The Maintenance of Wakefulness Test and Driving Simulator Performance

SLEEP, SLEEP RESTRICTION, AND PERFORMANCE The Maintenance of Wakefulness Test and Driving Simulator Performance Siobhan Banks, PhD 1,2 ; Peter Catcheside, PhD 1 ; Leon C. Lack, PhD 1,3 ; Ron R. Grunstein, MD, PhD 4 ; R. Doug McEvoy, MD 1,2 1 Adelaide Institute for Sleep Health, Repatriation General Hospital Daw Park, Adelaide; 2 School of Medicine and 3 School of Psychology, Flinders University of South Australia, Adelaide; 4 Woolcock Institute of Medical Research, Sydney, Australia Study Objectives: It has been suggested that the Maintenance of Wakefulness Test (MWT) may be clinically useful to assess fitness to drive, yet little is known about the actual relationship between sleep latency and driving performance. This study examined the ability of 2 MWT trials to predict driving-simulator performance in healthy individuals. Design: Experimental Setting: NA. Patients or Participants: Twenty healthy volunteers (mean age 22.8 years; 9 men). Interventions: NA. Measurements and Results: The MWT and driving-simulator performance were examined under 2 conditions partial sleep deprivation and a combination of partial sleep deprivation and alcohol consumption. Each subject was studied a week apart, with the order randomly assigned. Subjects completed a nighttime 70-minute AusEd driving simulation task and two 40-minute MWT trials, 1 before (MWT1) and 1 after (MWT2) the driving task. In the sleep-deprived condition, the MWT1 sleep latency was inversely correlated with braking reaction time. During the partial sleep deprivation and alcohol condition, the number of microsleeps during the driving task, steering deviation, braking reaction time, and crashes all negatively correlated with the MWT1 sleep latency. Additionally, construction of a receiver-operator characteristic curve revealed that MWT1 sleep latency in the partial sleep deprivation plus alcohol condition significantly discriminated subjects who had a crash from those who did not. Conclusions: These results indicate that sleep latency on the MWT is a reasonable predictor of driving simulator performance in sleepy, alcohol-impaired, normal subjects. Further research is needed to examine the relationship between daytime MWT results and driving simulator performance in sleepy patients (eg, those with obstructive sleep apnea) and in experimentally sleep-deprived normal subjects. Keywords: MWT, Driving, Sleepiness, Alcohol Citation: Banks S; Catcheside P; Lack LC et al. The maintenance of wakefulness test and driving simulator performance SLEEP 2005;28(11): 1381-1385. INTRODUCTION Disclosure Statement This was not an industry supported study. Dr. Grunstein has received research support from Cephalon, ResMed, Sanofi-Synthelabo, GSK, and Neurocrine Pharmaceuticals. Dr. McEvoy has received research support and equipment from ResMed and Massimo. Drs. Banks, Catcheside, and Lack have indicated no financial conflicts of interest. Submitted for publication April 2005 Accepted for publication July 2005 Address correspondence to: Siobhan Banks, PhD, Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, University of Pennsylvania School of Medicine, 1013 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, USA 19104-6021; Tel: (215) 898-9665; Fax: (215) 573-6410 WHILE ESTIMATES VARY ACCORDING TO COUNTRY AND METHOD OF POLICE REPORTING, 1-3 IT IS THOUGHT THAT APPROXIMATELY 20% OF MOTOR VEHICLE crashes are caused by sleepiness or fatigue. People with obstructive sleep apnea, a disorder characterized by excessive daytime sleepiness, are 2- to 7-fold more likely to have a crash than are healthy drivers. 4, 5 One of the most important challenges facing the sleep medicine community is how to accurately measure individuals levels of sleepiness and accident risk. Currently there is no agreed-upon test or tests of driving safety for sleepy patients. One test that has been used both in research and clinical settings and that has substantial face validity as a measure of sleepiness is the maintenance of wakefulness test (MWT). The MWT requires subjects to stay awake while in a soporific environment for several periods over a day. It can be readily performed in most clinical sleep laboratories and, in fact, is currently recommended in Australia, 6 in conjunction with other tests, to assess fitness to drive in patients with sleep disorders (eg, obstructive sleep apnea) who are considered at risk of falling asleep while driving. The MWT has also been recommended to assess the alertness of United States Air Force pilots suffering from hypersomnia. 7 Despite the recent recommendations by regulatory authorities and the theoretical attraction of the MWT as a test of driving safety, little is known about the actual relationship between MWT sleep latency and driving performance. A small preliminary study examining only 5 patients with obstructive sleep apnea found no relationship between the MWT and driving simulator performance. 