SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

Patients with minimal hepatic encephalopathy (MHE) have attention, response inhibition, and working memory difficulties that are associated with driving impairment and high motor vehicle accident risk. Navigation is a complex system needed for safe driving that requires functioning working memory and other domains adversely affected by MHE. The aim of this study was to determine the effect of MHE on navigation skills and correlate them with psychometric impairment. Forty-nine nonalcoholic patients with cirrhosis (34 MHE+, 15 MHE−; divided on the basis of a battery of block design, digit symbol, and number connection test A) and 48 age/education-matched controls were included. All patients underwent the psychometric battery and inhibitory control test (ICT) (a test of response inhibition) and driving simulation. Driving simulation consisted of 4 parts: (1) training; (2) driving (outcome being accidents); (3) divided attention (outcome being missed tasks); and (4) navigation, driving along a marked path on a map in a “virtual city” (outcome being illegal turns). Illegal turns were significantly higher in MHE+ (median 1; P = 0.007) compared with MHE−/controls (median 0). Patients who were MHE+ missed more divided attention tasks compared with others (median MHE+ 1, MHE−/controls 0; P = 0.001). Similarly, accidents were higher in patients who were MHE+ (median 2.5; P = 0.004) compared with MHE− (median 1) or controls (median 2). Accidents and illegal turns were significantly correlated (P = 0.001, r = 0.51). ICT impairment was the test most correlated with illegal turns (r = 0.6) and accidents (r = 0.44), although impairment on the other tests were also correlated with illegal turns. Conclusion: Patients positive for MHE have impaired navigation skills on a driving simulator, which is correlated with impairment in response inhibition (ICT) and attention. This navigation difficulty may pose additional driving problems, compounding the pre-existing deleterious effect of attention deficits. (HEPATOLOGY 2008.)

Minimal hepatic encephalopathy (MHE) is a significant neurocognitive complication of cirrhosis that is associated with poor quality of life, increased progression to overt hepatic encephalopathy, and impaired driving skills.1–3 In a recent study, patients with MHE required a higher number of interventions by driving instructors to prevent accidents during road tests.4 Patients with cirrhosis with MHE also have a higher reported occurrence of motor vehicle accidents and traffic violations compared to patients with cirrhosis but without MHE, and healthy controls.4, 5 Because motor vehicle accidents are one of the leading causes of morbidity and mortality in the United States and prognosis of patients with cirrhosis is improving, a detailed understanding of treatable human factors, such as MHE-associated driving impairment, may assist in reducing this public health burden.6–8

The cognitive impairment in MHE is characterized by impairment in attention, response inhibition, visuo-motor coordination, and working memory.9–13 Because these processes are required for safe driving practices, impaired driving skills in MHE are likely to be related to this dysfunction.4

Working memory is the function responsible for short-term recall of newer incoming information or retrieved memory sets and is required for successful execution of daily tasks. It helps in rapid adaptation to new situations by guiding the correct response based on previous short-term experiences.12 Navigation, a complex human function that requires integration of multiple component systems, is a key element of proper driving, especially in new circumstances or unfamiliar surroundings.14, 15 Impairment in navigation has been demonstrated in HIV disease and Alzheimer's dementia, which also show deficits in working memory and attention.16–18

We hypothesized that patients with MHE have impaired navigation skills on a driving simulator, and that this correlates with psychometric impairment in tests of response inhibition and attention.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

All patients with cirrhosis included were between the ages of 18 and 65 years of age and were recruited from the hepatology clinics at the Medical College of Wisconsin. Exclusion criteria included alcohol use within 3 months of the study; alcohol as the etiology of cirrhosis; history of or current therapy for overt hepatic encephalopathy with rifaximin or lactulose; current use of psychoactive drugs (antidepressants, antipsychotics, anti-anxiety medications, and interferon); no valid driver's license; and driving less than 20 miles per week. Age/educational-matched controls were recruited from the community. Community controls who were currently on psychoactive drugs, who did not have a valid driver's license, and who drove less than 20 miles per week were also excluded.

Psychometric Testing and Diagnosis of MHE.

All patients with cirrhosis and controls enrolled in the study underwent a battery of number connection test A (NCT-A), digit symbol test (DST), and block design test (BDT) of the Wechsler's Adult Intelligence Scale (WAIS) III (battery conforms to recommendations of the working group on hepatic encephalopathy) along with an inhibitory control test (ICT), which is a test of response inhibition and attention that has a reported 90% sensitivity and specificity for the diagnosis of MHE.1, 19, 20 Control values for the local population had been determined a priori in a sample of 150 controls who were age-matched and education-matched to the patients with cirrhosis seen at the hepatology clinics at Medical College of Wisconsin (mean ± 2 standard deviation scores for community control norms were: NCT-A, 24 ± 10 seconds; DST, 91 ± 20 raw score; and BDT, 51 ± 20 raw score). Impairment of psychometric performance beyond 2 standard deviations of the predetermined control values on either NCT-A, DST, or BDT (NCT-A, >34 seconds; DST, <71 raw score; BDT, <31 raw score) was considered diagnostic of MHE. The remaining patients were deemed to have cirrhosis without MHE.20

Inhibitory Control Test.

