Recommendations of the 5th Canadian Consensus Conference on the diagnosis and treatment of dementia
Bibliographic record
Abstract
Since 1989, four Canadian Consensus Conferences on the Diagnosis and Treatment of Dementia (CCCDTD) have provided evidence-based dementia guidelines for Canadian clinicians and researchers. We present the results of the 5th CCCDTD, which convened in October 2019, to address topics chosen by the steering committee to reflect advances in the field, and build on previous guidelines. Topics included: (1) utility of the National Institute on Aging research framework for clinical Alzheimer's disease (AD) diagnosis; (2) updating diagnostic criteria for vascular cognitive impairment, and its management; (3) dementia case finding and detection; (4) neuroimaging and fluid biomarkers in diagnosis; (5) use of non-cognitive markers of dementia for better dementia detection; (6) risk reduction/prevention; (7) psychosocial and non-pharmacological interventions; and (8) deprescription of medications used to treat dementia. We hope the guidelines are useful for clinicians, researchers, policy makers, and the lay public, to inform a current and evidence-based approach to dementia.
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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 | 0.105 | 0.181 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.018 | 0.006 |
| Research integrity | 0.021 | 0.026 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".