Brain functional connectivity during the first day of coma reflects long-term outcome

被引:14
作者
Kustermann, Thomas [1 ,2 ]
Nguissi, Nathalie Ata Nguepnjo [1 ,2 ]
Pfeiffer, Christian [3 ]
Haenggi, Matthias [4 ]
Kurmann, Rebekka [5 ]
Zubler, Frederic [5 ]
Oddo, Mauro [2 ,6 ]
Rossetti, Andrea O. [2 ,7 ]
De Lucia, Marzia [1 ,2 ]
机构
[1] Univ Hosp CHUV, Lab Rech Neuroimagerie LREN, Lausanne, Switzerland
[2] Univ Lausanne, Lausanne, Switzerland
[3] Univ Zurich, Dept Psychol, Zurich, Switzerland
[4] Univ Bern, Bern Univ Hosp, Dept Intens Care Med, Inselspital, Bern, Switzerland
[5] Univ Bern, Bern Univ Hosp, Dept Neurol, Inselspital, Bern, Switzerland
[6] Univ Hosp CHUV, Dept Intens Care Med, Lausanne, Switzerland
[7] Univ Hosp CHUV, Dept Neurol, Lausanne, Switzerland
关键词
Cardiac arrest; Coma; EEG; Resting state; Functional connectivity; DEFAULT MODE; COMMUNITY STRUCTURE; EEG; CONSCIOUSNESS; NETWORKS; PROGNOSTICATION; DYNAMICS; SCALE;
D O I
10.1016/j.nicl.2020.102295
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Objective: In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. Methods: We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the 'debiased weighted phase lag index' over epochs of five seconds duration. We evaluated the network's topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients' outcomes by splitting the patient sample in training and test datasets. Results: Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. Interpretation: Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients' outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.
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页数:10
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