The ICT is a test of attention and response inhibition that has been studied in diseases such as attention-deficit disorder and schizophrenia.21–23 It has been studied in a selected group of patients with cirrhosis for the diagnosis of MHE with a sensitivity and specificity of 90%.20 Response inhibition is the basis for response to lures—stimuli that a patient is trained not to respond to in the training run but nevertheless incorrectly responds to instead of inhibiting the response.21

Driving Questionnaires.

After providing written informed consent, all patients completed a driving history questionnaire and a driving behavior questionnaire. The driving behavior questionnaire (DBQ) is a 26-part copyrighted survey that inquires about safe driving behavior with a maximum score of 104.24 A higher score indicates better driving practices. The DBQ also includes an overall driving assessment, which is self-evaluation of driving skills using a Likert scale between 1 and 10 (10 being the best self-assessment). After the questionnaires were completed, the 4 psychometric tests were administered.

Driving Simulation.

During the same sitting, the driving simulator task was performed. STISim Drive simulation software (Systems Technology Inc., Hawthorne, CA) was used in the simulator (Model BR1100, Los Gatos, CA), which had a computer screen, a steering wheel, a console consisting of a brake and accelerator, and automatic recordings of accidents and time taken for completion of tasks. This simulation software has been used in characterizing the effects of several disease processes such as HIV, aging, and sleep disorders on driving.16, 25–28 The overall driving simulation task consisted of 3 parts.

Training Simulation.

The first part was a 15-minute training run that was administered to all patients to familiarize them with the tasks and to ensure that they could comply with the directions that flashed across the computer screen.

Driving and Divided Attention Task.

The second part was a 25-minute driving run with divided attention tasks that consisted of driving through the following predetermined sequence: (1) straight road, (2) hill, (3) mountain, (4) highway, (5) large city, (6) beach town, (7) suburban area, and (8) small town. To ensure adequate sensitivity in detecting driving impairments, a challenging program was designed to evaluate driving outcomes in a short period. The primary outcome was the number of accidents on the simulation. There were clear speed limits posted and all traffic rules and directions were provided through road signs during the simulation (Fig. 1A). The weather settings were set to optimal visibility without rain or snow. The time required for completion was recorded but was a secondary outcome, because this factor may be influenced by following the speed limit and number of accidents. No minimum driving speed was required.

thumbnail image

Figure 1. Examples of the simulator screen during various tasks. (A) Simulator screen during the driving task clearly showing speed limits, traffic signs, and the speedometer. The rearview mirror image is constantly shown throughout the task to facilitate driving. (B) Divided attention task. A red sign appears on the left side of the screen, without any audible cues, prompting the patient to honk the horn. The sign appears for 5 seconds, during which time the patient has to press the horn (which makes a noise) to successfully complete the task. Three horn signs and 2 stop signs are scattered throughout this task to test for divided attention. (C) Navigation task. An example of a turn in the virtual city showing the correct (i.e., legal) way to turn (to the left in this case) and the clearly marked street signs. All turns in the virtual city were marked in this way, clearly indicating the way to go.

Download figure to PowerPoint

Scattered within the driving task were 5 divided attention tasks, 3 of which instructed the patients to press the horn on the steering wheel and 2 of which instructed the patient to stop the simulation using the brake (Fig. 1B). The number of attention tasks missed was recorded.

Navigation Task.

The third part was the navigation task, which consisted of driving through a virtual city that was created especially for our study as a modified version of the one used by Marcotte et al.16 (Fig. 2). All patients were instructed to get from the beginning to the end of a path marked on a paper map. All turns were clearly marked with signs guiding patients to make legal turns and leading them to the marked destination (Fig. 1C). Turns that led patients off the marked path were considered illegal turns, and they were the primary outcome of this task. The task was set up to have 30 possible illegal turns, 3 of which had built-in accidents that clearly demonstrated to the patient that an illegal turn had been made. However, the remaining 27 possible illegal turns did not come with any clear indication that an illegal turn was being made. Only the first turn off of the marked path was counted as an illegal turn.

thumbnail image

Figure 2. Map of virtual city for the navigation task. The virtual city created for this task was a modified version of the one used by Marcotte et al.16 Patients were instructed to follow a path given on the map (arrows). There were 30 possible turns that could be made illegally, 3 of which would result in an accident. All turns were clearly marked with signs indicating the correct way to go (as in Fig. 1C). An investigator blinded to the patient groups independently verified the illegal turns. The outcome of this task was the number of illegal turns made away from the marked path (only the first illegal turn was counted). Adapted with permission from Marcotte et al.16

Download figure to PowerPoint

To avoid bias, the psychometric tests were not scored until the end of the visit, and an instructor blinded to the groups verified illegal turns as they occurred without alerting the patient that an illegal turn had been made.

The institutional review board at the Medical College of Wisconsin approved the protocol.

Sample Size.

