Deprescribing anticholinergic and sedative medicines: protocol for a Feasibility Trial (DEFEAT-polypharmacy) in residential aged care facilities
Bibliographic record
Abstract
INTRODUCTION: Targeted deprescribing of anticholinergic and sedative medicines can lead to positive health outcomes in older people; as they have been associated with cognitive and physical functioning decline. This study will examine whether the proposed intervention is feasible at reducing the prescription of anticholinergic and sedative medicines in older people. METHODS AND ANALYSIS: The Standard Protocol Items: Recommendations for Interventional trials (SPIRIT checklist) was used to develop and report the protocol. Single group (precomparison and postcomparison) feasibility study design. STUDY POPULATION: 3 residential care homes have been recruited. INTERVENTION: This will involve a New Zealand registered pharmacist using peer-reviewed deprescribing guidelines, to recommend to general practitioners (GPs), sedative and anticholinergic medicines that can be deprescribed. The cumulative use of anticholinergic and sedative medicines for each participant will be quantified, using the Drug Burden Index (DBI). OUTCOMES: The primary outcome will be the change in the participants' DBI total and DBI PRN 3 and 6 months after implementing the deprescribing intervention. Secondary outcomes will include the number of recommendations taken up by the GP, participants' cognitive functioning, depression, quality of life, activities of daily living and number of falls. DATA COLLECTION POINTS: Participants' demographic and clinical data will be collected at the time of enrolment, along with the DBI. Outcome measures will be collected at the time of enrolment, 3 and 6 months' postenrolment. ETHICS AND DISSEMINATION: Ethics approval has been granted by the Human Disability and Ethics Committee. Ethical approval number (16/NTA/61). TRIAL REGISTRATION NUMBER: Pre-results; ACTRN12616000721404.
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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 | 0.045 | 0.036 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 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".