ABSTRACT
Background: The aim of the present study was to determine the maternal pre-pregnancy body mass index [BMI], first-trimester fasting blood sugar [FBS], and the combination of [BMI+FBS] cut-points for at-risk pregnant women conceived by assisted reproductive technology [ART] to better predict the risk of developing gestational diabetes mellitus [GDM] in infertile women
Materials and Methods: In this nested case-control study, 270 singleton pregnant women consisted of 135 [GDM] and 135 [non-GDM] who conceived using ART were assessed. The diagnosis of GDM was confirmed by a one-step glucose tolerance test [O-GTT] using 75 g oral glucose. BMI was classified base on World Health Organization [WHO] criteria. The relationship between BMI, FBS, and BMI+FBS with the risk of GDM development was deter- mined by logistic regression and adjusted for confounding factors. Receiver operating characteristic [ROC] curve analysis was performed to assess the value of BMI, FBS, and BMI+FBS for the prediction of GDM
Results: The GDM group had significantly higher age, BMI, family history of diabetes, and history of polycystic ovary syndrome in comparison with the non-GDM group [P<0.05]. Overweight and obese women had 3.27, and 5.14 folds increase in the odds of developing GDM, respectively. There was a 17% increase in the risk of developing GDM with each 1 mg/dl increase in fasting glucose level. The cut points for FBS 84.5 mg/dl [72.9% sensitivity, 74.4% specificity], BMI 25.4 kg/m2 [68.9% sensitivity, 62.8% specificity], and BMI+FBS 111.2 [70.7% sensitivity, 80.6% specificity] was determined
Conclusion: The early screening and high-quality prenatal care should be recommended upon the co-occurrence of high FBS [>/=84.5 mg/dl] in the first-trimester of the pregnancy and the BMI [=25.4 kg/m2] in pre-pregnancy period in women undergone ART. The combination of BMI and FBS is considered a better prediction value
ABSTRACT
Objectives: Polycystic ovary syndrome [PCOS] is a common endocrine disorder related to several metabolic consequences. However, there remains uncertainty regarding the metabolic features of various phenotypes. The aim of this study was to explore the relationship between the prevalence of gestational diabetes mellitus [GDM] and metabolic disorders among the four different phenotypes of PCOS
Methods: A crosssectional study was performed in Royan Institute including 208 pregnant women with a history of infertility and PCOS. Using the diagnostic criteria of the American Diabetes Association [ADA], pregnant women with a documented diagnoses of PCOS were further categorized into four different phenotypes [A, B, C, and D] as defined by the Rotterdam criteria
Results: The prevalence of GDM failed to demonstrate a significant relationship among the four phenotypes of PCOS. The mean levels of fasting blood sugar, plasma glucose concentrations at three hours [following the 100 g oral glucose tolerance test] and triglyceride levels were significantly higher in phenotype B compared to the remaining phenotypes [p < 0.050]. There was a statistically significant difference between the mean free testosterone level and phenotypes A and C groups [1.8+/-1.6 vs. 1.1+/-1.0, p = 0.003]
Conclusions: Women with a known diagnosis of PCOS who exhibited oligo/ anovulation and hyperandrogenism demonstrated an increase of metabolic disorders. These results suggest that metabolic screening, before conception or in the early stages of pregnancy, can be beneficial particularly in women with PCOS phenotypes A and B. Early screening and identification may justify enhanced maternal fetal surveillance to improve maternal and fetal morbidity among women affected with PCOS
ABSTRACT
Controlled ovarian hyperstimulation [COM] in conjunction with intrau-terine inseminations [IUI] are commonly used to treat infertile couples. In this study we evaluated the relationship between IUI outcome and special causes of infertility. We also aimed to examine parameters that might predict success following IUI. In this cross-sectional study, we included 994 IUI cycles in 803 couples who referred to the infertility Institute. All statistical analyses were performed by using SPSS program, t tests and chi-square. Stepwise multiple linear regression analysis was performed to compare the association between dependent and independent variables. Logistic regression was conducted to build a prediction model of the IUI outcome. Overall pregnancy rate per completed cycle [16.5%] and live birth rate per cycle [14.5%]. The mean age in the pregnant group was significantly lower than that of the non-pregnant group [P=0.01].There was an association between cause of infertility and clinical pregnancies [P=0.001]. Logistic regression identified four significant factors in determining the success of the IUI [menstrual irregularites [OR:2.3, CI: 1.6-3.4, P<0.001], duration of infertility [OR:0.8, CLO.8-0.9, P<0.001], total dose of gonado-tropin [OR:1.02, CL1.003-1.04, P=0.02] and semen volume [ORrl.l, CL1.008-1.2, P=0.03]] which were the most predictive of IUI success. Our study defined prognostic factors for pregnancy in COH+IUI. These variables can be integrated into a mathematical model to predict the chance of pregnancy rate in subsequent COH+IUI cycles
