Conversion to Dementia among Two Groups with Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVE: To determine the conversion rates to dementia in patients diagnosed with mild cognitive impairment (MCI) thought to be caused by incipient Alzheimer's disease (MCI-AD) or with MCI with features of vascular disease (MCI-Vas). METHODS: On the basis of patient history, neurocognitive, neurological and MRI evaluation, 99 patients were diagnosed with MCI-AD and 35 with MCI-Vas. Conversion to dementia over an average of a 2.4 +/- 1.8-year period was determined. RESULTS: Over the follow-up period, 44% converted to dementia, 51.5% remained classified as MCI, and 4.5% were reclassified as cognitively normal. The conversion rate to dementia was significantly faster at 3 years for the MCI-AD (50.5%) than for the MCI-Vas group (25.7%). The neuropsychological test found to best differentiate converters from non-converters was the Fuld-OME, a measure of learning and recall. Age, education, gender or APOE epsilon4 allele frequency did not differentiate converters from non-converters. CONCLUSIONS: MCI-AD and MCI-Vas are clinically meaningful subtypes of MCI that may convert to dementia at different rates. Prospective studies on larger subsets of MCI patients are required to confirm these findings.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".