Previous studies in our population have shown that control patients and patients with cirrhosis without MHE have similar psychometric performance.20 In previous studies from our population, 80% of patients had impaired psychometric performance (that is, MHE).20 Therefore, assuming that 65% of patients with cirrhosis make an illegal turn compared to 15% of controls, we estimated the need of at least 14 patients in the MHE group and 14 patients without MHE using a power of 0.80 and an alpha of 0.05. Since patients without MHE have similar psychometric performance to controls, 14 controls would also be needed.20, 11

Statistical Analysis.

Unpaired Student t tests were used for continuous variables, and Fisher's exact tests were used for dichotomous variables. Kruskal-Wallis and Mann Whitney U tests were used for comparison of accidents and illegal turns across groups. Spearman rank correlation coefficient was used to correlate illegal turns and accidents to individual psychometric tests.

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

Forty-nine patients with cirrhosis and 49 age/educational-matched community controls were included. Thirty-two of the patients were hepatitis C–positive, 9 had nonalcoholic steatohepatitis or cryptogenic cirrhosis, 6 had autoimmune cirrhosis, and 2 had primary biliary cirrhosis. Forty-three of the patients with cirrhosis were Child-Pugh class A and 6 were Child-Pugh class B.

Using the criteria defined a priori, the group of patients with cirrhosis was divided into 34 patients with MHE (MHE+) and 15 patients without MHE (MHE−).

Psychometric Tests.

MHE+ patients performed poorly on all psychometric tests compared with others, because this was the basis of their diagnosis of MHE. Of the 49 patients with cirrhosis, 11 had normal testing on all 3 standard tests, 12 had abnormalities in 1 test only, 8 had abnormalities in 2 tests, and 14 had abnormalities on all 3 tests.

Similar to our previous study, MHE patients responded to a significantly higher number of lures on the ICT, indicating poor performance.20 Eighty-six percent of MHE+ patients responded to more than 5 lures on the ICT.

Driving Behavior Questionnaire and Overall Assessment.

Patients with MHE performed worse on the driving behavior questionnaire and were significantly worse drivers in their self-assessment compared with patients without MHE and controls (Table 1).

Table 1. Demographic and Driving Simulator Characteristics
 MHE+ (n = 33)MHE− (n = 14)Controls (n = 48)P Value
  • ICT lures were significantly higher in MHE+ patients compared with others. A significantly higher number of illegal turns, accidents, and divided attention task misses on the driving simulator were observed in MHE+ patients compared with others. Two patients (1 control, 1 MHE+) could not complete the simulation because of simulator sickness and were excluded from this analysis. Navigation time was the total run time to complete the navigation task. DBQ and overall driving assessment was significantly lower in the MHE+ group compared with others, indicating that these individuals thought they were worse drivers than the rest. All data are expressed as the mean ± standard deviation unless mentioned otherwise. The P values listed represent comparisons between all 3 groups.

  • *

    P < 0.05.

  • **

    P < 0.01.

  • ***

    P < 0.001.

Age54 ± 453 ± 1151 ± 80.12
Sex (M/F)17/169/530/180.56
Driving experience, years35 ± 935 ± 933 ± 90.23
NCT-A, seconds32 ± 1122 ± 6***24 ± 6***0.0001
BDT, raw score34 ± 1140 ± 8***41 ± 8***0.008
DST, raw score56 ± 1282 ± 14***81 ± 7***0.0001
ICT lures (range)8 ± 6 (1–24)4 ± 3*** (0–7)4 ± 2*** (0–6)0.002
Overall self-assessment (maximum: 10)7.8 ± 1.48.2 ± 0.88.5 ± 0.9**0.03
DBQ score (maximum: 104)93.2 ± 8.198 ± 4.8**98 ± 5.3**0.002
Illegal turns, median (range)1 (0–4)0* (0–1)0** (0–1)0.007
Navigation task time (seconds)1156 ± 376989 ± 3091157 ± 2780.27
Number of accidents, median (range)2.5 (0–9)1** (0–4)2*** (0–5)0.004
Missed attention tasks (total: 5), median (range)1 (0–5)0*** (0–2)0*** (0–3)0.001

Driving Simulation.

Two patients with cirrhosis (1 MHE+, 1 MHE−) and 1 control could not complete the driving simulation because of simulator sickness, a well-known and self-limited adverse effect of simulation that is similar to motion sickness. Simulator sickness occurred within 5 minutes of the start of the training run and disappeared within 10 minutes of onset in all 3 individuals.

The total run time of the simulation task was not significantly different between groups (controls, 3732.6 ± 797.7 seconds; MHE−, 3543.3 ± 583.0 seconds; MHE+, 3885.7 ± 1076.4 seconds; P = 0.48).

Driving Task.

There was a significantly higher rate of collisions in the MHE group compared with the other groups (Table 1). There were a total of 100 accidents in the MHE+ group (mean 3.0 ± SE 0.4), 20 accidents in the MHE− group (mean 1.5 ± SE 0.4), and 89 accidents in the control group (mean 1.8 ± SE 0.2). Two patients in the MHE+ group, 1 patient in the MHE− group, and 3 patients in the control group had no accidents.