ABSTRACT
Different success rate of Intracytoplasmic Sperm injection [ICSI] has been observed in various causes of infertility. In this study, we evaluated the relation between ICSI outcome and different causes of infertility. We also aimed to examine parameters that might predict the pregnancy success rate following ICSI. This cross sectional study included1492 infertile women referred to Infertility Center of Royan Institute between 2010 and 2011. We assigned two groups including pregnant [n=504] and non-pregnant [n=988], while all participants underwent ICSI cycles. All statistics were performed by SPSS program. Statistical Analysis was carried out using Chi-square and t test. Logistic regression was done to build a prediction model in ICSI cycles. The overall clinical pregnancy rate in our study was 33.9% [n=1492]. There was a statistically significant difference in mean serum concentration on day 3 after application of luteinizing hormone [LH] between the pregnant and the non-pregnant groups [p<0.05]. However, There were no significant differences between two groups in the serum concentrations on day 3 after application of the following hormones: follicle-stimulating hormone [FSH], thyroid-stimulating hormone [TSH], and metoclopramide-stimulated prolactin [PRL] . We found no association between different causes of infertility and clinical outcomes . The number of metaphase II [MII] oocytes, embryo transfer, number of good embryo [grade A, B, AB], total dose of gonadotropin, endometrial thickness, maternal age, number of previous cycle were statistically significant between two groups [p<0.05]. Our results indicate that ICSI in an effective option in couples with different causes of infertility. These variables were integrated into a statistical model to allow the prediction for the chance of pregnancy following ICSI cycles. It is required that each infertility center gather enough information about the causes of infertility in order to provide more information and better assistance to patients. Therefore, we suggest that physicians prepare adequate training and required information regarding these procedures for infertile couples in order to improve their knowledge
ABSTRACT
The objective of this study was to identify the prognostic factors that influence the outcome of ovarian stimulation with intrauterine insemination [IUI] cycles in couples with different infertility etiology. This retrospective study was performed in data of 1348 IUI cycles with ovarian stimulation by clomiphene citrate [CC] and/or gonadotropins in 632 women with five different infertility etiology subgroups at Akbarabbadi Hospital, Tehran, Iran. The pregnancy rate [PR]/ cycle was highest [19.9%] among couples with unexplained infertility and lowest [10.6%] in couples with multiple factors infertility. In cases of unexplained infertility, the best PR[s] were seen after CC plus gonadotropins stimulation [26.3%] and with inseminated motile sperm count>30×10[6] [21.9%], but the tendency didn't reach statistical significant. In the ovarian factor group, the best PR[s] were observed in women aged between 30 and 34 years [20.8%], with 2-3 preovulatory follicles [37.8%] and infertility duration between 1and 3 years [20.8%], while only infertility duration [p=0.03] and number of preovulatory follicles [p=0.01] were statistically significant. Multiple logistic regression analysis determined that number of preovulatory follicles [p=0.02], duration of infertility [p=0.015], age [p=0.019], infertility etiology [p=0.05] and stimulation regimen [p=0.01] were significant independent factors in order to predict overall clinical PR. The etiology of infertility is important to achieve remarkable IUI success. It is worth mentioning that within different etiologies of infertility, the demographic and cycles characteristics of couples did not show the same effect. Favorable variables for treatment success are as follows: age <40, duration of infertility