Pregnancy outcome after false diagnosis of fetal growth restriction

Rinat Gabbay-Benziv, Amir Aviram, Eran Hadar, Rony Chen, Ron Bardin, Arnon Wiznitzer, Yariv Yogev

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: To evaluate pregnancy outcome following false diagnosis of fetal growth restriction (FGR). Methods: Retrospective analysis of all singleton term deliveries of appropriately grown fetuses (10–90th weight percentiles) in a single medical center (2007–2014). Elective cesarean-section, diabetes, and hypertension were excluded. Cohort was stratified based on third trimester sonographic estimated-fetal-weight (≥32 weeks). Women with false diagnosis FGR (<10th percentile) were compared with the rest (control). Induction of labor, cesarean deliveries, and short-term perinatal outcome were compared. Logistic regression analysis was performed to adjust outcome for birth weight and gestational age at delivery. Results: Of 34,474 pregnancies, 415 were falsely diagnosed as FGR (1.2%). Women in study group delivered earlier (38.6 ± 1.1 versus. 39.0 ± 0.9) with lower birth weights (2856 ± 270 versus 3271 ± 307 grams) and increased rate of labor inductions (19.8% versus 6.4%) and cesarean deliveries (10.8% versus 5.7%). Despite appropriate birth weight, study group neonates had higher rates of NICU admissions (10.6% versus 6.8%), mechanical ventilation (1.7% versus 0.5%), transient tachypnea of the newborn (1.7% versus 0.5%), hypoglycemia (1.7% versus 0.5%), and jaundice (11.3% versus 7.0%). p < 0.01 for all. All remained significant after adjustment to confounders. Conclusions: False diagnosis of FGR is associated with higher rates of induction of labor, cesarean deliveries, and short-term adverse neonatal outcome.

Original languageEnglish
Pages (from-to)1916-1919
Number of pages4
JournalJournal of Maternal-Fetal and Neonatal Medicine
Volume30
Issue number16
DOIs
StatePublished - 18 Aug 2017

Keywords

  • FGR outcome
  • Fetal growth restriction
  • estimated fetal weight
  • false diagnosis

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