Nomograms of Iranian fetal middle cerebral artery Doppler waveforms and uniformity of their pattern with other populations' nomograms

<p>Abstract</p> <p>Background</p> <p>Doppler flow velocity waveform analysis of fetal vessels is one of the main methods for evaluating fetus health before labor. Doppler waves of middle cerebral artery (MCA) can predict most of the at risk fetuses in high risk pregnancies. In this study, we tried to obtain normal values and their nomograms during pregnancy for Doppler flow velocity indices of MCA in 20 – 40 weeks of normal pregnancies in Iranian population and compare their pattern with other countries' nomograms.</p> <p>Methods</p> <p>During present descriptive cross-sectional study, 1037 normal pregnant women with 20^th–40^thweek gestational age were underwent MCA Doppler study. All cases were studied by gray scale ultrasonography initially and Doppler of MCA afterward. Resistive Index (RI), Pulsative Index (PI), Systolic/Diastolic ratio (S/D ratio), and Peak Systolic Velocity (PSV) values of MCA were determined for all of the subjects.</p> <p>Results</p> <p>Results of present study showed that RI, PI, S/D ratio values of MCA decreased with parabolic pattern and PSV value increased with simple pattern, as gestational age progressed. These changes were statistically significant (P = 0.000 for all of indices) and more characteristic during late weeks of pregnancy.</p> <p>Conclusion</p> <p>Values of RI, PI and S/D ratio indices reduced toward the end of pregnancy, but PSV increased. Despite the trivial difference, nomograms of various Doppler indices in present study have similar pattern with other studies.</p

Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes : a systematic review and meta-analysis and analysis of two pregnancy cohorts

BACKGROUND: Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. METHODS: We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. RESULTS: Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. CONCLUSIONS: Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608

Macrosomia and large for gestational age in Asia:One size does not fit all

Macrosomia, usually defined as infant birth weight of >= 4000 g, does not consider gestational age, sex, or country/region-specific differences in mean birth weight and maternal body weight. This issue is particularly relevant for Asia, where 60% of the world's population lives, due to variations in maternal size and birth weights across populations. Large for gestational age (LGA), defined as birth weight > 90th centile, is a more sensitive measure as it considers gestational age and sex, though it is dependent on the choice of growth charts. We aimed to review reporting of macrosomia and LGA in Asia. We reviewed the literature on prevalence and risk of macrosomia and LGA in Asia over the last 29 years. Prevalence of macrosomia ranged from 0.5% (India) to 13.9% (China) while prevalence of LGA ranged from 4.3% (Korea) to 22.1% (China), indicating substantial variation in prevalence within and between Asian countries. High pre-pregnancy body mass index, excessive gestational weight gain, and impaired glucose tolerance conferred risk of macrosomia/LGA. Incidence of macrosomia and LGA varies substantially within and between Asian countries, as do the growth charts and definitions. The latter makes it impossible to make comparisons but suggests differences in intrauterine growth between populations. Reporting LGA, using standardized country/regional growth charts, would better capture the incidence of high birth weight and allow for comparison and identification of contributing factors. Better understanding of local drivers of excessive intrauterine growth could enable development of improved strategies for prevention and management of LGA