Medication Reviews and Clinical Outcomes in Persons with Dementia: A Scoping Review
Bibliographic record
Abstract
Persons diagnosed with dementia are often faced with challenges related to polypharmacy and inappropriate medication use and could benefit from regular medication reviews. However, the benefit of such reviews has not been examined in this population. Therefore, the current scoping review was designed to identify the gaps in the current knowledge regarding the impact of medication reviews on the clinical outcomes in older adults with dementia. Relevant studies were identified by searching three databases (Ovid MEDLINE, Ovid EMBASE, and Scopus) from inception to January 2022 with a combination of keywords and medical subject headings. After the removal of duplicates and ineligible articles, 22 publications of the initial 8346 were included in this review. A total of 57 outcomes were identified, including those pertaining to the evaluation of medication use (n = 17), drug-related interventions (n = 11), drug-related problems (n = 10), dementia-related behavioral symptoms (n = 8), cost-effectiveness (n = 2), drug-related hospital admissions (n = 1), as well as outcomes classified as other (n = 7). Gaps identified through this scoping review included the paucity of studies measuring the impact of medication reviews on the medication management capacity and medication adherence, quality of life, and mortality.
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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 | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".