Crash types were divided into 5 categories: (1) head-on collision with a vehicle; (2) loss of vehicle control and hitting a motionless object; (3) hitting a pedestrian/dog; (4) swerving off the road; and (5) other. The majority of accidents in the MHE+ group were head-on collisions with a vehicle and hitting a pedestrian or dog (56%), far more than in the MHE− (25%) and control (23%) groups (P = 0.001).

All patients who had accidents experienced them in at least 2 areas of the simulation: (1) when asked to overtake a slow-moving vehicle in their lane by crossing into the lane of oncoming traffic, a miscalculation of the time needed to overtake that vehicle resulted in a head-on collision; and (2) collision with a dog in the suburban town occurred when the dog darted out from between parked cars.

In the group of patients with cirrhosis, there was no significant difference in accidents between hepatitis C patients [n = 32; number of accidents = 82 (mean, 2.6)] and hepatitis C–negative patients [n = 15; number of accidents = 38 (mean, 2.5)]. Similarly, there was no difference in the number of accidents between men [n = 26; number of accidents = 69 (mean, 2.6)] and women [n = 21; number of accidents = 51 (mean, 2.4)].

Divided Attention Task.

There was a significantly higher “miss” rate on the 5 attention tasks in the MHE+ group compared with the other groups (Table 1).

Navigation Task.

MHE+ patients had significantly more illegal turns compared with MHE− patients and controls, although the time required was similar between groups for completion of all tasks (Table 1, Fig. 3). There were a total of 34 illegal turns made in the MHE+ group (n = 33), 6 in the MHE− group (n = 14), and 6 in the control group (n = 48). Most of the illegal turns made were not associated with an accident (72%, 67%, and 84%, respectively; P = 0.1); the proportion did not significantly differ among the groups. Therefore, most of the patients who made an illegal turn continued on the incorrect path after they had made the turn. They returned to the path indicated on the map only when they realized themselves that they had made an illegal turn, without prompting from the supervisor.

thumbnail image

Figure 3. Number of illegal turns on the navigation task on the driving simulator. Patients with MHE had a significantly higher rate of illegal turns (median 1) compared to patients without MHE (median 0) and controls (median 0) (P = 0.007). The line between the 3 groups joins the medians between the groups.

Download figure to PowerPoint

In the group of patients with cirrhosis, there were no significant differences in number of illegal turns between hepatitis C patients [n = 32; illegal turns = 28 (mean, 0.9)] and hepatitis C–negative patients [n = 15; number of accidents = 12 (mean, 0.8)]. Similarly, there was no difference in the number of accidents between men [n = 26; illegal turns = 23 (mean, 0.9)] and women [n = 21; illegal turns = 17 (mean, 0.8)].

The number of illegal turns was significantly correlated with the number of accidents in the driving task (r = 0.51, P = 0.0001).

Correlation Between Psychometric Tests and Illegal Turns and Accidents in the Group of Patients with Cirrhosis.

There was significant correlation in psychometric test impairment between all 4 tests and the illegal turns on the driving simulator. The highest correlation with illegal turns was with ICT lures (Table 2). There was a significant positive correlation between number of abnormal tests and illegal turns (r = 0.56, P = 0.0001).

Table 2. Correlation Between Illegal Turns, Accidents and Individual Psychometric Tests
 Correlation Coefficient with Illegal TurnsP ValueCorrelation Coefficient with Number of AccidentsP Value
  1. Illegal turns and number of simulator accidents were maximally correlated with ICT lures. All other psychometric test impairments correlated significantly with illegal turns, and all but BDT impairment were significantly correlated with simulator accidents. ICT lures are determinants of ICT performance; higher lures indicate worse performance.

ICT lures0.600.00010.440.002
NCT-A0.540.00010.380.009
DST−0.490.001−0.400.006
BDT−0.390.006−0.060.68

ICT, NCT-A, and DST impairment were significantly correlated with the number of accidents on the driving simulator. The highest correlation was again between ICT lures and number of accidents. Correlation of number of accidents and BDT impairment did not reach statistical significance (Table 2).

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References

This study demonstrates that driving abnormalities in MHE consist of impairment in navigation in addition to attention deficits, both of which are highly correlated with difficulties in attention and response inhibition. The illegal turns and accidents on the simulator correlated mostly with abnormal performance on the ICT.

MHE is a significant neurocognitive complication of cirrhosis that is associated with impaired driving skills and a high risk of motor vehicle accidents and traffic violations.4, 5 The need to diagnose MHE is growing given this potential public health problem.29 Therefore, an in-depth investigation of MHE-associated driving abnormalities is essential to propose treatment and management strategies.

Previous studies have shown that attention deficits may result in impaired driving skills in MHE.4, 16 Nyberg et al.30 reported that cirrhotic patients with MHE had an impaired ability to follow a map compared with patients who did not have MHE. This preliminary investigation of 15 cirrhotic patients without age-matched controls did not exclude patients with alcoholic cirrhosis or those receiving therapy for hepatic encephalopathy with lactulose or rifaximin. The present study confirms and extends the findings of Nyberg et al. with respect to impairment of navigation skills in a larger cohort of cirrhotic patients without involvement of alcohol or current treatment for encephalopathy and with age-matched controls.

