Lindsey A Sjaarda1, Paul S Albert1, Sunni L Mumford1, Stefanie N Hinkle1, Pauline Mendola1, S Katherine Laughon2. 1. Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD. 2. Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD. Electronic address: laughonsk@mail.nih.gov.
Abstract
OBJECTIVE: Using a cohort of 110,447 singleton, term pregnancies, we aimed to validate the previously proposed customized standard of large-for-gestational-age (LGA) birthweight, derive an additional customized LGA model excluding maternal weight, and evaluate the association between differing definitions of customized LGA and perinatal morbidities. STUDY DESIGN: Three customized LGA classifications, in addition to a population-based 90th percentile, were made according to the principals described by Gardosi: (1) customized LGA using Gardosi's previously published coefficients (LGA-Gardosi), (2) customized LGA using coefficients derived by a similar method but from our larger cohort, and (3) derived without customization for maternal weight. Associations between the LGA classifications and various perinatal morbidity outcomes were evaluated. RESULTS: Coefficients derived here for physiologic and pathologic effects on birthweight were similar to those previously reported by Gardosi. Customized LGA (any method) generally identified more births to younger, nonwhite, nulliparous mothers with female neonates of lower birthweight compared with population-based LGA. Rates of maternal and neonatal morbidity were greatest in births classified by both population-based LGA and customized LGA (any method). However, the model that excluded customization for maternal weight, revealed a greater proportion of women previously unidentified by population-based LGA who were more frequently black (40% vs 25%) and obese (30% vs 5.1%), along with greater rates of shoulder dystocia, neonatal intensive care unit admission and neonatal respiratory complications, than with LGA-Gardosi. CONCLUSION: The use of customized methods of defining LGA was not decisively superior compared with population-based LGA, but custom LGA may be improved by modification of the parameters included in customization.
OBJECTIVE: Using a cohort of 110,447 singleton, term pregnancies, we aimed to validate the previously proposed customized standard of large-for-gestational-age (LGA) birthweight, derive an additional customized LGA model excluding maternal weight, and evaluate the association between differing definitions of customized LGA and perinatal morbidities. STUDY DESIGN: Three customized LGA classifications, in addition to a population-based 90th percentile, were made according to the principals described by Gardosi: (1) customized LGA using Gardosi's previously published coefficients (LGA-Gardosi), (2) customized LGA using coefficients derived by a similar method but from our larger cohort, and (3) derived without customization for maternal weight. Associations between the LGA classifications and various perinatal morbidity outcomes were evaluated. RESULTS: Coefficients derived here for physiologic and pathologic effects on birthweight were similar to those previously reported by Gardosi. Customized LGA (any method) generally identified more births to younger, nonwhite, nulliparous mothers with female neonates of lower birthweight compared with population-based LGA. Rates of maternal and neonatal morbidity were greatest in births classified by both population-based LGA and customized LGA (any method). However, the model that excluded customization for maternal weight, revealed a greater proportion of women previously unidentified by population-based LGA who were more frequently black (40% vs 25%) and obese (30% vs 5.1%), along with greater rates of shoulder dystocia, neonatal intensive care unit admission and neonatal respiratory complications, than with LGA-Gardosi. CONCLUSION: The use of customized methods of defining LGA was not decisively superior compared with population-based LGA, but custom LGA may be improved by modification of the parameters included in customization.
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