Utilidad de los test cognoscitivos breves para detectar la demencia en población mexicana
Bibliographic record
Abstract
Los test cognoscitivos breves o de cribado (TCB) son instrumentos que se han utilizado para detectar a las personas con demencia, entre los más utilizados a nivel internacional son el Mini Mental State Examination (MMSE), el Montreal Cognitive Assessment (MoCA), el Seven Minute Screen Test (7MS) y el Memory Impairment Screen (MIS).El objetivo de esta revisión fue analizar la utilidad de los TCB para detectar la demencia en población mexicana, se realizó una búsqueda de artículos en bases de datos y sitios web (PubMed, EBSCO y Google Scholar). El MMSE ha sido el instrumento más utilizado en México para detectar la demencia en comparación con el MoCA y el MIS, no se encontraron estudios relevantes acerca del 7MT. Sin embargo, el MoCA ha sido más útil para detectar el DCL y la demencia en comparación con el MMSE y el MIS. Cada instrumento presenta limitaciones y aspectos a considerar cuando son administrados para detectar la demencia como la edad y la escolaridad.
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".