Navigation is an essential component of daily functioning and driving that is dependent on retrieval of information and rapid adaptation to new information.14 It is a complex human function that requires multicomponent system integration. These processes include visual attention, visuo-perceptual analysis and judgment, episodic and spatial memory, map interpretation, working memory operations that serve to integrate and update the essential salient information pool of the moment, executive decision making, and result monitoring operations. In addition, response inhibition is required for every step of this system.15 Because navigation involves an intricate set of mental operations, it is particularly vulnerable to encephalopathic mechanisms that affect any one component or combination of components.

In this study, the patients were allowed to consult the map; therefore, attention and working memory were taxed in the navigation exercise. Attention and working memory have been shown to be impaired in MHE31; therefore, the navigation task was used to highlight the effect of this deficit on driving performance, in addition to the well-known MHE-associated neuropsychological impairments.12 The virtual city was designed to test the responses of patients in an unfamiliar environment with visual scanning (reading the map), visuo-motor coordination (driving the vehicle without accidents), working memory (realizing where to go from a map and following appropriate signs to avoid making illegal turns), and resultant appropriate responses leading to legal turns and avoidance of illegal turns.

There was a significantly higher rate of illegal turns in MHE+ patients compared with MHE− patients and controls. This is an especially significant finding, because the paper map had a clearly marked route, and stop signs and markers pointing in the right direction were located at every possible turn in the virtual city. There was also no minimum speed requirement, which may explain the similar total run times and navigation times across the groups. Therefore, translating the map into practice, which requires visual scanning, processing, and visuo-motor coordination was impaired in patients with MHE. This brings into focus that there may be multiple dimensions of driving impairment in MHE patients.

Navigation impairments can be an important issue for MHE patients in unfamiliar surroundings. Problems in navigation are central to the disease progression of Alzheimer's disease and HIV-related dementia, and they are associated with poor outcomes in driving and daily functioning.16–18 Translation of these findings into real-world driving suggests that an inability to follow signs or a map may be an important dimension of the driving impairment in MHE patients in addition to problems in attention and reaction time.

Impairment in the navigation task was significantly correlated with number of accidents in the separate driving task. In the driving task, patients had to follow on-screen cues that would help them complete the task without causing an accident. Accidents in the driving simulator occurred due to problems in reaction time (e.g., inability to apply brakes in time) or visual scanning and attention deficits (e.g., inability to gauge time needed to overtake vehicles and avoid oncoming traffic). This is in line with known deficits of MHE patients on formal driving tests. Wein et al.4 showed that patients with MHE had significantly worse performances in car handling as rated by skilled driving instructors and performed poorly on tasks that required complex attention and executive function (e.g., acknowledging pedestrians and cyclists, checking rearview mirrors, following road signs and traffic rules). Driving instructors also had to intervene to prevent a traffic accident at a significantly higher rate in MHE patients compared with others. The driving simulator in the present study confirmed these findings in that MHE patients had a significantly higher rate of accidents as a result of poor judgment (when overtaking another car) or prolonged reaction times in applying brakes (to avoid crashing into a pedestrian or a dog). It also confirms that the driving simulator functions as a tool that correlates with previous driving experience in MHE patients.

In the real world, divided attention is essential when performing a task in addition to driving (e.g., talking on a cellular telephone or changing channels on the car radio). The divided attention tasks in this study were simple, requiring patients to either blow the horn or stop the vehicle after appearance of visual cues during the driving simulation. These cues were missed more often in MHE patients compared with other groups. This confirms existing knowledge that attention tasks are negatively affected in MHE patients and extends this impairment to include tasks that require divided attention while driving.12, 30, 32

Interestingly, there was a significant correlation between poor performances on all psychometric tests; ICT lures, DST, BDT, and NCT-A with navigation impairment and all except BDT with accidents. ICT lures had the highest correlation with illegal turns and number of accidents. In this population, there was an 86% sensitivity using more than 5 lures, likely reflecting the older age group of all 3 populations compared with the initial study.20 Response inhibition is the basis for response to lures—stimuli that a patient is trained not to respond to in the training run but nevertheless incorrectly responds to instead of inhibiting the response.21 Successful response inhibition is necessary at every step in this complex navigation task to prevent an incorrect response—in this case, illegal turns. Impaired response inhibition is an integral part of the neuropsychological abnormalities in MHE, and it is associated with altered executive control.9, 13 Executive control is responsible for supervising several cognitive functions and resolving conflicts from differing stimuli in order to produce the correct response.33 The navigation task consisted of coordinating the marked path on the paper map with the signs in the virtual city. Therefore, making an illegal turn would stem from defective executive control, which prevents inputs from the paper map path from being coordinated with the virtual city. This would then explain the high degree of correlation between abnormal lure response and illegal turns. However, because this complex task also tests for simple visual attention, visuo-perceptual analysis, and judgment, it is not surprising that poor performance on navigation is also correlated with poor performance on the NCT-A, DST, and BDT.

