Zopiclone’s Residual Effects on Actual Driving Performance in a Standardized Test: A Pooled Analysis of Age and Sex Effects in 4 Placebo-Controlled Studies
Bibliographic record
Abstract
BACKGROUND: In many European countries, Canada, and Japan, the nonbenzodiazepine zopiclone is now among the most frequently prescribed hypnotic drugs. This finding can be explained by the growing view among physicians that zopiclone is more effective and safer than conventional benzodiazepines. However, in 4 studies using similar procedures, it has been shown that zopiclone 7.5 mg causes moderate to severe impairment in driving performance. OBJECTIVE: The goal of the present article was to review these studies and analyze the pooled data to determine whether the severity of effects is modified by the sex and age of the subjects. METHODS: The driving data of the placebo and zopiclone 7.5 mg evening treatment periods from a total of 4 studies conducted at Maastricht University were included in this pooled analysis. All studies were conducted according to balanced double-blind, crossover designs. The effects on driving were always measured the next morning, between 10 and 11 hours after administration, by using a standardized highway driving test. A total of 101 healthy volunteers of both sexes in equal proportions (with no reports of insomnia) participated. Subjects comprised young volunteers (age range, 21-45 years) in 3 studies and older volunteers (age range, 55-75 years) in the fourth study. RESULTS: Results show that zopiclone 7.5 mg has significant and clinically relevant performance-impairing effects on driving in the morning, until 11 hours after bedtime ingestion. The effects did not differ between male and female subjects and did not increase with age, at least until 75 years. The effects of zopiclone 7.5 mg are comparable to the effects of a mean blood alcohol concentration between 0.5 and 0.8 mg/mL, which has been associated with a 2- to 3-fold increase in the risk of becoming involved in a traffic accident. CONCLUSIONS: We concluded that patients using an evening dose of zopiclone 7.5 mg should avoid activity in skilled work and participation in traffic the morning after intake. General practitioners' beliefs regarding the beneficial safety profile of zopiclone may need adjustment, and patients using zopiclone 7.5 mg should be warned accordingly. There is no need to differentiate warnings about zopiclone's residual impairing effects depending on the sex of the patient.
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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 | 0.020 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.026 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".