Association between road traffic accidents and drugs belonging to the antiseizure medications class: A pharmacovigilance analysis in VigiBase

AIMS

Due to their central mechanism of action, antiseizure medications (ASMs) could lead to adverse effects likely to impair driving skills. Their extended use to neuropsychiatric disorders makes it a class of drugs to monitor for their road traffic accidental (RTA) potential. We aimed to assess the reporting association between ASMs and RTAs using the World Health Organization pharmacovigilance database (VigiBase).

METHODS

We performed a disproportionality analysis to compute adjusted reporting odds ratios to evaluate the strength of reporting association between ASMs and RTAs. A univariate analysis using the reporting odds-ratio was used to assess drug-drug interactions between ASMs and RTAs.

RESULTS

There were 1 341 509 reports associated with at least 1 ASM in VigiBase of whom 2.91‰ were RTAs reports. Eight ASMs were associated with higher reporting of RTAs compared to others (ranging from 1.35 [95% confidence interval 1.11-1.64] for lamotrigine to 4.36 [95% confidence interval 3.56-5.32] for cannabis). Eight significant drug-drug interactions were found between ASMs and the onset of RTA, mainly involving CYP450 induction.

CONCLUSION

A significant safety signal between RTAs and some ASMs was identified. Association of several ASMs might further increase the occurrence of RTA. ASMs prescription in patients with identified risk factors of RTA should be considered with caution. Study number: ClinicalTrials.gov, NCT04480996.

Medical impairment and road traffic crashes among older drivers in Sweden - A national, population-based, case-control study

BACKGROUND

Several medical conditions are known to impair sensory, cognitive and motor functions and are associated with road traffic crashes (RTC). For the drivers of today, we lack updated knowledge on how driving-impairing conditions are associated with RTCs, across all driving-impairing conditions in a given population. We aim to determine this among older drivers in Sweden.

METHODS

A national, population register-based, matched case-control study comparing acknowledged driving-impairing health conditions among all older drivers (65 years or older) involved in an injurious RTC in the period 2011-2016 (n = 13,701) with those of controls: older drivers not involved in any RTC (n = 26,525) matched to the cases by age, sex and residential area. The medical conditions, extracted from the National Patient Register from 1997 up until date of RTC, were identified based on ICD-10 diagnosis codes and categorized into the 13 groups of medical conditions listed in the Swedish driver's license regulations. Conditional logistic regression was used to estimate crude and adjusted odds ratios (ORs) with 95% confidence intervals.

RESULTS

Unadjusted ORs for RTC were increased for all conditions. After taking the other 12 medical conditions into account, the ORs remained significant in 11 out of the 13. A strong association was found for the group "ADHD and autism spectrum disorders" (OR 2.79, CI 1.47-5.30), although with very low prevalence among cases (0.2%). Moderate associations were found for three conditions with a case prevalence between 1.3% and 8.5%: epilepsy and seizure disorders (OR 1.53, CI 1.25-1.89), substance abuse and dependence (OR 1.45, CI 1.29-1.63), psychological diseases and mental disorders (OR 1.28, CI 1.18-1.39) and for one condition with a case prevalence of 14.7%, diabetes (OR 1.28, CI 1.20-1.36).

CONCLUSIONS

In Sweden, in the current generation of older drivers, acknowledged driving-impairing medical conditions at the national and European levels remain a concern. After adjustment for one another, all but 2 of the conditions are associated with RTCs albeit to varying degrees and more pronounced in the age group 65-79 compared to 80 or older. To promote and sustain older people's mobility, addressing this issue will require a blend of interventions where, hopefully, technological and infrastructural innovations may help counteracting individual health-related shortcomings.

Medicine consumptions and occupational road risk

BACKGROUND

Whereas an increased risk of road traffic crashes has been highlighted as linked to some medicine consumptions, there is no available data on this risk according to the type of journey (private, commuting or mission). Drivers on occupational journey (commuting or mission) are likely to have different coping behaviors related to the use of medicines than drivers on private journey. The aim of our study was to investigate the association between exposure to ten classes of medicines and the risk of being responsible for a road traffic crash according to the type of journey (private, commuting or mission).

METHODS

The data used came from three French national databases: the national police database of injurious crashes, the police reports and the national health care insurance database. A total of 179,269 drivers aged between 18 and 65 years old involved in an injurious crash in France between July 2005 and December 2015 were included in the analyses. Logistic regression models stratified by journey were used to estimate the Odds Ratios (OR) and 95 % confidence intervals (95 % CI), adjusted for potential confounding factors.

