Role of intrapartum AI in predicting labor outcome
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 61
- 试验地点
- 1
- 主要终点
- Correlation between Intrapartum AI and traditional assessment of labor . Hence helps in reducing unnecessary interventions such as prolonged labor, cesarean section.
研究概览
简要总结
This prospective observational study will be conducted in Kasturba Hospital, Manipal. Ethical clearance by Institutional ethical committee (IEC), Kasturba Hospital, Manipal will be taken. Pregnant women who will be admitted to the hospital will be screened based on the inclusion and exclusion criteria, as mentioned in the proforma and thereafter, baseline demographic characteristics will be obtained. Written and informed consent will be taken from the participants after a brief explanation of the procedure. Intrapartum AI is Digital assessment of labor progress, where 8 maternal parameters such as BMI, Parity index, gestational age, Duration of labor, Cervical dilatation, Head-Perineum distance, fetal position and caput will be taken into account to predict labor outcome. Based on these 8 parameters intrapartum AI will predict likelihood of normal vaginal delivery. We will conduct parallel traditional clinical assessment and wait for the outcome- vaginal delivery or c-section. From all the data collected we will employ statistical analysis to know the accuracy of Intrapartum AI in predicting labor outcome.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 45.00 Year(s)(—)
- 性别
- Female
入选标准
- •Singleton pregnancy Term pregnancy (37-41 weeks) Cervical dilatation 4-10cm.
排除标准
- •Mulifetal pregnancy VBAC.
结局指标
主要结局
Correlation between Intrapartum AI and traditional assessment of labor . Hence helps in reducing unnecessary interventions such as prolonged labor, cesarean section.
时间窗: At term (37weeks- 41 weeks), during labor
次要结局
- Not applicable(Not applicable)
研究者
Dr Radhika Maheshwari
Kasturba medical college
