Relationship between obstructive sleep apnoea, driving simulator performance, and risk of road traffic accidents

Background-Obstructive sleep apnoea (OSA) has been shown to be associated w ith an increased risk of road traffic accidents (RTAs). Predicting the driv ing ability and risk of RTAs in an individual with OSA is difficult. On-roa d testing is the gold standard, but this is time consuming, expensive, and potentially dangerous. Simple computer based driving simulators have been d eveloped to help determine driving ability. Although patients with OSA have been shown to perform poorly compared with matched controls, it is not kno wn whether these simulators can predict those at most risk of accidents. In this study we evaluated whether data derived from a simple driving simulat or provided information over and above that obtained from the history and a sleep study that might be useful for advising patients about driving. Methods-We examined 150 patients admitted for routine sleep studies for inv estigation of OSA and snoring. Each patient performed a 20 minute driving s imulation and completed a questionnaire regarding their driving history and experience. Results-Logistic regression analysis was used to investigate factors associ ated with patients' performance on the simulator. It was found that patient characteristics, older age (OR 1.05, 95% CI 1.01 to 1.09, p <0.01), female sex (OR 9.32, 95% CI 1.09 to 79.4, p <0.04), and self-reported alcohol con sumption (OR 1.04, 95% CI 1.01 to 1.07, p <0.01) had the greatest influence ; however, the number of self-reported near miss accidents was independentl y associated with a poor performance (OR 2.62, 95% CI 1.00 to 6.88, p <0.05 ). A further logistic regression was used to investigate whether clinical h istory, sleep study results, and data from the driving simulator were usefu l in classifying patients with OSA as having had an RTA. The number of off- road events per hour on the simulator was independently associated with a h istory of previous RTA (OR 1.004,95% CI 1.0004 to 1.008, p <0.03). The Epwo rth score was independently associated with episodes of falling asleep at t he wheel (OR 1.21, 95% CI 1.12 to 1.31, p <0.00001) and near miss accidents (OR 1.15, 95% CI 1.07 to 1.23, p <0.0001). Using this model, 100% of patie nts who did not have an accident could be identified, but only 10% of those who did. Conclusions-Although factors not directly related to OSA influence performa nce on a driving simulator, there is an independent relationship between dr iving ability in patients with OSA and performance on a simple computer bas ed simulator. When combined with clinical history, it is those not reportin g hypersomnolence and not having off-road events on the simulator who appea r to be at least risk of adverse driving events. Poor performance on the si mulator, however, relates poorly to accident history. These data require co nfirmation in future studies before simple computer simulators can be used in,clinical practice to advise whether an individual is safe to drive.