Use of sedative‐hypnotic medications and risk of dementia: A systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: Growing evidence suggests an association between the use of sedative-hypnotic medications and risk of dementia. The aim of this study is to examine this association using a meta-analysis approach. METHODS: MEDLINE (PubMed) and Scopus were systematically searched for studies published in English only. The quality of studies was evaluated using the Newcastle-Ottawa scale, and an overall odds ratio was pooled using a random-effects model. RESULTS: A total of 35 articles were included in the analysis. Pooled odds ratios (ORs) for dementia from all records were (OR; 1.33, 95% CI 1.19-1.49) for benzodiazepine (BZD) combined use (Subgroup-1), (OR: 1.46, 95% CI 1.23-1.73) for short-acting BZD use (Subgroup-2), (OR: 1.72, 95% CI 1.48-1.99) for long-acting BZD use (Subgroup-3), (OR: 1.13, 95% CI 0.97-1.32) for BZDs without specification of duration of action (Subgroup-4), (OR: 1.64, 95% CI 1.13-2.38) for the combined BZDs and Z-drugs, (OR: 1.43, 95% CI 1.17-1.74) for Z-drugs only, (OR: 1.14, 95% CI 0.88-1.46) for antidepressant use, (OR: 0.97, 95% CI 0.68-1.39) for antipsychotic use and (OR: 0.98, 95% CI 0.85-1.13) for anticonvulsant use. When sensitivity analysis was performed, association between overall use of BZDs and short-acting BZDs with the increased risk of dementia disappeared after exclusion of studies that were not adjusted for age covariate (OR: 1.2, 95% CI 1.0-1.44) and (OR: 1.22, 95% CI 0.75-2.01), respectively. Adjustment for protopathic bias by introduction of a lag period showed no evidence of increased risk of dementia with the use of BZDs (Subgroup-1) (OR: 1.14, 95% CI 0.82-1.58), Z-drugs (OR: 1.29, 95% CI 0.78-2.13), and combined BZDs and Z-drugs (OR: 1.51, 95% CI 0.91-2.53). Combined use of BZDs and Z-drugs showed more positive association when only studies of non-user design were analysed (OR: 2.75, 95% CI 2.23-3.39). CONCLUSIONS: All the investigated sedative-hypnotics showed no association with increased risk of dementia except for BZDs. However, the observed association with BZDs did not persist after exclusion of studies with potential reverse causation and confounding by indication. Therefore, this association needs to be assessed carefully in future research.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.047 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".