■结果的二元预测模型[死亡,认知,脑瘫(CP)的存在和严重程度],尚未开发出适用于个体结局预测的MRI和早期临床数据。
■从2006年12月1日至2013年12月31日,我们招募了178名患有中度或重度缺氧缺血性脑病(HIE)包括产后塌陷(PNC,n=12)和使用CoolCap/TOBY试验进入标准的其他诊断(n=12),包括降低的振幅整合EEG(aEEG)。在168名婴儿中获得了早期临床/生化变量和MRI扫描(中位第8天)。皮质损伤严重程度评分,基底神经节/丘脑(BGT),白质(WM)和内囊后肢,总结为总伤害评分(TIS,范围0-11)。从Bayley-III域(截止值85)和包括CP分类在内的神经系统检查,在18-24个月时将结果分类为不利或有利。
■HIE和入口aEEG严重程度在整个研究中是稳定的。结果在133/178婴儿中有利,在45/178中不利:17死亡,28人的认知/语言得分较低,(包括9例重度CP和6例轻度CP);7例患有轻度CP,认知结果良好。WMxBGT产品评分和TIS是强有力的结果预测因子,当在二元逻辑回归中添加临床/生化变量时,预测有所改善。不良结局的阳性预测值为88%,在排除患有PNC和其他诊断的婴儿后增加到95%。在回归中使用WMxBGT预测了9名患有严重CP的儿童中的8名。
■使用WMxBGT或TIS和临床变量的二元逻辑回归提供了出色的结果预测,比单变量交叉列表好12%。我们的MRI评分和回归模型很容易获得,值得在其他队列中进行群体和个体预测。
■我们感谢国家卫生服务(NHS)以及我们在英国和挪威的大学和资助者:SPARKS,Moulton基金会,挪威研究理事会,乐达尔急性医学基金会和慈善捐款,以支持冷却疗法。
BACKGROUND: Binary prediction-models for outcome [death, cognition, presence and severity of cerebral palsy (CP)], using MRI and early clinical data applicable for individual outcome prediction have not been developed.
METHODS: From Dec 1st 2006 until Dec 31st 2013, we recruited 178 infants into a population-based cohort with moderate or severe hypoxic-ischaemic encephalopathy (HIE) including postnatal collapse (PNC, n = 12) and additional diagnoses (n = 12) using CoolCap/TOBY-trial entry-criteria including depressed amplitude-integrated EEG (aEEG). Early clinical/biochemical variables and MRI scans (median day 8) were obtained in 168 infants. Injury severity was scored for cortex, basal ganglia/thalami (BGT), white matter (WM) and posterior limb of the internal capsule, summating to a total injury score (TIS, range 0-11). Outcome was categorized as adverse or favourable at 18-24 months from Bayley-III domains (cut-off 85) and neurological examination including CP classification.
RESULTS: HIE and entry-aEEG severity were stable throughout the study. Outcome was favourable in 133/178 infants and adverse in 45/178: 17 died, 28 had low Cognition/Language scores, (including 9 with severe CP and 6 mild); seven had mild CP with favourable cognitive outcome. WMxBGT product scores and TIS were strong outcome predictors, and prediction improved when clinical/biochemical variables were added in binary logistic regression. The Positive Predictive Value for adverse outcome was 88%, increasing to 95% after excluding infants with PNC and additional diagnoses. Using WMxBGT in the regression predicted 8 of the 9 children with severe CP.
CONCLUSIONS: Binary logistic regression with WMxBGT or TIS and clinical variables gave excellent outcome prediction being 12% better than single variable cross-tabulation. Our MRI scoring and regression models are readily accessible and deserve investigation in other cohorts for group and individual prediction.
BACKGROUND: We thank the National Health Service (NHS) and our Universities and funders in UK and Norway: SPARKS, The Moulton Foundation, The Norwegian Research Council, The Lærdal Foundation for Acute Medicine and charitable donations for their support for cooling therapy.