8 A recent study of drivers who had crashed their cars demonstrated that the drivers who crashed had significantly more sleepiness, slower reaction times, and a trend for shorter MWT sleep latencies compared with control subjects. 9 A study that examined the multiple sleep latency test (MSLT), another objective test of sleepiness, and driving simulator performance found that, while there was a reasonable relationship between the 2 tests, MSLT sleep latency explained little of the error in the driving task. 10 Today s society is very demanding on time, both professionally and socially, resulting in a high prevalence of sleep restriction. The associated impact on the ability to perform complex tasks is potentially devastating. More investigation is needed to ascertain the validity of electroencephalogram (EEG)-based sleep laboratory tests of sleepiness to predict driving performance. The aim of this study was to examine the ability of the MWT sleep latency to predict driving simulator performance in healthy young individuals who were sleep restricted with and without the presence of low-dose alcohol. Results from the same experiment showing the effects of sleep restriction and low-dose alcohol on driving performance have been reported previously. 11 1381

METHODS The relationship between MWT sleep latency and driving simulator performance was examined under 2 conditions partial sleep deprivation (PSD) and a combination of PSD and alcohol consumption (PSD-A). Each subject was studied a week apart, with the order randomly assigned. The MWT and driving simulator performance were examined under 2 conditions. The research and ethics committee at the Repatriation General Hospital - Daw Park, Adelaide approved the study, and all subjects gave written informed consent. Participants Advertisements were posted at the Flinders University of South Australia campus. Young adults were recruited for this study due to the high number of 18- to 30-year olds who have sleep-related car accidents in the early hours of the morning. Subjects were excluded if they had a history of sleep disorders (eg, self-reported snoring or difficulty sleeping), were taking any medication or had a history of motion sickness. All subjects received an honorarium of $100. Familiarization Session During the first visit to the laboratory, which occurred in the daytime, subjects were introduced to the testing equipment and driving simulator. Subjects underwent three 10-minute practice sessions on the driving simulator and were randomly assigned to condition order. After three 10-minute sessions, the driving simulator performance learning effect had become asymptotic (defined as less than a 10% change in performance between the practice trials). The subjects then completed the Epworth Sleepiness Scale. 12 The subjects took home an activity monitor and a sleep diary to be completed in the week prior to testing. Subjects were not required to obtain a specific amount of sleep during the testing period (except on the PSD night). They were instructed to keep to their normal sleep-wake pattern. Maintenance of Wakefulness Test All MWT trials were performed in a similar setting using a simplified recording montage (C 3, O 1, electromyogram, and electrooculogram). The testing room was sound attenuated, insulated from external light, and equipped with dimmer lights overhead. Ambient temperature in the room was approximately 22 o C. Bedroom doors were closed, and all monitoring was performed external to the bedroom to keep noise to a minimum. During each MWT trial, subjects sat semiupright (10 o to 30 o back from vertical) in a comfortable lounge chair that had a high back to support the head and neck. Prior to each trial, subjects were instructed to keep your eyes open and try not to fall asleep. Subjects were asked not to use any extraordinary mental or physical measures (eg face slapping to avoid sleep). The recordings were then started, and the lights dimmed to an illumination of 1 lux. Each trial was terminated at the first occurrence of sustained sleep (3 consecutive 30-second epochs of stage 1 sleep or 1 epoch of any other stage) or after 40 minutes if there was no sleep. AusEd Driving Simulator The AusEd driving simulation task used in this study is a computer program devised to monitor driving impairment from a number of variables, including position on the road, speed deviation over time, reaction time to a braking task (appearance of trucks), and crashes (driving off the road, stoppage events and crashing into the back of a truck). Early work suggests that this test is sensitive to varying degrees of sleep deprivation and sleepiness. 