Validity and Reliability of Event Related Potential in Subacute Stroke
Bibliographic record
Abstract
Abstract The aim of this study was assess the test-retest reliability of the ERP and resting EEG test in subacute stroke patients. Additionally, we compared the validity of the EEG, ERP test to MMSE (Mini-Mental State Exam) and MoCA (Montreal Cognitive Assessment) to use it as an objective tool to evaluate cognitive function. We recruited 20 patients with subacute ischemic stroke who were 19 years of age or older and had an MMSE score of 20 or higher. All participants were tested K-MMSE (Korean Mini Psychostatistics Test) and K-MoCA (Korea-Montreal Cognitive Assessment). The resting-state EEG and P300 wave using an auditory and visual oddball paradigm were measured at baseline and once again in 24 hours. We calculated the brain symmetry index (BSI) and directional BSI (BSIdir) over different frequency bands and delta/alpha ratio (DAR). The intra-rater reliability and validity of the P300 latency, amplitude, BSI, BSIdir and DAR were measured by intra-class correlation (ICC) analysis and by Pearson`s correlation coefficient analysis, respectively. P300 latency showed excellent ICC level (auditory P contralesional, ICC = 0.918, visual P contralesional, ICC = 0.972, visual Pz, ICC = 0.945). In the visual ERP (latency), there was a significant correlation between Cz, C ipsilesional and Mini-Mental State Exam (MMSE) and C ipsilesional and Montreal Cognitive Assessment (MoCA). The P contralesional and Pz latency of visual ERP showed significant reliability, and the Cz and C ipsilesional of visual latency showed effectiveness in reflecting the cognitive function. Thus, these montages could be used as a basis for future studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".