EMPOWERing Hospitalized Older Adults to Deprescribe Sedative Hypnotics: A Pilot Study
Bibliographic record
Abstract
OBJECTIVES: To distribute the EMPOWER patient education brochure and use hospitalization as an opportunity to reduce inappropriate sedatives. DESIGN: Participants were sequentially recruited until we achieved 30-day follow-up telephone and pharmacy records for 50 individuals. The proportion meeting the primary outcome was compared with that of a control cohort and with rates of cessation achieved in the community. SETTING: Fifty-two-bed medical clinical teaching unit in Montréal, Canada. PARTICIPANTS: Inpatients aged 65 and older who were chronic, regular sedative users. MEASUREMENTS: The primary outcome was short-term sustained cessation 30-days after discharge. As a secondary outcome, we compared self-reported sleep disturbance before and after the intervention. RESULTS: Sedatives were deprescribed in 32 of 50 (64%) participants who received the EMPOWER brochure, which was significantly higher than our historical rate of 21% (p<.001). Participants did not report significant worsening in their quality of sleep after sedative cessation. CONCLUSION: Hospitalized individuals are willing to deprescribe, and contact with the healthcare system provides the opportunity to initiate the process with educational brochures. This type of intervention requires few resources and is feasible and inexpensive.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".