Machine Learning Miscarriage Management Clinical Decision Support Tool Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- Machine learning predictive model development for miscarriage management outcomes.
研究概览
简要总结
Machine learning used to develop an algorithm to determine chance of success with expectant or medical management for an individual patient. Taking into account the following objective measures:
- Demographics: Maternal Age, Parity
- History: Previous CS, Previous SMM/MVA, Previous Myomectomy
- Gestation by LMP
- Presenting symptoms: Bleeding score, Pain score
- USS Measurements: CRL, GS, RPOC 3 dimensions, Vascularity
- Discrepancy between gestation by CRL and LMP
Audit to collate 1000 cases and identify features contributing to an algorithm that can predict outcome of miscarriage management for individualized case management.
详细描述
- Artificial intelligence discovery science: Algorithm Development based on a retrospective Audit of approximately 1000 cases of miscarriage
- To determine the reliability of the tool with test data sets
- To increase the sensitivity and specificity of the decision aid by widening the data collection to multiple sites and testing the algorithm with prospective data
The study will be conducted at Queen Charlotte's and Chelsea Hospital at Imperial College Healthcare NHS Trusts (Primary Centre of the study).
This is a multi-centre retrospective, cohort observational study.
The study will be conducted over a minimum of three years to enable sufficient time to go through the retrospective data and collate test data sets.
Retrospective annonymised cases of missed miscarriage and incomplete miscarriage managed at Imperial College Healthcare NHS Trust will be analyse:
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 16 Years 至 55 Years（Child, Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- •Missed miscarriage and incomplete miscarriage less than 14weeks gestation
- •Follow-up recorded at 2 weeks
排除标准
- •Final outcome data unavailable
结局指标
主要结局
Machine learning predictive model development for miscarriage management outcomes.
时间窗: Jan 2023- June 2024
Machine learning predictive model development based on a retrospective audit of approximately 1000 cases of miscarriage.
次要结局
- Prospective audit to test and validate predictive model(July 2024-June 2025)