The metabolic demands of driving for drivers with type 1 diabetes mellitus

Hypoglycemia While Driving in Insulin-Treated Patients: Incidence and Risk Factors

OBJECTIVES

This study aimed to investigate a potential daily-life concern for patients with diabetes hypoglycemia while driving by (1) estimating their incidence in insulin-treated drivers, (2) determining factors associated with their occurrence, and (3) analyzing patients' behavior regarding prevention of hypoglycemia.

METHODS

We conducted an observational study from November 2013 to May 2018 in the endocrinology-diabetology-nutrition department of our university hospital. All patients treated for diabetes older than 18 years admitted in the department were eligible. A specific questionnaire assessing attitudes, knowledge, and consequences of hypoglycemia was provided. In this study, only insulin-treated patients who regularly drive were analyzed.

RESULTS

On the 233 insulin-treated drivers included, 45 (19%) self-reported at least 1 hypoglycemia while driving in the preceding year. Two factors were significantly associated with their occurrence: type 1 diabetes (odds ratio [OR] = 3.19; 95% confidence interval [CI] = 1.55-6.57) and experiences of asymptomatic hypoglycemia (OR = 2.20; 95% CI = 1.05-4.63). Awareness of the treatment hypoglycemia risk because of information provided by a medical specialist was also but nonsignificantly associated with hypoglycemia while driving (OR = 2.61; 95% CI = 0.86-7.92). Forty-one patients (18%) combined those 3 variables, 20 (49%) of them self-reported hypoglycemia while driving. Thirty-four percent of the patients never carried carbohydrates for hypoglycemia correction. Seventy-six percent do not monitor blood glucose level before driving.

CONCLUSIONS

Our questionnaire allowed us to highlight that 19% our cohort of insulin-treated drivers declared experiencing hypoglycemia while driving. Risk factors identified and prevention data collected should help us better target patient education.

Exploring Knowledge and Safety Practices for Driving in Youth With Type 1 Diabetes

OBJECTIVES

The aim of this work was to survey how well adolescents with type 1 diabetes mellitus (T1D) of legal driving age understand the risks associated with driving with diabetes and report adherence to recommendations.

METHODS

This study was a cross-sectional survey of 191 adolescents, 14 to 18 years of age, with T1D.

RESULTS

The average (standard deviation [SD]) glycated hemoglobin of respondents with a learner's or a driver's license was 9.0% (SD, 1.9%) and 8.9% (SD, 1.9%), respectively (p=0.91). The proportions of adolescents with a learner's or a driver's license who almost always or always checked their blood glucose prior to driving was 69% and 41%, respectively (p=0.01). Eighteen percent of adolescents with a learner's license and 41% with a driver's license experienced hypoglycemia while driving. The average number of weekly hypoglycemic events in each group was 2.0 (SD, 1.4) and 2.3 (SD, 2.0), respectively. There was a higher reported frequency of weekly mild hypoglycemic events between drivers who reported pulling over at least once while driving due to symptoms of hypoglycemia (3.25±2.38) and those who reported never having pulled over for hypoglycemia (1.87±1.31) (p=0.012). Respondents with a learner's license reported higher adherence to guidelines than those with a full license.

CONCLUSIONS

Clinical education needs to reinforce adherence to recommendations, particularly checking blood glucose or wearing a continuous glucose monitor prior to driving, for all adolescents of driving age. The frequency of mild hypoglycemic events per week is associated with self-reported hypoglycemic events while driving.

Glucose Variations During Driving in People With Type 1 Diabetes Using a Continuous Glucose Monitoring System

OBJECTIVE

Hypoglycemic events during driving are life-threatening complications in people with type 1 diabetes (T1D). While preliminary studies showed increased glucose demand in driving simulations, we investigated interstitial fluid (ISF) glucose when driving under real-life circumstances.

RESEARCH DESIGN AND METHODS

We measured ISF glucose in 10 participants with stable T1D during a 2-h driving course using a continuous glucose monitoring system.

RESULTS

Our data show a driving-associated rise of ISF glucose. Initially increasing glucose was followed by decreasing values. Under control conditions at the same time of the day without driving, no specific glucose changes were observed.

