ENSEMBLE: European Newborn Study: Early Markers for a Better LifE
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,000
- 试验地点
- 8
- 主要终点
- Development of a machine learning based prediction model
研究概览
简要总结
The goal of this observational study is to create a computer model to help doctors predict any problems occurring during development of babies after being diagnosed with brain injury. This will help provide better care to future babies. Next to this, the experiences of parents or caregivers surrounding the first two years after birth of a baby at risk of developing cerebral palsy will be researched to develop recommendations to support parents.
Parents of participants will:
- Fill in two online questionnaires, one when their child is 3-4 months corrected age. The second when their child is 2 years corrected age.
For the child no additional tests are needed. Only tests that are part of standard clinical practice are performed and are also saved in the study database.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 0 Years 至 2 Years（Child）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •All infants with confirmed brain injury on MRI at high risk for CP.
- •Particularly, infants with the following brain injuries at risk for CP will be considered on MRI at term equivalent age or within 10 days after birth or sentinel event:
- •Extensive punctate white matter injury.
- •Periventricular hemorrhagic infarction (any location).
- •Cerebellar injury (ischemic and/or hemorrhages) involving the vermis or involving more than 1/3 of the cerebellar hemisphere and/or lesions involving the cerebellar vermis (Meijler & Steggerda, 2019).
- •Cystic periventricular leukomalacia (grade 3 & 4).
- •intraventricular hemorrhages grade III.
- •Posthemorrhagic ventricular dilatation exceeding the 97°percentile + 4mm for the ventricular index (Cizmeci et al., 2020).
- •Perinatal asphyxia with hypoxic ischemic injury of the central gray matter and/or perirolandic area.
- •Perinatal asphyxia with hypoxic ischemic injury in the watershed areas.
- •Perinatal ischemic arterial stroke at high risk for CP, thus with involvement of the corticospinal tracts, cortex, white matter and basal ganglia (Wagenaar et al., 2018).
- •Presence of other brain injuries with expected adverse motor outcome (i.e. big subdural and parenchymal bleedings with/without midline shift, bilirubin induced brain injury) in preterm infants, term infants with neonatal encephalopathy with/without neonatal seizures.
- •Written informed parental consent (Dutch, English, French, German, Italian, Spanish).
排除标准
- •Infants not matching the inclusion criteria.
- •Any proven or suspected severe congenital anomaly, genetic or metabolic disorder.
- •Presence of an infection of the central nervous system.
- •Parents < 18 years old.
- •Not being able to read one of the six Informed Consent languages.
结局指标
主要结局
Development of a machine learning based prediction model
时间窗: Neurodevelopmental outcome at 2 years predicted by clinical data from birth to 3-4 months corrected age
To develop and evaluate a new prediction model using machine learning to predict the risk, severity, and long-term outcome of cerebral palsy (CP) at the level of the individual patient. This model will also provide automatic scoring for each clinical modality (MRI, EEG, GM, HINE, infant cry), which is to be compared with the clinician assessments.
次要结局
- Gaining insight into parental mental well-being and family= and social functioning.(Parent experience asked in questionnaires at age 3-4 months and 2 years.)
研究者
dr. M.J.N.L. Benders
Prof. dr.
UMC Utrecht