967 resultados para Distracted driving


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Cannabis use has increased considerably during the last 15 years. One of the major problems dealing with cannabis use is driving under the influence of drugs. With the exception of ethyl alcohol, the majority of the epidemiological studies have shown that cannabis is the most frequently detected substance in people suspected of driving under the influence of drugs. Experimental studies are therefore needed to assess cannabis effects on driving capability. Many studies indicate that cannabis impairs psychomotor performance. This impairment becomes obvious when high doses of cannabis are taken, when ethyl alcohol or other drugs are simultaneously ingested, or when sustained attention is needed. Moreover, cannabis effects are qualitatively different from those observed after ethyl alcohol consumption. In forensic practice, cannabis impairment of driving performance must be related to cannabinoids blood concentrations. To facilitate the interpretation of cannabinoids blood levels, several models were set up recently. These models must be further improved in order to fit in with all circumstances of cannabis use.

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Introduction: In forensic toxicology, cocaine is better known for its powerful stimulating effects of nervous system and its high potential for recreational abuse, than for his therapeutic use. However, cocaine is still use as a topical anesthetic and peripheral vasoconstrictor in surgeries of eye, ear, nose and throat. Last decade, an increase of the presence of cocaine and metabolites in blood samples of drivers suspected to drive under the influence of drugs (DUID) was observed in Switzerland (Augsburger et al., Forensic Sci Int 153 (2005) 11-15; Senna et al., Forensic Sci Int 198 (2010) 11-16). Observed blood concentration ranges of cocaine and benzoylecgonine were 10-925 μg/L and 20-5200 μg/L, respectively. Since 2005, zero-tolerance approach was introduced in the Swiss legislation for different substances, especially cocaine (analytical cutoff: 15 μg/L). Thus, the interpretation often amounts to determine if the concentration is situated above or under the limit. However, it is important for the interpretation to take into account the context and to be critical with the obtained results, at the risk of ending in erroneous conclusions. Methods: Systematical toxicological analyses were performed on blood and urine, if available, for 5 DUID cases, as already published (Augsburger et al., Forensic Sci Int 153 (2005)). Positive results were confirmed and drugs were quantified in biological samples by GCMS, GC-MS/MS or LC-MS/MS. Results: Administration of cocaine after traffic accident was identified in five cases. All people were admitted to the emergency room because of severe trauma. Maxillofacial surgery was done shortly after admission to the emergency room, involving use of nasal application of cocaine (swab). For all cases, use of cocaine swab was not mentioned in the document filled by the police and by medical staff requested for blood and urine sampling. The information was obtained retrospectively after consultation of the medical records, without precise indication of the application time or dose. Case 1. A 83-year old man (pedestrian) was hit by a car. Blood (+11h after the accident): cocaine (16 μg/L), benzoylecgonine (370 μg/L). Urine: cocaine (1700 μg/L), benzoylecgonine (560 μg/L). Case 2. A 84-year old woman (pedestrian) was hit by a car. Blood (+1.5h after the accident): cocaine (230 μg/L), benzoylecgonine (370 μg/L). Urine was not available. Hair (+4 months after the accident): segment 1 (0-2 cm), cocaine not detected; segment 2 (2-4 cm), cocaine: <0.5 ng/mg. Case 3. A 66-year old man was involved in a car/car accident. He died 2 hours and 5 minutes after the crash. Blood (+1.5h after the accident): cocaine and metabolites not detected. Blood (+2h after the accident): cocaine (1750 μg/L), benzoylecgonine (460 μg/L). Blood (post-mortem): cocaine (370 μg/L), benzoylecgonine (200 μg/L). Urine (+1.5h after the accident): cocaine not detected. Case 4. A 57-year old woman on a motor scooter was hit by a car. She died 2 hours and 10 minutes after the crash. Blood (+0.5h after the accident): cocaine and metabolites not detected. Urine (post-mortem): cocaine (<20 μg/L), benzoylecgonine (120 μg/L). Case 5. A 30-year old man was involved in a car accident. Blood (+4h after the accident): cocaine (29 μg/L), benzoylecgonine (< 20 μg/L). Urine (+4h after the accident): cocaine and metabolites not detected. Ethanol (1,32 g/kg) and cannabinoids (THC (2,0 μg/L), THCCOOH (38 μg/L)) were also detected in blood. Conclusion: To our knowledge, this is the first description of DUID cases involving therapeutic use of cocaine after an accident. These results indicate that even if a per se law is effective for prosecution case of DUID, a critical interpretation of the results is always needed, especially if a medical intervention occurs after an accident.

