EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

Dynamic functional connectivity of the EEG in relation to outcome of postanoxic coma

ObjectiveEarly EEG contains reliable information for outcome prediction of comatose patients after cardiac arrest. We introduce dynamic functional connectivity measures and estimate additional predictive values.MethodsWe performed a prospective multicenter cohort study on continuous EEG for outcome prediction of comatose patients after cardiac arrest. We calculated Link Rates (LR) and Link Durations (LD) in the α, δ, and θ band, based on similarity of instantaneous frequencies in five-minute EEG epochs, hourly, during 3 days after cardiac arrest. We studied associations of LR and LD with good (Cerebral Performance Category (CPC) 1–2) or poor outcome (CPC 3–5) with univariate analyses. With random forest classification, we established EEG-based predictive models. We used receiver operating characteristics to estimate additional values of dynamic connectivity measures for outcome prediction.ResultsOf 683 patients, 369 (54%) had poor outcome. Patients with poor outcome had significantly lower LR and longer LD, with largest differences 12 h after cardiac arrest (LR_θ 1.87 vs. 1.95 Hz and LD_α 91 vs. 82 ms). Adding these measures to a model with classical EEG features increased sensitivity for reliable prediction of poor outcome from 34% to 38% at 12 h after cardiac arrest.ConclusionPoor outcome is associated with lower dynamics of connectivity after cardiac arrest.SignificanceDynamic functional connectivity analysis may improve EEG based outcome prediction.     

Therapeutic effectiveness of a single exercise session combined with Walk Aide functional electrical stimulation in post-stroke patients:a crossover design study

A growing body of evidence has suggested that the imbalance of epigenetic markers and oxidative stress appears to be involved in the pathophysiology and progression of stroke. Thus, strategies that modulate these biomarkers might be considered targets for neuroprotection and novel therapeutic opportunities for these patients. Physical exercise has been reported to induce changes in these epigenetic markers and improve clinical outcomes in different populations. However, little is reported on this in post-stroke patients. The purpose of this study was to investigate the effect of a single exercise session with Walk Aide functional electrical stimulation(FES) on cognitive performance, clinical functional parameters, oxidative stress and epigenetic modulation in post-stroke individuals. In this crossover design study, 12 post-stroke individuals aged 54–72 years of either sexes were included and subjected to a single session of exercise(45 minutes) without Walk Aide functional electrical stimulation(EXE alone group), followed by another single session of exercise(45 minutes) with Walk Aide functional electrical stimulation(EXE + FES group). The clinical functional outcome measures, cognitive performance and blood collections for biomarker measurements were assessed pre-and post-intervention. After intervention, higher Berg Balance Scale scores were obtained in the EXE + FES group than in the EXE alone group. There was no significant difference in the Timed Up and Go test results post-intervention between EXE alone and EXE + FES groups. After intervention, a better cognitive performance was found in both groups compared with before the intervention. After intervention, the Timed Up and Go test scores were higher in the EXE + FES group than in the EXE alone group. In addition, the intervention induced lower levels of lipid peroxidation. After intervention, carbonyl level was lower, superoxide dismutase activity and superoxide dismutase/catalase activity ratio were higher in the EXE + FES group, compared with the EXE group alone. In each group, both histone deacetylase(HDAC2) and histone acetyltransferase activities were increased after intervention compared with before the intervention. These findings suggest that a single exercise session with Walk Aide FES is more effective on balance ability and cognitive performance compared with conventional exercise alone in post-stroke patients. This is likely to be related to the regulation of oxidative stress markers. The present study was approved by the Research Ethics Committee of the Methodist University Center-IPA(approval No. 2.423.376) on December 7, 2017 and registered in the Brazilian Registry of Clinical Trials—Re BEC(RBR-9 phj2 q) on February 11, 2019.     

Differentiating ictal/subclinical spikes and waves in childhood absence epilepsy by spectral and network analyses: A pilot study

ObjectiveChildhood absence epilepsy (CAE) is a disease with distinct seizure semiology and electroencephalographic (EEG) features. Differentiating ictal and subclinical generalized spikes and waves discharges (GSWDs) in the EEG is challenging, since they appear to be identical upon visual inspection. Here, spectral and functional connectivity (FC) analyses were applied to routine EEG data of CAE patients, to differentiate ictal and subclinical GSWDs.MethodsTwelve CAE patients with both ictal and subclinical GSWDs were retrospectively selected for this study. The selected EEG epochs were subjected to frequency analysis in the range of 1–30 Hz. Further, FC analysis based on the imaginary part of coherency was used to determine sensor level networks.ResultsDelta, alpha and beta band frequencies during ictal GSWDs showed significantly higher power compared to subclinical GSWDs. FC showed significant network differences for all frequency bands, demonstrating weaker connectivity between channels during ictal GSWDs.ConclusionUsing spectral and FC analyses significant differences between ictal and subclinical GSWDs in CAE patients were detected, suggesting that these features could be used for machine learning classification purposes to improve EEG monitoring.SignificanceIdentifying differences between ictal and subclinical GSWDs using routine EEG, may improve understanding of this syndrome and the management of patients with CAE.     

集束化护理干预对前列腺癌术后盆底功能锻炼依从性及尿失禁的影响

目的探讨集束化护理干预对前列腺癌患者术后盆底功能锻炼依从性及尿失禁的影响。方法选取2020年1月至2020年12月间上海中医药大学附属曙光医院收治的50例前列腺癌根治术患者作为研究对象。其中,围手术期采用常规护理的20例患者纳入对照组。围手术期采用集束化护理的30例患者纳入观察组。比较两组术后盆底功能锻炼的依从性及尿失禁情况。结果观察组拔管后1个月、3个月盆底功能锻炼的依从性分别为76.7%和70.0%,均高于对照组的45.0%和35.0%,差异均有统计学意义(均P <0.05)。观察组拔管后1个月、3个月的尿失禁发生率分别为10.0%和6.7%,低于对照组的40.0%和35.0%,差异均有统计学意义(均P <0.05)。观察组尿失禁持续时间为(3.83±0.95)天,短于对照组的(5.38±1.97)天,观察组拔管后3个月尿失禁问卷评分低于对照组,差异均有统计学意义(均P <0.05)。结论集束化护理干预能够提高前列腺癌患者术后盆底功能锻炼的依从性,预防术后尿失禁的发生。