| 杨元元,孙丹华,嵇萍.分娩潜伏期AOP、HPD与初产妇产程时长的关系及对分娩方式的预测价值.[J].中南医学科学杂志.,2024,(3):474-476. |
| 分娩潜伏期AOP、HPD与初产妇产程时长的关系及对分娩方式的预测价值 |
| Relationship between AOP, HPD during delivery incubation period and duration of labor stages, and their predictive value for delivery modes in primipara |
| 投稿时间：2023-06-16 修订日期：2024-03-19 |
| DOI：10.15972/j.cnki.43-1509/r.2024.03.041 |
| 中文关键词: 分娩潜伏期 AOP HPD 初产妇 分娩方式 产程时长 [ |
| 英文关键词:delivery incubation period AOP HPD primipara delivery mode duration of labor stage |
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| 中文摘要: |
| 目的探讨分娩潜伏期胎头进展角度(AOP)、胎头至会阴距离(HPD)与初产妇产程时长的关系及对分娩方式的预测价值。 方法选取初产妇117例,根据最终分娩方式分为阴道分娩组(n＝94)、剖宫产组(n＝23)。于分娩潜伏期超声测量AOP、HPD,ROC分析AOP、HPD对分娩方式的预测效能。Pearson分析阴道分娩组第二产程时长与AOP、HPD的关系。 结果阴道分娩组AOP高于剖宫产组,HPD低于剖宫产组(P＜0.05)。ROC分析显示,AOP、HPD联合检测对初产妇分娩方式具有良好的预测效能(P＜0.001)。第二产程时长与AOP呈正相关,与HPD呈负相关(P＜0.05)。 结论分娩潜伏期AOP和HPD与初产妇产程时长相关,且对分娩方式有较高的预测价值。 |
| 英文摘要: |
| AimTo explore the relationship between angle of progression (AOP) and head-perineum distance (HPD) during delivery incubation period and duration of labor stages, and their predictive value for delivery modes in primipara. MethodsA total of 117 primiparas were enrolled. According to the final delivery modes, they were divided into vaginal delivery group (n＝94) and cesarean section group (n＝23). AOP and HPD were measured by ultrasound during delivery incubation period. The predictive efficiency of AOP and HPD for delivery modes was analyzed by ROC. The relationship between duration of second labor stage and AOP and HPD in vaginal delivery group was analyzed by Pearson correlation analysis. ResultsAOP in vaginal delivery group was higher than that in cesarean section group, while HPD was lower than that in cesarean section group (P＜0.05). ROC curves analysis showed that AOP combined with HPD was of good predictive efficiency for delivery modes (P＜0.001). The duration of second labor stage was positively correlated with AOP, while negatively correlated with HPD (P＜0.05). ConclusionAOP and HPD during delivery incubation period are correlated with duration of labor stages in primiparas, which have high predictive value for delivery modes. |
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