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Predictive power of abnormal electroencephalogram for post-cerebral infarction depression.

ABSTRACT: Electroencephalography is a sensitive indicator for measuring brain condition, and can reflect early changes in brain function and severity of cerebral ischemia. However, it is not yet known whether electroencephalography can predict development of post-cerebral infarction depression. A total of 321 patients with ischemic stroke underwent electroencephalography and Hamilton Depression Rating Scale assessment to analyze the relationship between electroencephalography and post-cerebral infarction depression. Our results show that electroencephalograms of ischemic stroke patients with depression exhibit low-amplitude alpha activity and slow theta activity. In contrast, electroencephalograms of ischemic stroke patients without depression show fast beta activity and slow delta activity. These findings confirm that low-amplitude alpha activity and slow theta activity can be considered as independent predictors for post-cerebral infarction depression.

SUBMITTER: Zheng YP

PROVIDER: S-EPMC5879903 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Predictive power of abnormal electroencephalogram for post-cerebral infarction depression.

Zheng Yan-Ping YP Wang Fu-Xi FX Zhao De-Qiang DQ Wang Yan-Qing YQ Zhao Zi-Wei ZW Wang Zhan-Wen ZW Liu Jun J Wang Jun J Luan Ping P

Neural regeneration research 20180201 2

Electroencephalography is a sensitive indicator for measuring brain condition, and can reflect early changes in brain function and severity of cerebral ischemia. However, it is not yet known whether electroencephalography can predict development of post-cerebral infarction depression. A total of 321 patients with ischemic stroke underwent electroencephalography and Hamilton Depression Rating Scale assessment to analyze the relationship between electroencephalography and post-cerebral infarction ...[more]

PMID: 29557381

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Project description:AimTo examine the contribution of treatment resistant depression (TRD) to mortality in depressed post-myocardial infarction (MI) patients independent of biological and social predictors.MethodsThis secondary analysis study utilizes the Enhancing Recovery in Coronary Heart Disease (ENRICHD) clinical trial data. From 1834 depressed patients in the ENRICHD study, there were 770 depressed post-MI patients who were treated for depression. In this study, TRD is defined as having a less than 50% reduction in Hamilton Depression (HAM-D) score from baseline and a HAM-D score of greater than 10 in 6 mo after depression treatment began. Cox regression analysis was used to examine the independent contributions of TRD to mortality after controlling for the biological and social predictors.ResultsTRD occurred in 13.4% (n = 103) of the 770 patients treated for depression. Patients with TRD were significantly younger in age (P = 0.04) (mean = 57.0 years, SD = 11.7) than those without TRD (mean = 59.2 years, SD = 12.0). There was a significantly higher percentage of females with TRD (57.3%) compared to females without TRD (47.4%) [χ(2) (1) = 4.65, P = 0.031]. There were significantly more current smokers with TRD (44.7%) than without TRD (33.0%) [χ(2) (1) = 7.34, P = 0.007]. There were no significant differences in diabetes (P = 0.120), history of heart failure (P = 0.258), prior MI (P = 0.524), and prior stroke (P = 0.180) between patients with TRD and those without TRD. Mortality was 13% (n = 13) in patients with TRD and 7% (n = 49) in patients without TRD, with a mean follow-up of 29 mo (18 mo minimum and maximum of 4.5 years). TRD was a significant independent predictor of mortality (HR = 1.995; 95%CI: 1.011-3.938, P = 0.046) after controlling for age (HR = 1.036; 95%CI: 1.011-1.061, P = 0.004), diabetes (HR = 2.912; 95%CI: 1.638-5.180, P < 0.001), heart failure (HR = 2.736; 95%CI: 1.551-4.827, P = 0.001), and smoking (HR = 0.502; 95%CI: 0.228-1.105, P = 0.087).ConclusionThe analysis of TRD in the ENRICHD study shows that the effective treatment of depression reduced mortality in depressed post-MI patients. It is important to monitor the effectiveness of depression treatment and change treatments if necessary to reduce depression and improve cardiac outcomes in depressed post-MI patients.

Project description:ObjectiveThis study aimed to evaluate the role of an objective physiologic biomarker, arterial blood pressure variability, for the early identification of adverse short-term electroencephalogram (EEG) outcomes in infants with hypoxic-ischemic encephalopathy (HIE).Study designIn this multicenter observational study, we analyzed blood pressure of infants meeting these criteria: (1) neonatal encephalopathy determined by modified Sarnat exam, (2) continuous mean arterial blood pressure (MABP) data between 18 and 27 hours after birth, and (3) continuous EEG performed for at least 48 hours. Adverse outcome was defined as moderate-severe grade EEG at 48 hours. Standardized signal preprocessing was used; the power spectral density was computed without interpolation. Multivariate binary logistic regression was used to identify which MABP time and frequency domain metrics provided improved predictive power for adverse outcomes compared with standard clinical predictors (5-minute Apgar score and cord pH) using receiver operator characteristic analysis.ResultsNinety-one infants met inclusion criteria. The mean gestational age was 38.4 ± 1.8 weeks, the mean birth weight was 3,260 ± 591 g, 52/91 (57%) of infants were males, the mean cord pH was 6.95 ± 0.21, and 10/91 (11%) of infants died. At 48 hours, 58% of infants had normal or mildly abnormal EEG background and 42% had moderate or severe EEG backgrounds. Clinical predictor variables (10-minute Apgar score, Sarnat stage, and cord pH) were modestly predictive of 48 hours EEG outcome with area under curve (AUC) of 0.66 to 0.68. A composite model of clinical and optimal time- and frequency-domain blood pressure variability had a substantially improved AUC of 0.86.ConclusionTime- and frequency-domain blood pressure variability biomarkers offer a substantial improvement in prediction of later adverse EEG outcomes over perinatal clinical variables in a two-center cohort of infants with HIE.Key points· Early outcome prediction in HIE is suboptimal.. · Patterns in blood pressure physiology may be predictive of short-term outcomes.. · Early time- and frequency-domain measures of blood pressure variability predict short-term EEG outcomes in HIE infants better than perinatal factors alone..

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Predictive power of abnormal electroencephalogram for post-cerebral infarction depression.

Publications

Predictive power of abnormal electroencephalogram for post-cerebral infarction depression.

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