Association Between Z Drugs Use and Risk of Cognitive Impairment in Middle-Aged and Older Patients With Chronic Insomnia
Bibliographic record
Abstract
Background: Benzodiazepines (BZDs) and Non-BZDs (NBZDs) have been widely used for patients with chronic insomnia. Long-term uses of BZDs may cause cognitive impairment and increase the risk for dementia in older patients. NBZD as an agonist of the GABA A receptor complex includes eszopiclone, zopiclone, zolpidem, and zaleplon, also collectively known as Z drugs. However, evaluations for an association between cognitive impairment and Z drug use have been limitedly performed. This study aimed to investigate the association between the risk of cognitive decline and exposure to Z drugs in middle-aged and older patients with chronic insomnia. Methods: Investigations were performed on patients with chronic insomnia who visited the outpatient Department of Neurology, Beijing Friendship Hospital, and were assessed for the global cognitive function (MoCA) and memory (AVLT), executive function (TMT-B), visuospatial ability (CDT), verbal function (BNT-30), and attention (DST). Multiple regression analysis was conducted to determine the independent factors of cognition and evaluated the effect of Z drug use (zolpidem and zopiclone) on cognition. Results: A total of 120 subjects were identified. In our analysis, BZD exposure density ( P = 0.025, OR = 1.43, 95% CI, 1.25–1.86) was an independent risk factor of cognitive impairment in middle-aged and older patients with chronic insomnia. Neither Z drug use ( P = 0.103) nor Z drug exposure density ( P = 0.765) correlated with global cognitive function. Moreover, there was a positive association between Z drug use and attention [( P = 0.002, OR = 0.42, 95% CI, 0.24–0.73)]. Additionally, income level ( P = 0.001, OR = 0.23, 95% CI, 0.10–0.53), severity of insomnia ( P = 0.019, OR = 1.20, 95% CI, 1.03–1.40) and age ( P = 0.044, OR = 1.07, 95% CI, 1.00–1.14) were also independent factors of global cognitive function. Conclusion: BZD exposure density was an independent risk factor of cognitive impairment in middle-aged and older patients with chronic insomnia, but no correlation was found between Z drug use and cognitive impairment. Moreover, the use of Z drugs seemed to be associated with protection for attention. The use for prescription of BZDs, in this case, should be avoided or limited to low doses. Due to the addiction and tolerance, Z drugs should also be prescribed with great caution in middle-aged and elderly patients.
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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".