Customized Growth Curves Research Articles

Impact of customized growth curves on screening for small for gestational age twins

ObjectiveThe choice of a growth curve determines the screening for small-for-gestational-age (SGA) fetuses and little data is available on SGA twins. Our aim was to evaluate small-for-gestational-age (SGA) detection rate in twin pregnancies and assess whether the use of a customized curve allowed better identification of SGA fetuses. Study designRetrospective study including all twins between 2010 and 2013. Two groups were formed: the SGA and the non-SGA group. Four curves were compared: Hadlock’s curve, a customized curve, EPOPé M0 and EPOPé M1. We defined a composite neonatal complication criterion (transfer to intensive care unit, respiratory distress and death). Result472 fetuses were included with a 34.3% prevalence of SGA. Hadlock’s curve showed better sensitivity for the detection of SGA <10th percentile (67.3% vs. 63%, 59.9% and 57.4% respectively). Diagnostic Odd Ratio were comparable for the detection of SGA. For the composite variable, there was a significant difference between the 2 groups using a customized curve adjusted for fetal sex (EPOPé M1). ConclusionThe EPOPé (M0 and M1) and customized curves do not improve screening for SGA infants below the 10th percentile. The reduced effectiveness of customized curves can be related to the greater impact of placentation or cord insertion on the potential for fetal growth.

Comparison of fetal weight distribution improved by paternal height by Spanish standard versus Intergrowth 21st standard

Abstract Objective: Our main objective was to study the influence on birth and ultrasound fetal weight of traditional factors in combination with non-traditionally explored predictors such as paternal height to provide a new customized in utero growth model. We also have compared it in our population with other customized and non-customized models. Methods: We collected 5243 cases of singleton pregnancies. An integrated study of the different variables was performed in a multivariate model to predict the fetus birthweight and customized growth curves were created following the Gardosi procedure. Results: Gestational age (P&lt;0.001), parity (P&lt;0.001), maternal age (P&lt;0.001), maternal body mass index (P&lt;0.001), maternal height (P&lt;0.001), parental height (P&lt;0.001), pregnancy-associated plasma protein A (PAPP-A) (P&lt;0.001), free-beta human chorionic gonadotropin (FBHCG) (P&lt;0.013), single umbilical artery (SUA) (P&lt;0.009), region of origin (P&lt;0.001), fetal sex (P&lt;0.001), smoking (P&lt;0.001) and pre-gestational diabetes (P&lt;0.001) showed statistical significance. We created two growth customized models (simple and advance) that have shown good performance in predicting fetal weight at delivery and estimated by ultrasounds. The percentage of small for gestational age (SGA) cases (P10) predicted by the two models at birth were 9.9% and 9%, and for large gestational ages (LGA) (P90) we obtained values of 90.1% and 90.3%. Also, using the fetal weights measured by ultrasounds, we obtained P10 adjusted predictions, 9.2% and 9.4%, for the simpler and advance models, respectively, which were more adjusted than the 0.4, 4.6 and 10.6 obtained using the other compared models. For an easy use of models an app and a nomogram is provided. Conclusion: Using new predictor variables we implemented new growth in utero model, with predictions more adjusted to our population than Spanish customized or Intergrowth 21st models with better performance for birth and ultrasound fetal weights. We propose using a prediction model that includes parental height.

667: Population vs. customized growth curves and composite neonatal morbidity: a secondary analysis of 10 MFMU trials

