Deprescribing to reduce polypharmacy: study protocol for a randomised controlled trial assessing deprescribing of anticholinergic and sedative drugs in a cohort of frail older people living in the community
Bibliographic record
Abstract
BACKGROUND: Targeted deprescribing of anticholinergic and sedative medications in older people may improve their health outcomes. This trial will determine if pharmacist-led reviews lead to general practitioners deprescribing anticholinergic and sedative medications in older people living in the community. METHODS AND ANALYSIS: The standard protocol items: Recommendations for Interventional Trials (SPIRIT) checklist was used to develop and report the protocol. The trial will involve older adults stratified by frailty (low, medium, and high). This will be a pragmatic two-arm randomized controlled trial to test general practitioner uptake of pharmacist recommendations to deprescribe anticholinergic and sedative medications that are causing adverse side effects in patients. STUDY POPULATION: Community-dwelling frail adults, 65 years or older, living in the Canterbury region of New Zealand, seeking publicly funded home support services or admission to aged residential care and taking at least one anticholinergic or sedative medication regularly. INTERVENTION: New Zealand registered pharmacists using peer-reviewed deprescribing guidelines will visit participants at home in the community, review their medications, and recommend anticholinergic and sedative medications that could be deprescribed to the participant's general practitioner. The total use of anticholinergic and sedative medications will be quantified using the Drug Burden Index (DBI). OUTCOMES: The primary outcome will be the change in total DBI between baseline and 6-month follow-up. Secondary outcomes will include entry into aged residential care, prolonged hospitalization, and death. DATA COLLECTION POINTS: Data will be collected at the time of interRAI assessments (T0), at the time of the baseline review (T1), at 6 months following the baseline review (T2), and at the end of the study period, or end of study participation for participants admitted into aged residential care, or who died (T3). ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Human, Disability and Ethics Committee: ethical number (17CEN265). TRIAL REGISTRATION: ClinicalTrials.gov ACTRN12618000729224 . Registered on May 2, 2018, with the Australian New Zealand Clinical Trials Registry.
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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 | 0.036 | 0.052 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.092 | 0.016 |
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".