Karakteristik Fungsi Kognitif Pasien Pasca Stroke Hemoragik Berdasarkan Lokasi Dan Volume Perdarahan Di RSUD Inche Abdoel Moeis Samarinda
Bibliographic record
Abstract
Stroke hemoragik terjadi ketika pembuluh darah pecah menyebabkan perdarahan otak dan disabilitas yang parah, salah satunya adalah gangguan fungsi kognitif. Tujuan penelitian ini adalah untuk mengetahui karakteristik fungsi kognitif, distribusi domain fungsi kognitif, dan karakteristik fungsi kognitif berdasarkan lokasi perdarahan, volume perdarahan, dan waktu pasca stroke pada pasien pasca stroke hemoragik di RSUD Inche Abdoel Moeis Samarinda. Penelitian ini menggunakan desain deskriptif obervasional dengan pendekatan cross-sectional yang dilaksanakan pada Agustus – Oktober 2024. Data diperoleh melalui wawancara menggunakan Montreal Cognitive Assessment-Indonesia (MoCA-Ina) dan rekam medik. Pengambilan sampel dilakukan dengan total sampling. Sebanyak delapan sampel memenuhi kriteria inklusi. Hasil penelitian ini menunjukkan bahwa seluruh responden mengalami gangguan fungsi kognitif (100%) dengan domain memori tertunda (100%) dan bahasa (100%) yang paling terpengaruh, sebagian besar lokasi perdarahan di hemisfer serebri sinistra (62,5%) dengan volume perdarahan 20-40 ml (62,5%), dan seluruhnya mengalami gangguan fungsi kognitif ³ 3 bulan pasca stroke (100%). Sebagai kesimpulan, semua responden mengalami gangguan fungsi kognitif dengan domain memori tertunda dan bahasa yang paling terdampak, mayoritas lokasi perdarahan di hemisfer serebri sinistra dengan volume perdarahan 20-40 ml, dan seluruhnya mengalami gangguan fungsi kognitif ³ 3 bulan pasca stroke.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".