CONCLUSIONS

Real-life driving may have caused an initial glucose increase followed by decreasing glucose values in this cohort with well-controlled T1D. These findings may be limited to the selected study population.

Mental Work Requires Physical Energy: Self-Control Is Neither Exception nor Exceptional

The brain’s reliance on glucose as a primary fuel source is well established, but psychological models of cognitive processing that take energy supply into account remain uncommon. One exception is research on self-control depletion, where debate continues over a limited-resource model. This model argues that a transient reduction in self-control after the exertion of prior self-control is caused by the depletion of brain glucose, and that self-control processes are special, perhaps unique, in this regard. This model has been argued to be physiologically implausible in several recent reviews. This paper attempts to correct some inaccuracies that have occurred during debate over the physiological plausibility of this model. We contend that not only is such limitation of cognition by constraints on glucose supply plausible, it is well established in the neuroscience literature across several cognitive domains. Conversely, we argue that there is no evidence that self-control is special in regard to its metabolic cost. Mental processes require physical energy, and the body is limited in its ability to supply the brain with sufficient energy to fuel mental processes. This article reviews current findings in brain metabolism and seeks to resolve the current conflict in the field regarding the physiological plausibility of the self-control glucose-depletion hypothesis.

Low normal fasting glucose and risk of accidental death in Korean adults: A prospective cohort study

AIM

This study aimed to prospectively examine whether low normal glucose levels and hypoglycaemia are associated with increased mortality due to external causes, especially unintentional accidents.

METHODS

A total of 345,318 normoglycaemic Korean adults who had undergone health examinations during 2002-2003 were followed-up to 2013. To avoid potential biases related to glucose-lowering medication use, those with known diabetes or hyperglycaemia were excluded.

RESULTS

During 3.6 million person-years of follow-up, 1293 participants died because of unintentional accidents. Hazard ratios (HRs) for these accidental deaths were 1.26 (95% CI: 1.11-1.42), 1.60 (1.21-2.11) and 3.07 (1.37-6.85) for fasting serum glucose (FSG) levels of 70-79, 55-69 and <55mg/dL (3.9-4.4, 3.05-3.83 and <3.05mmol/L), respectively, compared with 80-99mg/dL (4.44-5.5mmol/L). FSG levels<80mg/dL were associated with an approximately 30% higher mortality due to accidents: specifically, 40% were non-fall-related injury; 50% were automobile-related; and 80% were motorcycle-related. The associations were weak (approximately 10% higher mortality, with P>0.05 for each cause) for deaths due to traffic accidents (pedestrians, pedal cyclists), falls, intentional self-harm and physical assault. The population attributable risks for FSG levels <80mg/dL were 10% (95% CI: 2-18%) for non-fall-related injury, 11% (6-17%) for car accidents and 17% (6-27%) for motorcycle accidents.

CONCLUSION

FSG levels of 70-79mg/dL (3.9-4.4mmol/L) as well as <70mg/dL are risk factors for accidental death. Appropriate management of the impact of FSG levels <80mg/dL might reduce unintended deaths due to non-fall-related injury, and automobile and motorcycle accidents, by ≥10%.

Predicting and Reducing Driving Mishaps Among Drivers With Type 1 Diabetes

OBJECTIVE

Two aims of this study were to develop and validate A) a metric to identify drivers with type 1 diabetes at high risk of future driving mishaps and B) an online intervention to reduce mishaps among high-risk drivers.

RESEARCH DESIGN AND METHODS

To achieve aim A, in study 1, 371 drivers with type 1 diabetes from three U.S. regions completed a series of established questionnaires about diabetes and driving. They recorded their driving mishaps over the next 12 months. Questionnaire items that uniquely discriminated drivers who did and did not have subsequent driving mishaps were assembled into the Risk Assessment of Diabetic Drivers (RADD) scale. In study 2, 1,737 drivers with type 1 diabetes from all 50 states completed the RADD online. Among these, 118 low-risk (LR) and 372 high-risk (HR) drivers qualified for and consented to participate in a 2-month treatment period followed by 12 monthly recordings of driving mishaps. To address aim B, HR participants were randomized to receive either routine care (RC) or the online intervention "DiabetesDriving.com" (DD.com). Half of the DD.com participants received a motivational interview (MI) at the beginning and end of the treatment period to boost participation and efficacy. All of the LR participants were assigned to RC. In both studies, the primary outcome variable was driving mishaps.

