Association between Benzodiazepine Use and Dementia: Data Mining of Different Medical Databases
Bibliographic record
Abstract
Purpose: Some studies have suggested that the use of benzodiazepines in the elderly is associated with an increased risk of dementia. However, this association might be due to confounding by indication and reverse causation. To examine the association between benzodiazepine anxiolytic drug use and the risk of dementia, we conducted data mining of a spontaneous reporting database and a large organized database of prescriptions. Methods: Data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) from the first quarter of 2004 through the end of 2013 and data from the Canada Vigilance Adverse Reaction Online Database from the first quarter of 1965 through the end of 2013 were used for the analyses. The reporting odds ratio (ROR) and information component (IC) were calculated. In addition, prescription sequence symmetry analysis (PSSA) was performed to identify the risk of dementia after using benzodiazepine anxiolytic drugs over the period of January 2006 to May 2014. Results: Benzodiazepine use was found to be associated with dementia in analyses using the FAERS database (ROR: 1.63, 95% CI: 1.61-1.64; IC: 0.66, 95% CI: 0.65-0.67) and the Canada Vigilance Adverse Reaction Online Database (ROR: 1.88, 95% CI: 1.83-1.94; IC: 0.85, 95% CI: 0.80-0.89). ROR and IC values increased with the duration of action of benzodiazepines. In the PSSA, a significant association was found, with adjusted sequence ratios of 1.24 (1. 05-1.45), 1.20 (1.06-1.37), 1.23 (1.11-1.37), 1.34 (1.23-1.47), 1.41 (1.29-1.53), and 1.44 (1.33-1.56) at intervals of 3, 6, 12, 24, 36, and 48 months, respectively. Furthermore, the additional PSSA, in which patients who initiated a new treatment with benzodiazepines and anti-dementia drugs within 12-and 24-month periods were excluded from the analysis, demonstrated significant associations of benzodiazepine use with dementia risk. Conclusion: Multi-methodological approaches using different methods, algorithms, and databases suggest that long-term use of benzodiazepines and long-acting benzodiazepines are strongly associated with an increased risk of dementia.
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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 | 0.003 | 0.017 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".