Yun Chen ◽  
Ying Zhao ◽  
...  

Objective This meta-analysis evaluated the effect of probiotics and synbiotics on insulin resistance in patients with polycystic ovary syndrome (PCOS). Methods A systematic search was performed to identify all relevant publications listed on the electronic databases (PubMed®, Web of Science, Embase® and China National Knowledge Infrastructure) between inception and 30 October 2020. All statistical analyses were performed on randomized controlled trials (RCTs) using RevMan version 5.3 software provided by the Cochrane Collaboration. Results A total of 486 patients from seven RCTs were included in the meta-analysis. Probiotic and synbiotic supplementation appeared to improve levels of homeostatic model assessment of insulin resistance (mean difference = –0.37; 95% confidence interval –0.69, –0.05) and serum insulin (standardized mean difference = –0.66; 95% confidence interval –1.19, –0.12). The results failed to show any influence of probiotic and synbiotic supplementation on body mass index, waist circumference, hip circumference and fasting blood sugar. Conclusions Probiotics and synbiotics appear to have a partially beneficial effect on indices of insulin resistance in patients with PCOS.


2019 ◽  
Vol 104 (9) ◽  
pp. 3835-3850 ◽  
Author(s):  
Matthew Dapas ◽  
Ryan Sisk ◽  
Richard S Legro ◽  
Margrit Urbanek ◽  
Andrea Dunaif ◽  
...  

AbstractContextPolycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5% to15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date.ObjectiveThe objective of this study was to test whether rare genetic variants contribute to PCOS pathogenesis.Design, Patients, and MethodsWe performed whole-genome sequencing on DNA from 261 individuals from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis.ResultsWe found rare variants in DENND1A (P = 5.31 × 10−5, adjusted P = 0.039) that were significantly associated with reproductive and metabolic traits in PCOS families.ConclusionsCommon variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.


2019 ◽  
Vol 51 (01) ◽  
pp. 22-34 ◽  
Author(s):  
Mina Amiri ◽  
Fahimeh Tehrani ◽  
Razieh Bidhendi-Yarandi ◽  
Samira Behboudi-Gandevani ◽  
Fereidoun Azizi ◽  
...  

AbstractWhile several studies have documented an increased risk of metabolic disorders in patients with polycystic ovary syndrome (PCOS), associations between androgenic and metabolic parameters in these patients are unclear. We aimed to investigate the relationships between biochemical markers of hyperandrogenism (HA) and metabolic parameters in women with PCOS. In this systematic review and meta-analysis, a literature search was performed in the PubMed, Scopus, Google Scholar, ScienceDirect, and Web of Science from 2000 to 2018 for assessing androgenic and metabolic parameters in PCOS patients. To assess the relationships between androgenic and metabolic parameters, meta-regression analysis was used. A total number of 33 studies involving 9905 patients with PCOS were included in this analysis. The associations of total testosterone (tT) with metabolic parameters were not significant; after adjustment for age and BMI, we detected associations of this androgen with low-density lipoproteins cholesterol (LDL-C) (β=0.006; 95% CI: 0.002, 0.01), high-density lipoproteins cholesterol (HDL-C) (β=–0.009; 95% CI: –0.02, –0.001), and systolic blood pressure (SBP) (β=–0.01; 95% CI: –0.03, –0.00). We observed a positive significant association between free testosterone (fT) and fasting insulin (β=0.49; 95% CI: 0.05, 0.91); this association remained significant after adjustment for confounders. We also detected a reverse association between fT and HDL-C (β=–0.41; 95% CI: –0.70, –0.12). There was a positive significant association between A4 and TG (β=0.02; 95% CI: 0.00, 0.04) after adjustment for PCOS diagnosis criteria. We also found significant negative associations between A4, TC, and LDL-C. Dehydroepiandrosterone sulfate (DHEAS) had a positive association with LDL-C (β=0.02; 95% CI: 0.001, 0.03) and a reverse significant association with HDL-C (β=–0.03; 95% CI: –0.06, –0.001). This meta-analysis confirmed the associations of some androgenic and metabolic parameters, indicating that measurement of these parameters may be useful for predicting metabolic risk in PCOS patients.


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