Increased Odds of Cognitive Impairment in Adults with Depressive Symptoms and Antidepressant Use
Bibliographic record
Abstract
INTRODUCTION: The relationship between antidepressant use and class with cognition in depression is unclear. This study aimed to evaluate the association of cognition with depressive symptoms and antidepressant use (class, duration, number). METHODS: Data from the National Health and Nutrition Examination Survey were examined for cognitive function through various tests and memory issues through the Medical Conditions questionnaire. Depressive symptoms were assessed using the Patient Health Questionnaire-9. RESULTS: A total of 2867 participants were included. Participants with depressive symptoms had significantly higher odds of cognitive impairment (CI) on the animal fluency test (aOR=1.89, 95% CI=1.30, 2.73, P=0.002) and Digit Symbol Substitution test (aOR=2.58, 95% CI=1.34, 4.9, P=0.007), as well as subjective memory issues (aOR=7.25, 95% CI=4.26, 12.32, P<0.001) than those without depression. There were no statistically significant associations between any of the CI categories and depressive symptoms treated with an antidepressant and antidepressant use duration. Participants who were using more than one antidepressant had significantly higher odds of subjective memory issues than those who were using one antidepressant. Specifically, users of atypical antidepressants, selective serotonin reuptake inhibitors, or tricyclic antidepressants (TCAs) had significantly higher odds of subjective memory issues in comparison to no antidepressants, with TCAs showing the largest odds (aOR=4.21, 95% CI=1.19, 14.86, P=0.028). DISCUSSION: This study highlights the relationship between depressive symptoms, antidepressant use, and CI. Future studies should further evaluate the mechanism underlying this phenomenon.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".