The effects of visual-field loss from panretinal photocoagulation of proliferative diabetic retinopathy on performance in a driving simulator

ABSTRACT BACKGROUND The purpose of this study was to compare driving-simulator performance of participants with visual-field loss (VFL) from panretinal photocoagulation (PRP) of

proliferative diabetic retinopathy (PDR) with a normally sighted control group. Furthermore, we investigated the effects of VFL of different extent on driving. METHODS Data on performance

and safety from a traffic-simulator test for 27 participants with VFL from PRP of PDR were retrospectively compared with data from 83 individuals without visual deficits in a cross-sectional

study. Individuals with diabetes that regained their driving licences after a successful simulator test were then followed in a national accident database. RESULTS Diabetes participants

passed the test in 56% of the cases. Compared with the control group, diabetes participants had more risky “failed to give way” events and longer reaction times. Failed diabetes participants

had lower mean sensitivity in the superior visual field than those who passed. None of the participants with a regained licence were involved in a motor vehicle accident during the 3–6-year

follow-up after the simulator test. CONCLUSIONS Diabetes participants had worse performance and safety than the controls. However, even individuals with VFL from PRP might drive safely,

which highlights the need for individual assessments in licencing issues. You have full access to this article via your institution. Download PDF SIMILAR CONTENT BEING VIEWED BY OTHERS THE

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FUNCTION LOSS IN DRIVERS WITH SIMULATED MEDIA OPACITY Article Open access 01 August 2022 INTRODUCTION Driving a car is inarguably a highly visual task. Countries all over the world have

therefore set visual requirements for holding a driver’s license that usually includes minimum visual acuity and visual field. The relationship between visual-field loss (VFL) and driving is

however far from clear. Some studies have shown that drivers with VFL are more unsafe, others have failed to show any correlation [1]. Comparing results is also complicated as definitions

of both VFL and safe driving vary across studies. Two major outcomes are used in research on driving, safety, and performance. Safety is defined by adverse events, typically collisions that

might be studied in accident statistics or surveys. Performance refers to behavior while maneuvering a vehicle. Both safety and performance may also be tested either on road or in

simulators. On road, driving is obviously more authentic, but it is difficult to test hazardous situations in a systematic way. Simulator tests on the other hand can test attention and

reactions under standardized conditions. However, it is not yet possible to create a perfect imitation of reality in simulators, that also might give severe dizziness (simulator sickness).

In the absence of a strong correlation between visual functions and driving, the ultimate method and cutoff values for vision testing in licensing issues are still left to discover and

visual requirements for driving differ both between and within nations [2]. DIABETES AND VISUAL-FIELD LOSS Proliferative diabetic retinopathy (PDR) is the most common cause of vision

impairment and blindness among working-age adults around the world [3]. Even if intravitreous antivascular endothelial growth-factor (VEGF) injections have emerged as a treatment alternative

the last decade, panretinal photocoagulation (PRP) has been the standard treatment for patients with PDR since the 1970s [4]. Although effective in reducing the risk for severe visual loss,

the destructive nature of laser treatment may also cause peripheral VFL with implications for the patient’s ability to drive. Estimates for the prevalence of VFL sufficient to preclude

driving at 6 months after bilateral PRP range from 10 to 50% [5,6,7]. Empirically, one might expect a close relationship between the total burn area and the degree of visual-field loss. This

might explain why more recent studies of PRP with modern multispot lasers have shown none or very mild visual-field loss [8, 9]. It is further important to note that retinal ischemia from

PDR also causes visual-field changes. In the 5-year results from DRCRnet Protocol S, patients treated with anti-VEGF had similar changes of the visual field as patients treated with PRP

[10]. PREVIOUS STUDIES OF VISUAL-FIELD LOSS FROM DIABETES ON ROAD AND SIMULATED DRIVING Despite the impact of diabetic retinopathy on visual function, few studies have evaluated its

association with driving performance and safety. A case-control study of over 200 drivers involved in motor vehicle accidents has shown that older drivers with diabetic retinopathy have a

similar risk of injurious crash involvement compared with healthy controls [11]. However, this study included no information of severity or treatment of the retinopathy. A small-scale

driving-simulator study of 25 drivers with diabetic retinopathy, about half of them with previous PRP, demonstrated that both laser scarring and retinal thickness negatively impacted driving

performance. Laser scar grades significantly correlated with longer response time [12]. The purpose of this study was to compare driving-simulator performance of participants with VFL from

