HUBUNGAN NILAI P300 DENGAN MOCA-INA PADA PASIEN DENGAN GANGGUAN KOGNITIF VASKULAR PASCASTROKE ISKEMIK
Bibliographic record
Abstract
ASSOCIATION OF P300 VALUE WITH MOCA-INA IN VASCULAR COGNITIVE IMPAIRMENT POST-ISCHEMIC STROKE PATIENTSABSTRACTIntroduction: Stroke is a major threat in human life because it can cause disability and mortality. Cognitive impairment in early stroke is strong predictor for long term vascular cognitive impairment while neuropsychology method is superior than conventional method to diagnose cognitive impairment, especially P300.Aim: To identify the association between P300 values and MoCA-Ina in vascular cognitive impairment post ischemic stroke patients.Methods: It is a cross sectional design study for ischemic stroke patients who suffered from vascular cognitive impairment during April to June 2018 in Neurology Clinic of Dr. Wahidin Sudirohusodo Hospital, Makassar. The statistical analysis was performed by Pearson’s correlation test.Result: There were 20 samples, male (60%) and female (40%). The average MoCA-Ina score was 19.35±6.06; the average P300 latency in Fz, Cz, and Pz were 370.22±49.01ms, 360.78±38.27ms, and 361.02±44.45ms, respectively; the average P300 in Fz, Cz, and Pz amplitude were 6.09±3.10µV, 5.67±3.49µV, and 6.10±2.77µV, respectively. The Pearson’s showed that P300 latency had significantly correlation with MoCA-Ina score while no correlation between the P300 amplitude and MoCA-Ina.Discussion: There was correlation between P300 latency with MoCA-Ina in vascular cognitive impairment post ischemic stroke patients.Keywords: Ischemic stroke, MoCA-Ina, P300 value, vascular cognitive impairment.ABSTRAKPendahuluan: Stroke merupakan suatu ancaman terbesar di kehidupan manusia karena dapat menimbulkan kecacatan dan kematian. Gangguan kognitif pada awal stroke merupakan prediktor kuat untuk gangguan kognitif vaskular jangka panjang dan metode neuropsikologi lebih unggul daripada metode konvensional untuk mendiagnosis gangguan kognitif, terutama P300.Tujuan: Untuk mengetahui hubungan nilai P300 dengan MoCA-Ina pada pasien gangguan kognitif vaskular pascastroke iskemik.Metode: Desain studi potong lintang terhadap pasien stroke iskemik yang mengalami gangguan kognitif vaskular selama bulan April sampai Juni 2018 di Poliklinik Saraf RSUP Dr. Wahidin Sudirohusodo, Makassar. Data diolah menggunakan uji korelasi Pearson’s.Hasil: Didapatkan 20 orang sampel laki-laki (60%) dan perempuan (40%). Nilai MoCA-Ina rata-rata 19,35±6,06; hasil rata-rata latensi gelombang P300 di Fz, Cz, dan Pz masing-masing adalah 370,22±49,01, 360,78±38,27, dan 361,02±44,45; rata-rata tinggi amplitudo P300 di Fz masing-masing adalah 6,09±3,10, 5,67±3,49, dan 6,10±2,77. Hasil uji korelasi Pearson’s menunjukkan latensi P300 berkorelasi signifikan terhadap MoCA-Ina, sedangkan amplitudo P300 tidak.Pembahasan: Ada hubungan antara latensi gelombang P300 dengan MoCA-Ina pada pasien gangguan kognitif vaskular pascastroke iskemik.Kata kunci: Gangguan kognitif vaskular, MoCA-Ina, nilai P300, stroke iskemik
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".