Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_4704_Библиотеки_им_академика_М_И_Перельмана
.pdf
160 A. S. BaHammam et al.
Garde A, Dehkordi P, Karlen W, Wensley D, Ansermino JM, Dumont GA (2014) Development of a
screening tool for sleep disordered breathing in children using the phone Oximeter™. PLoS One
9(11):e112959.
https://doi.org/10.1371/journal.pone.0112959
Khosla S, Deak MC, Gault D, Goldstein CA, Hwang D, Kwon Y, O’Hearn D, Schutte-Rodin S,
Yurcheshen M, Rosen IM, Kirsch DB, Chervin RD, Carden KA, Ramar K, Aurora RN, Kristo
DA, Malhotra RK, Martin JL, Olson EJ, Rosen CL, Rowley JA, American Academy of Sleep
Medicine Board of Directors (2018) Consumer sleep technology: an American Academy of
Sleep Medicine position statement. J Clin Sleep Med 14(5):877–880
Liang Z, Chapa-Martell MA (2019) Accuracy of fitbit wristbands in measuring sleep stage
transitions and the effect of user-specific factors. JMIR Mhealth Uhealth 7(6):e13384.
https://
doi.org/10.2196/13384
Miller DJ, Lastella M, Scanlan AT et al (2020) A validation study of the WHOOP strap against
polysomnography to assess sleep. J Sports Sci 38(22):2631–2636.
https://doi.org/10.1080/
02640414.2020.1797448
Moreno-Pino F, Porras-Segovia A, López-Esteban P, Artés A, Baca-García E (2019) Validation of
Fitbit Charge 2, and Fitbit Alta HR against polysomnography for assessing sleep in adults with
obstructive sleep apnea. J Clin Sleep Med 15(11):1645–1653
Mouritzen NJ, Larsen LH, Lauritzen MH, Kjær TW (2020) Assessing the performance of a
commercial multisensory sleep tracker. PLoS One 15(12):e0243214.
https://doi.org/10.1371/
journal.pone.0243214
Newman J (2013) 50 best android apps for 2013. Time Magazine. http://techland.time.com/2013/0
7/01/50-best-android-apps-for-2013/slide/sleep-as-android
Perez-Pozuelo I, Zhai B, Palotti J et al (2020) The future of sleep health: a data-driven revolution in
sleep science and medicine. NPJ Digit Med 3:42.
https://doi.org/10.1038/s41746-020-0244-4
Sadek I, Bellmunt J, Kodyš M, Abdulrazak B, Mokhtari M (2020) Novel unobtrusive approach for
sleep monitoring using fiber optics in an ambient assisted living platform. In International
Conference on Smart Homes and Health Telematics, Springer, pp 48–60
Sleep Cycle (2014). http://sleepcycle.com
Stevens S, Siengsukon C (2019) Commercially available wearable provides valid estimate of sleep
stages (P3.6-042). Neurology 92(15 Suppl):P3.6-042
Stevens S, Siengsukon CF, Yu S, Fehler M, Chen N-H, Chuang L-P, Lin S-W, Burgett S (2019)
1007 validation of consumer wearable technology to assess sleep apnea risk. Sleep 42(Suppl_1):
A405. https://doi.org/10.1093/sleep/zsz067.1004
Stone JD, Rentz LE, Forsey J, Ramadan J, Markwald RR, Finomore VS Jr, Galster SM, Rezai A,
Hagen JA (2020) Evaluations of commercial sleep technologies for objective monitoring during
routine sleeping conditions. Nat Sci Sleep 12:821–842. https://doi.org/10.2147/NSS.S270705
Svensson T, Chung U, Tokun S et al (2019) A validation study of a consumer wearable sleep tracker
compared to a portable EEG system in naturalistic conditions. J Psychosom Res 126:109822
Tuominen J, Peltola K, Saaresranta T, Valli K (2019) Sleep parameter assessment accuracy of a
consumer home sleep monitoring ballistocardiograph beddit sleep tracker: a validation study. J
Clin Sleep Med 15(3):483–487
Urbandroid Team (n.d.) Sleep as android. http://urbandroid.org/
Yang R-Y et al (2019) Pneumatic sensor for cardiorespiratory monitoring during sleep. Biomed
Phys Eng Express 5:055014
https://t.me/medicina_free
Chapter 11
Traffic Safety in Sleep Deprivation,
Sleepiness, and Sleep Disorders
Ahmed S. BaHammam, Mahadevappa Hunasikatti,
and Seithikurippu R. Pandi-Perumal
Abstract Every year, a substantial number of people are killed or injured due to
motor vehicle accidents (MVAs). A large number of these collisions are caused by
driving errors. Vehicles travel at fast speeds, necessitating the driver’s constant
attention and alertness. However, scientific evidence suggests that tired drivers or
drivers who drive at unusual hours are more prone to make mistakes. When drivers
have sleep disorders such as obstructive sleep apnea (OSA) or central
hypersomnolence disorders, the situation worsens. Patients with OSA and narco-
lepsy have been found to have an increased risk of falling asleep behind the wheel
and crashing. Narcolepsy and OSA treatment has increased driver vigilance and
minimized the likelihood of MVAs. Motorists susceptible to dozing off while
driving can benefit from tests that determine the level of daytime sleepiness or
drowsiness while driving. As a result, unambiguous standards must be developed
to oversee the periodic assessment of drivers’ risk of falling asleep behind the wheel,
particularly commercial drivers.