11,13-15 Subjects were required to drive the AusEd simulator using a steering wheel and pedals. The view, seen from a frontseat perspective, was of a dual-carriage rural road at night, with the usual lane divisions and the road edges marked by reflective posts. A speedometer was displayed in the top left corner of the computer screen. Subjects were asked to maintain their position in the left-hand lane on the road (in accordance with Australian driving code), to maintain speed within 60 to 80 kilometers per hour, and to react by braking firmly and as quickly as possible to any trucks that appeared ahead in the driving lane. The simulator was programmed to present 4 trucks at approximately 10-minute intervals during the 70-minute task. Experimental Conditions The subjects were required to keep a detailed diary of their sleep habits and to wear an activity monitor (Gaehwiler Electronic, Hombrechtikon, Switzerland), which measured their sleep-wake activity for 1 week prior to the experimental conditions. This was done to verify that the subjects had regular sleep habits in the week prior to testing, followed the sleep-deprivation protocols, and did not nap during the day of testing. Subjects participated in the 2 experimental conditions in a repeated-measures design, attending the laboratory twice with a week separating each visit. In the PSD condition subjects were restricted to 5 hours time in bed on the night prior to testing (1 AM -6 AM). They were required to telephone a time- and date-stamped answering machine before going to bed and after rising in the morning to ensure compliance. In the PSD-A condition, subjects were required to restrict sleep according to the protocol above and to consume alcohol prior to the driving task to produce a blood alcohol concentration (BAC) of approximately 0.04 g/dl, which is just below the legal BAC limit for driving in Australia, 0.05g/dL. To achieve this, subjects consumed 1 ml of 50% alcohol per kg of body weight (in a carbonated, noncaffeinated beverage) at 10:30 PM. At 12:15 AM, they consumed another drink with 0.5 ml of 50% alcohol per kg of body weight. Blood alcohol levels were estimated immediately before and after the MWT trials and driving test using a calibrated Breathalyzer (Dräger, Alcotest 7410 Plus Lübeck, Germany) accurate to 0.005 g/dl. Subjects were not blinded to alcohol presentation, as our aim in this study was to test the subjects in a realworld common situation in which the subjects would be aware of alcohol consumption. Experimental Procedure Subjects arrived at the laboratory at 9:00 PM. Their BAC was ascertained with the Breathalyzer, a urine sample was taken to test for habitual drugs of abuse (eg, opioids, cannabinoids, and amphetamine all tested negative), and activity monitors were downloaded to ensure that the subjects had complied with the study protocol requirements. The subjects timepieces were removed so that they had no external time cues. Standard surface electrodes were applied for monitoring: EEG (C 3, C 4 /A 1 ), 1382

submental electromyogram, left and right eye movements, and electrocardiogram. All parameters were recorded using the Sleepwatch (Compumedics, Melbourne, Australia) data-acquisition system. Subjects then completed the Stanford Sleepiness Scale. 16 Subjects were allowed a short practice run on the driving simulator and given a standardized snack (150 calories; dry biscuits and cheese) and alcohol or an equivalent volume of the carbonated noncaffeinated beverage at 10:30 PM and at 12:15 AM. The protocol of this study had to allow for the consumption of alcohol (10 minutes to consume and 30 minutes to stabilize for BAC readings) and other tests (eg, the Psychomotor Vigilance Task, the results of which have been reported previously). 17 The first MWT (MWT1) commenced at 11:30 PM. Subjects started the 70-minute driving simulation at 1:00 AM and were prompted every 4.5 minutes during the driving task to answer simple questions about their perception of level of driving performance and crash risk (results reported elsewhere). 11 Subjects were told that the probes would sound at random intervals. The driving task took place in a private, semidark (10 lux), and sound-attenuated room. The second MWT (MWT2) commenced at 02:15 AM. The experiment concluded at approximately 3 AM, and subjects were driven home by taxi cab. DATA ANALYSIS Maintenance of Wakefulness Test Sleep latency was defined as the first appearance of 3 epochs of stage 1 sleep or 1 epoch of any other sleep stage. Subjects with no sleep onset were assigned a value of 40 minutes. Both the individual trial sleep latencies and the mean sleep latency were recorded for each condition. AusEd Driving Simulator This study examined mean steering deviation (subject s median position on the road, excluding crashes), reaction time (in response to trucks on the road ahead), and number of driving simulator crashes (off-road, truck collision, or stoppage events). The mean number of crashes was determined for each 4.5-minute bin and for the whole task. EEG Microsleep Analysis The EEG (C 3 -A 2 ) during the driving simulation task was assessed for the appearance of microsleeps. A microsleep was defined as a burst of EEG theta activity greater than 3 seconds in duration. 