scholarly journals Mean platelet volume and polycystic ovary syndrome: A systematic review and meta-analysis

Author(s):  
Li Li ◽  
◽  
Jianxiu Yu ◽  
Zhongwei Zhou
2022 ◽  
Vol 50 (1) ◽  
pp. 030006052110673
Author(s):  
Li Li ◽  
Jianxiu Yu ◽  
Zhongwei Zhou

Objective This meta-analysis evaluated the association between the mean platelet volume (MPV) and polycystic ovary syndrome (PCOS). Methods A systematic literature search using PubMed, EMBASE, and Web of Science databases until June 2021 was conducted. Pooled standardized mean differences (SMD) and 95% confidence intervals (CI) were determined using a random effects model. Results Ten studies involving 866 women with PCOS and 548 age- and body mass index-matched women without PCOS were included. The MPV was significantly increased in women with PCOS compared with non-PCOS women (SMD = 0.43, 95% CI = 0.13–0.72). Subgroup analyses showed that this trend was consistent in cross-sectional studies (SMD = 0.44, 95% CI = 0.03–0.86) and in Turkish women (SMD = 0.46, 95% CI = 0.13–0.79). Meta-regression analysis revealed a marginally positive correlation between the MPV and the homoeostasis model assessment of insulin resistance in women with PCOS. The sensitivity analysis showed that the effect estimate was robust and stable, and publication bias was not evidenced in the pooled analysis. Conclusions This meta-analysis revealed that women with PCOS have a significantly increased MPV than women without PCOS, which is probably associated with insulin resistance. INPLASY registration number: INPLASY2021100021.


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

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.


2012 ◽  
Vol 14 (2) ◽  
pp. 95-109 ◽  
Author(s):  
S. S. Lim ◽  
R. J. Norman ◽  
M. J. Davies ◽  
L. J. Moran

2016 ◽  
Vol 106 (3) ◽  
pp. e256
Author(s):  
W.J. Walker ◽  
D. Lizneva ◽  
L. Gavrilova-Jordan ◽  
L.E. Blake ◽  
S. Brakta ◽  
...  

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