Latest canadian consensus conference on the diagnosis and treatment of dementia for primary care clinicians
Bibliographic record
Abstract
Context: Dementia, characterized by a progressive decline in cognition, affects more than 50 million people globally. In 2020, the 5th Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD5) published up-to-date recommendations to guide the clinical management of persons living with dementia (PLWD) and their caregivers. However, primary care clinicians are not always up-to-date with current evidence as the information might be fragmented. Objective: To provide selected new and updated clinical guidance on the management of patients with dementia that are simple to use in a routine primary care practice. Study design: Recommendations were approved and graded based on the Appraisal of Guidelines for Research and Evaluation (AGREE II collaboration), GRADE, and a Delphi process. Setting: Working groups included experts from different backgrounds (primary care physicians, nurse practitioners and other primary care clinicians, neurologists, psychiatrists and geriatricians, researchers, knowledge translation experts, decisions makers, and PLWD and caregivers' representatives). The experts carried out systematic reviews, which guided the development of new recommendations for dementia care. Recommendations included: We summarize the most relevant CCCDTD5 recommendations for primary care clinicians Results: The relevant recommendations for primary care were focused on: a) risk reduction for the general population (nutrition, exercise, social engagement, education, and medication management), as well as for persons at risk of dementia (evaluation of hearing status and sleep, and cognitive training stimulation); b) screening and diagnosis of dementia, including the role of the informant, screening for patients at risk or with symptoms, use of cognitive tests and neuro-imaging, management of subjective cognitive decline); c) de-prescribing medications for dementia, including aspirin and cognitive enhancers; and d) non-pharmacological interventions for persons with dementia (exercise, cognitive stimulation therapy, psychoeducational interventions for caregivers, case management and dementia-friendly community/organizations). Conclusions: The development of recommendations for ongoing management of dementia is an iterative process as new evidence on interventions for dementia are published. The present recommendations are of importance for dementia care in a primary care setting as the entry point for PLWD into the health system.
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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 | 0.071 | 0.118 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.013 | 0.008 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".