Progress on the research of scales of preoperative evaluation for mild cognitive impairment
Bibliographic record
Abstract
Background Mild cognitive impairment(MCI) is a syndrome defined as cognitive decline is ahead of expectation for an individual′s age and education level but that does not interfere notably with activities of daily life. MCI has a high risk of developing into dementia. Objective Preoperative evaluation for high-risk patients is conductive to the implementation of the precision anesthesia. In other words, with proper anesthetic medicine and method, the progression of MCI can be controlled or even delayed. Content The author comprehensively reviewed the screening scales of MCI home and abroad. Trend Although the application of Montreal cognitive assessment(MoCA) on poorly educated patients has drawbacks, this screening scale is still the best single scale for preoperative evaluation so far. In addition, the application of the Montreal cognitive assessment-basic(MoCA-B) and Mini-mental status examination(MMSE) combined with other scales will provide new thoughts for accurate assessment of the cognitive function of the MCI patients. Key words: Mild cognitive impairment; Preoperative evaluation; Scale of cognitive function
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".