Preliminary dating and growth assessment

preliminary dating and growth assessment

Correct assessment of gestational age and fetal growth is essential for .. The results show that initial dating is always more reliable than in. Expect Respect Support Groups: Preliminary Evaluation of a Dating . participants did not show expected growth in healthy relationship skills. Preliminary assessment of a direct age- determination method for 3 Online publication date: 15 November docuticle, where growth bands have.

Furthermore, the comparison between the conventional growth curves and the mathematical models showed that the former do not require complex calculations and are conceptually simpler and easier to use [ 28 ]. Customized growth charts The debate around "fetal growth potential" assessment started with the studies on customized growth charts performed by Gardosi et al. The pregnancy characteristics are used in order to calculate the Term Optimal Weight - the weight that the baby is predicted to achieve in the absence of pathological influences at 40 weeks of pregnancy [ 33 ].

The fetal growth standard should be "customized" for each fetus, including physiological characteristics of mother and fetus like race, ethnicity, maternal height and weight at booking, parity and sex of the fetus [ 2127 ]. These growth curves must be based upon intrauterine fetal growth, as premature birth will result in a fetus with a lower weight than the fetus that continues to grow in utero [ 2930 ].

It seems that in the pathological pregnancies, the in utero growth is affected and premature birth represents a way of escaping the unfavorable milieu that would lead to further fetal distress [ 31 ].

preliminary dating and growth assessment

Another important issue in defining the fetal growth potential is the exclusion of pathology — like hypertension or diabetes and smoking, which would affect the birthweight [ 32 ].

With the aid of customized charts we can identify a group of truly growth restricted fetuses that have not been recognized through population charts and present a higher perinatal risk. Furthermore, another group of previously small fetuses would be considered normal and having a good outcome.

In the beginning of the s, Gardosi et al. Taking into account populational differences, various fetal growth potential were developed in countries like United Kingdom, Australia, New Zeeland, France, United States, Spain [ 2734 - 38 ].

Although promising, the customized growth charts were contested by some researchers [ 3940 ]. However, their apparent benefits are more likely to have been derived from their incorporation of intrauterine-based EFW reference values at preterm ages than their adjustment for maternal characteristics. Growth trajectories — new promising tools The value of detecting true small babies is real but what is questionable is the prediction of customized growth curves for perinatal morbidity and mortality, because a great amount of fetuses are premature and the prematurity complications superpose over the IUGR complications.

However, the usefulness of fetal growth trajectories is real in detecting the anomalies of growth patterns, which are important in detecting growth-impaired fetuses whose echografic parameters are still above the 10th percentile but decrease from an ultrasound exam to another. In a recent study [ 41 ], two fetal growth trajectories normal and pathologic were described in a group of fetuses with impaired growth, helping in the detection of undergrown fetuses at real risk of poor neonatal outcome.

Although it has some limitations it includes a cohort of fetuses already diagnosed with abnormal growththe strong points of the study were the dynamic assessment of growth and the individual approach based on repeated examination of the same fetus. Conclusions The diagnosis of FGR has as a first step the identification of impaired fetal growth and the confirmation is made with tools like fetal arterial and venous Doppler assessment, biophysical indices.

Growth assessment in diagnosis of Fetal Growth Restriction. Review

The failure of FGR identification is an important cause of perinatal morbidity with an increase of the level of adverse perinatal outcome. SFH measurement could be used as a cost-effective method of screening for fetal growth from 20—24 gestation weeks in the appropriate cases.

For the definition of a small fetus, a referential and a cut off value are necessary.

Along the years, researchers have tried to find a predictible model of growth for the fetus in order to early detect anomalies of growth. The use of customized centiles, seemed to increase the prediction of at risk pregnancies for perinatal mortality and the association with other perinatal complications like PIH, PE, threatened labor, antepartum hemorrhage, emergency cesarian section for fetal distress, low Apgar score and necessity of NICU admission.

The latest research patterns purpose of fetal growth — growth trajectories — being promissing in identifying fetuses with an affected development.

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What is really important is to distinguish between small fetuses with poor periantal outcome and physiologically small fetuses and perform a protocol of increased surveillance on the risk fetuses.

Footnotes Sources of Funding: Disclosures and Conflicts of Interest: American College of Obstetricians and Gynecologists Practice bulletin no.

Optimizing the definition of intrauterine growth restriction: Am J Obstet Gynecol. Perinatal outcome in SGA births defined by customised versus population-based birthweight standards.

