Effects of Prescription Drug Reduction on Quality of Life in Community-Dwelling Patients with Dementia
Bibliographic record
Abstract
PURPOSE: Due to the use of multiple drugs and prevalence of diminished cognitive function, community-dwelling elderly individuals are more likely to have drug-related issues. We examined changes in quality of life (QOL) and activities of daily living (ADL) 3 months and 6 months after reducing drug use of dementia patients who had newly begun community-dwelling care. METHODS: Prescription drug use was reduced in the intervention group, whereas the non-intervention group continued their regimen or began using additional drugs. QOL and ADL were assessed with the Japanese version of the EQ-5D and the Barthel Index, respectively. RESULTS: Subjects were 32 individuals aged ≥65 years who had begun community-dwelling between March and July 2014 and had received approval for long-term care insurance. On average, the intervention group (n = 19) stopped using 2.6 prescription drugs. After 6 months, the differences in the QOL and ADL scores in the intervention group were -0.03 ± 0.29 and 6.32 ± 18.6, respectively, while the differences in the QOL and ADL scores in the non-intervention group (n = 13) were -0.13 ± 0.29 and -2.69 ± 23.7, respectively. In the intervention group, ADL scores were significantly increased by 14.0 ± 11.1 6 months after reduced benzodiazepine use. CONCLUSIONS: QOL was maintained with reduced drug use, while ADL score was slightly increased. In addition, the reduction of benzodiazepine use significantly increased ADL. In order to reduce polypharmacy among community-dwelling elderly patients, it is necessary to create an opportunity for pharmacists to re-examine their prescriptions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".