RESULTS

Related to aim A, in study 1, the RADD demonstrated 61% sensitivity and 75% specificity. Participants in the upper third of the RADD distribution (HR), compared with those in the lower third (LR), reported 3.03 vs. 0.87 mishaps/driver/year, respectively (P < 0.001). In study 2, HR and LR participants receiving RC reported 4.3 and 1.6 mishaps/driver/year, respectively (P < 0.001). Related to aim B, in study 2, MIs did not enhance participation or efficacy, so the DD.com and DD.com + MI groups were combined. DD.com participants reported fewer hypoglycemia-related driving mishaps than HR participants receiving RC (P = 0.01), but more than LR participants receiving RC, reducing the difference between the HR and LR participants receiving RC by 63%. HR drivers differed from LR drivers at baseline across a variety of hypoglycemia and driving parameters.

CONCLUSIONS

The RADD identified higher-risk drivers, and identification seemed relatively stable across time, samples, and procedures. This 11-item questionnaire could inform patients at higher risk, and their clinicians, that they should take preventive steps to reduce driving mishaps, which was accomplished in aim B using DD.com.

Driving and diabetes: problems, licensing restrictions and recommendations for safe driving

Driving is a complex process that places considerable demands on cognitive and physical functions. Many complications of diabetes can potentially impair driving performance, including those affecting vision, cognition and peripheral neural function. Hypoglycemia is a common side-effect of insulin and sulfonylurea therapy, impairing many cognitive domains necessary for safe driving performance. Driving simulator studies have demonstrated how driving performance deteriorates during hypoglycemia. Driving behavior that may predispose to hypoglycemia while driving is examined. Studies examining the risk of road traffic accidents in people with insulin-treated diabetes have produced conflicting results, but the potential risk of hypoglycemia-related road traffic accidents has led to many countries imposing restrictions on the type and duration of driving licenses that can be issued to drivers with diabetes. Guidance that promotes safe driving practice has been provided for drivers with insulin-treated diabetes, which is the group principally addressed in this review.

Recurrent Hypoglycemia Increases Anxiety and Amygdala Norepinephrine Release During Subsequent Hypoglycemia

Recurrent hypoglycemia (RH) is a common and debilitating side effect of therapy in patients with both type 1 and, increasingly, type 2 diabetes. Previous studies in rats have shown marked effects of RH on subsequent hippocampal behavioral, metabolic, and synaptic processes. In addition to impaired memory, patients experiencing RH report alterations in cognitive processes that include mood and anxiety, suggesting that RH may also affect amygdala function. We tested the impact of RH on amygdala function using an elevated plus-maze test of anxiety together with in vivo amygdala microdialysis for norepinephrine (NEp), a widely used marker of basolateral amygdala cognitive processes. In contrast to findings in the hippocampus and prefrontal cortex, neither RH nor acute hypoglycemia alone significantly affected plus-maze performance or NEp release. However, animals tested when hypoglycemic who had previously experienced RH had elevated amygdala NEp during plus-maze testing, accompanied by increased anxiety (i.e., less time spent in the open arms of the plus-maze). The results show that RH has widespread effects on subsequent brain function, which vary by neural system.

Diabetes and driving

The principal safety concern for driving for people treated with insulin or insulin secretagogues is hypoglycaemia, which impairs driving performance. Other complications, such as those causing visual impairment and peripheral neuropathy, are also relevant to medical fitness to drive. Case control studies have suggested that drivers with diabetes pose a modestly increased but acceptable and measurable risk of motor vehicle accidents compared to non-diabetic drivers, but many studies are limited and of poor quality. Factors which have been shown to increase driving risk include previous episodes of severe hypoglycaemia, previous hypoglycaemia while driving, strict glycaemic control (lower HbA1c) and absence of blood glucose monitoring before driving. Impaired awareness of hypoglycaemia may be counteracted by frequent blood glucose testing. The European Union Third directive on driving (2006) has necessitated changes in statutory regulations for driving licences for people with diabetes in all European States, including the UK. Stricter criteria have been introduced for Group 1 vehicle licences while those for Group 2 licences have been relaxed. Insulin-treated drivers can now apply to drive Group 2 vehicles, but in the UK must meet very strict criteria and be assessed by an independent specialist to be issued with a 1-year licence.

