From the The Department of Intensive Care Medicine, Centre Hospitalier Universitaire Vaudois, University Hospital and Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Chest. 2014 Nov;146(5):1375-1386. doi: 10.1378/chest.14-0523.
Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.
心脏骤停后昏迷（CA）是 ICU 入院的重要原因。在过去的十年中，CA 后昏迷患者的预后有了显著改善，这主要得益于积极的复苏后护理和使用治疗性目标温度管理（TTM）。用于维持控制冷却的 TTM 和镇静剂可能会延迟神经反射并降低临床检查的准确性。在 ICU 早期阶段，患者的良好恢复（仅基于神经检查）可能经常与最终预后不良的患者难以区分。因此，CA 后昏迷的预后评估已经发展为一种多模态方法，将神经检查与脑电图和诱发电位相结合。血液生物标志物（例如神经元特异性烯醇化酶[NSE]和可溶性 100-β 蛋白）是昏迷预后预测的有用补充；然而，不同商业实验室检测的结果存在差异，不建议应用单一截止值（例如，NSE ＞33μg/L）来预测预后不良。神经影像学，主要是弥散 MRI，作为预后预测的一种很有前途的工具正在出现，但在广泛应用之前，需要进一步研究其确切作用。这种多模态方法可能会降低预后不良的假阳性率，从而为昏迷的 CA 幸存者提供最佳预后。本综述的目的是总结目前用于预后预测的研究和主要工具，并描述 CA 后昏迷的多模态预后的实用方法，重点介绍神经监测工具。我们还提出了在 CA 后昏迷的 ICU 早期阶段优化使用这些多模态工具的算法。