18,19 The cumulative theta time (seconds) was determined for each subject. Correlations Pearson correlations were conducted between the driving simulator parameters (mean steering deviation, reaction time, and crashes), mean cumulative microsleep, and MWT sleep latency for both conditions. ROC Curve Analysis Receiver operating characteristic (ROC) curves were constructed to assess the ability of MWT to distinguish those subjects who had a crash during the simulation task from those who did not. A ROC curve is a plot of the true positive rate against the false positive rate for all possible cut points of a diagnostic test. An area of 0.84 under the curve, for example, means that a randomly selected individual from the positive group has a test value larger than that of a randomly chosen individual from the negative group 84% of the time. The closer the curve follows the left-hand and the top border of ROC curve space, the more accurate the test. The closer the curve is to the 45-degree diagonal of ROC curve space, the less accurate the test. The area under a ROC curve therefore provides a measure of the performance of the test, in this case the utility of MWT sleep latency to predict driving simulator crashes. Mann-Whitney U tests were used to determine if the area under the ROC curves differed from 0.5 (ie, a test that discriminates no better than pure chance). RESULTS Twenty healthy subjects (11 women, mean age 21.9±2.2; 9 men, mean age 23.8±4.8) participated. All subjects had normal body mass index (23.3±3.1). All participants were university students, who consumed 2 or fewer servings of caffeine (2 small cups of regular coffee or tea, 2 chocolate bars [50 grams each], 2 cans of cola, etc) per week and 6 or fewer standard alcoholic beverages a week (eg weekend social drinkers). In addition, all subjects had current driver s licenses, and all were experienced at computer game controls and formats. The mean Epworth Sleepiness Scale score at familiarization for the whole group was 6.4±3.9. All subjects had a regular sleep-wake cycle in the week prior to testing, with activity-monitor data showing subjects were inactive for an average of 411±37 minutes per night. They subjectively reported (sleep diary kept for 7 days) that they obtained an average of 423.6±45.8 minutes of sleep per night. No subjects were excluded on the basis of the amount of sleep obtained in the week before testing. All subjects had zero BAC and a negative urine drug test on arrival at the laboratory on experimental nights. Data from the activity monitors showed that subjects complied with the sleep-restriction protocol. They were inactive for 270±20 minutes on the night before testing. Subjects rated themselves as moderately sleepy according to the Stanford Sleepiness Scale on both experimental nights (PSD mean 4.0±1.2 and PSD-A mean 4.0±1.3). MWT mean sleep latency was significantly lower at the 2:15 am trial than at 11:30 PM trial in both the experimental conditions (P<.001). There was a trend for a reduction in the mean sleep latency with the consumption of alcohol, but the difference was not statistically significant (P=.07; See Table 1). Forty percent and 80% of subjects achieved sleep onset in the PSD and PSD-A conditions, respectively. The subjects mean BACs on the alcohol night at the start and end of the 70-minutes driving simulation were 0.037±0.011g/dL and 0.021±0.009g/dL. Before and after MWT1, subjects mean Table 1 Sleep Latency on the Maintenance of Wakefulness Test Sleep Deprivation Sleep Deprivation and Alcohol MWT1 MWT2 Mean MWT1 MWT2 Mean 31.7±11.9 25.2±16.2 28.9±13.2 25.4±16.1 19.3±14.6 22.3±14.8 Sleep latency is presented in minutes, mean + SD; Maintenance of Wakefulness Test 1 (MWT1) occurred at 11:30 PM and MWT2 occurred at 2:15 AM. 1383

Table 2 Correlations Between Driving Simulator Parameters and Sleep Latency on the Maintenance of Wakefulness Test Sleep Deprivation Sleep Deprivation and Alcohol MWT1 MWT2 MWT1 MWT2 Microsleeps -0.02 0.00-0.45* -0.43 Reaction time -0.52* -0.47-0.51* -0.15 Mean steering deviation -0.24-0.27-0.59** -0.25 Number of crashes -0.19-0.14-0.54* -0.27 *P<.05 **P<.01 Maintenance of Wakefulness Test 1 (MWT1) occurred at 11:30 PM and (MWT2) occurred at 2:15 AM. BACs were 0.031±0.01g/dL and 0.026±0.012g/dL, and, before and after MWT2, subjects mean BACs were 0.021±0.009g/dL and 0.012±0.008g/dL. In the PSD condition only driving simulator reaction time to the appearance of trucks correlated with MWT1 (see Table 2). In the combined PSD-A condition, however, the driving simulator parameters and the duration of microsleeps correlated with MWT sleep latency but only at the 11:30 PM trial, with the MWT1 explaining between 20% to 35% of the variance of the driving simulator parameters (see Table 2). A ROC curve (see figure 1) revealed that the MWT trial directly before the driving task in the PSD-A condition was able to discriminate between subjects who crashed and those who did not (Mann-Whitney U test, P=.006). The area under the curve was 0.81±0.10. Neither the MWT before or after the driving task in the PSD condition (P=.22 and P=.32, respectively) nor the MWT after the driving task in the PSD-A condition (P=.23) significantly discriminated between the 2 conditions (crash, no-crash). DISCUSSION This study found that MWT1 correlated with reaction time in both conditions, with a slightly greater magnitude of relationship in the PSD-A condition. Other parameters such as microsleeps, steering