Psychotropic prescribing in the oldest old attending a geriatric psychiatry service: a retrospective, cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: More people are living beyond their 90s, yet this group has not been much studied. This study aimed to describe a sample of non-agenarians and centerians attending an old age psychiatry service with a focus on pharmacotherapy. METHODS: Retrospective, cross-sectional survey of patients aged >90 in contact with the Department of Old Age Psychiatry in a university hospital over a 1-year period. Results were compared with the Beers, the Canadian and Screening Tool of Older Persons' potentially inappropriate Prescriptions (STOPP) criteria. RESULTS: A total of 65 nonagenarians or centerians were identified (mean age 93, 82% female). The majority (65%) resided in a nursing home; dementia was the most common diagnosis (77%), followed by depression (29%). The most commonly prescribed psychotropics were antidepressants (58%), followed by antipsychotics (45%), hypnotics (42%), anti-dementia agents (31%) and anxiolytics (26%). Overall, patients were on a mean of 2.1 (S.D. 1.3, range 0-5) psychotropics and 4.99 (S.D. 2.7, range 0-11) non-psychotropics. Mean Mini Mental State Examination (MMSE) score was 15 (S.D. 8.1). Increasing anticholinergic burden was negatively associated with MMSE scores (B = -1.72, p = 0.013). Residing in a nursing home was associated with a higher rate of antidepressant [OR 5.71 (95% CI 1.9-17.4)], anxiolytic [OR 13.5 (95% CI 1.7-110.4)] and antipsychotic [OR 3.4 (95% CI 1.1-10.4)] use. Potentially inappropriate prescribing included long-term benzodiazepine use (26%) and long-term antipsychotic use (25%). CONCLUSIONS: Our sample had a high psychiatric morbidity burden with high levels of psychotropic use. Ongoing review and audit of psychotropic use in elderly patients can identify potentially inappropriate prescribing in a group vulnerable to high levels of polypharmacy and extended psychotropic use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".