Deprescribing for older adults during acute care admission: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to understand the current body of knowledge regarding deprescribing in adults aged 60 years or older in acute care settings, including the deprescribing activities that are being undertaken, and the feasibility, challenges, and outcomes of the practice. INTRODUCTION: Polypharmacy is prevalent amongst older adults, despite risks to patients. Much of the existing research on deprescribing has occurred in the outpatient context, with recent research emerging on the unique opportunity that acute care may provide. INCLUSION CRITERIA: This review will include deprescribing in adults aged 60 years or older in acute care. It will consider deprescribing occurring during inpatient admission and at the time of discharge from hospital. METHODS: The JBI method for scoping reviews will guide this review. A search of MEDLINE (Ovid), Scopus, Web of Science Core Collection, CINAHL (EBSCOhost), Embase (Ovid), and the Cochrane Database of Systematic Reviews will be undertaken from inception to present with no language restrictions. Qualitative, quantitative, and mixed method studies, clinical practice guidelines, and opinion papers will be considered for inclusion. Systematic reviews and scoping reviews will be excluded. Google Scholar and a general Google search will be conducted for gray literature. Two reviewers will assess articles for inclusion and any disagreements will be discussed and resolved by discussion or a third reviewer, if required. Findings will be presented in the scoping review using a narrative approach with supporting quantitative data in a tabular format according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist (PRISMA-ScR). REVIEW REGISTRATION: Open Science Framework https://osf.io/pb7aw/.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".