Navigation is an intricate activity that demands that many component subsystems work together in concert.15 Driving, especially in unfamiliar surroundings, brings all these systems into play. Therefore, it is likely that differing facets of impairment in the multicomponent navigation task add a separate and important layer of difficulties during driving in MHE patients.

Correlation of NCT-A, DST, and ICT lures with accidents in the driving simulator is similar to previous experience with MHE patients reporting more accidents and traffic violations on anonymous questionnaires and highlights attention deficits as a contributor toward accidents. This is further highlighted by the positive correlation between abnormal performance on the number of tests (NCT-A, BDT, and DST) and illegal turns. Illegal turns and accidents in the driving simulator were also highly correlated with each other; this may be due to varying consequences of dysfunction in the attention–executive control circuit.9 The independent contribution of navigation abnormalities would likely increase the risk of placing patients in situations where an accident may occur, because attention and reaction times are already impaired.

Navigation studies in healthy humans have demonstrated that egocentric (navigation using fixed angles and distances from one point to another) and allocentric navigation (navigation from distal cues using flexible representation) are distinct processes.34 The current navigation task in the virtual city tested both processes and included the visual input of the handheld paper map guiding the patients to the correct location. Although this test was not strictly a navigation task based on memory, because we allowed patients to consult the map, they still had to respond to visual cues throughout the navigation task to follow the marked route. An investigation of healthy individuals undergoing a virtual reality task (with arrows marking the proper route) with concurrent functional MRI revealed that the right hippocampus and right inferior parietal cortex blood flow and activation were increased with successful navigation.35 Critical flicker function testing, which involves rapid decision making, has revealed impaired blood flow to the right inferior parietal lobe in patients with MHE.36 Although the present study was not designed to evaluate specific brain activation, it is possible that the impairment of navigation associated with MHE is related to impairment in the decision-making circuit, working memory, executive control, and response inhibition.

Previous studies have suggested that men may have an advantage over women with respect to navigational sense.35 In the present study, illegal turns and accidents experienced by men were comparable to women in both the control and cirrhotic patient groups. Hepatitis C status is independently associated with psychometric abnormalities; therefore, a post hoc analysis of number of accidents and illegal turns between hepatitis C–positive and hepatitis C–negative cirrhotic patients was performed.37, 38 This comparison did not reveal any significant differences between the 2 groups. Therefore, in our population, sex and hepatitis C virus status was not significantly associated with navigation or driving performance on the driving simulator.

There are several factors that can result in traffic accidents, including human and environmental factors.7 This being a simulator study, we were able to keep the environment constant so that the human factors could be studied in detail. Other factors that negatively influence driving performance, such as age, driving experience, and alcohol use, were not significantly different between groups. The study patients only included nonalcoholics; none of the cirrhotic patients had used alcohol within 3 months, and controls were age-matched to the cirrhotic patients. Therefore, presence of MHE is likely the reason for navigation and driving impairment in this study.

The self-recognition of driving abnormalities was evident in poor scores on the DBQ and overall self assessment of driving performance in MHE+ patients compared with MHE− and controls, although the absolute difference between the groups on the DBQ and overall assessment was slight. The DBQ is a 26-part copyrighted survey that inquires about specific driving practices that have been validated in attention deficit hyperactivity disorder.24 It was used in the present study because patients with attention deficit hyperactivity disorder struggle with attention deficits similar to patients with MHE. This significant difference in scores could mean that MHE patients have some insight into their driving impairments—although despite this poor performance, none of the MHE patients scored themselves below 7 for overall self-assessment (maximum 10) or below 90 for the DBQ (maximum 104). Further research into the ability of the DBQ to evaluate safe drivers in MHE is needed. It follows that an in-depth questioning of cirrhotic patients with MHE—with or without the DBQ—may be an important first step in elucidating the burden of the associated driving problems.

The present study was limited by the use of a driving simulator and not actual driving tests. However, because the primary aim of the study was to investigate navigation skills in a previously unknown route using standard driving conditions, we believed that a simulator would be a better choice than a real-world driving test. It would have been difficult to design a navigation route on a public road that was unfamiliar to the patients, because all of them lived in the Milwaukee area; therefore, we used the simulator's virtual city to study navigation skills. In addition, a simulator—which engages the patient to feel a presence (i.e., the subjective experience of being in one place while physically being in another) and has cues that are as close to real life as possible—is considered optimal for studying navigation skills.35 However, simulators do not provide the additional vestibular input during driving that can also guide navigation and driving.39 Further studies using on-road driving tests may be required to confirm abnormal navigation in MHE patients.

Driving abnormalities with respect to attention deficits in MHE have been described using actual driving tests.4 Therefore, the simulated driving task was included in the present study to extend the validity of the psychometric test-based division of the cirrhotic patient group into MHE+ and MHE− groups against accidents and to confirm that the simulator driving task findings were in line with current knowledge.