Publications differ on the improved accuracy of identifying adverse neonatal outcomes based on population nomograms (birthweight [BW] and gestational age [GA]) vs. customized (for maternal height, weight, ethnicity, parity, GA and BW) growth curve. Our objective was to assess the diagnostic accuracy of population vs. customized growth curves (PopGC vs. CusGC) in identifying newborns with composite neonatal morbidity (CNM), including stillbirth and neonatal mortality. Non-anomalous singletons delivered at ≥ 24 wks. in 10 MFMU trials were analyzed. PopGC we based on Alexander’s nomogram while CusGC utilized software from http://www.gestation.net/index.htm, to categorize newborns as SGA (BW < 10% for GA), AGA (BW at 10-89%) or LGA (BW ≥ 90%). Random-effect logistic regression was used to estimate adjusted odds ratio (aOR) with 95% confidence intervals (CI). Receiver operator characteristic (ROC) curves (identifying CNM) with area under the curves (AUC) were constructed. Of 86,809 singleton pregnancies enrolled in 10 trials, 90% (N=77,987) met inclusion criteria. Using the PopGC, 12% were SGA and 10% LGA; with CusGC, rate of SGA and LGA was 15% and 16%, respectively. Compared to PopGC, aOR for SGA based on CusGC was higher for CNM, stillbirth and neonatal death; the same pattern was seen when evaluating aOR for CNM and stillbirth among LGA. Sensitivity for identifying stillbirth among SGA was higher with CusGC than PopGC (54%; 95% CI 47% - 60%) vs. 36%; 30% - 43%), as was for neonatal mortality (48%; 95% CI 44% - 53% vs. 27%; 95% CI 24% - 32%). Comparison AUC for SGA to identify CNM, stillbirth and neonatal mortality is significantly better with customized than population nomogram (P < 0.01; Table). For LGA, customized nomogram was better at identifying cases of stillbirth than population nomogram (P=0.03) but not for CNM (0.64; 95% CI, 0.63 - 0.64) vs. 0.64; 95% CI, 0.63 - 0.65) or neonatal death (p=0.06). Though CusGC was better than PopGC at identifying deliveries with CNM, stillbirth and neonatal mortality, it is not useful to obstetricians for BW is unknown during pregnancy. Thus, a randomized trial comparing customized fetal growth curve with population curve is warranted to determine which method mitigates morbidity and mortality with aberrant fetal growth.

Identification of small for gestational age by population-based and customized growth charts in newborns of obese and normal-weight primiparous women

Objective: Our hypothesis was that newborns of obese mothers would be more likely to be classified as small for gestational age (SGA) by their customized growth curves than by the standard growth curves when compared to newborns of normal-weight mothers.Methods: This is a retrospective cohort of primiparous patients delivering between 1 July 2008 and 30 June 2012. Normal-weight was defined as BMI ≤25 kg/m2 and obese as BMI ≥ 30 kg/m2. Infant birth-weight was characterized as SGA or non-SGA from the Lubchenco curve, the Fenton Preterm Growth Chart, and the customized growth curve.Results: Infants were more likely to be classified as SGA on the customized curve compared with Lubchenco curve. Odds ratio was 2.8 (CI: 1.7–4.4; p = 0.001) for obese women and was 2.9 (CI: 1.7–5.1; p < 0.001) for normal-weight women. Infants were also more likely to be classified as SGA based on the customized curve compared with the Fenton Preterm Growth Curve. The odds ratio was 2.3 (CI: 1.4–3.8; p = 0.001) for obese women and was 1.5 (CI: 1.01–2.33; p = 0.04) for normal-weight women.Conclusions: Population-based curves may mask SGA in obese women. Our study demonstrates that customized growth curves identify more SGA than population-based growth curves in obese and normal-weight women.

Curvas de crecimiento personalizadas para optimizar el diagnóstico de restricción de crecimiento Intrauterino