Keywords Drivers · Drowsiness · Sleepiness · Legisla tion · Narcolepsy ·
Obstructive sleep apnea
A. S. BaHammam (✉)
The University Sleep Disorders Center, Department of Medicine, College of Medicine, King
Saud University, Riyadh, Saudi Arabia
King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
e-mail: ashammam@ksu.edu.sa
M. Hunasikatti
Division of Respiratory, Sleep and Anesthesiology (DSRA), OHT1, Food and Drug
Administration (FDA), Silver Spring, MD, USA
S. R. Pandi-Perumal
Somnogen Canada Inc., College Street, Toronto, ON, Canada
Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences,
Saveetha University, Chennai, Tamil Nadu, India
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023
A. S. BaHammam, M. Hunasikatti (eds.), Sleep Apnea Frontiers, Progress in Sleep
Research,
https://doi.org/10.1007/978-981-99-7901-1_11
161
https://t.me/medicina_free
162 A. S. BaHammam et al.
Key Points
• One of the leading causes of car accidents is drowsiness.
• Sleep deprivation, obstructive sleep apnea, and central hypersomnias are all
common sleep issues linked to hypersomnolence and MVAs.
• Effective treatment of sleep problems and sleep deprivation can boost vigilance,
lowering the risk of an accident.
• Sleepiness can be measured with diagnostic tests, which can be used to determine
driving fitness.
• Physic ians, especially family physicians and general practitioners, should be
taught about the dangers of sleepy driving and the significance o f assessing
patients’ fitness to drive regularly.
• Before giving driver’s licenses, legislation should be drafted to measure
hypersomnolence.
11.1 Introduction
The number of automobiles sold has increased in recent years, implying that the
number of people driving or riding in vehicles has also increased. As the number of
vehicles and drivers has grown, so has the number of accidents. Motor vehicle
accidents (MVAs) are a prominent source of death and morbidity worldwide, and
they are anticipated to be the fourth greatest cause of death by 2030 (World Health
Organization 2011, 2018). MVAs claim the lives of approximately 1.3 million
people globally each year, with another 20 to 50 million suffering nonfatal injuries
that result in severe disability (World Health Organization 2011). According to the
current research, weariness, and sleepiness are substantial risk factors for MVAs
(Gupta et al.
2017). Although it is difficult to assess the frequency of MVAs
involving drowsy drivers, several modeling studies have suggested that the fatal
accident rate ranges from 15% to 33% (Centers for Disease Control and Prevention
2013). Drowsiness results in various neurological problems, including slower reac-
tion times, decreased concentration, and poor decision-making abilities (Centers for
Disease Control and Prevention
2013). According to French research of 4774
drivers, 11.8% had Epworth sleepiness scores (ESS) of 11, 29% reported having
sleepiness at the wheel severe enough to need halting, and 47% and 39% reported
feeling sleepy while driving at night and day, respectively (Sagaspe et al.
2010).
Furthermore, 10.7% of respondents said they had a near-miss accident in the
preceding year (46% of which were sleep-related), and 6% said they had an accident
(5% of which were sleep-related) (Sagaspe et al.
