Risk Factors for Progression of Alzheimer Disease in a Canadian Population: The Canadian Outcomes Study in Dementia (COSID)
Bibliographic record
Abstract
OBJECTIVE: To determine risk factors for clinically significant progression during 12 months in patients with mild-to-moderate Alzheimer disease. METHOD: Community-dwelling patients with mild-to-moderate Alzheimer disease were enrolled in a 3-year prospective study, the Canadian Outcomes Study in Dementia (commonly referred to as COSID), at 32 Canadian sites. Assessments included the Global Deterioration Scale (GDS) for disease severity, the Mini-Mental State Examination (MMSE) for cognition, the Functional Autonomy Measurement System (SMAF) for daily functioning, and the NeuroPsychiatric Inventory (NPI) for behaviour, measured at baseline and at 12 months. Logistic regression identified factors associated with GDS decline, and subsequent stepwise regression identified key independent predictors. Area under the curve (AUC) was then calculated for the model. RESULTS: Among 488 patients (mean age 76.5 years [SD 6.4], MMSE 22.1 [SD4.6], 44.1% male), 225 (46%) showed GDS decline. After adjusting for age, baseline risk factors for deterioration included the following: poorer cognition (lower MMSE score, OR 0.55; 95% CI 0.4 to 0.72 per 5 points, P ≤ 0.001), greater dependence (lower SMAF, OR 0.72; 95% CI 0.63 to 0.83 per 5 points, P ≤ 0.001), and more neuropsychiatric symptoms (higher NPI, OR 1.11; 95% CI 1.02 to 1.2 per 5 points, P = 0.02), with a protective effect of male sex (OR 0.59; 95% CI 0.39 to 0.9, P = 0.02), and higher (worse) GDS score (very mild, compared with mild OR 0.25; 95% CI 0.09 to 0.70, P ≤ 0.01; compared with moderate, OR 0.08; 95% CI 0.03 to 0.23, P < 0.001; compared with moderately severe, OR 0.03; 95% CI 0.01 to 0.11, P < 0.001). The AUC was 73% (P < 0.001) (sensitivity 90% and specificity 33%). CONCLUSION: The progression of Alzheimer disease in Canada can be predicted using readily available clinical information.
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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 | 0.003 |
| 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".