Build a Decision Aid Tool to Help Emergency Intensive Care Specialists in the Context of Hypoxic Ischemic Encephalopathy. NEWBORN NEURO-DIGITAL STUDY
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 106
- 试验地点
- 1
- 主要终点
- Decision of hypothermia protocol start
研究概览
简要总结
The project aims at designing a machine learning solution able to recognize characteristics signals patterns of brain damages in full term babies born within a context of Hypoxic Ischemic Encephalopathy (HIE)
详细描述
Retrospective study based on a digital EEG signal library intending to design, train and test an efficient AI solution for hypothermia protocol start indications.
The output of the Project is to make available to pediatric resuscitation units an adequate tool to guide them in the decision of hypothermia protocol start in a general context of neurophysiologist competence scarcity. EEG signal that would allow the algorithm design will be based on several parameters of the conventional EEG and not only on signal amplitude
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
- — 至 2 Days（Child）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Full term (> 36 weeks)
- •HIE context
- •EEG recording before 6 hours of life
排除标准
- •Opposition of parental authority holders of a patient born after 2015
结局指标
主要结局
Decision of hypothermia protocol start
时间窗: 6 months
Use of EEG signal in order to develop an algorithm
次要结局
未报告次要终点