Treatment of MHE improves psychometric performance; however, the effect of treatment on driving performance is not clear.40, 41 Because driving performance on a simulator and psychometric impairment are highly correlated, it can be hypothesized that improvement in one leads to improvement in the other. Further study into the effect of MHE therapy on driving and navigation tasks is warranted.

In conclusion, the present study shows that patients with MHE have impaired complex navigation skills on a driving simulator, and this correlates with impairment in response inhibition and attention. This navigation difficulty may pose additional problems during real-life driving, compounding the pre-existing deleterious effect of slow reaction times and attention deficits and predisposing MHE patients to have traffic accidents. Impairment as revealed by the ICT, which tests response inhibition and is a measure of executive control, was highly correlated with navigation and driving difficulties. Further studies to gauge the effect of MHE therapy on navigation and driving skills are warranted.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  • 1
    Ferenci P, Lockwood A, Mullen K, Tarter R, Weissenborn K, Blei AT. Hepatic encephalopathy—definition, nomenclature, diagnosis, and quantification: final report of the working party at the 11th World Congresses of Gastroenterology, Vienna, 1998. HEPATOLOGY 2002; 35: 716721.
  • 2
    Groeneweg M, Quero JC, De Bruijn I, Hartmann IJ, Essink-bot ML, Hop WC, et al. Subclinical hepatic encephalopathy impairs daily functioning. HEPATOLOGY 1998; 28: 4549.
  • 3
    Romero-Gomez M, Boza F, Garcia-Valdecasas MS, Garcia E, Aguilar-Reina J. Subclinical hepatic encephalopathy predicts the development of overt hepatic encephalopathy. Am J Gastroenterol 2001; 96: 27182723.
  • 4
    Wein C, Koch H, Popp B, Oehler G, Schauder P. Minimal hepatic encephalopathy impairs fitness to drive. HEPATOLOGY 2004; 39: 739745.
  • 5
    Bajaj JS, Hafeezullah M, Hoffmann RG, Saeian K. Minimal hepatic encephalopathy: a vehicle for accidents and traffic violations. Am J Gastroenterol 2007; 102: 19031909.
    Direct Link:
  • 6
    Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA 2004; 291: 12381245.
  • 7
    Evans L. The dominant role of driver behavior in traffic safety. Am J Public Health 1996; 86: 784786.
  • 8
    Talwalkar JA, Kamath PS. Influence of recent advances in medical management on clinical outcomes of cirrhosis. Mayo Clin Proc 2005; 80: 15011508.
  • 9
    Amodio P, Schiff S, Del Piccolo F, Mapelli D, Gatta A, Umilta C. Attention dysfunction in cirrhotic patients: an inquiry on the role of executive control, attention orienting and focusing. Metab Brain Dis 2005; 20: 115127.
  • 10
    Weissenborn K, Ennen JC, Schomerus H, Ruckert N, Hecker H. Neuropsychological characterization of hepatic encephalopathy. J Hepatol 2001; 34: 768773.
  • 11
    Ortiz M, Jacas C, Cordoba J. Minimal hepatic encephalopathy: diagnosis, clinical significance and recommendations. J Hepatol 2005; 42(Suppl): S45S53.
  • 12
    Weissenborn K, Giewekemeyer K, Heidenreich S, Bokemeyer M, Berding G, Ahl B. Attention, memory, and cognitive function in hepatic encephalopathy. Metab Brain Dis 2005; 20: 359367.
  • 13
    Schiff S, Vallesi A, Mapelli D, Orsato R, Pellegrini A, Umilta C, et al. Impairment of response inhibition precedes motor alteration in the early stage of liver cirrhosis: a behavioral and electrophysiological study. Metab Brain Dis 2005; 20: 381392.
  • 14
    Maguire EA, Burgess N, Donnett JG, Frackowiak RS, Frith CD, O'Keefe J. Knowing where and getting there: a human navigation network. Science 1998; 280: 921924.
  • 15
    Kolb B, Whishaw IQ. Spatial behavior. In: KolbB, WhishawIQ, eds. Fundamentals of Human Neuropsychology. 5th ed. New York: Worth Publishers; 2003: 643676.
  • 16
    Marcotte TD, Wolfson T, Rosenthal TJ, Heaton RK, Gonzalez R, Ellis RJ, et al. A multimodal assessment of driving performance in HIV infection. Neurology 2004; 63: 14171422.
  • 17
    Cherrier MM, Mendez M, Perryman K. Route learning performance in Alzheimer disease patients. Neuropsychiatry Neuropsychol Behav Neurol 2001; 14: 159168.
  • 18
    Tetewsky SJ, Duffy CJ. Visual loss and getting lost in Alzheimer's disease. Neurology 1999; 52: 958965.
  • 19
    Wechsler D. Wechsler Adult Intelligence Scale III. San Antonio, TX: Psychological Corp; 1999.