Growth charts and IUGR. Fetal growth screening by fundal height measurement. Prediction of small-for-dates infants by measurement of symphysial-fundal-height. Br J Obstet Gynaecol. Symphysis-fundal height and size at birth. Int J Gynaecol Obstet.

Growth assessment in diagnosis of Fetal Growth Restriction. Review

When to Screen in Obstetrics and Gynecology. The Royal College of Obstetricians and Gynaecologists The investigation and management of the small-for-gestational-age fetus. Green Top Guidline, No.

Controlled trial of fundal height measurement plotted on customised antenatal growth charts. Serial plotting on customised fundal height charts results in doubling of the antenatal detection of small for gestational age fetuses in nulliparous women. Symphysial fundal height SFH measurement in pregnancy for detecting abnormal fetal growth. Cochrane Database Syst Rev. Longitudinal studies of fetal growth using volume parameters determined with ultrasound. Is sonographic assessment of fetal weight influenced by formula selection?

Computer assisted analysis of fetal age in the third trimester using multiple fetal growth parameters. A new and improved population-based Canadian reference for birth weight for gestational age. The relationship between intrauterine growth restriction and preterm delivery: Fetal growth and onset of delivery: A United States national reference for fetal growth.

Customised antenatal growth charts. Mathematical modeling of fetal growth: Influence of the interval between time points on individual fetal growth curve standards derived from Rossavik models and two ultrasound scans before 26 weeks, menstrual age. First-trimester growth and the risk of low birth weight. N Engl J Med. Early fetal size and growth as predictors of adverse outcome.

An adjustable fetal weight standard. Diminished growth in fetuses born preterm after spontaneous labor or rupture of membranes. Prematurity and fetal growth restriction. In utero analysis of fetal growth: A customized birthweight centile calculator developed for an Australian population. A customised birthweight centile calculator developed for a New Zealand population.

As a consequence in clinical practice, generic charts are preferred to specific ones or to more complex approaches based on suitable mathematic models [ 11 ], because of their feasibility.

Moreover, the World Health Organization WHO standards are still commonly based on generic reference charts; they do not differentiate by ethnic origin and are not subject to frequent update, so they are unsuitable to assess the biometric parameters in several cases of practical interest. To preserve the feasibility of the approach without losing diagnostic power, some authors proposed the adoption of purposely developed software tools Web Applications, Mobile Application, etc.

Medical literature clearly showed its main drawbacks: A the number of patients considered in the studies some thousandth is low with respect to the total number of newborn per year about Millions in in the world; B patients considered in the studies are not representative of the variety of anthropometrical factors due to ethnicity, familial aspects, and other relevant internal and external factors; C the commonly used growth curves are up to five decades old; they are not updated for the current population and they are not suitable to investigate temporal trends and dynamic aspects in fetal growth curves.

Nevertheless, fetal growth is influenced by a variety of factors, racial, social, and economic among others, as well as specific medical conditions that may preexist or that may develop during pregnancy. Hence, it is not surprising that fetal biometric parameters show high degree of variation in evaluated population from country to country and from area to area, within the same country.

Beyond ethnicity, many other factors affect fetal growth including fetus gender, physiological and pathological variables, maternal height and weight, drug or tobacco exposure, genetic syndromes, congenital anomalies, and placental failure [ 15 — 18 ]. In this context, it is necessary to have personalized charts for fetal growth in order to provide an accurate fetal assessment and to make the presence of false positive and false negative potentially avoidable.

The adoption of wrong reference curves on specific fetuses could cause an incorrect evaluation of fetal biometric parameters, identifying for example cases known in literature as Small for Gestational Age SGA or Large for Gestational Age LGA. In this scenario, authors quantify and analyse the impact of the adoption of such wrong growth charts on fetal diagnoses.

As initial results, authors show how much different are values and boundaries of certain biometric parameters according to ethnicity. Salentinian population southeast of Italy has been analysed and its samples have been compared with the reference curves adopted for Italian [ 19 ] and European [ 20 ] fetuses.

Material and Methods The study includes a population of about Italian women undergoing ultrasound examination between the 11th and 41th weeks of gestation, between November and September All pregnant women were enrolled in a previously defined area, southeast of Italy, in the Vito Fazzi Hospital, Italy, and Departments of Obstetrics and Gynecology assessed the investigation. Gestational age was established by using US imaging during the first visit, at study enrolment.

