Cyril Chaufton

Modafinil Improves Real Driving Performance in Patients with Hypersomnia: A Randomized Double-Blind Placebo-Controlled Crossover Clinical Trial

STUDY OBJECTIVE Patients with excessive daytime sleepiness (EDS) are at high risk for driving accidents, and physicians are concerned by the effect of alerting drugs on driving skills of sleepy patients. No study has up to now investigated the effect of modafinil (a reference drug to treat EDS in patients with hypersomnia) on on-road driving performance of patients suffering from central hypersomnia. The objective is to evaluate in patients with central hypersomnia the effect of a wake-promoting drug on real driving performance and to assess the relationship between objective sleepiness and driving performance. DESIGN AND PARTICIPANTS Randomized, crossover, double-blind placebo-controlled trial conducted among 13 patients with narcolepsy and 14 patients with idiopathic hypersomnia. Patients were randomly assigned to receive modafinil (400 mg) or placebo for 5 days prior to the driving test. Each condition was separated by at least 3 weeks of washout. MEASUREMENTS Mean number of Inappropriate Line Crossings, Standard Deviation of Lateral Position of the vehicle and mean sleep latency in the Maintenance of Wakefulness Test were assessed. RESULTS Modafinil reduced the mean number of Inappropriate Line Crossings and Standard Deviation of Lateral Position of the vehicle compared to placebo (F(1,25) = 4.88, P < 0.05 and F(1,25) = 3.87, P = 0.06 tendency). Mean sleep latency at the Maintenance of Wakefulness Test significantly correlated with the mean number of Inappropriate Line Crossings (r = -0.41, P < 0.001). CONCLUSIONS Modafinil improves driving performance in patients with narcolepsy and idiopathic hypersomnia. The Maintenance of Wakefulness Test is a suitable clinical tool to assess fitness to drive in this population.

Complaints of Poor Sleep and Risk of Traffic Accidents: A Population-Based Case-Control Study.

Introduction This study aimed to determine the sleepiness-related factors associated with road traffic accidents. Methods A population based case-control study was conducted in 2 French agglomerations. 272 road accident cases hospitalized in emergency units and 272 control drivers matched by time of day and randomly stopped by police forces were included in the study. Odds ratios were calculated for the risk of road traffic accidents. Results As expected, the main predictive factor for road traffic accidents was having a sleep episode at the wheel just before the accident (OR 9.97, CI 95%: 1.57–63.50, p<0.05). The increased risk of traffic accidents was 3.35 times higher in subjects who reported very poor quality sleep during the last 3 months (CI 95%: 1.30–8.63, p<0.05), 1.69 times higher in subjects reporting sleeping 6 hours or fewer per night during the last 3 months (CI 95%: 1.00–2.85, p<0.05), 2.02 times higher in subjects reporting symptoms of anxiety or nervousness in the previous day (CI 95%: 1.03–3.97, p<0.05), and 3.29 times higher in subjects reporting taking more than 2 medications in the last 24 h (CI 95%: 1.14–9.44, p<0.05). Chronic daytime sleepiness measured by the Epworth Sleepiness Scale, expressed heavy snoring and nocturnal leg movements did not explain traffic accidents. Conclusion Physicians should be attentive to complaints of poor sleep quality and quantity, symptoms of anxiety-nervousness and/or drug consumption in regular car drivers.

Excessive daytime sleepiness in adult patients with ADHD as measured by the Maintenance of Wakefulness Test, an electrophysiologic measure.

OBJECTIVE To quantify the objective level of sleepiness in adult attention-deficit/hyperactivity disorder (ADHD) patients and to determine the relationship between excessive daytime sleepiness and simulated driving performance. METHOD Forty adult ADHD patients (DSM-IV criteria) and 19 matched healthy control subjects were included between June 30, 2010, and June 19, 2013. All participants completed the Epworth Sleepiness Scale and the Manchester Driving Behavior Questionnaire. After nocturnal polysomnography, they performed 2 neuropsychological tests, a 4 × 40-minute Maintenance of Wakefulness Test, and a 1-hour driving session. The primary outcome measure was the mean sleep latency on the Maintenance of Wakefulness Test. ADHD patients were divided into 3 groups defined by their Maintenance of Wakefulness Test scores. Participants (patients and control subjects) were allocated as follows: sleepy ADHD (0-19 min), intermediate ADHD (20-33 min), alert ADHD (34-40 min), and control group (34-40 min). The driving performance outcome was the mean standard deviation of lateral position of the vehicle during the simulated session. RESULTS The group mean (SD) Epworth Sleepiness Scale score was higher in ADHD patients (12.1 [4.4]) than in controls (6.0 [2.7]) (P < .001). On the basis of the Maintenance of Wakefulness Test scores, 14 patients (35%) were in the sleepy group, 20 (50%) were in the intermediate group, and only 6 (15%) were in the alert group. Sleepy ADHD patients exhibited significantly deteriorated driving performance compared to the other 3 groups (P < .01). CONCLUSIONS Our study shows that a significant proportion of adult ADHD patients exhibit an objective excessive daytime sleepiness, which, in addition, has an impact on simulated driving performance. Excessive daytime sleepiness, therefore, may be a key element needed to better evaluate these ADHD patients. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01160874.