Introducción: Los fetos con restricción de crecimiento intrauterino (RCIU) tienen riesgo alto de morbimortalidad perinatal y existe mucha dificultad para diferenciarlos de los pequeños para la edad gestacional (PEG), debido a que incluso la ecografía Doppler tiene limitaciones al respecto. Se ha planteado que las curvas de crecimiento personalizadas podrían esclarecer esta disyuntiva. Objetivos: Diseñar un software con curvas de crecimiento personalizadas para optimizar el diagnóstico de RCIU en EsSalud. Diseño: Estudio comparativo, observacional y descriptivo. Institución: Hospital Edgardo Rebagliati Martins (HNERM), EsSalud, Lima, Perú. Participantes: Gestantes y sus fetos y recién nacidos. Metodología: Se construyó una curva de crecimiento con mediciones ultrasónicas de fetos de gestantes del HNERM cuyo peso se conoció al nacimiento y, en base a esta, se diseñó un software con curvas personalizadas. Se usó t de student, ANOVA y pruebas no paramétricas para el estudio estadístico y se consideró p&lt;0,05 para la significancia. Principales medidas de resultados: Curva de crecimiento fetal personalizada. Resultados: Se seleccionó 29 239 recién nacidos, atendidos entre 2003 y 2010. El peso neonatal estuvo influido por la talla materna, el peso pregestacional, la edad materna (ANOVA: F=3,8; F= 214,7 y F=11,2, respectivamente; p&lt;0,05), el sexo fetal masculino y la multiparidad (t de student; p&lt;0,001). Se diseñó un software, basado en estos parámetros, para la predicción del peso fetal para cada semana gestacional. Conclusiones: Se diseñó un software con curvas de crecimiento intrauterino personalizadas para optimizar el diagnóstico de fetos con RCIU, en EsSalud.

Re: Customized growth curves for identification of large‐for‐gestational age neonates in pre‐eclamptic women. J. Espinoza, W. Lee, S. R. Martin and M. A. Belfort. Ultrasound Obstet Gynecol 2014; 43: 165–169

Linked Comment: Ultrasound Obstet Gynecol 2014; 43: 165–169

225: Predicting small for gestational age–customized versus standard growth curves

Infants born small for gestational age are at increased risk of perinatal mortality and adult disease. Traditionally, a standardized growth curve has been used to determine those SGA infants. At our institution, both the Lubchenco curve and the Fenton growth chart are used for this determination. There is evidence that prenatal screening for fetuses destined to be SGA is imperfect, especially in the obese, whose infants are already at increased risk of poor neonatal outcomes. This has led to the development of customized growth curves.

Customized growth curves for identification of large‐for‐gestational age neonates in pre‐eclamptic women

To compare the role of two nomograms to classify large-for-gestational age (LGA) neonates in women with pre-eclampsia and to determine the frequency of placental vascular lesions according to the timing of delivery. This cohort study included 118 consecutive women with pre-eclampsia delivering between 23 and 41 weeks’ gestation. The frequencies of LGA neonates according to customized growth curves and a national birth weight (BW) chart were compared. Similarly, the frequencies of LGA neonates and histological placental vascular lesions were compared between pre-eclamptic women delivering at <34 weeks (n=40) and those delivering later (n=78). Customized growth curves allowed classification of a higher proportion of LGA neonates than did BW curves (18.6% (22/118) vs 10.2% (12/118); P=0.002). Among pre-eclamptic women delivering at ≥34 weeks, but not earlier, the proportion of neonates classified as LGA by customized growth curves was higher than that classified by BW curves (26.9% (21/78) vs 15.4% (12/78); P=0.004). Placental vascular lesions were less frequent in pre-eclamptic women delivering at ≥34 weeks than in those delivering earlier (41% (32/78) vs 62.5% (25/40); P=0.03). Customized growth curves allow classification of a higher proportion of LGA neonates than do population birth weight curves among women with pre-eclampsia delivering at ≥34 weeks. Pre-eclamptic women delivering at ≥34 weeks have fewer placental vascular lesions than do those delivering earlier.

Retard de croissance intra-utérin et cerveau en développement

Fetal growth restriction is the second leading cause of perinatal morbidity and mortality, behind prematurity, and is present in 5-12% of all pregnancies in the general population. Often confused with children constitutionally small for gestational age, those who had not achieved their potential for fetal growth and therefore having true growth restriction can be identified using customized growth curves. The point is to accurately identify fetuses with slowing growth or cessation of growth reflecting a pathological process, because these are at risk of death in utero or chronic fetal hypoxia with a significant impact on brain development. The kinetics of growth and prenatal markers of fetal growth restriction will influence the decision to extract the fetus and the gestational age at birth, as well as other factors involved in the neurodevelopmental outcome. Cognitive deficits and executive, motor, and behavioral dysfunctions described in the short term seem to persist together with greater risk of metabolic syndrome in adulthood. Decisions of fetal extraction by C-section continue to be debated until new epidemiological data will be available on large cohorts monitored over the long term using accurate neurocognitive tools. Understanding the effects of fetal growth restriction on the structure and function of the developing brain is essential for improving the relevance of fetal extraction decisions, perinatal care, and early evaluation of treatments for the prevention of neurodevelopmental disorders.

