Can the MSLT be a useful tool to assess motor vehicle crash risk in sleepy drivers?

Comparison of the Oxford Sleep Resistance Test and the Multiple Sleep Latency Test

OBJECTIVE

The Oxford Sleep Resistance Test (OSLER) consists of four tests over 40 min conducted in a dark and quiet room. If a dim light flashes the patient has to briefly depress a button and then press it again immediately, which indicates that the patient resists sleep. The Maintenance of Wakefulness test (MWT) is another test to assess the ability to maintain wakefulness. Previous studies found a good correlation between the sleep latencies measured with the Osler and the MWT. The most widely used Multiple Sleep Latency Test (MSLT) measures the propensity to fall asleep and not the inability to stay awake. Up to this date there have been no studies comparing the Osler and the MSLT, which is the aim of the study presented here.

APPROACH

After a night of polysomnography we investigated the sleep latencies the following day with the Osler and the MSLT in 43 patients suffering from moderate or severe obstructive sleep apnea (OSA) (33 men and 10 women; median age 59 years; median apnea hypopnea index 30.5 per hour sleep). We analysed the correlation between these two tests and between values in the Epworth Sleepiness Scale (ESS) and the Karolinska Sleepiness Scale (KSS) and these two tests.

MAIN RESULTS

We did not find a correlation between the Osler and the MSLT nor between these two tests and the questionnaires (ESS, KSS). The only significant correlation was found between the mean MSLT latency and the sleep onset latency in the polysomnography the night before. Seven patients stayed awake during the Osler and showed a decreased mean sleep latency in the MSLT.

SIGNIFICANCE

The Osler, the MSLT and the questionnaires measure different objective and subjective aspects of sleepiness. In untreated OSA patients an increased propensity to fall asleep was not automatically associated with the inability to stay awake.

Heart Rate Variability-Based Driver Drowsiness Detection and Its Validation With EEG

OBJECTIVE

Driver drowsiness detection is a key technology that can prevent fatal car accidents caused by drowsy driving. The present work proposes a driver drowsiness detection algorithm based on heart rate variability (HRV) analysis and validates the proposed method by comparing with electroencephalography (EEG)-based sleep scoring.

METHODS

Changes in sleep condition affect the autonomic nervous system and then HRV, which is defined as an RR interval (RRI) fluctuation on an electrocardiogram trace. Eight HRV features are monitored for detecting changes in HRV by using multivariate statistical process control, which is a well known anomaly detection method.

RESULT

The performance of the proposed algorithm was evaluated through an experiment using a driving simulator. In this experiment, RRI data were measured from 34 participants during driving, and their sleep onsets were determined based on the EEG data by a sleep specialist. The validation result of the experimental data with the EEG data showed that drowsiness was detected in 12 out of 13 pre-N1 episodes prior to the sleep onsets, and the false positive rate was 1.7 times per hour.

CONCLUSION

The present work also demonstrates the usefulness of the framework of HRV-based anomaly detection that was originally proposed for epileptic seizure prediction.

SIGNIFICANCE

The proposed method can contribute to preventing accidents caused by drowsy driving.

Obstructive sleep apnea and driving: A Canadian Thoracic Society and Canadian Sleep Society position paper

Untreated patients with obstructive sleep apnea (OSA) are at increased risk for motor vehicle collisions; however, it is unclear how this should be translated into fitness-to-drive recommendations. Accordingly, the Canadian Thoracic Society (CTS) Sleep Disordered Breathing Clinical Assembly and the Canadian Sleep Society (CSS) assembled a CTS-CSS working group to propose recommendations with regard to driving in patients with OSA. Recommendations for assessing fitness to drive in noncommercial drivers: 1. Severity of OSA alone is not a reliable predictor of collision risk and, therefore, should not be used in isolation to assess fitness to drive; 2. The severity of sleep apnea should be considered in the context of other factors to assess fitness to drive; 3. The decision to restrict driving is ultimately made by the motor vehicle licensing authority; however, they should take into account the information and recommendations provided by the sleep medicine physician and should follow provincial guidelines; 4. For patients prescribed continuous positive airway pressure (CPAP) therapy, objective CPAP compliance should be documented. Efficacy should also be documented in terms of reversing the symptoms and improvement in sleep apnea based on physiological monitoring; 5. For patients treated with surgery or an oral appliance, verification of adequate sleep apnea treatment should be obtained; and 6. A driver diagnosed with OSA may be recertified as fit to drive based on assessment of symptoms and demonstrating compliance with treatment. The assessment should be aligned with the provincial driver's license renewal period. Commercial vehicles: Assessment of fitness to drive should be more stringent for patients operating commercial vehicles. In general, the CTS-CSS working group was in agreement with the Medical Expert Panel recommendations to the Federal Motor Carrier Safety Administration in the United States; these recommendations were adapted for Canadian practitioners.

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.

Sleep loss and accidents--work hours, life style, and sleep pathology

A very important outcome of reduced sleep is accidents. The present chapter will attempt to bring together some of the present knowledge in this area. We will focus on the driving situation, for which the evidence of the link between sleep loss and accidents is quite well established, but we will also bring up working life in general where evidence is more sparse. It should be emphasized that reduced sleep as a cause of accidents implies that the mediating factor is sleepiness (or fatigue). This link is discussed elsewhere in this volume, but here we will bring in sleepiness (subjective or physiological) as an explanatory factor of accidents. Another central observation is that many real life accident studies do not link accidents to reduced sleep, but infer reduced sleep and/or sleepiness from the context, like, for example, from work schedules, life styles, or sleep pathology. Reduced sleep is mainly due to suboptimal work schedules (or to a suboptimal life style) or to sleep pathology. We have divided the present chapter into two areas.