Inconsistent patterns of twin growth and their relationship with obstetric adverse outcomes
Objective To determine different patterns of fetal growth dissonance in twin pregnancies and their predictive role in obstetric adverse outcomes.Methods The medical records of 531cases of twin-pregnancy women who underwent labor examination and delivery in our hospital from January 2014 to december 2021 were retrospectively analyzed.According to the ultrasound parameters during the prenatal examination,the inconsistencies between twins were divided into four modes:mode 1:no significant inconsistencies group(268cases),Mode 2:early progressive inconsistencies(23cases),mode 3:early inconsistencies with plinosis(91cases)and mode 4:late inconsistencies(149cases).The dynamic changes of each model and its correlation with adverse outcomes were investigated.Results Pattern 2 and Pattern 3 inconsistencies>10%(20.5 and 20.7 weeks of gestation)and>20%(27.7 and 26.3weeks of gestation)occurred at similar times.Mode 2 had the highest rate of inconsistent progression(0.92%/week),which peaked at 23.7%at 36weeks of gestation.Mode 3 progressed at a slower rate(0.49%/week),with a smaller variance after 20weeks(from 13.3%at 20weeks to 16%at 36weeks).The onset time of pattern 4 inconsistencies was>10%at 29.8weeks of gestation,and the peak inconsistencies(14.8%)were lower than pattern 2 and pattern Using mode 1(no significant inconsistency)as a reference,after adjusting for relevant covariates,mode 2 and 3 were risk factors for preterm birth and preeclampsia at 34 and 32weeks of gestation,mode 2 was a risk factor for 5-minute Apgar score<7,and mode 2,3,and 4 were risk factors for newborn birth weight<10th percentile.Conclusion According to the occurrence,development and intensity of neonatal growth dissonance,four different dissonance patterns were identified to be associated with different obstetric outcomes.These models provide more predictive information than the single point in time when measurements of fetal size are inconsistent,which is commonly used.
万方数据
维普
