Diurnal effects of polypharmacy with high drug burden index on physical activities over 23 h differ with age and sex
Bibliographic record
Abstract
Aging, polypharmacy (concurrent use of ≥ 5 medications), and functional impairment are global healthcare challenges. However, knowledge of the age/sex-specific effects of polypharmacy is limited, particularly on daily physical activities. Using continuous monitoring, we demonstrated how polypharmacy with high Drug Burden Index (DBI-cumulative anticholinergic/sedative exposure) affected behaviors over 23 h in male/female, young/old mice. For comparison, we also evaluated how different drug regimens (polypharmacy/monotherapy) influenced activities in young mice. We found that after 4 weeks of treatment, high DBI (HDBI) polypharmacy decreased exploration (reduced mean gait speed and climbing) during the habituation period, but increased it during other periods, particularly in old mice during the transition to inactivity. After HDBI polypharmacy, mean gait speed consistently decreased throughout the experiment. Some behavioral declines after HDBI were more marked in females than males, indicating treatment × sex interactions. Metoprolol and simvastatin monotherapies increased activities in young mice, compared to control/polypharmacy. These findings highlight that in mice, some polypharmacy-associated behavioral changes are greater in old age and females. The observed diurnal behavioral changes are analogous to drug-induced delirium and sundowning seen in older adults. Future mechanistic investigations are needed to further inform considerations of age, sex, and polypharmacy to optimize quality use of medicines.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".