Wahabi Hayfaa, Fayed Amel, Elmorshedy Hala, Esmaeil Samia Ahmad, Amer Yasser S, Saeed Elshazaly, Jamal Amr, Aleban Sarah A, Aldawish Reema Abdullah, Alyahiwi Lara Sabri, Abdullah Alnafisah Haya, AlSubki Raghad E, Albahli Norah Khalid, Almutairi Aljohara Ayed
Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.
Department of Family and Community Medicine, King Saud University Medical City and College of Medicine, Riyadh, Saudi Arabia.
Int J Womens Health. 2023 Aug 8;15:1283-1293. doi: 10.2147/IJWH.S414380. eCollection 2023.
The worldwide rate of cesarean section (CS) is increasing. Development of prediction models for a specific population may improve the unmet need for CS as well as reduce the overuse of CS.
To explore risk factors associated with emergency CS, and to determine the accuracy of predicting it.
A retrospective analysis of the medical records of women who delivered between January 1, 2021-December 2022 was conducted, relevant maternal and neonatal data were retrieved.
Out of 1793 deliveries, 447 (25.0%) had emergency CS. Compared to control, the risk of emergency CS was higher in primiparous women (OR 2.13, 95% CI 1.48 to 3.06), in women with higher Body mass index (BMI) (OR 1.77, 95% CI 1.27 to 2.47), in association with history of previous CS (OR 4.81, 95% CI 3.24 to 7.15) and in women with abnormal amniotic fluid (OR 2.30, 95% CI 1.55 to 3.41). Additionally, women with hypertensive disorders had a 176% increased risk of emergency CS (OR 2.76, 95% CI 1.35-5.63). Of note, the risk of emergency CS was more than three times higher in women who delivered a small for gestational age infant (OR 3.29, 95% CI 1.93-5.59). Based on the number of risk factors, a prediction model was developed, about 80% of pregnant women in the emergency CS group scored higher grades compared to control group. The area under the curve was 0.72, indicating a good discriminant ability of the model.
This study identified several risk factors associated with emergency CS in pregnant Saudi women. A prediction model showed 72% accuracy in predicting the likelihood of emergency CS. This information can be useful to individualize the risk of emergency CS, and to implement appropriate measures to prevent unnecessary CS.
全球剖宫产率正在上升。针对特定人群开发预测模型可能会改善剖宫产未满足的需求,并减少剖宫产的过度使用。
探讨与急诊剖宫产相关的危险因素,并确定预测其发生的准确性。
对2021年1月1日至2022年12月期间分娩的妇女的病历进行回顾性分析,检索相关的孕产妇和新生儿数据。
在1793例分娩中,447例(25.0%)进行了急诊剖宫产。与对照组相比,初产妇急诊剖宫产的风险更高(比值比2.13,95%置信区间1.48至3.06),体重指数(BMI)较高的妇女(比值比1.77,95%置信区间1.27至2.47),有既往剖宫产史(比值比4.81,95%置信区间3.24至7.15)以及羊水异常的妇女(比值比2.30,95%置信区间1.55至3.41)。此外,患有高血压疾病的妇女急诊剖宫产的风险增加176%(比值比2.76,95%置信区间1.35 - 5.63)。值得注意的是,分娩小于胎龄儿的妇女急诊剖宫产的风险高出三倍多(比值比3.29,95%置信区间1.93 - 5.59)。基于危险因素的数量,开发了一个预测模型,急诊剖宫产组中约80%的孕妇得分高于对照组。曲线下面积为0.72,表明该模型具有良好的判别能力。
本研究确定了沙特孕妇中与急诊剖宫产相关的几个危险因素。一个预测模型在预测急诊剖宫产可能性方面显示出72%的准确率。这些信息有助于个体化评估急诊剖宫产风险,并采取适当措施预防不必要的剖宫产。