A qEEG-based prognostic model for cognitive impairment after ischemic stroke: Development and internal validation.
The study developed a model that predicts cognitive impairment after ischemic stroke using qEEG parameters, but further validation is needed before it can be used clinically.
Where it sits
this study against the rest of the dsip corpusSummary and findings
This study developed a prognostic model for cognitive impairment at six months after first-ever ischemic stroke using quantitative electroencephalography (qEEG) parameters. The model identified three significant predictors: occipital Delta/Alpha Ratio (DAR), frontal Peak Alpha Frequency (PAF), and education level. The study included 96 participants, with 44 (46%) developing cognitive impairment.
Abstract
<h4>Background</h4>Cognitive impairment is a frequent and disabling consequence of ischemic stroke, yet early prognostic tools are limited. Quantitative electroencephalography (qEEG) offers a portable, low-cost measure of post-stroke cortical dysfunction. We aimed to develop a prognostic model for six-month cognitive impairment after first-ever ischemic stroke.<h4>Methods</h4>In this single-centre prospective cohort study, patients with first-ever supratentorial ischemic stroke (NIHSS < 15) were enrolled within 7 days of onset at a tertiary hospital in Vietnam. Resting-state 19-channel EEG and brain MRI were acquired at baseline. Four region-specific qEEG parameters were derived for five cortical regions and globally: Delta/Alpha Ratio (DAR), Delta-Theta/Alpha-Beta Ratio, Peak Alpha Frequency (PAF), and Dominant Frequency Variability. The primary outcome was cognitive impairment at six months (education-adjusted MoCA < 26). Predictors were selected by AIC-guided forward stepwise logistic regression. Internal validation used a selection-aware bootstrap (1000 replicates), with multiple imputation and sensitivity analyses. Reporting followed TRIPOD and STROBE guidelines.<h4>Results</h4>The analytic cohort comprised 96 participants; 44 (46%) developed cognitive impairment at six months. Higher occipital DAR (OR 2.09, 95% CI 1.45-3.39), lower frontal PAF (OR 0.46, 95% CI 0.27-0.74), and education below high school (OR 7.16, 95% CI 1.89-34.18) increased risk of cognitive impairment. Infarct volume was associated univariably but did not survive multivariable selection. Apparent AUC was 0.937 (95% CI 0.890-0.984); optimism-corrected AUC was 0.891 (0.861-0.945), with good calibration (Brier score 0.098). Effects were preserved across multiple imputation and alternative MoCA cutoffs.<h4>Conclusions</h4>In this single-centre development cohort, a parsimonious three-variable model combining occipital DAR, frontal PAF, and educational attainment showed good internal discrimination and calibration for six-month cognitive impairment after first-ever ischemic stroke. These variables should be regarded as candidate predictors rather than an established prognostic tool; external multicentre validation against clinically adjudicated endpoints is the necessary next step before any clinical interpretation.
Background
Cognitive impairment is a common consequence of ischemic stroke, yet effective early prognostic tools are lacking. Previous research has indicated that qEEG may provide insights into cortical dysfunction post-stroke. This study aims to fill the gap by developing a model that predicts cognitive impairment at six months using qEEG parameters.
Methods
This was a single-centre prospective cohort study involving 96 patients with first-ever supratentorial ischemic stroke (NIHSS < 15), enrolled within 7 days of onset. Baseline assessments included resting-state 19-channel EEG and brain MRI. The primary outcome was cognitive impairment at six months, defined as an education-adjusted MoCA score of less than 26. Predictors were identified using AIC-guided forward stepwise logistic regression.
Results
The primary endpoint revealed that 44 out of 96 participants (46%) developed cognitive impairment at six months. The model identified higher occipital DAR (OR 2.09, 95% CI 1.45-3.39), lower frontal PAF (OR 0.46, 95% CI 0.27-0.74), and education below high school (OR 7.16, 95% CI 1.89-34.18) as significant predictors. The model exhibited an apparent AUC of 0.937 (95% CI 0.890-0.984) and an optimism-corrected AUC of 0.891 (0.861-0.945).
Interpretation
The findings suggest that the identified qEEG parameters may be useful in predicting cognitive impairment after ischemic stroke, although the effect sizes, particularly for frontal PAF, may be considered small. The study's single-centre design and relatively small sample size limit the external validity of the results. Further validation in multicentre studies is necessary before clinical application.
Key findings
- 44 (46%) developed cognitive impairment at six months.
- Higher occipital DAR associated with increased risk (OR 2.09, 95% CI 1.45-3.39).
- Lower frontal PAF associated with increased risk (OR 0.46, 95% CI 0.27-0.74).
- Education below high school increased risk (OR 7.16, 95% CI 1.89-34.18).
- Apparent AUC was 0.937 (95% CI 0.890-0.984); optimism-corrected AUC was 0.891 (0.861-0.945).
- Brier score for calibration was 0.098.
Limitations
- Single-centre study limits generalizability.
- Small sample size (n=96) may affect robustness.
- No external validation performed.
- Short follow-up period of six months.
- Education-adjusted MoCA may not capture all cognitive domains.