S J Pugh1, A M Ortega-Villa2, W Grobman3, R B Newman4, J Owen5, D A Wing6,7, P S Albert2, K L Grantz1. 1. Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA. 2. Biostatistics Branch, Division of Cancer Epidemiology and Genetics, Medical Center Drive, National Cancer Institute, Rockville, MD, USA. 3. Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. 4. Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC, USA. 5. Department of Ob/Gyn, The University of Alabama at Birmingham Center for Women's Reproductive Health, Birmingham, AL, USA. 6. Division of Maternal-Fetal Medicine, Department of Obstetrics-Gynecology, School of Medicine, University of California, Irvine, Orange, CA, USA. 7. Miller Children's Hospital/Long Beach Memorial Medical Center, Long Beach, CA, USA.
Abstract
OBJECTIVE: Accurate assessment of gestational age (GA) is critical to paediatric care, but is limited in developing countries without access to ultrasound. Our objectives were to assess the accuracy of prediction of GA at birth and preterm birth classification using routinely collected anthropometry measures. DESIGN: Prospective cohort study. SETTING: United States. POPULATION OR SAMPLE: A total of 2334 non-obese and 468 obese pregnant women. METHODS: Enrolment GA was determined based on last menstrual period, confirmed by first-trimester ultrasound. Maternal anthropometry and fundal height (FH) were measured by a standardised protocol at study visits; FH alone was additionally abstracted from medical charts. Neonatal anthropometry measurements were obtained at birth. To estimate GA at delivery, we developed three predictor models using longitudinal FH alone and with maternal and neonatal anthropometry. For all predictors, we repeatedly sampled observations to construct training (60%) and test (40%) sets. Linear mixed models incorporated longitudinal maternal anthropometry and a shared parameter model incorporated neonatal anthropometry. We assessed models' accuracy under varied scenarios. MAIN OUTCOME MEASURES: Estimated GA at delivery. RESULTS: Prediction error for various combinations of anthropometric measures ranged between 13.9 and 14.9 days. Longitudinal FH alone predicted GA within 14.9 days with relatively stable prediction errors across individual race/ethnicities [whites (13.9 days), blacks (15.1 days), Hispanics (15.5 days) and Asians (13.1 days)], and correctly identified 75% of preterm births. The model was robust to additional scenarios. CONCLUSIONS: In low-risk, non-obese women, longitudinal FH measures alone can provide a reasonably accurate assessment of GA when ultrasound measures are not available. TWEETABLE ABSTRACT: Longitudinal fundal height alone predicts gestational age at birth when ultrasound measures are unavailable.
OBJECTIVE: Accurate assessment of gestational age (GA) is critical to paediatric care, but is limited in developing countries without access to ultrasound. Our objectives were to assess the accuracy of prediction of GA at birth and preterm birth classification using routinely collected anthropometry measures. DESIGN: Prospective cohort study. SETTING: United States. POPULATION OR SAMPLE: A total of 2334 non-obese and 468 obese pregnant women. METHODS: Enrolment GA was determined based on last menstrual period, confirmed by first-trimester ultrasound. Maternal anthropometry and fundal height (FH) were measured by a standardised protocol at study visits; FH alone was additionally abstracted from medical charts. Neonatal anthropometry measurements were obtained at birth. To estimate GA at delivery, we developed three predictor models using longitudinal FH alone and with maternal and neonatal anthropometry. For all predictors, we repeatedly sampled observations to construct training (60%) and test (40%) sets. Linear mixed models incorporated longitudinal maternal anthropometry and a shared parameter model incorporated neonatal anthropometry. We assessed models' accuracy under varied scenarios. MAIN OUTCOME MEASURES: Estimated GA at delivery. RESULTS: Prediction error for various combinations of anthropometric measures ranged between 13.9 and 14.9 days. Longitudinal FH alone predicted GA within 14.9 days with relatively stable prediction errors across individual race/ethnicities [whites (13.9 days), blacks (15.1 days), Hispanics (15.5 days) and Asians (13.1 days)], and correctly identified 75% of preterm births. The model was robust to additional scenarios. CONCLUSIONS: In low-risk, non-obese women, longitudinal FH measures alone can provide a reasonably accurate assessment of GA when ultrasound measures are not available. TWEETABLE ABSTRACT: Longitudinal fundal height alone predicts gestational age at birth when ultrasound measures are unavailable.
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