RESULTS

Medicines exposure levels were generally lower for drivers during occupational journeys, the risk of being responsible for a road traffic crash seems to be higher on commuting or mission journeys than on private journeys for four medicines. Indeed, for antiepileptics the OR was 1.59 [1.01-2.51] for mission journeys, 1.63 [1.24-2.15] for commuting journeys, and 1.47 [1.25-1.73] for private journey. For psycholeptics the OR was 1.02 [0.80-1.28] for mission journey, 1.19 [1.03-1.39] for commuting and 1.17 [1.08-1.26] for private journey. For psychoanaleptics OR was 1.35 [1.02-1.78] for mission journeys, 1.37 [1.17-1.60] for commuting journeys and 1.26 [1.14-1.40] for private journeys. Finally, for other nervous system drugs OR reached 2.04 [1.35-3.07] for mission journeys compared to 1.43 [1.21-1.70] for private journeys.

CONCLUSION

Our results encourage the implementation of preventive measures about some treatments and diseases in the context of occupational journeys.

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.

Epilepsy, antiepileptic drugs, and serious transport accidents: A nationwide cohort study

OBJECTIVES

To investigate the association between epilepsy and antiepileptic drugs and serious transport accidents requiring emergency care or resulting in death.

METHODS

We identified 29,220 individuals 18 years or older with epilepsy without cerebral palsy or intellectual disability and 267,637 matched controls using Swedish registers. This nationwide cohort was followed from 2006 to 2013 for serious transport accidents. We used Cox regression to analyze the risk of serious transport accidents between individuals with epilepsy and matched controls, and then stratified Cox regression to compare the risk during periods of medication with the risk during nonmedication period within the same individual with epilepsy. We adjusted for civil status, employment, education, living area, psychiatric disorders prior to the start of follow-up, and psychotropic medication.

RESULTS

Compared to matched controls, individuals with epilepsy were at increased risk of serious transport accidents (hazard ratio [HR] 1.37; 95% confidence interval [CI] 1.29-1.46). There were increased risks of pedestrian accidents (HR 2.24, 95% CI 1.69-2.97), bicycle accidents (HR 1.68, 95% CI 1.49-1.89) and car accidents (HR 1.31, 95% CI 1.19-1.44). However, among patients with a diagnosis of epilepsy, use of antiepileptic drugs did not influence the risk of serious transport accidents in population-level comparisons (HR 0.97; 95% CI 0.85-1.11) or within-individual comparisons (HR 0.99; 95% CI 0.69-1.42).

CONCLUSION

Serious transportation accidents were more common in individuals with epilepsy, but this risk was independent of use of antiepileptic drugs.

Risks of road injuries in patients with bipolar disorder and associations with drug treatments: A population-based matched cohort study

OBJECTIVE

Using a nation-wide, population-based dataset, we aimed to investigate the risk of road injury among individuals with bipolar disorder (BD) compared to individuals without BD. In addition, we investigated the putative moderating effects of prescription for lithium, anticonvulsants, antidepressants, and/or first- or second-generation antipsychotic agents on the association between BD and risk of road injury.

METHOD

As part of an16-year longitudinal cohort study, we compared the risk of road injuries among study subjects aged 16 and above with a diagnosis of BD, with ten age- and sex-matched sample of individuals without BD. Individuals were compared on measures of incidence on road injuries using medical claims data based on the ICD-9-CM codes: E800~807, E810~817, E819~830, E840~848. Time dependent Cox regression models were used to adjust for time-varying covariates such as age, and medication uses. Hazard ratios before and after adjusting for age, sex, other comorbidities, and drug use were calculated.

RESULTS

3953 people with BD were matched with 39,530 controls from general population. Adjusted hazard ratios revealed a 1.66-fold (95% CI 1.40-1.97) increase in risk of road injuries among bipolar subjects when compared to controls. Female gender, older age (i.e. over 80), residence in areas of highest levels of urbanization, and use of antidepressants were associated with a lower risk of road injuries.

CONCLUSIONS

In this large, national, population-based cohort, BD was associated with an elevated risk of road injuries. However, prescriptions of antidepressants might help mitigate the foregoing risk.

The use and safety of medications known to affect driving in Jordan: A cross-sectional study

OBJECTIVES

The aim of this study was to estimate the main driving-impairing medications used by drivers in Jordan, the reported frequency of medication side effects, the frequency of motor vehicle crashes (MVCs) while using driving-impairing medicines, as well as factors associated with MVCs.

METHODS

A cross-sectional study involving 1,049 individuals (age 18-75 years) who are actively driving vehicles and taking at least one medication known to affect driving (anxiolytics, antidepressants, hypnotics, antiepileptics, opioids, sedating antihistamines, hypoglycemic agents, antihypertensives, central nervous system [CNS] stimulants, and herbals with CNS-related effects) was conducted in Amman, Jordan, over a period of 8 months (September 2013-May 2014) using a structured validated questionnaire.

RESULTS

Sixty-three percent of participants noticed a link between a medicine taken and feeling sleepy and 57% stated that they experience at least one adverse effect other than sleepiness from their medication. About 22% of the participants reported having a MVC while on medication. Multiple logistic regression analysis showed that among the participants who reported having a crash while taking a driving-impairing medication, the odds ratios were significantly higher for the use of inhalant substance (odds ratio [OR] = 2.787, P = .014), having chronic conditions (OR = 1.869, P = .001), and use of antiepileptic medications (OR = 2.348, P = .008) and significantly lower for the use of antihypertensives (OR = 0.533, P = .008).

