PERBEDAAN FUNGSI KOGNITIF PADA LANSIA HIPERTENSI DENGAN DAN TANPA DIABETES MELLITUS
Bibliographic record
Abstract
Latar Belakang : Diabetes mellitus dapat memperburuk gangguan fungsi kognitif melalui mekanisme vaskular dan non vaskular. Tujuan : Menilai perbedaan fungsi kognitif pada lansia hipertensi dengan diabetes mellitus dan tanpa diabetes mellitus Metode : Jenis penelitian adalah penelitian observasional dengan desain belah lintang. dilaksanakan di poliklinik penyakit dalam dan instalasi rawat jalan geriatri RSUP Dr. Kariadi Semarang pada bulan Maret sampai bulan Mei 2016. Subjek penelitian adalah pasien lansia rawat jalan geriatri dan penyakit dalam dengan hipertensi (n=30). Subjek kemudian dibagi menjadi 2 kelompok berdasarkan status diabetes mellitusnya. Status diabetes mellitus dan hipertensi diketahui dari catatan medik rawat jalan, sedangkan fungsi kognitif diukur dengan kuesioner Montreal Cognitive Assessment versi Indonesia (MoCA-Ina). Hasil : Hasil pemeriksaan fungsi kognitif yang dilakukan pada 30 subjek didapatkan rerata 23,80±2,27 pada kelompok lansia hipertensi tanpa DM dan 21,80±2,24 pada kelompok lansia hipertensi dengan DM (p=0,022). Domain kognitif yang terganggu pada kelompok lansia hipertensi dengan DM bila dibandingkan dengan kelompok hipertensi tanpa DM adalah domain delayed recall (p=0,009). Semua domain kognitif pada kelompok hipertensi tanpa DM lebih baik bila dibandingkan dengan kelompok hipertensi dengan DM. Kesimpulan : Diabetes mellitus memperburuk fungsi kognitif, khususnya domain delayed recall pada lansia hipertensi.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".