PRP for PDR with a normally sighted control group. Furthermore, we investigated the effects of VFL of different extents on driving. MATERIALS AND METHODS PARTICIPANTS In the end of 2014 and

beginning of 2015, normally sighted individuals were recruited to perform a driving-simulator test at the Swedish Road and Traffic research institute (VTI) in Linköping. They should state

themselves as healthy, drive approximately 15,000 km/year, and be between 55 and 75 years of age. All of them were screened for visual-field defects with Humphrey perimetry 24–2. These 83

individuals were paid 100 Euro for participation. Their driving behavior was used to create reference values used to define a passed test. Thereafter, between June 2016 and August 2018,

individuals with a withdrawn licence due to VFL could apply for the test. It was initially performed only for research purposes, but a successful test was later accepted by the Swedish

Transport Agency as a cause of dispensation (i.e., return of the driver’s licence), if no other medical complications were present. Nearly all (95%) of the participants therefore knew that

they could have their driver’s license renewed following a successful test. The remaining individuals were also informed of the possibility to use the test result as a cause of dispensation,

which made all participants highly motivated. The cost for the individual was about 2000 euro. Despite the price, the interest was very high. More than 300 individuals with VFL for

different reasons completed the test until August 2018 when the activity was paused for evaluation. The participants attached medical records and visual-field charts when applying for the

simulator test. Diagnosis and visual-field examinations were therefore always done in advance in a clinical setting. Besides PRP for PDR, stroke and glaucoma were other common reasons for

VFL. This study analyzes the result from the driving-simulator test for 27 participants with VFL from a full 360-degree scatter for PDR compared with the control group. Ethical approval was

given by Linköping University Committee (Dnr 2014/124–31). FIELD OF VISION As all diabetes participants had withdrawn licenses, everyone also had severe visual-field loss according to the

Swedish legislation. To hold a driver’s license in Sweden, the extent of the visual field should be at least 120 degrees horizontal and 40 degrees vertical. More than two adjacent missed

points with Esterman perimetry within this area preclude driving. No missed points are allowed within the central 20-degree radius [13]. To be included in analysis of visual field, an

examination with Esterman program with Humphrey or Octopus perimetry was needed. The number of missed test points in different visual-field clusters was counted for each participant for

comparison (Fig. 1). THE SIMULATOR The driving simulator Sim III consisted of a real truncated car body [14]. Moving road patterns and landscape were shown on a large screen in front of the

car. Six projectors created one seamless image on the screen. The field of view was therefore approximately 140 degrees. By linking the cradle’s motion to the vehicle, the simulator’s motion

algorithm creates realistic lateral motions. Three LCD displays were used to simulate rear-view and side mirrors. A vibration table provided high-frequency reproduction of road unevenness

and moved the compartment/cab relative to the projected image. Even if the simulator resembled an authentic vehicle in almost all respects, it was still a simulated reality, which all

participants knew and understood (Fig. 2). PROCEDURE The procedure was the same for the control group and the diabetes participants in a number of respects. However, the normally sighted

also completed a screening perimetry test, which showed that none had visual-field loss. This group also completed some cognitive tests such as reading span [15]. The pretesting took

approximately one hour. Diabetes participants on the other hand completed the background questionnaire at home before the driving-test session. All participants signed an informed consent

before the test drive. The testing in the simulator started with a practice session for approximately 8 min, giving the participant a possibility to get acquainted with the car (especially

braking and steering behavior). All participants could abort at any time, without giving an explanation (however, all participants completed the test). THE SIMULATOR SCENARIO The driving

scenario contained three types of roads: urban section (speed limit 30–50 km/h), rural road (speed limit 70 km/h), and motorway (speed limit 110 km/h). The drive took approximately 50 min to

complete, depending on the participant’s chosen speed. Thirty-seven events that required a response by the driver were of particular interest for sufficient safety margins. However, the

drive also included situations that were not critical, but were included to provide a feeling of ordinary driving and thus normalize the drivers to a more relaxed driving behavior.