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Introduction : Driving is a complex everyday task requiring mechanisms of perception, attention, learning, memory, decision making and action control, thus indicating that involves numerous and varied brain networks. If many data have been accumulated over time about the effects of alcohol consumption on driving capability, much less is known about the role of other psychoactive substances, such as cannabis (Chang et al.2007, Ramaekers et al, 2006). Indeed, the solicited brain areas during safe driving which could be affected by cannabis exposure have not yet been clearly identified. Our aim is to study these brain regions during a tracking task related to driving skills and to evaluate the modulation due to the tolerance of cannabis effects. Methods : Eight non-smoker control subjects participated to an fMRI experiment based on a visuo-motor tracking task, alternating active tracking blocks with passive tracking viewing and rest condition. Half of the active tracking conditions included randomly presented traffic lights as distractors. Subjects were asked to track with a joystick with their right hand and to press a button with their left index at each appearance of a distractor. Four smoking subjects participated to the same fMRI sessions once before and once after smoking cannabis and a placebo in two independent cross-over experiments. We quantified the performance of the subjects by measuring the precision of the behavioural responses (i.e. percentage of time of correct tracking and reaction times to distractors). Functional MRI data were acquired using on a 3.0T Siemens Trio system equipped with a 32-channel head coil. BOLD signals will be obtained with a gradient-echo EPI sequence (TR=2s, TE=30ms, FoV=216mm, FA=90°, matrix size 72×72, 32 slices, thickness 3mm). Preprocessing, single subject analysis and group statistics were conducted on SPM8b. Results were thresholded at p<0.05 (FWE corrected) and at k>30 for spatial extent. Results : Behavioural results showed a significant impairment in task and cognitive test performance of the subjects after cannabis inhalation when comparing their tracking accuracy either to the controls subjects or to their performances before the inhalation or after the placebo inhalation (p<0.001 corrected). In controls, fMRI BOLD analysis of the active tracking condition compared to the passive one revealed networks of polymodal areas in superior frontal and parietal cortex dealing with attention and visuo-spatial coordination. In accordance to what is known of the visual and sensory motor networks we found activations in V4, frontal eye-field, right middle frontal gyrus, intra-parietal sulcus, temporo-parietal junction, premotor and sensory-motor cortex. The presence of distractors added a significant activation in the precuneus. Preliminary results on cannabis smokers in the acute phase, compared either to themselves before the cannabis inhalation or to control subjects, showed a decreased activation in large portions of the frontal and parietal attention network during the simple tracking task, but greater involvement of precuneus, of the superior part of intraparietal sulcus and middle frontal gyrus bilaterally when distractors were present in the task. Conclusions : Our preliminary results suggest that acute cannabis smoking alters performances and brain activity during active tracking tasks, partly reorganizing the recruitment of brain areas of the attention network.

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Fitness to drive in elderly drivers is most commonly discussed with a focus on cognitive impairment. Therefore, this article is focussing on mental illness and the use of psychotropic drugs in elderly drivers, which can both interfere with fitness to drive. Based on a detailed literature review and on clinical judgement, we propose signposts and "red flags" to judge the individual risks. Health professionals dealing with elderly patients should in particular be aware of the dangers related to cumulative risks and need to inform the patients appropriately. For medico-legal reasons the information provided to patients must be written down in the medical record. Individual counselling is important as fitness to drive is a complex topic.

