Prediction of Successful Induction of Labor Using Ultrasonic Fetal Parameters

CURRENT WOMENS HEALTH REVIEWS(2022)

引用 4|浏览4
暂无评分
摘要
Background: Induction of labor (IOL) is a common obstetrical procedure. Bishop's score was the single predictor element used by practitioners to assess the risk of failure, which led to an increase in cesarean sections (CS). Ultrasound (US) examination was proposed since the variability limitations of Bishop score warranted alternative assessment tools. Objective: This study verifies how the US and other maternal parameters are used in the transperineal approach as an indication and as a predictor of successful induction. Material and Methods: A prospective clinical study of 100 participants was conducted with term singleton pregnancy referred for IOL and who fit the criteria of this study. Their maternal parameters and fetal head to perineum distance (HPD), measured by the transperineal US, were calculated before the induction. After the induction, the patients were stratified into two groups, vaginal delivery (68%) and CS (32%). The estimated time interval to delivery was also recorded. Results: None of the maternal parameters was significant; the P-values of maternal age, parity, body mass index (BMI), gestational age, and weight of the fetus were 0.75, 0.75, 0.69, 0.81, and 0.81, respectively. One-way ANOVA test estimated the most significant factors for inducing labor. Fetal HPD and induction to delivery interval were remarkably significant in both groups <0.0001. Conclusion: The shorter the HPD (<47.65 +/- 1.66 mm), the higher the possibility of vaginal delivery and a shorter delivery interval. By contrast, the longer HPD (>52.56 +/- 1.93mm), the lower the possibility of vaginal delivery and a longer delivery interval. These promising results may serve as a valuable tool in predicting a mode of delivery.
更多
查看译文
关键词
Induction of labor, bishop score, transperneal ultrasound, head to perineum distance, induction to delivery interval, fetal parameters
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要