All patients received written and oral information about the study, and they signed the informed consent. Data Harvesting Methodology Before enrolment, authors defined, in the setup study, the inclusion and exclusion criteria Inclusion criteria were: Cases with low birth weight, preterm delivery, or other prenatal complications were not excluded from analysis.

Gestational age was based on the last menstrual period and in all cases adjusted according to the CRL measured in the first trimester ultrasound. Pregnant women were excluded from analysis if they joined the study after the 24th week of pregnancy, because reliable dating of pregnancy is more difficult as pregnancy proceeds.

All machines had a standard US setting of Doppler and grey scale, provided by companies. Measurements of the biparietal diameter BPD and head circumference HC were obtained from a transverse axial plane of the fetal head showing a central midline echo broken in the anterior third by the cavum of septum pellucidi and demonstrating the anterior and posterior horns of the lateral ventricle.

The BPD was measured from the outer margin of the proximal skull to the inner margin of the distal skull. The HC was measured fitting a computer-generated ellipse to include the outer edges of the calvarial margins of the fetal skull. The abdominal circumference AC was measured fitting a computer-generated ellipse through a transverse section of the fetal abdomen at the level of the stomach and bifurcation of the main portal vein into its right and left branches.

The femur length FL was measured in a longitudinal scan where the whole femural diaphysis was seen almost parallel to the transducer and measured from the greater trochanter to the lateral condyle.

In the third trimester, particular care was taken not to include the epiphysis.

preliminary dating and growth assessment

Statistical Methods Each interval of gestational age was centred on a week, so that from 13 weeks and 4 days up to 14 weeks and 3 days has been considered as 14th week. Statistical analysis has been performed using appropriate packages of R Software http: The normality of measurements at each week of gestation was assessed using the Shapiro-Wilk test [ 21 ], which is one of the most powerful tests to use for the normality assessment, especially for small samples.

It tests the null hypothesis that a given sample came from a normally distributed population. In order to obtain normal ranges for fetal measurements, a multistep procedure based on regression model has been used, according to the recommended methodology for this type of data [ 2223 ]. Assuming that, at each gestational age, the measurement of interest has a Gaussian distribution with a mean and a standard deviation SD and that, in general, both vary smoothly with gestational age, a centile curve has been calculated using the well-known formula: The mean has been estimated by the fitted values from an appropriate polynomial regression curve of the measurement of interest on gestational age.

Several curve-fitting and smoothing techniques have been tested for the mean estimation of the different biometric parameters and the goodness of fit for each regression model has been carefully assessed. The polynomial model that better satisfies the experimental data is the cubic one, since it better fulfils the fractional polynomial and the logarithmic transformations. These residuals are the differences between the measurements and the estimated curve for the mean with the sign removed and multiplied by a corrective constant equal to.

Generally, if the scaled absolute residuals appear to show no trend with gestational age, the SD is estimated as the standard deviation of the unscaled residuals measurements minus the estimated mean curve. If there is a trend, then polynomial regression analysis is needed to estimate an appropriate curve in the same way of the mean. For BPD, HC, and AC biometric parameters, the residuals were regressed on gestational ages by using a linear model in the form of While, considering the FL parameter, the quadratic regression seems to better fulfil the linear one.

The adopted equation is Finally, these predictive mean and SD equations allow calculating any required centile, replacing the value in the centile formula. Data analysis showed that neither the use of fractional polynomials the greatest power of the polynomials being 3 nor the logarithmic transformation improved the fitting of the curves.

Therefore, the data were kept in their original scale. To choose the best fitting model, we have taken into consideration primarily the index which is the linear determination index: Other factors we have considered include the validity and the effectiveness of the model. There will be an improvement in fit as higher-order terms are added, but because these terms are not theoretically justified, the improvement will be sample-specific.

Unless the sample is very small, the fits of higher-order polynomials are unlikely to be very different from those of a quadratic over the main part of the data range. Consider that, for example, the for the quadratic specification of BPD parameter is 0. Further, the cubic and quartic curves both exhibit implausible strange twists at the extremities Figures 1 and 2.

Third order polynomial regression for biparietal diameter. Fourth order polynomial regression for biparietal diameter. The scatter of absolute residuals from the regression for estimation of the standard deviation of femur length as a function of gestational age is shown in Figure 3. Absolute scaled residuals for FL measurement. The corresponding regression equations, with the respective index for the mean and the standard deviation, are illustrated in Table 1.

In each table, it is also indicated that the sample number, the mean, and the standard deviation are related to each gestational week. Fitted centiles of head circumference mm.