Hypoglycemia and safe driving

The lack of awareness of the effects of hypoglycemia on safe driving is a real issue for diabetic patients and a challenge for health care providers. Taking the form of questions and answers, this review addresses the issue of road traffic accidents and drivers with type 1 diabetes mellitus. While there is little evidence showing higher accident rates among diabetic drivers, there is research indicating that hypoglycemia compromises driving performance, resulting in slower response times and reduced cognitive function. Unawareness of an early fall in plasma glucose is another important issue that affects some diabetic drivers. The driver with type 1 diabetes is obliged to check their blood glucose before driving. The physician's duty is to familiarize the patient with the risk of hypoglycemia. If hypoglycemic unawareness is present, the physician should advise the patient to stop driving until the condition is reversed. The doctor should consider informing authorities if he concludes there is a risk and the driver cannot be persuaded to stop driving.

Driving with diabetes in the future: in-vehicle medical monitoring

The motor car is a ubiquitous feature of modern life, and most of us spend significant amounts of time in a car, behind the wheel. Driving a vehicle requires complex coordination of cognitive, motor, and sensory skills. All of these aspects can be affected adversely by diabetes per se, with hypoglycemia being the main concern for people with diabetes who drive. Here we introduce the concept of using the motor vehicle as a device to collect and deliver physiological and clinical information, which, in turn, may enable more people to drive more safely by reducing the chances of medical mishaps behind the wheel. This is particularly relevant for people living with diabetes who are at risk from a number of medical conditions that have the potential to have an impact on safe driving. The development of in-vehicle medical monitoring presents a new opportunity for novel collaborations between two industries, which have safety as a core value.

Mini-review: impact of recurrent hypoglycemia on cognitive and brain function

Recurrent hypoglycemia (RH), the most common side-effect of intensive insulin therapy for diabetes, is well established to diminish counter-regulatory responses to further hypoglycemia. However, despite significant patient concern, the impact of RH on cognitive and neural function remains controversial. Here we review the data from both human studies and recent animal studies regarding the impact of RH on cognitive, metabolic, and neural processes. Overall, RH appears to cause brain adaptations which may enhance cognitive performance and fuel supply when euglycemic but which pose significant threats during future hypoglycemic episodes.

Development of a neural network for prediction of glucose concentration in type 1 diabetes patients

BACKGROUND

A major difficulty in the management of diabetes is the optimization of insulin therapies to avoid occurrences of hypoglycemia and hyperglycemia. Many factors impact glucose fluctuations in diabetes patients, such as insulin dosage, nutritional intake, daily activities and lifestyle (e.g., sleep-wake cycles and exercise), and emotional states (e.g., stress). The overall effect of these factors has not been fully quantified to determine the impact on subsequent glycemic trends. Recent advances in diabetes technology such as continuous glucose monitoring (CGM) provides significant sources of data, such that quantification may be possible. Depending on the CGM technology utilized, the sampling frequency ranges from 1-5 min. In this study, an intensive electronic diary documenting the factors previously described was created. This diary was utilized by 18 patients with insulin-dependent diabetes mellitus in conjunction with CGM. Utilizing this dataset, various neural network models were constructed to predict glucose in these diabetes patients while varying the predictive window from 50-180 min. The predictive capability of each neural network within the fully trained dataset was analyzed as well as the predictive capabilities of the neural networks on unseen data.

METHODS

Neural network models were created using NeuroSolutions software with variable predictive windows of 50, 75, 100, 120, 150, and 180 min. Neural network models were trained using patient datasets ranging from 11-17 patients and evaluated on patient data not included in the neural network formulation. Performance analysis was completed for the neural network models using MATLAB. Performance measures include the calculation of the mean absolute difference percent overall and at hypoglycemic and hyperglycemic extremes, and the percentage of hypoglycemic and hyperglycemic occurrences were predicted.

