Revisiting systematic reviews on deprescribing trials to better inform future practice and research
Bibliographic record
Abstract
Deprescribing aims to address the problem of medication overuse in older adults. There has been an increasing number of systematic reviews of 'deprescribing'. We aimed to describe the categories of trials included in recent systematic reviews, and to make recommendations for future research. We categorized 122 trials included in eight recent deprescribing systematic reviews into: discontinuation, deprescribing implementation, medication optimisation (including medication initiation) and non-initiation trials. We identified heterogeneity and inconsistency in the categories of trials included in deprescribing systematic reviews. For example, 39 trials (32.0%) involved medication initiation in addition to the deprescribing component. It is now time for international researchers to develop and validate terminology used for trials involving discontinuation/deprescribing of medications, and to provide recommendations for evidence synthesis that will better inform future research, and translation into practice and policy.
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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 | 0.397 | 0.729 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.020 | 0.016 |
| Bibliometrics | 0.037 | 0.030 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.010 | 0.008 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".