External validation of models to estimate gestational age in the second and third trimester using ultrasound: A prospective multicentre observational study

Abstract

AbstractObjectivesAccurate assessment of gestational age (GA) is important at both individual and population levels. The most accurate way to estimate GA in women who book late in pregnancy is unknown. The aim of this study was to externally validate the accuracy of equations for GA estimation in late pregnancy and to identify the best equation for estimating GA in women who do not receive an ultrasound scan until the second or third trimester.DesignThis was a prospective, observational cross‐sectional study.Setting57 prenatal care centres, France.ParticipantsWomen with a singleton pregnancy and a previous 11–14‐week dating scan that gave the observed GA were recruited over an 8‐week period. They underwent a standardised ultrasound examination at one time point during the pregnancy (15–43 weeks), measuring 12 foetal biometric parameters that have previously been identified as useful for GA estimation.Main Outcome MeasuresA total of 189 equations that estimate GA based on foetal biometry were examined and compared with GA estimation based on foetal CRL. Comparisons between the observed GA and the estimated GA were made using R2, calibration slope and intercept. RMSE, mean difference and 95% range of error were also calculated.ResultsA total of 2741 pregnant women were examined. After exclusions, 2339 participants were included. In the 20 best performing equations, the intercept ranged from −0.22 to 0.30, the calibration slope from 0.96 to 1.03 and the RSME from 0.67 to 0.87. Overall, multiparameter models outperformed single‐parameter models. Both the 95% range of error and mean difference increased with gestation. Commonly used models based on measurement of the head circumference alone were not amongst the best performing models and were associated with higher 95% error and mean difference.ConclusionsWe provide strong evidence that GA‐specific equations based on multiparameter models should be used to estimate GA in late pregnancy. However, as all methods of GA assessment in late pregnancy are associated with large prediction intervals, efforts to improve access to early antenatal ultrasound must remain a priority.Trial RegistrationThe proposal for this study and the corresponding methodological review was registered on PROSPERO international register of systematic reviews (registration number: CRD4201913776).