Novel approaches to prediction in severe brain injury.
Novel approaches to prediction in severe brain injury.
复制标题
新颖的预测严重脑损伤方法。
DOI：
10.1097/wco.0000000000000875
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发表时间：
2020-12
影响因子：
4.8
通讯作者：
Claassen J
中科院分区：
文献类型：
--
作者：
Fidali BC;Stevens RD;Claassen J
严重脑损伤后的恢复是可变的，在个体患者水平上准确预测具有挑战性。这篇综述强调了临床预测的新发展，特别关注意识的预测和对数据科学方法的日益依赖。最近的研究已经利用血清生物标志物，定量脑电图，磁共振成像生理时间序列来建立恢复预测模型。高分辨率数据的分析和不同模态特征的整合可以通过有效的计算技术来实现。神经生理学和神经影像学的进展，结合计算方法，代表了一种新的范式预测意识和功能恢复后，严重脑损伤。需要进行研究以产生可靠的患者水平预测，从而对临床决策产生有意义的影响。
Recovery after severe brain injury is variable and challenging to accurately predict at the individual patient level. This review highlights new developments in clinical prognostication with a special focus on the prediction of consciousness and increasing reliance on methods from data science. Recent research has leveraged serum biomarkers, quantitative electroencephalography, magnetic resonance imaging physiological time-series to build models for recovery prediction. The analysis of high-resolution data and the integration of features from different modalities can be approached with efficient computational techniques. Advances in neurophysiology and neuroimaging, in combination with computational methods, represent a novel paradigm for prediction of consciousness and functional recovery after severe brain injury. Research is needed to produce reliable, patient-level predictions that could meaningfully impact clinical decision making.