Cognitive toxicity of drugs used in the elderly
Bibliographic record
Abstract
The aged are an extremely heterogeneous population that is growing worldwide, included are healthy and agile individuals in their early sixties, as well as an increasing number of people over the age of 35. Pharmacotherapy is expected to continue its prominent role in the medical management of a wide range of conditions that affect older people. Adverse consequences of all kinds complicate the use of medications, and such events seem to increase in incidence with polypharmacy. Cognitive impairment can occur during the course of treatment with a wide range of medications and can have a variety of presentations, Both the number of concurrent medications that older individuals routinely use and physiologic changes in these patients render them more susceptible to developing cognitive toxicity. Most of the frequently implicated medications carry documentation of their ability to cause cognitive disturbances in their package labeling, suggesting that the level of vigilance for adverse effects during the course of their use should always be high. Such caution can be used to guide appropriate drug treatment of the aged so that clinicians do not need to opt for undertreatment to avoid toxicity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".