The association between antidepressant use and deaths from road traffic accidents: a case-crossover study

Population-Based Signals of Antidepressant Drug Interactions Associated With Unintentional Traumatic Injury

Antidepressants are very widely used and associated with traumatic injury, yet little is known about their potential for harmful drug interactions. We aimed to identify potential drug interaction signals by assessing concomitant medications (precipitant drugs) taken with individual antidepressants (object drugs) that were associated with unintentional traumatic injury. We conducted pharmacoepidemiologic screening of 2000-2015 Optum Clinformatics data, identifying drug interaction signals by performing self-controlled case series studies for antidepressant + precipitant pairs and injury. We included persons aged 16-90 years codispensed an antidepressant and ≥ 1 precipitant drug(s), with an injury during antidepressant therapy. We classified antidepressant person-days as either precipitant-exposed or precipitant-unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to calculate confounder adjusted rate ratios (RRs) and accounted for multiple estimation via semi-Bayes shrinkage. We identified 330,884 new users of antidepressants who experienced an injury. Among such persons, we studied concomitant use of 7,953 antidepressant + precipitant pairs. Two hundred fifty-six (3.2%) pairs were positively associated with injury and deemed potential drug interaction signals; 22 of these signals had adjusted RRs > 2.00. Adjusted RRs ranged from 1.06 (95% confidence interval: 1.00-1.12, P = 0.04) for citalopram + gabapentin to 3.06 (1.42-6.60) for nefazodone + levonorgestrel. Sixty-five (25.4%) signals are currently reported in a seminal drug interaction knowledgebase. We identified numerous new population-based signals of antidepressant drug interactions associated with unintentional traumatic injury. Future studies, intended to test hypotheses, should confirm or refute these potential interactions.

Association between opioid analgesic plus benzodiazepine use and death: A case-crossover study

OBJECTIVE

We aimed to investigate whether concomitant use of benzodiazepines and opioids is associated with an increased risk of death in a population-based case-crossover setting.

METHODS

We conducted a case-crossover study using the National Sample Cohort database. We introduced a 30-day hazard period before the onset of death and three consecutive previous 30-day control periods with a 30-day washout period. The use of opioids and/or benzodiazepines during the hazard period was compared with that in the three control periods. We performed the conditional logistic regression analysis to estimate the adjusted odds ratios (aORs) and their 95% confidence intervals (CIs).

RESULTS

A total of 13,161 individuals who previously used benzodiazepines or opioids and died were included in the study. The risk of death was higher in patients with concomitant use of benzodiazepines and opioids (aOR, 1.86; 95% CI, 1.71-2.02) than in those who used either benzodiazepines or opioids only. In the subgroup analysis among concomitant users, the mortality risks were highest in patients aged less than 20 years (aOR, 3.85; 95% CI, 1.65-8.99), male patients (aOR, 2.20; 95% CI, 1.93-2.51), and patients with renal disease (aOR, 2.42; 95% CI, 1.57-3.74).

CONCLUSION

In this study, concomitant use of benzodiazepines and opioids was associated with a higher risk of death compared with use of a single drug. The risks and benefits of co-prescribing of benzodiazepines and opioids must be weighed carefully.

Factors associated with serious vehicular accidents: A cross-sectional study in hospital emergency rooms

AIMS

Pictograms on medicine boxes warn of potential drug-related driving hazard; we studied their association with serious accidents.

METHODS

Prospective study in emergency departments of the hospitals in Bordeaux and Périgueux (France), of drivers with serious (admitted at least 24 hours) or nonserious vehicular accidents. Minors, passengers, pedestrians or subjects incapable of answering an interview were excluded. Interviews ascertained driver and accident characteristics, use of drugs with or without pictograms, use of alcohol and abuse substances, sleepiness, distractions, and mind wandering at the time of the accident, RESULTS: Between 18 October 2016 and 26 December 2018, 1200 of the 6212 drivers admitted to the hospital emergency rooms, 741 nonserious, 459 serious, were interviewed. Serious accidents were associated with male sex (odds ratio 1.89, 95% confidence interval [1.36-2.64]), age above 60 years (3.64 [2.21-6.00]), driving on local roads (3.34 [2.34-4.76]), driving a motorcycle (3.39 [2.29-5.00]), having drunk alcohol within 6 hours (2.89 [1.85-4.51]) and using a drug with a pictogram during the 24 hours previous to the accident (1.57 [1.06-2.32]). From 207 police reports, 101 drivers were not responsible, and 106 were responsible, associated with age below 40 years, driving in overcast or rainy weather (2.62 [1.29-5.33]), on local roads (3.89 [1.90-7.95]), and use of at least 1 pictogram drug in the previous week (3.12 [1.31-7.41]).

CONCLUSION

The known risks of alcohol and pictogram drugs, of riding motorcycles and using local roads were confirmed. As measured, behavioural sleepiness did not predict accidents.