Pedestrians, buses, and cars coming from left or right and sometimes from two directions at the same time were presented. These objects imitated behavior from real life, i.e., pedestrians

could emerge behind a bus to “take a look” if it was possible to pass. The actions made by buses, cars, and pedestrians were initiated by the speed and distance from the car driven by the

participant. The actions of interest (with buses, cars, pedestrians, etc.) were scripted events and the same for all participants. In such a scripted event, several aspects were measured:

speed when a parked bus was seen, speed while passing the bus, position in the lane, braking pressure when the face/body of the pedestrian to detect was visible, brake reaction time,

collisions, distance to bus, and speed passing the pedestrian. The events used in the scenario should also be of different criticality and difficulty, in order to reduce floor or ceiling

effects, i.e., to be able to discriminate between drivers with good safety margins vs. those with insufficient safety margins. During the development of the scenario, it contained turning 90

degrees left and right. However, the pilot testing with individuals at this age revealed that over 50 percent strongly experienced simulator sickness. The final version, and the version

used in this study, therefore did not include any sharp turns. It should also be noted that collisions were not followed by a “crash experience” (sound or vibration etc.). In this way, all

participants could complete the scenario and continue to gather data on performance and safety without negative psychological effects from previous critical driving. ASSESSMENT OF PASSED VS.

FAILED All test results were digitally stored in protocols divided into 37 events together with a video recording of the full driving scenario. This was retrospectively analyzed by two

independent traffic-safety experts, one traffic inspector and one traffic-safety researcher. These did a subjective assessment of the scenario out from risk management, scanning, speed

adjustment, and maneuvering. The assessments were completed with the help of test protocols and video recordings from the simulator. The experts could replay the complete drive on their own

computer screen and move forward or back in time at different speeds if necessary. The assessment was also performed in accordance with reference values from the control group. The

instruction to the traffic inspector (who assesses on road driving on a daily basis) was to use their understanding of a normal driving-licence session. The traffic-safety researcher used

the values in the protocol (THW, speed, brake power, and TTC, etc.) with normally sighted data to a further extent, in combination with the video recordings. Hence, the classification into

pass and fail was still based on a subjective assessment. However, if the experts disagreed in their opinion, a third assessment was performed by an additional traffic-safety researcher.

Disagreements were rare, less than 7% needed a third assessment. DESIGN The design was a between-participant design with diabetes vs. normally sighted as one variable. The dependent measures

used in this study were a passed test, but also several safety and performance parameters. The most important safety parameters were actual collisions and failure to give way and the most

important performance parameters were reaction time and time headway (THW). COLLISIONS The test included 33 possible collisions, including both with other cars and pedestrians. Among these,

7 collisions were to objects in front of the car, 6 in the back, 14 to the right, 2 to the left, and 4 both to the right and to the left. FAILURE TO GIVE WAY Failure to give way (FGW) was a

specific situation where the test driver came too close to a pedestrian, either by stopping too close or by passing too close, measured as the minimal distance to the pedestrian. FGW was

measured 11 times, 7 were to the right and 4 to the left. Distances between 0 and 1 meter were considered as hazardous and distances between 1 and 2 meters as risky. TIME HEADWAY Time

headway (THW) is the distance to different moving objects divided by the experimental vehicle speed [16]. THW was measured 29 times during the test. The number of THW values below 1 s were

considered as critical [17]. REACTION TIME Reaction time was measured 17 times during the test with objects (vehicle or pedestrian) that suddenly appeared and required braking. VELOCITY The

speed on different stretches was recorded from the simulator. Participants drove in three different environments, urban, rural, and motorway. STATISTICAL CONSIDERATIONS The comparisons of

interest was initially between normally sighted and diabetes participants. The second step was to compare passed diabetes participants with failed. The dependent measures used in the study

created different statistical analyses. The alpha level of p < 0.05 was always used. CAR ACCIDENTS AMONG DISPENSATION CASES One part of the evaluation of the simulator-based driving test

was to conduct a follow-up of all individuals that had regained their driving licence after a successful performance in the simulator. The Swedish Traffic Accident Data Acquisition (STRADA)

database was used and includes all road accidents with personal injuries in Sweden reported by the police or emergency hospitals. RESULTS DESCRIPTIVES The diabetes group was slightly younger

than the controls and had a somewhat lower proportion of women. The diabetes participants passed the simulator test in 56% overall (Table 1). Younger participants were not significantly

more successful than older (Fig. 3). DIABETES PARTICIPANTS VS. NORMAL SIGHTED Statistical analysis of average speed (with ANOVA), reaction times, lateral position (with independent t-tests),

collisions, THW events, and FGW events (with Fischer exact test) revealed that diabetes participants drove as fast as normally sighted on all stretches, slower reaction times, and the same

lateral position. Diabetes participants had the same number of collisions, more risky FGW events, and a tendency for more critical THW events (_p_ = 0.08) (Table 1). PASSED-DIABETES

