Despite advances in resuscitation practice, patient survival following cardiac arrest remains poor. The utilization of MRI in neurological outcome prognostication post-cardiac arrest is growing and various classifications has been proposed; however a consensus has yet to be established. MRI, though valuable, is resource-intensive, time-consuming, costly, and not universally available. This study aims to validate a MRI lesion pattern score in a cohort of out of hospital cardiac arrest patients at a tertiary referral hospital in Switzerland. This cohort study spanned twelve months from February 2021 to January 2022, encompassing all unconscious patients aged ≥ 18 years who experienced out-of-hospital cardiac arrest of any cause and were admitted to the intensive care unit (ICU) at Inselspital, University Hospital Bern, Switzerland. We included patients who underwent the neuroprognostication process, assessing the performance and validation of a MRI scoring system. Over the twelve-month period, 137 patients were admitted to the ICU, with 52 entering the neuroprognostication process and 47 undergoing MRI analysis. Among the 35 MRIs indicating severe hypoxic brain injury, 33 patients (94%) experienced an unfavourable outcome (UO), while ten (83%) of the twelve patients with no or minimal MRI lesions had a favourable outcome. This yielded a sensitivity of 0.94 and specificity of 0.83 for predicting UO with the proposed MRI scoring system. The positive and negative likelihood ratios were 5.53 and 0.07, respectively, resulting in an accuracy of 91.49%. We demonstrated the effectiveness of the MLP scoring scheme in predicting neurological outcome in patients following cardiac arrest. However, to ensure a comprehensive neuroprognostication, MRI results need to be combined with other assessments. While neuroimaging is a promising objective tool for neuroprognostication, given the absence of sedation-related confounders—compared to electroencephalogram (EEG) and clinical examination—the current lack of a validated scoring system necessitates further studies. Incorporating standardized MRI techniques and grading systems is crucial for advancing the reliability of neuroimaging for neuroprognostication. Trial Registration: Registry of all Projects in Switzerland (RAPS) 2020-01761.

中文翻译：

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MRI 病变模式评分在预测院外心脏骤停后神经系统结果中的表现：回顾性队列分析


尽管复苏实践取得了进步，但心脏骤停后患者的生存率仍然很低。 MRI 在心脏骤停后神经系统结果预测中的应用不断增长，并提出了各种分类；但尚未达成共识。 MRI 虽然很有价值，但它是资源密集型、耗时、昂贵的，而且并不普遍可用。本研究旨在验证瑞士一家三级转诊医院的一组院外心脏骤停患者的 MRI 病变模式评分。这项队列研究从 2021 年 2 月到 2022 年 1 月，历时 12 个月，涵盖所有年龄≥ 18 岁、经历过任何原因的院外心脏骤停并入住伯尔尼大学医院 Inselspital 重症监护室 (ICU) 的所有昏迷患者， 瑞士。我们纳入了接受神经预测过程的患者，评估 MRI 评分系统的性能和验证。在 12 个月期间，137 名患者入住 ICU，其中 52 名患者进入神经预测流程，47 名患者接受 MRI 分析。在 35 例显示严重缺氧性脑损伤的 MRI 中，33 名患者 (94%) 经历了不良结果 (UO)，而 12 名没有或仅有极少 MRI 损伤的患者中有 10 名 (83%) 具有良好结果。使用所提出的 MRI 评分系统预测 UO 的敏感性为 0.94，特异性为 0.83。阳性和阴性似然比分别为 5.53 和 0.07，准确率为 91.49%。我们证明了 MLP 评分方案在预测心脏骤停后患者神经系统结果方面的有效性。 然而，为了确保全面的神经预测，MRI 结果需要与其他评估相结合。虽然神经影像学是一种很有前景的神经预测客观工具，但与脑电图 (EEG) 和临床检查相比，由于不存在与镇静相关的混杂因素，因此目前缺乏经过验证的评分系统，因此需要进一步研究。结合标准化 MRI 技术和分级系统对于提高神经影像学神经预测的可靠性至关重要。试用注册：瑞士所有项目注册 (RAPS) 2020-01761。