The risk of cognitive impairment in older community-dwelling women after benzodiazepine use
Bibliographic record
Abstract
SIR—Long-term benzodiazepine (BZD) use has been associated with cognitive impairment that was reversible [1, 2] or not [3]. Few cohort studies have examined the association between BZD use and incident cognitive decline or dementia [4]. Chronic BZD users had a significantly increased risk of cognitive impairment, while episodic or recurrent users had not [5]. In the French community-dwelling persons, BZD use was associated with an increased risk of dementia [6]. Nevertheless, the study design did not allow us to rule out a protopathic bias, whereby BZDs could be prescribed for early symptoms of cognitive impairment resulting in a spurious association. Another study reported a lower incidence of dementia in older persons using BZDs [7]. Since subjects exposed only at baseline were not distinguished from those exposed both at baseline and follow-up assessments, a depletion of susceptible effect may explain the protective effect finding [8], as BZDs may have been discontinued in subjects with incident cognitive impairment. To help clarify the association between BZD use and cognitive decline, a case-control analysis was carried out using data from a large representative cohort of Canadian older women, in order to examine the association between BZD use and the occurrence of cognitive decline including dementia.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".