Sedative use by older adults with dementia is higher among women than men and exceeds recommendations
Bibliographic record
Abstract
Abstract Background Sedative medications (benzodiazepines and Z‐drugs) are used to treat responsive behaviours in those with dementia despite association with adverse drug events and accepted status as potentially inappropriate medications. The objective of this study was to complete a sex‐based analysis of sedative use in a cohort of older adults with dementia in Nova Scotia, Canada. Method We examined sedative use in a cohort of adults aged 65 years and older with dementia in Nova Scotia, Canada. Prescription data was examined from April 1, 2010 to March 31, 2015. Concordance with prescribing guidelines was compared for men and women using descriptive statistics and unadjusted odds ratios. Result Of the 30,703 older adults with dementia in the cohort 11,647 (37.9%) received at least one prescription for a sedative. Women were more likely to receive a benzodiazepine (OR 1.44; 95% CI [1.36‐1.53]) or a Z‐drug (OR 1.10; 95% CI [1.01‐1.19]). Lorazepam was the most commonly prescribed sedative (52% of sedative users). Zopiclone was the second most commonly prescribed (27% of sedative users). Sedative use (37.9% of cohort) which is potentially inappropriate was almost two times greater than cholinesterase inhibitor use (19.3% of cohort) which is potentially appropriate for older adults with dementia. Conclusion Among older adults with dementia, sedatives are more commonly prescribed than cholinesterase inhibitors. Sedatives are more often used by women, suggesting that targeted interventions toward reducing sedative use in women is needed. This pattern of sedative use is not in accordance with prescribing guidelines for older adults with dementia.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".