deviation, and crashes, only correlated with MWT1 in the PSD-A condition. The MWT was found to explain a fifth to a third of the variance in the driving-performance measures in the PSD-A condition when the subjects were more sleepy and impaired due to the alcohol consumption. The MWT trial prior to the driving task in the PSD-A condition was able to discern subjects who had a crash during the driving task from those who did not. These results suggest that there is validity in using the MWT to predict driving performance. The subjects BACs during the first MWT on the PSD-A night were close to those during the driving task (0.031±0.010g/dL before MWT1 and 0.037±0.011g/dL before the driving simulation task). However, during the second MWT, the average BACs were much lower (0.021±0.009g/dL before MWT2). The higher BACs likely contributed to the increased degree of relationship between the first MWT and the subjects performance during the driving simulation task. The consumption of alcohol was an important factor in this study. Low doses of alcohol have been found to increase sleepiness and performance impairment in the already sleep-restricted individual. 11,20 In the current study, there was a trend for a reduction in the mean sleep latency with the consumption of alcohol, Sensitivity (True +ve rate) Area under curve= 0.81 1-Specificity (False +ve rate) Figure 1 The true positive rate (short Maintenance of Wakefulness Test [MWT] sleep latency and presence of a driving simulator crash) versus false positive rate (short MWT sleep latency without subjects having crashed) of the MWT directly before the driving task during the combined sleep restriction and alcohol condition. but the difference was not statistically significant, consistent with increased variance in sleep-latency after alcohol consumption. We postulate that increased variance in subjects sleepiness after alcohol consumption allowed the relationship between MWT and driving simulator performance to become evident. The increased variance in sleepiness after alcohol consumption was most likely due to more subjects falling asleep and less truncation of the sample to 40 minutes. This relationship needs further examination in patient populations (eg, those with obstructive sleep apnea and narcolepsy) who have existing trait sleepiness rather than experimentally induced sleepiness in normal subjects with alcohol. Alcohol may have also affected MWT sleep latency by reducing subject compliance and motivation to follow instructions and remain vigilant. There is some literature to suggest that alcohol reduces subjects general motivation to perform. 21 The MWT and driving simulator reaction-time results correlated well in both conditions, with MWT sleep latency accounting for just under one third of the variance in reaction time. Reaction time has been found to be very sensitive to sleep loss and alcohol consumption 20,22 and is recognized as a good measure of performance. 23-29 Reaction time is a vital component of driving performance. The correlation between MWT sleep latency and reaction time increases the validity of the MWT as an indicator of driving safety. A limitation of this study was that polysomnography was not conducted in the subjects to completely rule out the presence of a sleep disorder. However, every effort was made to ensure that the results of all screening tools used (eg, the Pittsburg Sleep Quality Inventory and Epworth Sleepiness Scale) were within normal limits. Additionally, the subjects were young, had normal body mass indexes, and wore actigraphy for several weeks, confirming that all subjects had normal sleep-wake times. It remains possible, however, that a subject may have had a sleep disorder that effected their MWT results and driving simulation performance. In conclusion, these results indicate that MWT sleep latency is a reasonable predictor of driving simulator performance in sleepy, alcohol-impaired, normal subjects. This study represents a first step in examining the relationship between MWT and driv- 1384

ing performance. We reasoned that conducting the MWT trials in close proximity to a driving task in the early hours of the morning when sleep-restricted subjects are under the most circadian pressure for sleep would strengthen relationships between MWT sleep latency and measures of performance. Normal sleep laboratory practice, however, is to conduct 4 evenly spaced MWT trials in the daytime. It will be important in future studies, therefore, to explore the relationship between daytime MWT mean sleep latency and driving simulator performance in sleepy patient populations and to compare results in older versus younger subjects. Ideally the MWT should also be directly compared to real-life, on-road, driving performance. ACKNOWLEDGEMENT Study funded by the Brewers Foundation of Australia REFERENCES 1. Lyznicki JM, Doege TC, Davis RM, Williams MA, Sleepiness, driving, and motor vehicle crashes. Council on Scientific Affairs, American Medical Association. JAMA 1998;279:1908-13. 2. 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