Persistence of Antipsychotic Treatment in Elderly Dementia Patients: A Retrospective, Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: Antipsychotics are commonly used to manage behavioral and psychological symptoms of dementia. Concerns over their safety and efficacy in this role have resulted in antipsychotics typically being recommended for short-term usage only when used among dementia patients. However, there is little work examining the duration of antipsychotic treatment in the elderly dementia patient population. OBJECTIVE: To determine the persistence of use of antipsychotics in elderly dementia patients and the role of dose on therapy duration. METHODS: A retrospective, population-based cohort study using administrative data, including dispensing records from a provincial public drug program, from Ontario, Canada between 2009 and 2012. Elderly dementia patients newly initiated onto antipsychotics were followed until drug discontinuation, death, 2-year follow-up, or end of study. Competing risk analysis was performed to determine time to discontinuation, stratified by categories of initial dose. RESULTS: < 0.0001). CONCLUSION: Approximately half of elderly dementia patients treated with antipsychotics discontinue within 2 years, with those on higher doses more likely to discontinue. However, the number of patients remaining on therapy represents a serious public health concern.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".