THE EFFECT OF CHRONIC POLYPHARMACY, THE DRUG BURDEN INDEX (DBI) AND DEPRESCRIBING ON PHYSICAL FUNCTION IN AGED MICE
Bibliographic record
Abstract
Polypharmacy (use of ≥ 5 drugs) and increasing DBI (measure of total exposure to anticholinergic and sedative drugs) is associated with impaired physical function in observational studies of older adults. We aim to determine the effect of polypharmacy, DBI and deprescribing (withdrawing drugs) on functional outcomes in aged mice. From 12 to 21 months of age male C57BL/6 mice were fed control or treatment containing therapeutic doses of five drugs with Zero DBI (simvastatin, metoprolol, omeprazole, paracetamol, irbesartan), Low DBI (simvastatin, metoprolol, omeprazole, paracetamol, citalopram), High DBI (simvastatin, metoprolol, oxybutynin, oxycodone, citalopram), or single drug (simvastatin, metoprolol, oxybutynin, oxycodone or citalopram) (n=40/ group). At 21 months, animals either continued treatment or were deprescribed (n=20/ group). Functional tests were conducted at 12, 15, 18, 21 and 24 months. From 12–24 months, compared to control diet, locomotor activity (open field) and nest making declined following Low DBI, High DBI and citalopram treatment, frailty index score increased following High and citalopram treatment, and grip strength (wire hang) decreased following Low DBI and citalopram treatment (p<0.05). Deprescribing improved locomotor and nesting activity for Low DBI, High DBI and citalopram treatment and grip strength for Low DBI animals. Compared to control, a decline in muscle endurance (rotarod) was observed following citalopram treatment and was improved with deprescribing (p<0.05). Our results show for the first time in a preclinical model that chronic polypharmacy with increasing DBI or individual sedative or anticholinergic drugs impair function, which may be reversed with deprescribing. Future studies will investigate the mechanism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".