Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest.
Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest.
复制标题
DOI：
10.1007/s00134-020-06080-9
复制
发表时间：
2020-10
影响因子：
38.9
通讯作者：
Cronberg T
中科院分区：
文献类型：
--
作者：
Moseby-Knappe M;Westhall E;Backman S;Mattsson-Carlgren N;Dragancea I;Lybeck A;Friberg H;Stammet P;Lilja G;Horn J;Kjaergaard J;Rylander C;Hassager C;Ullén S;Nielsen N;Cronberg T
旨在评估欧洲复苏理事会（ERC）和欧洲重症监护医学会（ESICM）推荐的心脏骤停后神经系统起搏4步算法的性能。对目标体温管理（TTM）试验的数据进行回顾性描述性分析。针对算法的每个步骤，利用临床神经学检查、神经放射学（CT或MRI）、神经生理学（EEG和SSEP）和血清神经元特异性烯醇化酶的结果，研究预测和实际神经学结局之间的关联。包括在停搏后第4天（72-96 h）使用格拉斯哥昏迷量表运动评分（GCS-M）检查的患者和可用的6个月结局。不良结局定义为脑功能分级3-5级。在同一队列中探索了ERC/ESICM算法的变化。ERC/ESICM算法在585例患者的队列中以38.7%的灵敏度（95% CI 33.1-44.7）和100%的特异性（95% CI 98.8-100）识别了不良结局患者。血清神经元特异性烯醇化酶的替代截止值、替代EEG分类和GCS-M的变化对灵敏度的影响较小，而不会引起假阳性预测。在不考虑GCS-M评分的情况下，当对患者进行分类时，达到了最高的总体灵敏度，42.5%（95%CI 36.7-48.5），特异性为100%（95%CI 98.8-100）。ERC/ESICM算法及其在本研究中研究的所有探索性多模态变异预测不良结局，无假阳性预测，灵敏度为34.6- 42.5%。我们的研究结果应该进行前瞻性验证，最好是在患者中撤回维持生命的治疗是罕见的，以排除任何混杂的自我实现的预言。本文的在线版本（10.1007/s 00134 -020-06080-9）包含补充材料，可供授权用户使用。
To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). Retrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72–96 h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3–5. Variations of the ERC/ESICM algorithm were explored within the same cohort. The ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1–44.7) and 100% specificity (95% CI 98.8–100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7–48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8–100) remaining. The ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6–42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies. The online version of this article (10.1007/s00134-020-06080-9) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
6.5
作者：
Dragancea, Irina;Horn, Janneke;Cronberg, Tobias
通讯作者：
Cronberg, Tobias
影响因子：
6.5
作者：
Moseby-Knappe, Marion;Pellis, Tommaso;Cronberg, Tobias
通讯作者：
Cronberg, Tobias
影响因子：
158.5
作者：
Nielsen, Niklas;Wettersley, Jorn;Friberg, Hans
通讯作者：
Friberg, Hans
影响因子：
38.9
作者：
Oddo M;Sandroni C;Citerio G;Miroz JP;Horn J;Rundgren M;Cariou A;Payen JF;Storm C;Stammet P;Taccone FS
通讯作者：
Taccone FS
影响因子：
6.5
作者：
Kim, Ji Hoon;Kim, Min Joung;Chung, Sung Phil
通讯作者：
Chung, Sung Phil