RESULTS

Overall, the neural network models perform adequately at predicting at normal (>70 and <180 mg/dl) and hyperglycemic ranges (> or =180 mg/dl); however, glucose concentrations in areas of hypoglycemia were commonly overestimated. One potential reason for the "high" predictions in areas of hypoglycemia is due to the minimal occurrences of hypoglycemic events within the training data. The entire 18-patient dataset (consisting of 18,400 glucose values) had a relatively low incidence of hypoglycemia (1460 CGM values < or =70 mg/dl), which corresponds to approximately 7.9% of the dataset. On the contrary, hyperglycemia comprised approximately 35.7% of the dataset (6560 CGM values >or =180 mg/dl), and euglycemic values allotted for 56.4% of the dataset (10,380 CGM values >70 and <180 mg/dl). Results further indicate that an increase in predictive window leads to a decrease in predictive accuracy of the neural network model. It is hypothesized that the underestimation of hyperglycemic extremes is due to the extension of the predictive window and the associated inability of the neural network to determine oscillations and trends in glycemia as well as the occurrence of other relevant input events such as lifestyle, emotional states, insulin dosages, and meals, which may occur within the predicted time window and may impact or change neural network weights.

CONCLUSIONS

In this investigation, the feasibility of utilizing neural network models for the prediction of glucose using predictive windows ranging from 50-180 min is demonstrated. The predictive windows were chosen arbitrarily to cover a wide range; however, longer predictive windows were implemented to gain a predictive view of 120-180 min, which is very important for diabetes patients, specifically after meals and insulin dosages. Neural networks, such as those generated in this investigation, could be utilized in a semiclosed-loop device for guiding therapy in diabetes patients. Use of such a device may lead to better glycemic control and subsequent avoidance of complications.

Rebound effects with long-acting amphetamine or methylphenidate stimulant medication preparations among adolescent male drivers with attention-deficit/hyperactivity disorder

This study investigated whether OROS methylphenidate (OROS MPH, Concerta) or extended-release mixed amphetamine salts (se-AMPH ER, Adderall XR) were associated with worsening of driving performance, or drug rebound, relative to placebo 16-17 hours post-ingestion. Nineteen male adolescent drivers aged 17-19 with attention-deficit/hyperactivity disorder (ADHD) were compared on a virtual reality driving simulator and an on-road drive after taking 72 mg of OROS MPH, 30 mg of se-AMPH ER, or placebo. Medication was taken at 08:00 in a randomized, double-blind, placebo-controlled, crossover study. Participants drove a simulator at 17:00, 20:00, 23:00, and 01:00, and drove their own cars over a 16-mile road course at 24:00. The main outcome measures were composite scores of driving performance. Neither OROS MPH nor se-AMPH ER was associated with significant worsening of simulator performance relative to placebo 17 hours post-ingestion in group comparisons. However, inattentive on-road driving errors were significantly more common on se-AMPH ER relative to placebo at midnight (p = 0.04), suggesting possible rebound. During both late simulator and on-road testing, driving performance variance was approximately 300% greater during the se-AMPH ER compared to the OROS MPH condition.

Manual transmission enhances attention and driving performance of ADHD adolescent males: pilot study

OBJECTIVE

Inattention is a major contributor to driving mishaps and is especially problematic among adolescent drivers with ADHD, possibly contributing to their 2 to 4 times higher incidence of collisions. Manual transmission has been demonstrated to be associated with greater arousal. This study tests the hypotheses that manual transmission, compared to automatic transmission, would be associated with better attention and performance on a driving simulator.

METHOD

Ten adolescent drivers with ADHD practice driving on the simulator in the manual and automatic mode. Employing a single-blind, cross-over design, participants drive the simulator at 19:30 and 22:30 hr for 30 min in both transmissions and rate their attention to driving.

RESULTS

Subjectively, participants report being more attentive while driving in manual transmission mode. Objectively, participants drive safer in the manual transmission mode.

CONCLUSION

Although in need of replication, this pilot study suggests a behavioral intervention to improve driving performance among ADHD adolescents.