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In Switzerland, a two-tier system based on impairment by any psychoactive substances which affect the capacity to drive safely and zero tolerance for certain illicit drugs came into force on 1 January 2005. According to the new legislation, the offender is sanctioned if Delta(9)-tetrahydrocannabinol THC is >or=1.5ng/ml or amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyethylamphetamine (MDEA), cocaine, free morphine are >or=15ng/ml in whole blood (confidence interval+/-30%). For all other psychoactive substances, impairment must be proven in applying the so-called "three pillars expertise". At the same time the legal blood alcohol concentration (BAC) limit for driving was lowered from 0.80 to 0.50g/kg. The purpose of this study was to analyze the prevalence of drugs in the first year after the introduction of the revision of the Swiss Traffic Law in the population of drivers suspected of driving under the influence of drugs (DUID). A database was developed to collect the data from all DUID cases submitted by the police or the Justice to the eight Swiss authorized laboratories between January and December 2005. Data collected were anonymous and included the age, gender, date and time of the event, the type of vehicle, the circumstances, the sampling time and the results of all the performed toxicological analyses. The focus was explicitly on DUID; cases of drivers who were suspected to be under the influence of ethanol only were not considered. The final study population included 4794 DUID offenders (4243 males, 543 females). The mean age of all drivers was 31+/-12 years (range 14-92 years). One or more psychoactive drugs were detected in 89% of all analyzed blood samples. In 11% (N=530) of the samples, neither alcohol nor drugs were present. The most frequently encountered drugs in whole blood were cannabinoids (48% of total number of cases), ethanol (35%), cocaine (25%), opiates (10%), amphetamines (7%), benzodiazepines (6%) and methadone (5%). Other medicinal drugs such as antidepressants and benzodiazepine-like were detected less frequently. Poly-drug use was prevalent but it may be underestimated because the laboratories do not always analyze all drugs in a blood sample. This first Swiss study points out that DUID is a serious problem on the roads in Switzerland. Further investigations will show if this situation has changed in the following years.

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Les problèmes médicaux concernant la conduite automobile deviennent de plus en plus compliqués et de plus en plus fréquents. Dans la plupart des cantons suisses, chaque médecin peut potentiellement être interpellé en tant que médecin-conseil d'un de ses patients. Le présent article s'intéresse particulièrement aux problèmes de toxicodépendance dans le cadre du contexte législatif actuel et de la complexité croissante des soins. Medical problems involving driving aptitude are more and more common nowadays. Each doctor in Switzerland could be asked to give a certificate of driving aptitude for one of his/her patient. This paper relates to the problem of substance abusers in the current legal context and the growing complexity of care.

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BACKGROUND: In many countries, primary care physicians determine whether or not older drivers are fit to drive. Little, however, is known regarding the effects of cognitive decline on driving performance and the means to detect it. This study explores to what extent the trail making test (TMT) can provide indications to clinicians about their older patients' on-road driving performance in the context of cognitive decline. METHODS: This translational study was nested within a cohort study and an exploratory psychophysics study. The target population of interest was constituted of older drivers in the absence of important cognitive or physical disorders. We therefore recruited and tested 404 home-dwelling drivers, aged 70 years or more and in possession of valid drivers' licenses, who volunteered to participate in a driving refresher course. Forty-five drivers also agreed to undergo further testing at our lab. On-road driving performance was evaluated by instructors during a 45 minute validated open-road circuit. Drivers were classified as either being excellent, good, moderate, or poor depending on their score on a standardized evaluation of on-road driving performance. RESULTS: The area under the receiver operator curve for detecting poorly performing drivers was 0.668 (CI95% 0.558 to 0.778) for the TMT-A, and 0.662 (CI95% 0.542 to 0.783) for the TMT-B. TMT was related to contrast sensitivity, motion direction, orientation discrimination, working memory, verbal fluency, and literacy. Older patients with a TMT-A ≥ 54 seconds or a TMT-B ≥ 150 seconds have a threefold (CI95% 1.3 to 7.0) increased risk of performing poorly during the on-road evaluation. TMT had a sensitivity of 63.6%, a specificity of 64.9%, a positive predictive value of 9.5%, and a negative predictive value of 96.9%. CONCLUSION: In screening settings, the TMT would have clinicians uselessly consider driving cessation in nine drivers out of ten. Given the important negative impact this could have on older drivers, this study confirms the TMT not to be specific enough for clinicians to justify driving cessation without complementary investigations on driving behaviors.

