P.019 Safe prescribing of antipsychotic drugs in the elderly - Parkinson Disease
Bibliographic record
Abstract
Background: The Canadian Guideline for Parkinson Disease (PD) indicates clozapine and quetiapine are considered the only safe antipsychotics for people with PD, to avoid potentially exacerbating motor symptoms. In response to safety events in our centre, we explore contraindicated antipsychotic prescriptions being administered to hospital inpatients with PD to determine common factors and develop approaches to prevent future occurrences. Methods: Following a privacy impact analysis, the Interior Health Quality Improvement & Patient Safety Office identified inpatients at Kelowna General Hospital, between December 2018 and June 2021, with a coded diagnosis of PD. Pharmacy medication order and dispensing data were cross-referenced to determine patients exposed to a contraindicated antipsychotic for further chart analysis. Results: Of the 140 admissions with a PD diagnosis, 17 had at least one contraindicated antipsychotic prescribed or dispensed (12.1%). Loxapine (7) and haloperidol (6) were the most frequently prescribed. This occurred despite a diagnosis of PD being noted on admission in 14 cases, and 13 cases were known to be taking levodopa. Conclusions: These results demonstrate additional safety measures are needed to reduce the frequency of contraindicated antipsychotic prescriptions in this population. We propose developing a stepwise plan for behaviour de-escalation and pharmacological management.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.008 | 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".