Quantitative EEG Correlates with NIHSS and MoCA for Assessing the Initial Stroke Severity in Acute Ischemic Stroke Patients

Ahmad Asmedi; Abdul Gofir; Sekar Satiti; Paryono Paryono; Ditha Praritama Sebayang; Dyanne Paramita Arindra Putri; Amelia Vidyanti

doi:10.3889/oamjms.2022.8483

Authors

Ahmad Asmedi Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
Abdul Gofir Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia https://orcid.org/0000-0002-8469-3443
Sekar Satiti Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
Paryono Paryono Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
Ditha Praritama Sebayang Department of Neurology, Mitra Medika Hospital, Pontianak, Indonesia
Dyanne Paramita Arindra Putri Department of Neurology, Hermina Hospital, Yogyakarta, Indonesia
Amelia Vidyanti Department of Neurology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia https://orcid.org/0000-0002-2741-2983

DOI:

https://doi.org/10.3889/oamjms.2022.8483

Keywords:

qEEG, Stroke severity, NIHSS, MoCA, Acute ischemic stroke

Abstract

BACKGROUND: National Institutes of Health Stroke Scale (NIHSS) and Montreal Cognitive Assessment (MoCA) measure stroke severity by assessing the functional and cognitive outcome, respectively. However, they cannot be used to measure subtle evolution in clinical symptoms during the early phase. Quantitative EEG (qEEG) can detect any subtle changes in CBF and brain metabolism thus may also benefit for assessing the severity.

AIM: This study aims to identify the correlation between qEEG with NIHSS and MoCA for assessing the initial stroke severity in acute ischemic stroke patients.

METHODS: This was a cross-sectional study. We recruited 30 patients with first-ever acute ischemic stroke hospitalized in Dr. Sardjito General Hospital, Yogyakarta, Indonesia. We measured the NIHSS, MoCA score, and qEEG parameter during the acute phase of stroke. Correlation and regression analysis was completed to investigate the relationship between qEEG parameter with NIHSS and MoCA.

RESULTS: Four acute qEEG parameter demonstrated moderate-to-high correlations with NIHSS and MoCA. DTABR had positive correlation with NIHSS (r = 0.379, p = 0.04). Meanwhile, delta-absolute power, DTABR, and DAR were negatively correlated with MoCA score (r = −0.654, p = 0.01; r = −0.397, p = 0.03; and r = −0.371, p = 0.04, respectively). After adjusted with the confounding variables, delta-absolute power was independently associated with MoCA score, but not with NIHSS (B = −2.887, 95% CI (−4.304–−1.470), p < 0.001).

CONCLUSIONS: Several qEEG parameters had significant correlations with NIHSS and MoCA in acute ischemic stroke patients. The use of qEEG in acute clinical setting may provide a reliable and efficient prediction of initial stroke severity. Further cohort study with larger sample size and wide range of stroke severity is still needed.

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