Antipsychotic Medications and Drug‐Induced Movement Disorders Other Than Parkinsonism: A Population‐Based Cohort Study in Older Adults
Bibliographic record
Abstract
OBJECTIVES: To study the relationship between initiating therapy with an antipsychotic medication and a subsequent new diagnosis of a drug-induced movement disorder other than parkinsonism in older adults with dementia. DESIGN: Retrospective, population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Ontario residents aged 66 and older with a diagnosis of dementia newly started on treatment with typical or atypical antipsychotic therapy. MEASUREMENT: Estimated relative risk of developing a drug-induced movement other than parkinsonism in the 1-year follow-up period after starting therapy with an antipsychotic medication. RESULTS: From April 1, 1997, to March 31, 2001, 21, 835 older adults with dementia who were newly started on antipsychotic medications were identified. Nine thousand seven hundred ninety subjects were started on atypical antipsychotics and 12,045 subjects started on typical antipsychotics. Demographic characteristics were similar between the groups. There were 5.24 cases of tardive dyskinesia (TD) or other drug-induced movement disorder per 100 person-years on therapy with a typical antipsychotic and 5.19 cases per 100 person-years on therapy with an atypical antipsychotic. The risk of developing drug-induced movement disorder while being treated with an atypical agent was not statistically different from that with a typical antipsychotic (relative risk=0.99, 95% confidence interval=0.86-1.15; P<.93). CONCLUSION: Older adults with dementia who are treated with typical or atypical antipsychotic therapy are at risk for developing TD and other drug-induced movement disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".