2010). Globally, nearly 1.3 million
people die each year due to MVAs, and road accidents are the leading cause of death
in children and young adults aged 5–29 years (World Health Organization 2021). In
2013, drowsy drivers were accountable for more than 72,000 collisions, approxi-
mately 44,000 injuries, and there were 800 reported deaths in addition to the 72,000
accidents mentioned above and 44,000 injuries caused by drowsy drivers, as per the
Centers for Disease Control and Prevention (CDC) data (Centers of Disease Control
https://t.me/medicina_free
and Prevention 2020). However, according to the CDC analysis, this important risk
factor is vastly underreported (Centers of Disease Control and Prevention 2020).
Furthermore, the survey claims that some kinds of drivers are more likely to become
drowsy while driving. Those who do not get enough sleep (for whatever reason),
drivers of commercial vehicles, such as trucks and buses, drivers who use substances
that cause drowsiness (e.g., sleeping pills, alcoho l, and opiates), and those with sleep
problems are all at danger (Centers of Disease Control and Prevention
2020)
.
P
eople
who sleep less than 6 h per day and snore are more likely to fall asleep behind the
wheel, according to one study (Center s of Disease Control and Prevention 2020).
Short periods of sleep during the night and extended periods of driving have been
observed to enhance the likelihood of rear-end collisions and single-vehicle acci-
dents (Abe et al. 2010). Furthermore, driving at night increases the risk of an
accident (Rice et al. 2003).
11 Traffic Safety in Sleep Deprivation, Sleepiness, and Sleep Disorders 163
The available eviden
ce linking MVAs to tiredness, sleep loss, or sleep problems
is discussed in this chapter. Furthermore, we discuss the legal status of sleep-related
elements in the issue of driver’s licenses in various nations. Finally, we dig deeper
into the evidence of the impact of sleep disorders therapy on MVAs.
11.2 Sleep Deprivation
An Individual, either a long-haul truck driver or a long-haul or ultra-long-haul pilot,
might be subjected to acute or chronic sleep deprivation. Acute sleep deprivation is a
condition in which a person is unable to sleep for the entire night or a significant
portion of it. Chronic sleep deprivation is characterized by a persistent lack of
adequate sleep, whereby an individual fails to obtain the necessary amount of
daily sleep for a few days to several weeks. This sort of sleep deprivation also has
a cumulative impact, so the individual becomes chronically sleep-deprived after a
few days. Both sorts of sleep deprivation are harmful to one’s health. Sleep depri-
vation is estimated to cause 5 6,000 accidents in the United States each year (National
Highway Traffic Safety Administration
2011). Other countries have observed a
similar association between sleep deprivation and an increased risk of MVAs
(BaHammam et al.
2014; Leechawengwongs et al. 2006). It has been discovered
that after 17 h of continuous awake, cognitive skills (e.g., reaction time and hand-eye
coordination) suffer substantially, and an increasing number of errors occur
(Williamson and Feyer 2000). Attention, as well as the ability to comprehend
information, is severely hampered (Williamson and Feyer 2000). After 17 h of
continuous awake, cognitive and psychomotor performance deteriorates to a level
equal to the impairment seen in persons with a blood alcohol concentration of
0.05%, which is unsuitable for industrial or driving employment (Williamson and
Feyer 2000). A recent study of a representative sample of crashes of about 7000
drivers involved in the United States reported that driving after sleeping less than 7 h.
in a 24-h period is associated with an elevated risk of culpable crash involvement
(Tefft 2018). An inverse relationship was observed between sleep duration and the
https://t.me/medicina_free
risk of MVAs, with the most significant risk for drivers who have slept less than 4 h,
3.4 (95% CI = 2.1 to 5.6) times the increase in odds of culpable involvement in
single-vehicle crashes compared to those who slept 7–9 h (Tefft 2018).
164 A. S. BaHammam et al.
Another study looked at the effect
of awake time on performance impairment
during the simulated afternoon and midnight driving in a group of healthy persons
who had a normal sleep duration (7 h) before taking the test (Akerstedt et al.
2013).
The findings indicated that midnight driving was associated with increased tiredness
and an increased risk of accidents due to the prolonged period of wakefulness,
despite regular sleep duration on previous nights (Abe et al.
2010; Akerstedt et al.
2013; Anund et al. 2009). Most adults need at least 7 h of sleep per 24 h, while
adolescents need at least 8 h (Alfawaz et al. 2021). When the driving test was
administered during the day, adolescents who received 6.5 h of nightly sleep for
5 days performed worse on simulated driving than those who received 10 h of
nocturnal sleep (Garner et al. 2015).
Long-haul truck drivers commonly limit their sleep to 4 h per day while on duty,
resulting in sleep deprivation and an increased risk of an MVA (Perez-Chada et al.
