Psychotropic Polypharmacy Leading to Reversible Dementia: A Case Report
Bibliographic record
Abstract
Psychotropic polypharmacy presents a diagnostic challenge that may be further complicated by inadequate medication history and underappreciation of the cognitive effects of such polypharmacy. Here we present the case of a 57-year-old man who presented to our memory clinic with progressive cognitive decline and a prior neuropsychological evaluation supporting the diagnosis of a neurodegenerative disorder. He was taking multiple psychotropic medications at the time, but the exact dosages were unclear due to a lack of collateral history. He was also taking prescribed opioids and a combination of buprenorphine and naloxone for pain relief, again with unclear dosages at the time of presentation. Brain imaging and cerebrospinal spinal fluid biomarker testing were negative for Alzheimer pathophysiologic processes. Months later, the patient was taken to the emergency room after an overdose caused by overuse of opioid medications. Once he was taken off all psychoactive medications, the patient's cognitive impairment completely reversed, and he became independent in activities of daily living. Psychotropic polypharmacy can have a myriad of cognitive manifestations which need to be better recognized by clinicians. Deprescription of such medications should be attempted whenever clinically appropriate.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".