10 research outputs found
Road traffic crash risk associated with prescription of hydroxyzine and other sedating H1-antihistamines: A responsibility and case-crossover study
Background H1 antihistamines differ from each other by their ability to cross the blood-brain barrier. The resulting sedating effect can be sought in therapy but may be a driving hazard. The aim of this study was to estimate the impact of sedating H1-antihistamines on the risk of road traffic crash, with a particular focus on hydroxyzine which is also indicated as an anxiolytic in France. Methods The study consisted in extracting and matching data from three French nationwide databases: the national healthcare insurance database, police reports and the police national database of injurious crashes. All sedating H1-antihistamines, including hydroxyzine, were considered in the study. A case-control analysis, in which responsible drivers were cases and non-responsible were controls was performed. A case-crossover analysis, comparing for the same subject exposure during a period immediately before the crash with exposure during an earlier period, was also conducted. Results The extraction and matching procedures over the July 2005-December 2011 period led to the inclusion of 142,771 drivers involved in an injurious road traffic crash. The responsibility study found an increased risk of being responsible for an injurious road traffic crash in hydroxyzine users who were registered with a long-term chronic disease (mostly psychiatric disorders) on the day of the crash (OR=1.67 [1.22-2.30]). Among them, the risk was even higher in drivers with highest exposure levels (OR=2.60 [1.23-5.50]). There was no impact of sedating H1 antihistamine treatment initiation on the risk of crash. Conclusion Even if it is difficult to disentangle the part of the increased risk that would be causally related to hydroxyzine and the part related to behaviours of patients with a heavy psychiatric disorder, our study raises the alarm on the crash risk linked to hydroxyzine utilization in countries in which the anxiolytic indication is widespread
Road traffic crash risk associated with benzodiazepine and z-hypnotic use after implementation of a colour-graded pictogram: a responsibility study
Aims To assess potential change in medicine exposure and association with the risk of road traffic crash across a time period that started before the implementation of a grading system warning of the effect of medicine on driving performance. 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. Drivers involved in such crashes in France, from July 2005 to December 2011 and identified by their national identifier, were included. Association with the risk of crash was estimated using a case?control analysis comparing benzodiazepine and z-hypnotic use among drivers responsible or not responsible for the crash. Results Totals of 69?353 responsible and 73?410 non-responsible drivers involved in an injurious crash were included. Exposure to benzodiazepine anxiolytics was associated with an increased risk of being responsible for a road traffic crash during the pre-intervention period (OR=1.42 [1.24?1.62]). The association disappeared in the post-intervention period, but became significant again thereafter. The risk of being responsible for a crash increased in users of z-hypnotics across the study period. Conclusions Our results question the efficacy of the measures implemented to promote awareness about the effects of medicines on driving abilities. Prevention policies relating to the general driving population, but also to healthcare professionals, should be reviewed
Prescription medicine use by pedestrians and the risk of injurious road traffic crashes: A case-crossover study
<div><p>Background</p><p>While some medicinal drugs have been found to affect driving ability, no study has investigated whether a relationship exists between these medicines and crashes involving pedestrians. The aim of this study was to explore the association between the use of medicinal drugs and the risk of being involved in a road traffic crash as a pedestrian.</p><p>Methods and findings</p><p>Data from 3 French nationwide databases were matched. We used the case-crossover design to control for time-invariant factors by using each case as its own control. To perform multivariable analysis and limit false-positive results, we implemented a bootstrap version of Lasso. To avoid the effect of unmeasured time-varying factors, we varied the length of the washout period from 30 to 119 days before the crash. The matching procedure led to the inclusion of 16,458 pedestrians involved in an injurious road traffic crash from 1 July 2005 to 31 December 2011. We found 48 medicine classes with a positive association with the risk of crash, with median odds ratios ranging from 1.12 to 2.98. Among these, benzodiazepines and benzodiazepine-related drugs, antihistamines, and anti-inflammatory and antirheumatic drugs were among the 10 medicines most consumed by the 16,458 pedestrians. Study limitations included slight overrepresentation of pedestrians injured in more severe crashes, lack of information about self-medication and the use of over-the-counter drugs, and lack of data on amount of walking.</p><p>Conclusions</p><p>Therapeutic classes already identified as impacting the ability to drive, such as benzodiazepines and antihistamines, are also associated with an increased risk of pedestrians being involved in a road traffic crash. This study on pedestrians highlights the necessity of improving awareness of the effect of these medicines on this category of road user.</p></div
The case-crossover design of the study, with multiple drug exposures and a varying washout period.
<p>In the case-crossover design, only individuals with unequal exposures for the control period and the case period contribute to the analysis. For instance, with a control day defined at 120 days before the crash day, the individual shown in this figure has unequal exposures for the second drug (exposed during case day and unexposed during control day), but concordant exposures for the first drug (exposed both days) and the third drug (unexposed both days). In a case-crossover analysis, only the exposure to the second drug is used.</p
The 10 most consumed medicines among those listed in Table 2 as associated with road traffic crash involvement.
<p>The 10 most consumed medicines among those listed in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002347#pmed.1002347.t002" target="_blank">Table 2</a> as associated with road traffic crash involvement.</p
Flowchart of the inclusion procedure.
<p>Note that the discrepancy between the number of police reports and the number of records in the police national database of injurious crashes is explained by the fact that a small proportion of unavailable reports were being used for ongoing legal investigations. *Modified from Orriols et al. [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002347#pmed.1002347.ref024" target="_blank">24</a>].</p
Selection frequency of 48 medicine classes among the 90 case-crossover models, bias-corrected odds ratios, and unequal exposures.
<p>Selection frequency of 48 medicine classes among the 90 case-crossover models, bias-corrected odds ratios, and unequal exposures.</p
Results of the 90 case-crossover designs obtained when varying the washout period from 30 days to 119 days.
<p>A blank cell means that the medicine class was not retained in the final model for this control period, and a colored square means that the medicine class was selected by the model. Both the size and color intensity of the squares depend on the absolute value of the bias-corrected estimated coefficients. When varying the washout period, the frequency thresholds estimated using the Akaike information criterion varied from a minimum of 50% (washout = 40) to a maximum of 74% (washout = 104). A frequency threshold of 74% means that medicines selected in at least 74% of the 1,000 bootstraps were considered as associated risk factors for pedestrian road crash. The different colored forms on the far left indicate groups of medicines according to the location of the control periods (with respect to the crash day) for which there was an association of the medicine with increased risk of being involved in a road crash as a pedestrian: blue stars indicate increased risk in control periods close to the crash; yellow squares indicate increased risk in control periods far from the crash; green circles indicate increased risk in control periods both close to and far from the crash; black squares indicate increased risk in discontinuous control periods.</p