PARTICIPANTS COMPARED WITH FAILED-DIABETES PARTICIPANTS The same analysis as for diabetes versus normally sighted was computed for passed- versus failed-diabetes participants. No significant

differences (_p_ > 0.05) could be detected for average speed, FGW, or lane position. An independent two-tailed _t_-test revealed that the failed diabetes participants had more critical

THW events, meaning that the individuals who passed the test had better safety margins than individuals who failed. Two tendencies were also obtained for collisions and reaction times (_p_ =

 0.08 (collisions) and _p_ = 0.08 (reaction time), respectively). CENTRAL TEST POINTS AND SUPERIOR VS INFERIOR VISUAL-FIELD LOSS Visual-field data that met the inclusion criteria were found

in all cases. Although not significant, participants with less than 5 blind test points in the superior cluster (A1, A2, B1, and B2) passed the test in 75% vs. 40% for participants with 5 or

more blind test points in the same area. Failed-diabetes participants had also lower mean sensitivity than passed in the same cluster (_p_ < 0.05 with two-tailed _t_-test). No

significant differences of mean sensitivity could be detected for the remaining clusters (Table 2). CAR ACCIDENTS AMONG DISPENSATION CASES The majority (all except 2) individuals with a

passed test applied for a renewed driver’s license. The 13 individuals that regained their licence had to prove that their visual field defects had not deteriorated in a given interval (e.g.

every second year). All of them still had a driver’s licence 4 years after the test. At the same time, none of them were found involved in a motor vehicle accident according to The Swedish

Traffic Accident Data Acquisition (STRADA). DISCUSSION This study of simulator-driving performance of individuals with visual-field loss from panretinal photocoagulation for proliferative

diabetic retinopathy showed that this group had both worse driver performance and safety margins than a normal-sighted control group. Passed-diabetes participants had better driving

performance and safety margins than failed. Furthermore, passed-diabetes participants had fewer blind-test points than failed in the superior field of vision. To the best of our knowledge,

this is the largest study so far of driving behavior in a simulator for individuals with VFL from PRP for PDR and the only one with defined visual-field clusters. Other strengths of the

study are the detailed simulator scenario and that the patients performed the test with the aim to regain their licenses, which guarantees very good participation. The control group was also

reasonably sex-matched with the study group. This is important as men and women may have different comfort with speed and willingness to take risk. For example, a recent study of gender

differences in simulated driving found that men drove more carefully than women [18]. The study has however also important weaknesses. As we did not have access to the complete medical

records, we could not evaluate the importance of visual acuity, status of retinopathy, number of laser sessions, specific macula treatment or the period from diabetes onset, and panretinal

photocoagulation to the simulator test. We could further not separate a single spot from multispot PRP and analyze if the latter method had fewer negative effects on driving. For the same

reason, we could not divide patients with previous vitrectomy in a separate group. Sharp turns could not be used because of simulator illness, which made the simulator less like reality.

Furthermore, a simulator test also always requires an amount of visual simplification of the roadway. The most important weakness, however, is that the normally sighted participants were not

assessed in terms of passed and failed due to resources (i.e., the availability of traffic inspectors), whereupon we do not know if all controls passed the test. At the same time, the

reference values for a passed test were created based on the results of the normally sighted control group. It should also be noted that the high cost for the testing (2000 Euros) might have

affected the selection of participants in two different ways. Participants with a better economy and participants who believed that they would pass the test were likely overrepresented. It

is therefore not surprising that the success rate was as high as 56%. Individuals with VFL from PRP might be safe drivers, which conforms to previous research [11]. This might be explained

by both optimized performance, as a passed test could lead to return of the driver’s licence, and differences in the severity of PRP in the study group. However, reaction times were longer

