Enrique González Dávila

The effect of customized growth charts on the identification of large for gestational age newborns

Objective: To determine the effect of using customized vs. standard population birthweight curves to define large for gestational age (LGA) infants. Methods: We analyzed data obtained from 2,097 singleton pregnancies using three different methods of classifying newborn birthweight: standard population curves, British or Spanish customized curves. We recorded maternal characteristics, proportion of LGA newborns when using each method, percentage of LGA according to one method but not for the others, and concordance between the different methods. Results: The proportion of LGA newborns according to Spanish customized curves was significantly lower than that calculated using either standard general population birthweight curves or British curves (p < 0.001). A third (33.9%) of the infants classified as LGA according to the general population method were adequate for gestational age (AGA) when the Spanish customized curves were used, and 18.5% of non-LGA were LGA according to customized curves (p < 0.001). Concordance between the different models high, but on excluding AGA the concordance coefficient was low (Cohen’s κ <0.4). Conclusions: The use of customized curves allows differentiation between constitutional LGA and cases of fetal overgrowth, leading to a decrease in the rate of both false-positives and negatives as well as the overall proportion of LGA babies.

Customized weight curves for Spanish fetuses and newborns

Abstract Objectives: To construct a model of customized birthweight curves for use in a Spanish population. Materials and methods: Data of 20 331 newborns were used to construct a customized birthweight model. Multiple regression analysis was performed with newborn weight as the dependent variable and gestational age (GA), sex and maternal (M) weight, height, parity and ethnic origin as the independent variables. Using the new model, 27 507 newborns were classified as adequate for GA (AGA), large for GA (LGA) or small for GA (SGA). The results were compared with those of other customized and non-customized models. Results: The resulting formula for the calculation of optimal neonatal weight was: Optimum weight (g) = 3289.681 + 135.413*GA40–14.063*GA402–0.838*GA403 + 113.889 (if multiparous) + 165.560 (if origin = Asia) + 161.550 (South America) + 67.927 (rest of Europe) +109.265 (North Africa) + 9.392*Maternal-Height + 4.856*Maternal-Weight–0.098*Maternal-Weight2 + 0.001*Maternal-Weight3 + 67.188*Sex + GA40*(6.890*Sex + 9.032 (If multiparous) +0.006*Maternal-Height3 + 0.260*Maternal-Weight) + GA402 (−0.378*Maternal-Height – 0.008*Maternal-Height2) + GA403 (−0.032*Maternal-Height). Weight percentiles were obtained from standard data using optimum weight variation coefficient. Agreement between our customized model and other Spanish models was “good” (κ = 0.717 and κ = 0.736; p < 0.001). Conclusions: Our model is comparable to other Spanish models, but offers the advantage of being customized, updated and freely available on the web. The 30.6% of infants classified as SGA using our model would be considered as AGA following a non-customized model.

First and second trimester screening for large for gestational age infants.

Abstract Objectives: To find the best early predictor model for fetal growth and large for gestational age (LGA) infants considering clinical, ultrasonographic and biochemical variables. Method: In 2097 singleton pregnancies at first trimester, we evaluated maternal characteristics, PAPP-A and ß-HCG proteins, fetal nuchal translucency thickness and uterine artery pulsatility index (UtA-PI). At second trimester fetal ultrasound biometry and UtA-PI were then measured. The relationships between birth weight and LGA and maternal characteristics, first and second trimester variables, and all variables combined, were studied. The performance of screening was determined by receiver operating characteristic curves analysis. Results: Stepwise regression analysis showed that in the prediction of birthweight percentile there were significant contributions from all maternal factors, PAPP-A and Ut-A PI in the first trimester, and fetal biometric variables in the second trimester. Maternal charateristics combined with PAPP-A, β-hCG, fetal NT and uterine artery PI identified 30.2 % LGA (FPR 10%). The combined model reached a sensitivity of 41.2% (FPR 10%) and 56.2% (FPR 20%). Conclusions: Sensitivity of the screening for LGA improves significantly after addition of second trimester ultrasound measurements to first trimester variables and maternal characteristics.

Value of Placental Volume and Vascular Flow Indices as Predictors of Early and Late Preeclampsia at First Trimester

Introduction: We evaluated the utility of placental volume and three-dimensional (3D) vascular flow indices to predict early and late preeclampsia. Material and Methods: In 1,004 pregnancies attending routine care, we recorded first-trimester screening program for aneuploidy (FTSA) parameter and measured uterine artery pulsatility index (uterine-a PI). Placental volume and vascular flow indices were obtained using 3D power Doppler and VOCAL techniques. Results: Placental volume was lower and uterine-a PI was higher in both early and late preeclampsia groups versus nonaffected pregnancies. The prediction rate of placental volume in late preeclampsia was higher than that of uterine-a PI (AUROC 0.707 vs. 0.581, p < 0.011). The inclusion of placental volume improved significantly the prediction rate of total and late preeclampsia in the models constructed with maternal characteristics, FTSA, and uterine-a PI (AUROC 0.745 vs. 0.818, p < 0.004, and 0.740 vs. 0.812, p < 0.012, respectively). The inclusion of vascular indices did not improve the predictive value of these models. Discussion: Placental volume was an independent predictor of total, early, and late preeclampsia and its inclusion in combined predictive models significantly improved prediction rates. Reduced placental volume observed at first trimester in women with early and late preeclampsia suggests that these entities are the clinical expression of a similar pathophysiological process.

Twin pregnancy among women with pregestational type 1 or type 2 diabetes mellitus

To assess the impact of twin versus singleton pregnancy on obstetric and perinatal outcomes among women with pregestational diabetes mellitus (DM).