The Impact of General Anesthesia on Postoperative Cognitive Dysfunction Using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment–Indonesian Version (MOCA-Ina) in Geriatric Patients
Bibliographic record
Abstract
Abstract Postoperative cognitive dysfunction (POCD) is a serious issue in geriatric patients undergoing general anesthesia procedures. Perioperative cognitive function assessment is vital for selecting anesthesia techniques in elderly patients. This pretest–posttest cohort study assessed the effect of general anesthesia on POCD in geriatric patients ≥60 years from three government hospitals in Medan. Cognitive function was measured using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Indonesian version (MoCA-Ina) tests 1 day before and 3 days after surgery. Thirty-six patients were included, with an average age of 65.42 ± 4.23 years. The majority were female (52.8%), with a high school education (50%), and worked as farmers/laborers (25%). The average surgery duration was 150 ± 39.93 minutes. A significant decrease in MMSE (26.83 ± 1.5 vs. 26.58 ± 1.44) and MoCA-Ina (27.28 ± 1.06 vs. 27.05 ± 1.01) scores was observed 3 days postoperatively (p < 0.05), with high correlation between the two tests (97.2%; p > 1.00). General anesthesia significantly affects POCD in geriatric patients based on MMSE and MoCA-Ina scores.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".