Outcomes of Cognitively Impaired Not Demented at 2 Years in the Canadian Cohort Study of Cognitive Impairment and Related Dementias
Bibliographic record
Abstract
BACKGROUND: People who are cognitively impaired not demented (CIND) can be at an increased risk for developing dementia, but little is known about the natural history of CIND in clinical settings. METHOD: We examined the 2-year outcome of CIND subjects in the Canadian Cohort Study of Cognitive Impairment and Related Dementias.CIND was diagnosed when at least one positive item was endorsed on the DSM-III-R dementia criteria, but not all criteria were met. CIND was further subclassified as: pre-Alzheimer's disease (pre-AD), vascular cognitive impairment (VCI-ND), non-AD degenerative, psychiatric, other neurologic, other medical conditions, mixed disorders and no etiology identified (not otherwise specified [NOS]). RESULT: Of 146 CIND patients with 2-year follow-up data available, 49 (34%) progressed to dementia, while 20 (14%) recovered to not cognitively impaired (NCI). Progressors were significantly older than stable CIND and reverters (p < 0.0001; mean age = 71.1, 64.3, and 59.1, respectively), and there were significantly (p = 0.001) more ApoE epsilon4 carriers among progressors (67%) than stable CIND (29%) and reverters (12%). Pre-AD CIND and VCI-ND had the highest rate of conversion to dementia (41.0 and 40.0%, respectively), while psychiatric CIND and CIND NOS had highest rate of recovery to NCI (20.0 and 30.0%, respectively). All conversions in pre-AD CIND were to 'probable AD'. CONCLUSION: CIND consists of a heterogeneous group of disorders that can be classified syndromically. Many subclassess - not just those with pre-AD CIND - are at high risk of progression to dementia, usually to Alzheimer's disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".