EEG Delta/Theta Ratio and Microstate Analysis Originating Novel Biomarkers for Malnutrition-Inflammation Complex Syndrome in ESRD Patients

Abstract

The Malnutrition-Inflammation Score (MIS) was initially proposed to evaluate malnutrition-inflammation complex syndrome (MICS) in end-stage renal disease (ESRD) patients. Although MICS should be routinely evaluated to reduce the hospitalization and mortality rate of ESRD patients, the inconvenience of the MIS might limit its use. Cerebral complications in ESRD, possibly induced by MICS, were previously assessed by using spectral electroencephalography (EEG) via the delta/theta ratio and microstate analysis. Correspondingly, EEG could be used to directly assess MICS in ESRD patients, but the relationships among MICS and these EEG features remain inconclusive. Thus, we aimed to investigate the delta/theta ratio and microstates in ESRD patients with high and low risks of MICS. We also attempted to identify the correlation among the MIS, delta/theta ratio, and microstate parameters, which might clarify their relationships. To achieve these objectives, a total of forty-six ESRD subjects were willingly recruited. We collected their blood samples, MIS, and EEGs after receiving written informed consent. Sixteen women and seven men were allocated to low risk group (MIS ≤ 5, age 57.57 ± 14.88 years). Additionally, high risk group contains 15 women and 8 men (MIS > 5, age 59.13 ± 11.77 years). Here, we discovered that delta/theta ratio (p < 0.041) and most microstate parameters (p < 0.001) were significantly different between subject groups. We also found that the delta/theta ratio was not correlated with MIS but was strongly with the average microstate duration (ρ = 0.708, p < 0.001); hence, we suggested that the average microstate duration might serve as an alternative encephalopathy biomarker. Coincidentally, we noticed positive correlations for most parameters of microstates A and B (0.54 ≤ ρ ≤ 0.68, p < 0.001) and stronger negative correlations for all microstate C parameters (−0.75 ≤ ρ ≤ −0.61, p < 0.001). These findings unveiled a novel EEG biomarker, the MIC index, that could efficiently distinguish ESRD patients at high and low risk of MICS when utilized as a feature in a binary logistic regression model (accuracy of train-test split validation = 1.00). We expected that the average microstate duration and MIC index might potentially contribute to monitor ESRD patients in the future.

QEEG characteristics associated with malnutrition-inflammation complex syndrome

“…However, the alpha power may not differ because alpha deviations do not characterize cognitive impairment in patients with ESRD (Lizio et al, 2018 ). EEG coherence or/and amplitude asymmetry in the anterior-posterior regions of the brain might deviate in the ESRD-H group due to cerebral abnormalities in these regions (Jatupornpoonsub et al, 2022 ). As a result, we failed to confirm some of these hypotheses.…”

“…We reviewed all related methods used in our previous study (Jatupornpoonsub et al, 2022 ). The experimental protocols that involved participants in this study were approved by the Institutional Review Board of Phramongkutklao Hospital, with certificate of approval (COA) number S072h/62, and the Institutional Review Board of Mahidol University, with COA number MU-CIRB 2020/393.2511.…”

“…Different resting-state electroencephalogram (EEG) analysis methods have been utilized to study CKD patients with cerebral disorders. These approaches include time-domain visual inspection, frequency-domain spectral analysis, quantitative EEG (QEEG), and microstate analysis (Gadewar et al, 2015 ; Lizio et al, 2018 ; Jatupornpoonsub et al, 2022 ). Abnormal variations in EEG amplitudes are traditionally evaluated with visual inspections.…”

“…Therefore, widespread delta power was suggested as a distinctive marker of the early stage of cerebrovascular complications in CKD patients (Lizio et al, 2018 ). Recently, a study of the relationship between microstate EEG and MICS revealed that the frontoparietal microstate was considerably deviated in ESRD patients with more severe MICS, suggesting that abnormalities in the neural networks underlying this microstate may cause cognitive impairment (Jatupornpoonsub et al, 2022 ), which may also affect QEEG. As evidenced by the above studies, QEEG can be used for ESRD cerebral assessment and may be correlated with MICS severity.…”

Predicting Motor Imagery BCI Performance Based on EEG Microstate Analysis

“…Using this method, brain electrical activity can be represented by a time series of microstates. At present, there are many research directions for EEG microstates, such as the theoretical basis of microstates [ 23 ], the connection between microstates and brain cognitive function [ 24 , 25 ], the application of microstate analysis in neuropsychiatric diseases [ 26 , 27 , 28 , 29 ], etc. Thus, microstates may capture more information on the resting-state EEG, providing a new measure to predict subjects’ MI-BCI performance.…”