Kurek Krzysztof, Swieczkowski Damian, Pruc Michal, Tomaszewska Monika, Cubala Wieslaw Jerzy, Szarpak Lukasz
Department of Clinical Research and Development, LUXMED Group, 02-676 Warsaw, Poland.
Department of Toxicology, Faculty of Pharmacy, Medical University of Gdansk, 80-210 Gdansk, Poland.
J Clin Med. 2023 Dec 13;12(24):7655. doi: 10.3390/jcm12247655.
The prediction of outcomes following cardiac arrest continues to provide significant difficulties. A preferred strategy involves adopting a multimodal approach, which encompasses the careful evaluation of the biomarker neuron-specific enolase (NSE). This systematic review and meta-analysis aimed to gather and summarize new and existing evidence on the prediction effect of neuron-specific enolase for survival to hospital discharge among adult patients with cardiac arrest. We searched PubMed Central, Scopus, EMBASE databases, and the Cochrane Library without language restrictions from their inceptions until 30 October 2023 and checked the reference lists of the included studies. Pooled results were reported as standardized mean differences (SMDs) and were presented with corresponding 95% confidence intervals (CIs). The primary outcome was survival to hospital discharge (SHD). Eighty-six articles with 10,845 participants were included. NSE showed a notable degree of specificity in its ability to predict mortality as well as neurological status among individuals who experienced cardiac arrest ( < 0.05). This study demonstrates the ability to predict fatality rates and neurological outcomes, both during the time of admission and at various time intervals after cardiac arrest. The use of NSE in a multimodal neuroprognostication algorithm has promise in improving the accuracy of prognoses for persons who have undergone cardiac arrest.
心脏骤停后结局的预测仍然存在重大困难。一种优选策略是采用多模式方法，其中包括对生物标志物神经元特异性烯醇化酶（NSE）进行仔细评估。本系统评价和荟萃分析旨在收集和总结关于神经元特异性烯醇化酶对成年心脏骤停患者出院存活预测效果的新证据和现有证据。我们检索了PubMed Central、Scopus、EMBASE数据库以及Cochrane图书馆，检索时间从各数据库建库至2023年10月30日，无语言限制，并检查了纳入研究的参考文献列表。汇总结果以标准化均数差值（SMD）报告，并呈现相应的95%置信区间（CI）。主要结局是出院存活（SHD）。纳入了86篇文章，共10845名参与者。NSE在预测心脏骤停患者的死亡率以及神经状态方面显示出显著的特异性（<0.05）。本研究证明了在心脏骤停后的入院时以及不同时间间隔预测死亡率和神经结局的能力。在多模式神经预后评估算法中使用NSE有望提高心脏骤停患者预后的准确性。