Intrauterine Growth Restriction: Effects of Physiological Fetal Growth Determinants on Diagnosis

The growth of the fetus, which is strongly associated with the outcome of pregnancy, reflects interplay of several physiological and pathological factors. The assessment of fetal growth is based on comparison of birthweight (BW) or estimated fetal weight (EFW) to standards which define reference ranges at a spectrum of gestational ages. Most birthweight standards do not take into account effects of physiological determinants of fetal growth. Additionally, gestational age in many standards is based on the menstrual history and is often inaccurate. Fetal growth norms should be based on an early ultrasound estimate of gestational age. Customized standards, which have included only ultrasound-dated pregnancies, seem to be superior to population-based birthweight norms in predicting perinatal mortality and morbidity. Adjustment for individual variation in customized growth curves reduces false-positive diagnosis of IUGR and may lead to a very significant reduction in intervention for suspected IUGR. Customized growth potential identifies better the risk for adverse outcome than the currently used national standards, but customized charts may fail in detecting growth-restricted stillbirth. An individual's birthweight is the sum of physiological and pathological influences operating during pregnancy. Growth potential norms are a better discriminator of aberrations of fetal growth than population, ultrasound, and customized norms.

Customized versus population-based growth curves: Prediction of low body fat percent at term corrected gestational age following preterm birth

Objective: Compare customized versus population-based growth curves for identification of small-for-gestational-age (SGA) and body fat percent (BF%) among preterm infants. Methods: Prospective cohort study of 204 preterm infants classified as SGA or appropriate-for-gestational-age (AGA) by population-based and customized growth curves. BF% was determined by air-displacement plethysmography. Differences between groups were compared using bivariable and multivariable linear and logistic regression analyses. Results: Customized curves reclassified 30% of the preterm infants as SGA. SGA infants identified by customized method only had significantly lower BF% (13.8 ± 6.0) than the AGA (16.2 ± 6.3, p = 0.02) infants and similar to the SGA infants classified by both methods (14.6 ± 6.7, p = 0.51). Customized growth curves were a significant predictor of BF% (p = 0.02), whereas population-based growth curves were not a significant independent predictor of BF% (p = 0.50) at term corrected gestational age. Conclusion: Customized growth potential improves the differentiation of SGA infants and low BF% compared with a standard population-based growth curve among a cohort of preterm infants.

17: Customized growth curves better identify fetal growth restriction and short term neonatal outcomes in preterm low birth weight infants

17: Customized growth curves better identify fetal growth restriction and short term neonatal outcomes in preterm low birth weight infants

307: Improving antenatal detection of intra uterine growth restriction by using customized versus population based growth curves

Prenatal diagnosis of IUGR has proven to be challenging as it is often difficult to distinguish pathologically growth restricted babies from those that are healthy but constitutionally small. Our objective was to evaluate if use of customized growth curves improves the prenatal detection of IUGR.

Customized growth curves.

Fetal growth is the principal issue in antenatal surveillance today. Its urgency is highlighted by audit data showing a powerful association between growth restriction and antepartum stillbirths. Customized growth charts optimize the assessment of fetal growth and birth weight by taking individual physiologic variables into account and by deriving an optimal curve that delineates the potential weight gain in each pregnancy. This results in an increased detection rate of true growth restriction and a reduction in false-positive diagnoses for intrauterine growth restriction. Such advantages have yet to be translated into better screening strategies for early detection of growth restriction.