Are Antipsychotic Prescribing Patterns Different in Older and Younger Adults?: A Survey of 1357 Psychiatric Inpatients in Toronto
Bibliographic record
Abstract
OBJECTIVE: To compare antipsychotic prescribing patterns in younger (aged 59 years or younger) and older (aged 60 years or older) patients with psychotic or mood disorders. METHOD: Pharmacy records of all patients discharged from the Centre for Addiction and Mental Health over a 21-month period were reviewed. A total of 1357 patients who were prescribed an antipsychotic at the time of their discharge were included in the analysis (956 with a primary psychotic disorder and 401 with a primary mood disorder). World Health Organization-defined daily doses were used as the standardized dosing unit. RESULTS: Both in patients with a primary psychotic disorder and in patients with a primary mood disorder, the prescribing patterns were similar in older and younger patients, with no statistical difference in the proportions receiving first-generation antipsychotics, second-generation antipsychotics (SGAs), multiple antipsychotics, or long-acting (depot) antipsychotics. Overall, the mean daily antipsychotic doses were lower only in the older group of patients with a primary mood disorder. However, the mean dose of SGAs was about 30% lower in older patients in both diagnostic groups. Regardless of age, patients with a mood disorder were prescribed lower doses of antipsychotics than those with a psychotic disorder. CONCLUSIONS: Our data suggest that older patients are prescribed lower antipsychotic dosages primarily when using SGAs. This finding emphasizes the need for dose-finding studies assessing both the efficacy and the safety of antipsychotics in older patients with a psychotic or mood disorder.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".