Can You Have Dementia With an MMSE Score of 30?
Bibliographic record
Abstract
OBJECTIVE: To investigate the possibility that a patient with a diagnosis oF probable Alzheimer's disease (AD) can still obtain a score oF 30/30 on the Mini-Mental State Exam (MMSE). DESIGN: Chart review. Setting. The McGill University/Jewish General Hospital Memory Clinic. PARTICIPANTS: Participants were selected From the Memory Clinic's patient database. All underwent comprehensive evaluations, including relevant blood work and a computed tomographic scan or a magnetic resonance imaging scan oF the brain to rule out other causes oF dementia. MEASUREMENTS: All patients had one or more neuropsychological evaluation. Data oF all psychometric testing, including the MMSE, were gathered From these visits. Results. Eight patients were Found to meet the criteria oF AD although achieving a score oF 30/30 on the MMSE. Four oF 8 patients achieved this score although they were taking cholinesterase inhibitors. CONCLUSION: Although rare, it is possible to achieve a score oF 30/30 on the MMSE even iF a subject is suFFering From a dementing illness.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".