  • 20
    Bajaj JS, Saeian K, Verber MD, Mischke D, Hoffman RG, Franco J, et al. Inhibitory control test is a simple method to diagnose minimal encephalopathy and predict development of overt hepatic encephalopathy. Am J Gastroenterol 2007; 102: 754760.
    Direct Link:
  • 21
    Garavan H, Ross TJ, Stein EA. Right hemispheric dominance of inhibitory control: an event-related functional MRI study. Proc Natl Acad Sci U S A 1999; 96: 83018306.
  • 22
    Pliszka SR, Liotti M, Woldorff MG. Inhibitory control in children with attention-deficit/hyperactivity disorder: event-related potentials identify the processing component and timing of an impaired right-frontal response-inhibition mechanism. Biol Psychiatry 2000; 48: 238246.
  • 23
    Ford JM, Gray M, Whitfield SL, Turken AU, Glover G, Faustman WO, et al. Acquiring and inhibiting prepotent responses in schizophrenia: event-related brain potentials and functional magnetic resonance imaging. Arch Gen Psychiatry 2004; 61: 119129.
  • 24
    Barkley RA, Murphy KR, Dupaul GI, Bush T. Driving in young adults with attention deficit hyperactivity disorder: knowledge, performance, adverse outcomes, and the role of executive functioning. J Int Neuropsychol Soc 2002; 8: 655672.
  • 25
    Lenne MG, Triggs TJ, Redman JR. Interactive effects of sleep deprivation, time of day, and driving experience on a driving task. Sleep 1998; 21: 3844.
  • 26
    Marcotte TD, Heaton RK, Wolfson T, Taylor MJ, Alhassoon O, Arfaa K, et al. The impact of HIV-related neuropsychological dysfunction on driving behavior. The HNRC Group. J Int Neuropsychol Soc 1999; 5: 579592.
  • 27
    Ware JC, Risser MR, Manser T, Karlson KH Jr. Medical resident driving simulator performance following a night on call. Behav Sleep Med 2006; 4: 112.
  • 28
    Lee HC, Lee AH, Cameron D. Validation of a driving simulator by measuring the visual attention skill of older adult drivers. Am J Occup Ther 2003; 57: 324328.
  • 29
    Poordad FF. Review article: the burden of hepatic encephalopathy. Aliment Pharmacol Ther 2007; 25(Suppl 1): 39.
  • 30
    Nyberg SL, Baskin-Bey ES, Mitchell MM, Bida JP, Schneider NK, Smith GE, et al. Early experience with HEADS: Hepatic encephalopathy assessment driving simulator. Advances in Transportation Studies 2006: 5362.
  • 31
    Hilsabeck RC, Perry W, Hassanein TI. Neuropsychological impairment in patients with chronic hepatitis C. HEPATOLOGY 2002; 35: 440446.
  • 32
    Weissenborn K, Heidenreich S, Ennen J, Ruckert N, Hecker H. Attention deficits in minimal hepatic encephalopathy. Metab Brain Dis 2001; 16: 1319.
  • 33
    Carter CS, Braver TS, Barch DM, Botvinick MM, Noll D, Cohen JD. Anterior cingulate cortex, error detection, and the online monitoring of performance. Science 1998; 280: 747749.
  • 34
    Hort J, Laczo J, Vyhnalek M, Bojar M, Bures J, Vlcek K. Spatial navigation deficit in amnestic mild cognitive impairment. Proc Natl Acad Sci U S A 2007; 104: 40424047.
  • 35
    Maguire EA, Burgess N, O'Keefe J. Human spatial navigation: cognitive maps, sexual dimorphism, and neural substrates. Curr Opin Neurobiol 1999; 9: 171177.
  • 36
    Zafiris O, Kircheis G, Rood HA, Boers F, Haussinger D, Zilles K. Neural mechanism underlying impaired visual judgement in the dysmetabolic brain: an fMRI study. Neuroimage 2004; 22: 541552.
  • 37
    McAndrews MP, Farcnik K, Carlen P, Damyanovich A, Mrkonjic M, Jones S, et al. Prevalence and significance of neurocognitive dysfunction in hepatitis C in the absence of correlated risk factors. HEPATOLOGY 2005; 41: 801808.
  • 38
    Cordoba J, Flavia M, Jacas C, Sauleda S, Esteban JI, Vargas V, et al. Quality of life and cognitive function in hepatitis C at different stages of liver disease. J Hepatol 2003; 39: 231238.
  • 39
    McNaughton BL, Barnes CA, Gerrard JL, Gothard K, Jung MW, Knierim JJ, et al. Deciphering the hippocampal polyglot: the hippocampus as a path integration system. J Exp Biol 1996; 199: 173185.
  • 40
    Watanabe A, Sakai T, Sato S, Imai F, Ohto M, Arakawa Y, et al. Clinical efficacy of lactulose in cirrhotic patients with and without subclinical hepatic encephalopathy. HEPATOLOGY 1997; 26: 14101414.
  • 41
    Prasad S, Dhiman RK, Duseja A, Chawla YK, Sharma A, Agarwal R. Lactulose improves cognitive functions and health-related quality of life in patients with cirrhosis who have minimal hepatic encephalopathy. HEPATOLOGY 2007; 45: 549559.