Marlous M. L. H. Verhulst, Hanneke M. Keijzer, Pauline C. W. van Gils, Caroline M. van Heugten, Frederick J. A. Meijer, Bart A. R. Tonino, Judith L. Bonnes, Thijs S. R. Delnoij, Jeannette Hofmeijer, Rick C. Helmich
{"title":"静息态网络的功能连接与心脏骤停幸存者的短期整体认知功能有关。","authors":"Marlous M. L. H. Verhulst, Hanneke M. Keijzer, Pauline C. W. van Gils, Caroline M. van Heugten, Frederick J. A. Meijer, Bart A. R. Tonino, Judith L. Bonnes, Thijs S. R. Delnoij, Jeannette Hofmeijer, Rick C. Helmich","doi":"10.1002/hbm.26769","DOIUrl":null,"url":null,"abstract":"<p>Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCA<sub>hospital-3M</sub> = 2.89, <i>p</i> < 0.01), but not between 3 and 12 months (ΔMoCA<sub>3M–12M</sub> = 0.38, <i>p</i> = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (<i>β</i><sub>DMN</sub> = 0.85, <i>p</i> = 0.03; <i>β</i><sub>SN</sub> = 1.48, <i>p</i> < 0.01; <i>β</i><sub>DAN</sub> = 0.96, <i>p</i> = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long-term memory, attention, or executive functioning. Resting-state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short-term global, but not long-term global or domain-specific cognitive performance of survivors. 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Helmich\",\"doi\":\"10.1002/hbm.26769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCA<sub>hospital-3M</sub> = 2.89, <i>p</i> < 0.01), but not between 3 and 12 months (ΔMoCA<sub>3M–12M</sub> = 0.38, <i>p</i> = 0.52). 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引用次数: 0
摘要
心脏骤停幸存者普遍存在长期认知障碍。建议对高危患者进行筛查。脑功能磁共振成像（fMRI）有可能有助于预测认知结果。在这项研究中，我们调查了静息态网络的早期变化对预测心脏骤停幸存者短期和长期认知功能的可能价值。我们对荷兰三家医院的心脏骤停幸存者进行了一项前瞻性多中心队列研究。我们在心脏骤停后一个月内采集了静息态 fMRI 扫描。我们主要研究了默认模式网络（DMN）和显著性网络（SN）的功能连接，此外还探讨了其他七个网络的功能连接。认知结果在入院时、3个月和12个月时使用蒙特利尔认知评估（MoCA）进行测量，在12个月时使用神经心理学检查（NPE）进行测量。我们测试了混合效应模型，以评估网络内的连接性对预测三个时间点的整体认知结果以及记忆、注意力和执行功能领域的长期认知结果的价值。我们共纳入了 80 名患者（年龄为 60 ± 11 岁，72 人（90%）为男性）。入院至3个月期间，MoCA得分明显增加（ΔMoCAhospital-3M = 2.89, p 3M-12M = 0.38, p = 0.52）。入院期间，DMN、SN和背侧注意网络（DAN）内的连通性与整体认知功能呈正相关（βDMN = 0.85，p = 0.03；βSN = 1.48，p DAN = 0.96，p = 0.01），但在3个月和12个月时则不相关。网络连通性也与长期记忆、注意力或执行功能无关。在心脏骤停后的第一个月测量的DMN、SN和DAN的静息态功能连接与幸存者的短期整体认知能力有关，但与长期整体认知能力或特定领域认知能力无关。这些结果并不支持这些RSN内的功能连接对预测心脏骤停后长期认知表现的价值。
Functional connectivity in resting-state networks relates to short-term global cognitive functioning in cardiac arrest survivors
Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCAhospital-3M = 2.89, p < 0.01), but not between 3 and 12 months (ΔMoCA3M–12M = 0.38, p = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (βDMN = 0.85, p = 0.03; βSN = 1.48, p < 0.01; βDAN = 0.96, p = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long-term memory, attention, or executive functioning. Resting-state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short-term global, but not long-term global or domain-specific cognitive performance of survivors. These results do not support the value of functional connectivity within these RSNs for prediction of long-term cognitive performance after cardiac arrest.
期刊介绍：
Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged.
Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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