The association of antidepressant drug usage with cognitive impairment or dementia, including Alzheimer disease: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To determine if antidepressant drug usage is associated with cognitive impairment or dementia, including Alzheimer disease (AD). METHOD: We conducted a systematic search of Medline, PubMed, PsycINFO, Web of Science, Embase, CINAHL, and the Cochrane Library. An initial screen by abstracts and titles was performed, and relevant full articles were then reviewed and assessed for their methodologic quality. Crude effect estimates were extracted from the included articles and a pooled estimate was obtained using a random effects model. RESULTS: Five articles were selected from an initial pool of 4,123 articles. Use of antidepressant drugs was associated with a significant twofold increase in the odds of some form of cognitive impairment or dementia (OR = 2.17). Age was identified as a likely modifier of the association between antidepressant use and some form of cognitive impairment or AD/dementia. Studies that included participants with an average age equal to or greater than 65 years showed an increased odds of some form of cognitive impairment with antidepressant drug usage (OR = 1.65), whereas those with participants less than age 65 revealed an even stronger association (OR = 3.25). CONCLUSIONS: Antidepressant drug usage is associated with AD/dementia and this is particularly evident if usage begins before age 65. This association may arise due to confounding by depression or depression severity. However, biological mechanisms potentially linking antidepressant exposure to dementia have been described, so an etiological effect of antidepressants is possible. With this confirmation that an association exists, clarification of underlying etiologic pathways requires urgent attention.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".