Dementia and comorbidities in primary care: a scoping review
Bibliographic record
Abstract
BACKGROUND: People with dementia (PwD) are known to have more chronic conditions compared to those without dementia, which can impact the clinical presentation of dementia, complicate clinical management and reduce overall quality of life. While primary care providers (PCPs) are integral to dementia care, it is currently unclear how PCPs adapt dementia care practices to account for comorbidities. This scoping review maps recent literature that describes the role for PCPs in the prevention, detection/diagnosis and management of dementia in the context of comorbidities, identifies critical knowledge gaps and proposes potential avenues for future research. METHODS: We searched for peer-reviewed literature published between 2017-2022 in MEDLINE, Cochrane Library, and Scopus using key terms related to dementia, primary care, and comorbidity. The literature was screened for relevance by title-abstract screening and subsequent full-text screening. The prioritized papers were categorized as either 'Risk Assessment and Prevention', 'Screening, Detection, and Diagnosis' or 'Management' and were further labelled as either 'Tools and Technologies', 'Recommendations for Clinical Practice' or 'Programs and Initiatives'. RESULTS: We identified 1,058 unique records in our search and respectively excluded 800 and 230 publications during title-abstract and full-text screening. Twenty-eight articles were included in our review, where ~ 50% describe the development and testing of tools and technologies that use pre-existing conditions to assess dementia risk. Only one publication provides official dementia screening guidelines for PCPs in people with pre-existing conditions. About 30% of the articles discuss managing the care of PwD, where most were anchored around models of multidisciplinary care and mitigating potentially inappropriate prescribing. CONCLUSION: To our knowledge, this is the first scoping review that examines the role for PCPs in the prevention, detection/diagnosis and management of dementia in the context of comorbidities. Given our findings, we recommend that future studies: 1) further validate tools for risk assessment, timely detection and diagnosis that incorporate other health conditions; 2) provide additional guidance into how comorbidities could impact dementia care (including prescribing medication) in primary care settings; 3) incorporate comorbidities into primary care quality indicators for dementia; and 4) explore how to best incorporate dementia and comorbidities into models/frameworks of holistic, person-centred care.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".