Perinatal Outcomes among Cases of Predicted and Unpredicted Macrosomia
DOI:
https://doi.org/10.21613/GORM.2022.1379Keywords:
Cesarean section, Hadlock, Macrosomia , Ultrasound weight predictionAbstract
OBJECTIVE: Macrosomia is strongly associated with a range of adverse maternal and neonatal outcomes. The effectiveness of screening remains controversial because expecting a macrosomic fetus affects intrapartum management, promoting elective cesarean sections. This study aims to identify differences in outcomes and management among cases with predicted and unpredicted macrosomia.
STUDY DESIGN: This is a retrospective study of 779 live-born, cephalic, singleton macrosomic babies delivered at our institution from January 2017 to December 2019. Cases of macrosomia were categorized as unpredicted and predicted. Ultrasonographic weight predictions are made using the Hadlock formula. Data regarding mode of delivery, shoulder dystocia, perineal trauma, episiotomy use, and postpartum hemorrhage were retrieved. Data were stored in a secure database. The review board of the institution approved the study. Statistical analysis is performed utilizing the Mann-Whitney U test for continuous data, the chi-square test for cardinal variables, and logistic regression analysis. Significance was set as p<0.05.
RESULTS: Macrosomia is successfully predicted in 268 (34.4%) women. The rate of cesarean sections was significantly higher in the predicted group (46.4% vs. 35.4%, p=0.002). The higher rate of elective cesarean sections among women with predicted macrosomia (26.1% vs. 15.1%, p=0.02) contributed to this difference. Women with predicted macrosomic fetuses were more prone to perineal traumas, such as episiotomy (48.9% vs. 31.3%) or third/4th -degree lacerations (4.8% vs. 1.95%). Shoulder dystocia and other neonatal complications did not differ significantly among the groups.
CONCLUSION: Acknowledging macrosomia before delivery increases elective cesarean sections and it decreases the rate of adverse neonatal outcomes such as birth asphyxia.
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Copyright (c) 2023 Merita Isaku, Enxhi Vrapi, Tedi Bimbashi , Ina Cala, Kizjona Perdja, Redi Hoxhallari, Astrit Bimbashi
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