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Two retrospective epidemiologic studies have shown that cannabis is the main psychoactive substance detected in the blood of drivers suspected of driving under the influence of psychotropic drugs. An oral administration double-blind crossover study was carried out with eight healthy male subjects, aged 22 to 30 years, all occasional cannabis smokers. Three treatments and one placebo were administered to all participants at a two week interval: 20 mg dronabinol, 16.5 mg D9-tétrahydrocannabinol (THC) and 45.7 mg THC as a cannabis milk decoction. Participants were asked to report the subjective drug effects and their willingness to drive under various circumstances on a visual analog scale. Clinical observations, a psychomotor test and a tracking test on a driving simulator were also carried out. Compared to cannabis smoking, THC, 11-OH-THC and THC-COOH blood concentrations remained low through the whole study (&lt;13.1 ng THC/mL,&lt;24.7 ng 11-OH-THC/mL and&lt;99.9 ng THC-COOH/mL). Two subjects experienced deep anxiety symptoms suggesting that this unwanted side-effect may occur when driving under the influence of cannabis or when driving and smoking a joint. No clear association could be found between these adverse reactions and a susceptibility gene to propensity to anxiety and psychotic symptoms (genetic polymorphism of the catechol-O-methyltransferase). The questionnaires have shown that the willingness to drive was lower when the drivers were assigned an insignificant task and was higher when the mission was of crucial importance. The subjects were aware of the effects of cannabis and their performances on the road sign and tracking test were greatly impaired, especially after ingestion of the strongest dose. The Cannabis Influence Factor (CIF) which relies on the molar ratio of active and inactive cannabinoids in blood provided a good estimate of the fitness to drive.

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The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

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The leading cause of death during winter storms is transportation accidents. Preparing your vehicle for the winter season and knowing how to react if stranded or lost on the road are the keys to safe winter driving.

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Hepatitis A virus (HAV), the prototype of genus Hepatovirus, has several unique biological characteristics that distinguish it from other members of the Picornaviridae family. Among these, the need for an intact eIF4G factor for the initiation of translation results in an inability to shut down host protein synthesis by a mechanism similar to that of other picornaviruses. Consequently, HAV must inefficiently compete for the cellular translational machinery and this may explain its poor growth in cell culture. In this context of virus/cell competition, HAV has strategically adopted a naturally highly deoptimized codon usage with respect to that of its cellular host. With the aim to optimize its codon usage the virus was adapted to propagate in cells with impaired protein synthesis, in order to make tRNA pools more available for the virus. A significant loss of fitness was the immediate response to the adaptation process that was, however, later on recovered and more associated to a re-deoptimization rather than to an optimization of the codon usage specifically in the capsid coding region. These results exclude translation selection and instead suggest fine-tuning translation kinetics selection as the underlying mechanism of the codon usage bias in this specific genome region. Additionally, the results provide clear evidence of the Red Queen dynamics of evolution since the virus has very much evolved to re-adapt its codon usage to the environmental cellular changing conditions in order to recover the original fitness.

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Time-dependent correlation functions and the spectrum of the transmitted light are calculated for absorptive optical bistability taking into account phase fluctuations of the driving laser. These fluctuations are modeled by an extended phase-diffusion model which introduces non-Markovian effects. The spectrum is obtained as a superposition of Lorentzians. It shows qualitative differences with respect to the usual calculation in which phase fluctuations of the driving laser are neglected.