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Objective: The use of assisted reproductive technology (ART) has been associated with an increased risk of gestational diabetes mellitus (GDM) in previous studies, but its risk has not been consistent. Therefore, we aimed to estimate the risk of GDM in women who conceived with ART via a systematic review and meta-analysis of cohort studies. Methods: ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase databases were searched to identify studies that evaluated the risk of GDM through May 2017 using the relevant keywords. Two reviewers independently performed the screening, data extraction, and quality assessment. Meta-analysis was performed with a random effects model. Results: The search yielded 957 records relating to GDM and use of ART, from which 59 eligible cohorts were selected for meta-analysis (n=96,785). There was evidence of substantial heterogeneity among these studies (v(58) 2=3072.34, p<.001; I2=98.1%). The pooled estimate of GDM risk using the random effects model was 9.00% (95% CI: 7.90-10.20). Visual inspection of the funnel plot indicated the presence of low publication bias, but Egger's test did not reveal publication bias. Conclusions: The findings revealed that the risk of GDM was very high among women who conceived with ART treatment. GDM screening, management, and improved care are vital in ART pregnancy. [ABSTRACT FROM AUTHOR]

Objective: Previous studies have indicated that women with assisted reproductive technology (ART) pregnancy have an increased risk of preeclampsia. The aim of this current study was to estimate, through a systematic review and meta-analysis of cohort studies, the risk of preeclampsia in women who conceived with ART.Materials and methods: We searched ISI Web of Knowledge, Medline/PubMed, Scopus and Embase up to August 2017 for English-language articles pertaining to risk of preeclampsia in ART pregnancy using standard keywords. Data extraction was conducted by two authors and quality of the studies was assessed using the Newcastle-Ottawa Scale. A random-effects model was used for the meta-analysis.Results: In total, 72 cohort studies (n = 164 870) were included. The results of Cochran test and I2 statistic indicated considerable heterogeneity among studies (Q = 15 415.61, df = 71, p < .001, I2=99.5%). The pooled estimate of preeclampsia risk using the random effects model was 10.8% (95% CI: 9.10-12.5). Furthermore, the funnel plot and Begg's test showed evidence of publication bias.Conclusions: We found that the risk of preeclampsia was very high among women who conceived with ART. Women should be counseled carefully before undergoing ART treatment. [ABSTRACT FROM AUTHOR]

Objective: The use of assisted reproductive technology (ART) has been associated with an increased risk of gestational diabetes mellitus (GDM) in previous studies, but its risk has not been consistent. Therefore, we aimed to estimate the risk of GDM in women who conceived with ART via a systematic review and meta-analysis of cohort studies.Methods: ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase databases were searched to identify studies that evaluated the risk of GDM through May 2017 using the relevant keywords. Two reviewers independently performed the screening, data extraction, and quality assessment. Meta-analysis was performed with a random effects model.Results: The search yielded 957 records relating to GDM and use of ART, from which 59 eligible cohorts were selected for meta-analysis (n = 96,785). There was evidence of substantial heterogeneity among these studies (χ(58)2 = 3072.34, p < .001; I2=98.1%). The pooled estimate of GDM risk using the random effects model was 9.00% (95% CI: 7.90-10.20). Visual inspection of the funnel plot indicated the presence of low publication bias, but Egger's test did not reveal publication bias.Conclusions: The findings revealed that the risk of GDM was very high among women who conceived with ART treatment. GDM screening, management, and improved care are vital in ART pregnancy. [ABSTRACT FROM AUTHOR]

The objective of current study was to optimize the average diameter size of biosynthesized Silver Nanoparticles (AgNPs) induced by Penicillium citrinum. The AgNPs were prepared with a spherical shape and good monodispersity, determined by scanning electron microscopy (SEM), atomic force microscopy (AFM) and photon correlation spectroscopy (PCS). Besides, response surface methodology (RSM) was conducted to optimize the average diameter size of AgNPs by employing Box-Behnken design (BBD). The effective factors in this process were concentration of AgNO3 (mM) (X1), pH of solution (X2), temperature of shaker incubator (°C) (X3), rate of shaker incubator (rpm) (X4) and time of incubation (hour) (X5). The R2 (0.8894) value of the obtained model indicated a good correlation between the observed and predicted values. Overall, it could be concluded that multivariate analysis facilitated to find out the optimum conditions for the biosynthesis of AgNPs induced by P. citrinum with the reduced time and cost. [ABSTRACT FROM AUTHOR]

Hernan and Robins proposed a method for calculating marginal causal effect of treatment using standardization to propensity scores.  Data adaptive methods have been suggested as alternatives to logistic regression for the estimation of propensity scores. We examined the performance of various data mining methods using simulated data. The estimators' performance was evaluated in terms of relative bias, 95% CI coverage rate, and mean squared error.  All methods (except CART and GBM) displayed generally acceptable performance. However, under the conditions of moderate non-additivity and moderate nonlinearity, ANN and SL outperformed logistic regression with better bias reduction and more consistent 95% CI coverage. [ABSTRACT FROM AUTHOR]