OBJECTIVE Neurological outcome prediction is crucial early after cardiac arrest. Serum biomarkers released from brain cells after hypoxic-ischemic injury may aid in outcome prediction. The only serum biomarker presently recommended in the European Resuscitation Council prognostication guidelines is neuron-specific enolase (NSE), but NSE has limitations. In this study, we therefore analysed the outcome predictive accuracy of the serum biomarkers glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) in patients after cardiac arrest. METHODS Serum GFAP and UCH-L1 were collected at 24, 48 and 72hours after cardiac arrest. The primary outcome was neurological function at 6-month follow-up assessed by the cerebral performance category scale (CPC), dichotomized into good (CPC1-2) and poor (CPC3-5). Prognostic accuracies were tested with receiver-operating characteristics by calculating the area under the receiver-operating curve (AUROC) and compared to the AUROC of NSE. RESULTS 717 patients were included in the study. GFAP and UCH-L1 discriminated between good and poor neurological outcome at all time-points when used alone (AUROC GFAP 0.88-0.89; UCH-L1 0.85-0.87) or in combination (AUROC 0.90-0.91). The combined model was superior to GFAP and UCH-L1 separately and NSE (AUROC 0.75-0.85) at all time-points. At specificities ≥95%, the combined model predicted poor outcome with a higher sensitivity than NSE at 24hours and with similar sensitivities at 48 and 72hours. CONCLUSION GFAP and UCH-L1 predicted poor neurological outcome with high accuracy. Their combination may be of special interest for early prognostication after cardiac arrest where it performed significantly better than the currently recommended biomarker NSE.

中文翻译：

---

血清 GFAP 和 UCH-L1 用于预测昏迷性心脏骤停患者的神经系统结果

目的 神经学结果预测在心脏骤停后的早期至关重要。缺氧缺血性损伤后脑细胞释放的血清生物标志物可能有助于结果预测。目前欧洲复苏委员会预后指南中推荐的唯一血清生物标志物是神经元特异性烯醇化酶 (NSE)，但 NSE 有局限性。因此，在本研究中，我们分析了心脏骤停后患者血清生物标志物胶质纤维酸性蛋白 (GFAP) 和泛素 C-末端水解酶-L1 (UCH-L1) 的结果预测准确性。方法在心脏骤停后24、48和72小时收集血清GFAP和UCH-L1。主要结果是通过脑功能分类量表 (CPC) 评估的 6 个月随访时的神经功能，分为好 (CPC1-2) 和差 (CPC3-5)。通过计算受试者工作曲线下面积 (AUROC) 并与 NSE 的 AUROC 进行比较，以受试者工作特征测试预后准确性。结果 717 名患者被纳入研究。当单独使用 (AUROC GFAP 0.88-0.89; UCH-L1 0.85-0.87) 或联合使用 (AUROC 0.90-0.91) 时，GFAP 和 UCH-L1 在所有时间点区分良好和不良的神经系统结果。组合模型在所有时间点均优于单独的 GFAP 和 UCH-L1 以及 NSE (AUROC 0.75-0.85)。在特异性 ≥95% 时，组合模型预测较差的结果，在 24 小时时的敏感性高于 NSE，在 48 小时和 72 小时时的敏感性相似。结论 GFAP 和 UCH-L1 以高精度预测神经系统预后不良。