Theta-Alpha Variability on EEG Is Associated With Acute Brain Injury in Children and Young Adults With Liver Failure.

IF 2.3 Q3 CLINICAL NEUROLOGY Neurology. Clinical practice Pub Date : 2025-02-01 Epub Date: 2024-10-08 DOI:10.1212/CPJ.0000000000200389
Jacqueline Barnes, Allan Fong, Sarika Bharil, Nathan M Kattapuram, Taymour Hashemzadeh, Earn Chun Christabel Lee, Alexander Andrews
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Abstract

Background and objectives: Patients with liver failure experience long hospitalizations and acute neurologic complications. Encephalopathy limits the bedside examination, rendering presenting signs of acute brain injury less specific. Seizures are common. Brain MRI is the gold standard for detecting acute brain injury, but intensive medical needs may preclude immediate transfer for imaging. EEG is a bedside test applied in cases of seizure or encephalopathy. We hypothesized that EEG variables can predict MRI signs of acute brain injury in children hospitalized with liver failure.

Methods: In this retrospective cohort analysis, records were collected for patients admitted to a MedStar hospital between 2014 and 2022 with ICD-9/10 codes related to liver failure, who underwent brain MRI and EEG testing during the same admission. Exclusion criteria included age older than 24 years and >7 days elapsing between EEG and MRI testing. Clinical data of interest from chart review, reinterpreted MRI scans, reinterpreted EEG tracings, and quantitative EEG variables were compiled into a database. Quantitative EEG variables were processed using MNE-Python.

Results: Of 746 records screened, 52 patients met inclusion criteria comprising 63 EEG-MRI pairs. Univariate analysis of all quantitative EEG variables of interest showed depressed theta-alpha variability (TAV) when paired MRI involved abnormal restricted diffusivity in cortical or deep gray matter structures (TAV 0.705, SD 0.310; p < 0.001) compared with MRI with no abnormal restricted diffusivity (TAV 0.895, SD 0.095). Multilinear regression analysis including potential confounders demonstrated independent association of depressed TAV with this MRI finding, with an odds ratio of 4.0317 (95% CI 1.3868-11.7165; AUROC 0.83).

Discussion: Depressed TAV on EEG is associated with increased odds of abnormal restricted diffusivity in gray matter on brain MRI in children and young adults hospitalized with liver failure. This MRI finding is seen in scenarios where changes to medical management are time-sensitive (i.e., acute stroke and PRES) or where prognostic discussion may be influenced by MRI findings (hypoxic-ischemic injury). TAV thus has a potential role as an automated, bedside decision support tool for clinicians deciding on the urgency of brain MRI in critically ill patients.

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脑电图上的θ-α变异与肝衰竭儿童和青少年的急性脑损伤有关。
背景和目的:肝功能衰竭患者住院时间长,并伴有急性神经系统并发症。脑病限制了床边检查,使急性脑损伤的体征缺乏特异性。癫痫发作很常见。脑磁共振成像是检测急性脑损伤的金标准,但由于医疗需求旺盛,可能无法立即转院进行成像检查。脑电图是一种床旁检测方法,适用于癫痫发作或脑病病例。我们假设脑电图变量可以预测肝衰竭住院患儿急性脑损伤的 MRI 征象:在这项回顾性队列分析中,我们收集了 2014 年至 2022 年期间在 MedStar 医院住院、ICD-9/10 编码与肝衰竭相关的患者记录,这些患者在同一入院期间接受了脑 MRI 和脑电图检测。排除标准包括年龄超过 24 岁,脑电图和 MRI 测试之间间隔超过 7 天。通过病历审查、重新解读的磁共振成像扫描、重新解读的脑电图描记图和定量脑电图变量获得的相关临床数据被编入数据库。使用 MNE-Python 处理定量脑电图变量:在筛选出的 746 份记录中,52 名患者符合纳入标准,包括 63 对 EEG-MRI 对。对所有感兴趣的定量脑电图变量进行的单变量分析表明,与无异常局限性弥散的 MRI(TAV 0.895,SD 0.095)相比,当配对 MRI 涉及皮质或深部灰质结构的异常局限性弥散时,θ-α变异性(TAV)降低(TAV 0.705,SD 0.310;P <0.001)。包括潜在混杂因素在内的多线性回归分析表明,TAV低迷与这一核磁共振成像结果存在独立关联,几率比为4.0317(95% CI 1.3868-11.7165;AUROC 0.83):讨论:在因肝衰竭住院的儿童和年轻成人中,脑电图上的TAV抑制与脑MRI上灰质异常局限性弥散的几率增加有关。这种磁共振成像结果可见于改变医疗管理具有时间敏感性的情况(如急性中风和PRES),或预后讨论可能受磁共振成像结果影响的情况(缺氧缺血性损伤)。因此,TAV 有可能成为临床医生决定危重病人是否需要紧急进行脑部 MRI 检查的自动化床旁决策支持工具。
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来源期刊
Neurology. Clinical practice
Neurology. Clinical practice CLINICAL NEUROLOGY-
CiteScore
4.00
自引率
0.00%
发文量
77
期刊介绍: Neurology® Genetics is an online open access journal publishing peer-reviewed reports in the field of neurogenetics. The journal publishes original articles in all areas of neurogenetics including rare and common genetic variations, genotype-phenotype correlations, outlier phenotypes as a result of mutations in known disease genes, and genetic variations with a putative link to diseases. Articles include studies reporting on genetic disease risk, pharmacogenomics, and results of gene-based clinical trials (viral, ASO, etc.). Genetically engineered model systems are not a primary focus of Neurology® Genetics, but studies using model systems for treatment trials, including well-powered studies reporting negative results, are welcome.
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