for the PRP group than the healthy controls, which also confirms already-known differences during simulated driving [12]. However, it should also be noted that patients with diabetes

mellitus have longer reaction times than nondiabetic persons in response to a visual stimuli, also in the absence of PRP and PDR, possibly caused by neuropathy or impaired cognitive

functions [19]. The PRP participants with a passed test had fewer blind spots in the superior visual field. This has never been studied before but contradicts similar research on patients

with visual-field loss from glaucoma, where patients involved in collisions had lower mean sensitivity in the inferior hemifield [20]. Studies of simulated driving with visual-field defects

from glaucoma [21] or stroke [22, 23] have suggested that drivers might compensate for the impaired detection by increased explorative head and eye movements. This aspect has still not been

studied for patients with diabetes and was unfortunately not a part of the design in the present study. The individuals with a renewed licence had no higher risk of on-road collisions in

reality at follow-up. The significance of this result, however, is unsure due to the low number of licences. Hence, it is not possible to conclude that the simulator assessment developed can

discriminate between safe and unsafe drivers yet. However, the data support that the method is valid, but needs further evaluations. Previous studies have shown that driving-simulator

testing seems to be a well-standardized method with good conformity to on-road driving, appropriate for assessment of driving performance in individuals with binocular visual-field loss

[24]. Compared with individuals that applied for the simulator test for other reasons, diabetes participants had a lower success rate than glaucoma participants (56% compared with 71%). This

result cannot be explained by lower compensatory abilities at higher age, as the diabetes participants were also younger (mean 60 years compared with 69 years). Failed glaucoma participants

had a higher extent of central visual-field loss, but no differences could be found between the superior and inferior visual field [25]. In summary, superior VFL from PRP seems to be more

crucial than inferior. Even if the extent of visual-field loss may predict driver safety on a group level, even drivers with severe visual-field loss might also be safe drivers. It seems

therefore reasonable to provide an opportunity for individualized assessments of practical fitness to drive in licencing issues. Multivariate analysis of visual, attentional, perceptual,

cognitive, and psychomotor abilities combined with a structured-road test might distinguish safe from unsafe drivers [26]. On-road testing by a certified driving examiner is currently

considered the clinical golden standard. However, driving simulators may provide a useful adjunct to a road test for evaluation of responses to potential hazards under safe, controlled, and

repeatable conditions [27]. SUMMARY WHAT WAS KNOWN BEFORE * Panretinal photocoagulation has been the standard treatment for patients with proliferative diabetic retinopathy for a long time.

* Although effective in reducing the risk for severe visual loss, laser treatment may cause peripheral visual field loss with implications for the ability to drive. * The relationship

between visual field loss and driving is far from clear. WHAT THIS STUDY ADDS * Superior visual-field loss seems to be more crucial than inferior for safe driving among individuals with

visual-field loss from panretinal photocoagulation. * However, as even individuals with severe visual-field loss might drive safely, there is a need for individual assessments in licensing

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literature. Clin Exp Optom. 2016;99:402–18. Article  Google Scholar  Download references FUNDING This study was funded by Trafikverket, Skyltfonden (TRV 2018/25726). AUTHOR INFORMATION

AUTHORS AND AFFILIATIONS * Department of Ophthalmology Eksjö, Region Jönköping County and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden Tomas Bro *

Swedish National Road and Transport Research Institute Linköping, Linköping, Sweden Jan Andersson Authors * Tomas Bro View author publications You can also search for this author inPubMed 

Google Scholar * Jan Andersson View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS JA was responsible for the study design and extracting data.

TB wrote the report. Both JA and TB analyzed data and interpreted the results. CORRESPONDING AUTHOR Correspondence to Tomas Bro. ETHICS DECLARATIONS COMPETING INTERESTS This study was

funded by Trafikverket, Skyltfonden (TRV 2018/25726). The authors declare no potential conflicts of interest with respect to the research, authorship, or publication of this article.

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and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Bro, T., Andersson, J. The effects of visual-field loss from panretinal photocoagulation of proliferative diabetic retinopathy on

performance in a driving simulator. _Eye_ 37, 103–108 (2023). https://doi.org/10.1038/s41433-021-01832-3 Download citation * Received: 19 January 2021 * Revised: 04 October 2021 * Accepted:

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