Relative benefits of stimulant therapy with OROS methylphenidate versus mixed amphetamine salts extended release in improving the driving performance of adolescent drivers with attention-deficit/hyperactivity disorder

OBJECTIVE

Automobile accidents are the leading cause of death among adolescents, and collisions are 2 to 4 times more likely to occur among adolescents with attention-deficit/hyperactivity disorder. Studies have demonstrated that stimulants improve driving performance. This study compared 2 long-acting stimulant medications during daytime and evening driving evaluations.

METHODS

Adolescent drivers with attention-deficit/hyperactivity disorder were compared on a driving simulator after taking 72 mg of OROS methylphenidate, 30 mg of mixed amphetamine salts extended release, or placebo in a randomized, double-blind, placebo-controlled, crossover study design. During laboratory testing, adolescents drove a driving simulator at 5:00 pm, 8:00 pm, and 11:00 pm. Driving performance was rated by adolescents and investigators.

RESULTS

The study included 35 adolescent drivers with attention-deficit/hyperactivity disorder (19 boys/16 girls). The mean age was 17.8 years. The overall Impaired Driving Score demonstrated that OROS methylphenidate led to better driving performance compared with placebo and mixed amphetamine salts extended release, whereas mixed amphetamine salts extended release demonstrated no statistical improvement over placebo. Specifically, relative to placebo, OROS methylphenidate resulted in less time driving off the road, fewer instances of speeding, less erratic speed control, more time executing left turns, and less inappropriate use of brakes. OROS methylphenidate and mixed amphetamine salts extended release worked equally well for male and female adolescents and equally as well with teenagers who have combined and inattentive subtypes of attention-deficit/hyperactivity disorder.

CONCLUSIONS

This study validates the use of stimulants to improve driving performance in adolescents with attention-deficit/hyperactivity disorder. In the study, OROS methylphenidate promoted significantly improved driving performance compared with placebo and mixed amphetamine salts extended release.

Hypoglycemia: a complication of diabetes therapy in children

The experience of hypoglycemia is probably the most feared and hated consequence of life with type 1 diabetes among pediatric patients and their parents. Although transient detrimental effects are clearly disturbing and may have severe results, there is surprisingly little evidence of long-term CNS damage, even after multiple hypoglycemic episodes, except in rare instances. Despite the latter evidence, we advocate that every treatment regimen be designed to prevent hypoglycemia without inducing unacceptable hyperglycemia and increasing the risk of micro- and macrovascular complications.

Hypoglycaemia and driving in people with insulin-treated diabetes: adherence to recommendations for avoidance

BACKGROUND

Hypoglycaemia impairs driving performance, so drivers with insulin-treated diabetes should try to avoid hypoglycaemia when driving, and treat it effectively if it occurs. It is not known how many insulin-treated drivers are familiar with, or adhere to, recommended safe practice.

METHODS

We surveyed a representative sample of 202 current drivers with insulin-treated diabetes (115 with Type 1 diabetes), using a structured questionnaire. Data were obtained on driving history, estimated frequency of hypoglycaemia, and measures taken to avoid and treat hypoglycaemia when driving.

RESULTS

The licensing authority (DVLA) and motor insurance company had been informed by almost all participants. Sixty-four participants (31.7%) had experienced hypoglycaemia while driving, and 27 (13.4%) reported that this had occurred within the preceding year. A minimum blood glucose level of 4.0 mmol/l or higher was considered necessary for driving by 151 drivers (74.8%), and 176 (87.1%) reported always keeping carbohydrate in their vehicle. However, 77 (38.1%) reported never carrying a glucose meter when driving, and 121 (59.9%) that they never test blood glucose before driving, or test only if symptomatic of hypoglycaemia. Most participants (89%) would stop driving to treat hypoglycaemia and would not resume driving immediately, although only 28 (13.9%) would wait longer than 30 min. Almost half of participants were failing to observe at least one essential aspect of safe driving.

CONCLUSIONS

Compliance with statutory requirements to inform the licensing authority and motor insurer is good, and drivers' perceptions of the minimum safe blood glucose level for driving are encouraging. However, most drivers rely on symptoms to detect hypoglycaemia while driving, and seldom test blood glucose before driving. Patient education should emphasize the role of blood glucose monitoring in relation to driving, and highlight the potential deterioration in driving performance when blood glucose falls below 4.0 mmol/l.