Bae Sung Jin, Choi Yoon Hee, Ryu Seok Jin, Lee Dong Hun, Choi Yunhyung, Chun Minsoo, Kim Youngwoo, Lee Dong Hoon
Department of Emergency Medicine, Chung-Ang University Gwangmyeong Hospital, College of Medicine, Seoul, Chung-Ang University, 110, Deokan-ro, Gwangmyeong-si, Gyeonggi-do, Republic of Korea.
Ewha Womans University Mokdong Hospital, Department of Emergency Medicine, College of Medicine, Ewha Womans University, 1071, Anyangcheon-ro, Yangcheon-gu, Seoul, Republic of Korea.
Am J Emerg Med. 2025 Jan;87:123-129. doi: 10.1016/j.ajem.2024.11.003. Epub 2024 Nov 6.
Post-cardiac arrest care advancements have improved resuscitation outcomes, but many survivors still face severe neurological deficits or death from brain injury. Herein, we propose a consistent prognosis prediction approach using magnetic resonance imaging (MRI) to analyze anatomical regions represented by the gray and white matter, and subsequently apply it on computed tomography (CT) to calculate the gray-white matter ratio (GWR). We compared this novel method with traditional measures to validate its ability to predict the prognosis of patients resuscitated after cardiac arrest.
Conducted retrospectively at two South Korean tertiary university hospitals from January 2018 to December 2022, the study included adult cardiac arrest survivors treated with therapeutic target temperature management. Patients underwent brain CT within 2 h and brain MRI within 3 days of return of spontaneous circulation. The outcome was the neurological status at discharge. Statistical analyses included receiver operating characteristic curve analysis and determining cutoff values to predict poor neurological outcomes.
Overall, 51 of the 421 adult comatose cardiac arrest survivors examined met the inclusion criteria. Among these, 33 and 18 exhibited good and poor neurological outcomes, respectively. Demographic and cardiac arrest characteristics were compared between the two groups, revealing significant differences. Analyses of gray and white matter attenuation and GWR measurements highlighted significant differences between the good and poor outcome groups.
Our study introduces a novel method for measuring GWR using MRI-based brain CT, demonstrating superior prognostic accuracy in predicting neurological outcomes in patients with post-cardiac arrest syndrome compared to traditional methods.
心脏骤停后护理的进展改善了复苏结果,但许多幸存者仍面临严重的神经功能缺损或因脑损伤死亡。在此,我们提出一种一致的预后预测方法,使用磁共振成像(MRI)分析灰质和白质所代表的解剖区域,随后将其应用于计算机断层扫描(CT)以计算灰质-白质比率(GWR)。我们将这种新方法与传统测量方法进行比较,以验证其预测心脏骤停后复苏患者预后的能力。
该研究于2018年1月至2022年12月在韩国两家三级大学医院进行回顾性研究,纳入接受治疗性体温管理的成年心脏骤停幸存者。患者在自主循环恢复后2小时内接受脑部CT检查,并在3天内接受脑部MRI检查。结局指标为出院时的神经功能状态。统计分析包括受试者工作特征曲线分析和确定预测不良神经结局的临界值。
总体而言,421名接受检查的成年昏迷心脏骤停幸存者中有51人符合纳入标准。其中,33人神经功能结局良好,18人结局不佳。比较了两组的人口统计学和心脏骤停特征,发现存在显著差异。灰质和白质衰减分析以及GWR测量结果突出显示了良好和不良结局组之间的显著差异。
我们的研究引入了一种基于MRI的脑部CT测量GWR的新方法,与传统方法相比,在预测心脏骤停后综合征患者的神经功能结局方面显示出更高的预后准确性。