Maintenance of Wakefulness Test scores and driving performance in sleep disorder patients and controls

OBJECTIVE Sleepiness at the wheel is a risk factor for traffic accidents. Past studies have demonstrated the validity of the Maintenance of Wakefulness Test (MWT) scores as a predictor of driving impairment in untreated patients with obstructive sleep apnea syndrome (OSAS), but there is limited information on the validity of the maintenance of wakefulness test by MWT in predicting driving impairment in patients with hypersomnias of central origin (narcolepsy or idiopathic hypersomnia). The aim of this study was to compare the MWT scores with driving performance in sleep disorder patients and controls. METHODS 19 patients suffering from hypersomnias of central origin (9 narcoleptics and 10 idiopathic hypersomnia), 17 OSAS patients and 14 healthy controls performed a MWT (4×40-minute trials) and a 40-minute driving session on a real car driving simulator. Participants were divided into 4 groups defined by their MWT sleep latency scores. The groups were pathological (sleep latency 0-19 min), intermediate (20-33 min), alert (34-40 min) and control (>34 min). The main driving performance outcome was the number of inappropriate line crossings (ILCs) during the 40 minute drive test. RESULTS Patients with pathological MWT sleep latency scores (0-19 min) displayed statistically significantly more ILC than patients from the intermediate, alert and control groups (F (3, 46)=7.47, p<0.001). INTERPRETATION Pathological sleep latencies on the MWT predicted driving impairment in patients suffering from hypersomnias of central origin as well as in OSAS patients. MWT is an objective measure of daytime sleepiness that appears to be useful in estimating the driving performance in sleepy patients.

Could a virtual human be used to explore excessive daytime sleepiness in patients

Excessive daytime somnolence (EDS) is defined as the inability to stay awake in daily life activities. Several scales have been used to diagnose excessive daytime sleepiness, the most widely used being the Epworth Sleepiness Scale (ESS). Sleep disorders and EDS are very common in the general population. It is therefore important to be able to screen patients for this symptom in order to obtain an accurate diagnosis of sleep disorders. Embodied Conversational Agents (ECA) have been used in the field of affective computing and human interactions but up to now no software has been specifically designed to investigate sleep disorders. We created an ECA able to conduct an interview based on the ESS and compared it to an interview conducted by a sleep specialist. We recruited 32 consecutive patients and a group of 30 healthy volunteers free of any sleep complaints. The ESS is a self-administered questionnaire that asks the subject to rate (with a pen and paper paradigm) his or her probability of falling asleep. For the purpose of our study, the ECA or real-doctor questionnaire was modified as follows: Instead of the “I” formulate, questions were asked as “Do you.” Our software is based on a common 3D game engine and several commercial software libraries. It can run on standard and affordable hardware products. The sensitivity and specificity of the interview conducted by the ECA were measured. The best results (sensibility and specificity >98%) were obtained to discriminate the sleepiest patients (ESS ≥16) but very good scores (sensibility and specificity >80%) were also obtained for alert subjects (ESS<8). ESS scores obtained in the interview conducted by the physician were significantly correlated with ESS scores obtained in the interview the ECA conducted. Most of the subjects had a positive perception of the virtual physician and considered the interview with the ECA as a good experience. Sixty-five percent of the participants felt that the virtual doctor could significantly help real physicians. Our results show that a virtual physician can conduct a very simple interview to evaluate EDS with very similar results to those obtained by a questionnaire administered by a real physician. The expected massive increase in sleep complaints in the near future likely means that more and more physicians will be looking for computerized systems to help them to diagnose their patients.

Errors and Accidents

Sleep deprivation affects performance outcomes across a wide range of cognitive domains. Sleepiness and fatigue, caused by sleep loss, extended work and wakefulness, circadian misalignment, and sleep disorders are major causes of workplace human errors, incidents, and accidents. Car crashes related to falling asleep represent up to 20 % of all traffic accidents in industrial societies and are known to be more likely to cause death and severe injury. Sleep-related accidents are substantial in terms of personal injury, of property damage, lost productivity, and death. Management and prevention of sleep-related accidents should be a priority for the public, labor, governments, and industries. Scientific data on potentially useful countermeasures are needed.