ANTIDEMENTIA MEDICATION USE IS ASSOCIATED WITH DECREASED INFORMAL COSTS IN MILD DEMENTIA
Bibliographic record
Abstract
Antidementia medication use (ADMU) is associated with a delay in the progression of dementia symptoms, but their association with informal costs of dementia care has not been well-studied. Using the Cache County Dementia Progression Study, a population-based sample of persons with dementia (PWD), we examined daily caregiving hours for 219 PWD (46.9% female, mean (SD) age = 85.8 (5.0) years), which were estimated from the Caregiver Activity Survey. Informal costs were then calculated using the replacement cost method by multiplying hours of care by Utahan median wages in the visit year. Cost was adjusted for inflation using the Medical Consumer Price Index and expressed in 2015 dollars. ADMU was based on inspection of each participant’s medications and interview. Linear mixed models, with gamma log-link function, tested the association between antidementia medications and informal costs. Covariates included: psychotropic and anticholinergic medication use, participant’s health status, gender, and dementia severity (measured by the Clinical Dementia Rating Scale-Sum of Boxes). ADMU was 30.7% at baseline and median informal costs were $9.95/day. Overall, ADMU was not associated with informal costs (expβ = .79, p = .090) in the entire sample. In analyses restricted to participants with mild dementia severity at baseline, ADMU was associated with 28% lower costs (expβ = .72, p = .039). Among covariates, only dementia severity (time-varying) was significantly associated with informal costs. These results suggest that ADMU is associated with lower informal costs, particularly among PWD using these medications while in mild stages of dementia severity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".