Qualitative versus quantitative assessment of electroencephalography in cognitive decline: Comparison in a clinical population.

This study aimed to compare the diagnostic performance of visual assessment of electroencephalography (EEG) using the Grand Total EEG (GTE) score and quantitative EEG (QEEG) using spectral analysis in the context of cognitive impairment. This was a retrospective study of patients with mild cognitive impairment, with (MCI+V) or without (MCI) vascular dysfunction, and patients with dementia including Alzheimer's disease, Lewy Body Dementia and vascular dementia. The results showed that the GTE is a simple scoring system with some potential applications, but limited ability to distinguish between dementia subtypes, while spectral analysis appeared to be a powerful tool, but its clinical development requires the use of artificial intelligence tools.

Spectral quantitative and semi-quantitative EEG provide complementary information on the life-long effects of early childhood malnutrition on cognitive decline.

Objective: This study compares the complementary information from semi-quantitative EEG (sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect the life-long effects of early childhood malnutrition on the brain. Methods: Resting-state EEGs (N = 202) from the Barbados Nutrition Study (BNS) were used to examine the effects of protein-energy malnutrition (PEM) on childhood and middle adulthood outcomes. sqEEG analysis was performed on Grand Total EEG (GTE) protocol, and a single latent variable, the semi-quantitative Neurophysiological State (sqNPS) was extracted. A univariate linear mixed-effects (LME) model tested the dependence of sqNPS and nutritional group. sqEEG was compared with scores on the Montreal Cognitive Assessment (MoCA). Stable sparse classifiers (SSC) also measured the predictive power of sqEEG, spectral-qEEG, and a combination of both. Multivariate LME was applied to assess each EEG modality separately and combined under longitudinal settings. Results: The univariate LME showed highly significant differences between previously malnourished and control groups (p < 0.001); age (p = 0.01) was also significant, with no interaction between group and age detected. Childhood sqNPS (p = 0.02) and adulthood sqNPS (p = 0.003) predicted MoCA scores in adulthood. The SSC demonstrated that spectral-qEEG combined with sqEEG had the highest predictive power (mean AUC 0.92 ± 0.005). Finally, multivariate LME showed that the combined spectral-qEEG+sqEEG models had the highest log-likelihood (-479.7). Conclusion: This research has extended our prior work with spectral-qEEG and the long-term impact of early childhood malnutrition on the brain. Our findings showed that sqNPS was significantly linked to accelerated cognitive aging at 45-51 years of age. While sqNPS and spectral-qEEG produced comparable results, our study indicated that combining sqNPS and spectral-qEEG yielded better performance than either method alone, suggesting that a multimodal approach could be advantageous for future investigations. Significance: Based on our findings, a semi-quantitative approach utilizing GTE could be a valuable diagnostic tool for detecting the lasting impacts of childhood malnutrition. Notably, sqEEG has not been previously explored or reported as a biomarker for assessing the longitudinal effects of malnutrition. Furthermore, our observations suggest that sqEEG offers unique features and information not captured by spectral quantitative EEG analysis and could lead to its improvement.

Grand Total EEG Score Can Differentiate Parkinson's Disease From Parkinson-Related Disorders.

Background: Semi-quantitative electroencephalogram (EEG) analysis is easy to perform and has been used to differentiate dementias, as well as idiopathic and vascular Parkinson's disease. Purpose: To study whether a semi-quantitative EEG analysis can aid in distinguishing idiopathic Parkinson's disease (IPD) from atypical parkinsonian disorders (APDs), and furthermore, whether it can help to distinguish between APDs. Materials and Methods: A comprehensive retrospective review of charts was performed to include patients with parkinsonian disorders who had at least one EEG recording available. A modified grand total EEG (GTE) score evaluating the posterior background activity, and diffuse and focal slow wave activities was used in further analyses. Results: We analyzed data from 76 patients with a final diagnosis of either IPD, probable corticobasal degeneration (CBD), multiple system atrophy (MSA), or progressive supra-nuclear palsy (PSP). IPD patients had the lowest mean GTE score, followed those with CBD or MSA, while PSP patients scored the highest. However, none of these differences were statistically significant. A GTE score of ≤9 distinguished IPD patients from those with APD (p < 0.01) with a sensitivity of 100% and a specificity of 33.3%. Conclusion: The modified GTE score can distinguish patients with IPD from those with CBD, PSP or MSA at a cut-off score of 9 with excellent sensitivity but poor specificity. However, this score is not able to distinguish a particular form of APD from other forms of the disorder.

Deep brain stimulation and cognitive decline in Parkinson's disease: The predictive value of electroencephalography.

Some Parkinson's disease (PD) patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) develop new-onset cognitive decline. We examined whether clinical EEG recordings can be used to predict cognitive deterioration in PD patients undergoing STN-DBS. In this retrospective study, we used the Grand Total EEG (GTE)-score (short and total) to evaluate pre- and postoperative EEGs. In PD patients undergoing STN-DBS (N = 30), cognitive functioning was measured using Mini-Mental State Test and DemTect before and after surgery. Severity of motor impairment was assessed using the Unified Parkinson's Disease Rating Scale-III. Patients were classified into patients with or without cognitive decline after STN-DBS surgery. Epidemiological data, pre- and postoperative EEG recordings as well as neuropsychological and neurological data, electrode positions and the third ventricle width were compared. A logistic regression model was used to identify predictors of cognitive decline. Motor deficits significantly improved from pre- to post-surgery, while the mean GTE-scores increased significantly. Six patients developed cognitive deterioration 4-12 months postoperatively. These patients had significantly higher preoperative GTE-scores than patients without cognitive deterioration, although preoperative cognitive functioning was comparable. Electrode positions, brain atrophy and neurological data did not differ between groups. Logistic regression analysis identified the GTE-score as a significant predictor of postoperative cognitive deterioration. Data suggest that the preoperative GTE-score can be used to identify PD patients that are at high risk for developing cognitive deterioration after STN-DBS surgery even though their preoperative cognitive state was normal.