CONCLUSION

The study results show high prevalence of adverse effects of medications with potential for driving impairment, including involvement in MVCs. Our findings highlight the types of patient-related and medication-related factors associated with MVCs in Jordan, such as inhalant use, presence of chronic conditions, and use of antiepileptics.

[Drug use and driving]

Some drugs are known to impair driving because they can change the vision or hearing, and/or disrupt the intellectual or motor abilities: impaired vigilance, sedation, disinhibition effect, the coordination of movement disorders and the balance. The doctor during prescribing and the pharmacist during deliverance of drug treatment should inform their patients of the potential risks of drugs on driving or operating machinery. The driver has direct responsibility, who hired him and him alone, to follow the medical advice received. The pictograms on the outer packaging of medicinal products intended to classify substances according to their risk driving: The driver can whether to observe simple precautions (level one "be prudent"), or follow the advice of a health professional (level two "be very careful"), or if it is totally not drive (level three "danger caution: do not drive"). This classification only evaluates the intrinsic danger of drugs but not the individual variability. Medicines should be taken into account also the conditions for which the medication is prescribed. It is important to inform the patient on several points.

Driving under the influence, public policy, and pharmacy practice

Motor vehicle accidents due to prescription drug impairment have increased in the past decade. Typically, impairment is associated with medications causing excessive drowsiness, such as opioids or benzodiazepines, but the scope of driving under the influence (DUI)-drug charges is reaching into medications that are not typically considered impairing, such as antipsychotics, antiepileptics, and mood stabilizers. Data associating medication use with driving impairment are growing, especially with agents not typically thought of as impairing. Forty-three states currently train drug recognition experts who employ a 12-step evaluation to detect the presence of drug impairment. Seventeen states have instituted "per se" laws, which make it illegal to drive with the presence of drugs or metabolites in the body. Pharmacists should recognize an ethical, professional, and perhaps legal responsibility to inform patients of the risk of impaired driving with prescription agents. Pharmacists should reconsider how they are counseling patients on medication impairment and lower their threshold for warning a patient of potential impairment, expanding to agents typically not thought of as impairing. Pharmacists are in a position to ensure that patients fully understand the risk of impaired driving and the potential for DUI prosecution.

Long-term chronic diseases and crash responsibility: a record linkage study

OBJECTIVE

To assess the population impact of chronic conditions on the risk of road traffic crashes.

METHODS

Data from three French national databases were extracted and matched: the national health care insurance database, police reports and the national police database of injurious crashes. Exposure to chronic conditions were compared between responsible and nonresponsible drivers. Analysis was performed using the Lasso (least absolute shrinkage and selection operator) method.

RESULTS

69,630 drivers involved in an injurious crash in France between 2005 and 2008, were included. 6210 (8.9%) were suffering from at least one long-term disease. When adjusted for prescription of medicines, blood alcohol, demographic driver characteristics and crash characteristics, increased risk of being responsible for a crash was found in drivers registered in the French healthcare database with the following long-term diseases: epilepsy (odds ratio [OR]=2.53 [1.53-4.20]), type 1 diabetes (OR=1.47) [1.12-1.92], alcoholic liver disease (OR=3.37 [1.40-8.13]), asthma (OR=1.72 [1.13-2.60]) and specific personality disorders (OR=1.35 [1.05-1.74]). No association was found for cardiovascular diseases or Alzheimer's disease.

CONCLUSION

The results update the list of medical conditions that may impair driving skills. However, results should be considered cautiously with regards to potential regulatory driving judgments that could have a negative impact on patients' social life.

Variable selection on large case-crossover data: application to a registry-based study of prescription drugs and road traffic crashes

PURPOSE

In exploratory analyses of pharmacoepidemiological data from large populations with large number of exposures, both a conceptual and computational problem is how to screen hypotheses using probabilistic reasoning, selecting drug classes or individual drugs that most warrant further hypothesis testing.

METHODS

We report the use of a shrinkage technique, the Lasso, in the exploratory analysis of the data on prescription drugs and road traffic crashes, resulting from the case-crossover matched-pair interval approach described by Orriols and colleagues (PLoS Med 2010; 7:e1000366). To prevent false-positive results, we consider a bootstrap-enhanced version of the Lasso. To highlight the most stable results, we extensively examine sensitivity to the choice of referent window.

RESULTS

Antiepileptics, benzodiazepine hypnotics, anxiolytics, antidepressants, antithrombotic agents, mineral supplements, drugs used in diabetes, antiparkinsonian treatment, and several cardiovascular drugs showed suspected associations with road traffic accident involvement or accident responsibility.

CONCLUSION

These results, in relation to other findings in the literature, provide new insight and may generate new hypotheses on the association between prescription drugs use and impaired driving ability.