2005). According to another survey, over half of the truck drivers worked unrealistic
schedules, with more than 50 h of driving each week, and 27% of drivers reported
poor sleep quality (Braeckman et al.
2011). Professional drivers were found to have a
higher prevalence of sleep debt than control participants (Carter et al. 2003). These
examples demonstrate the consequences of prolonged partial sleep loss on MVA
risk. When paired with alcohol use, an increased length of wakefulness has been
shown to impair driving ability, even throughout the elimination phase of ethanol
use (Arnedt et al. 2000).
The effect of sleep loss on the risk of MVAs appears to be age-dependent. A
counterbalanced design study that assessed the effect of sleep restriction for the
previous 5 h on prolonged (2 h) afternoon simulated driving in 20 younger (mean
age 23 years) and 19 older (mean age 67 years) healthy drivers found that after sleep
restriction, young drivers had significantly more sleepiness-related lane deviations
and higher low-frequency EEG power (4–11 H) (Filtness et al. 2012).
11.2.1 Obstructive Sleep Apnea and Hazards of Driving Risks
Snoring serves as an indication or sign of obstructive sleep apnea (OSA), a prevalent
sleep disease that affects 6% to 17% of the population (Senaratna et al. 2017). Poor
performance on the psychomotor vigilance test is associated with OSA (Pack et al.
2006). Several studies have found that, when compared to controls, OSA patients are
three times more likely to fall asleep while driving and are three times as likely to
cause MVAs (Amra et al. 2012; Rodenstein 2009; Tregear et al. 2009; Bonsignore
et al.
2021). However, most studies were observational and used screening ques-
tionnaires with poor sensitivity or specificity, resulting in an unacceptably high
number of missed cases (false-negative) and false-positive cases (Bonsignore et al.
https://t.me/medicina_free
2021); therefore, there is an urgent need for good quality studies to describe the best
ways to diagnose OSA and detect sleepiness among drivers.
11 Traffic Safety in Sleep Deprivation, Sleepiness, and Sleep Disorders 165
A high-risk d
river has moderate to severe daytime sleepiness and a recent
unintentional motor vehicle crash or near miss due to sleepiness, weariness, or
inattention, according to the American Thoracic Society (ATS) (Strohl et al.
2013). Table 11.1 summarizes research conducted in various countr ies to examine
OSA, drowsiness, and the risk of MVAs. Using studies published between 1980 and
2003 and data from the National Safety Council, it has been estimated that OSA was
responsible for roughly 810,000 crashes in the United States, resulting in the loss of
1400 lives and $16 billion in damages per year (Sassani et al.
2004). However, the
link between OSA and poor performance is not ubiquitous, and some research found
no link between OSA and MVAs (Pack et al. 2006; de Mello et al. 2013; Ozoh et al.
2013). A recent study used both before-after and case-control study design to assess
the risk of MVAs among CPAP-treated, and untreated patients matched for gender,
age, and apnea-hypopnea index (AHI) and reported that the MVA incidence did not
change after CPAP treatment (Myllyla et al.
2020). Nonetheless, it has been stated
that reporting MVAs as a result of OSA may have a detrimental impact on an
individual’s employment and ability to keep their driver’s license (Kales and
Straubel
2014). As a result, drivers suffering from OSA may underreport MVAs to
their treating physicians.
The effect of OSA on driving performance is most likely related to the severity of
the OSA (Pack et al.
2006; Ozoh et al. 2013). Accident rates are proportional to the
severity of OSA, and the risk rises as the severity rises due to increased daytime
sleepiness (Cui et al.
2006; Horstmann et al. 2000). AHI values (AHI of 40) and
Epworth Sleepiness Scale (ESS) scores (ESS of 11 and ESS of 16) of 616 Japanese
drivers were shown to be associated with an increased chance of dozing off at the
wheel as well as a higher probability of being involved in MVAs in a study (Komada
et al.
2009). According to a systematic evaluation of published data, noncommercial
drivers with OSA had a considerably elevated probability of being involved in
MVAs (two to three times higher accident rate) (Ellen et al.
2006). In OSA patients,
increased drowsiness is a risk factor for MVAs. The European sleep apnea database
of 8476 drivers with OSA found that an ESS score of >16, driving more than
15,000 km/year, sleeping fewer than 5 h/day, and usage of hypnotics were the main
risk factors for MVAs, with an increasing number of risk variables across the OSA
severity spectrum (Karimi et al.
2014). Other eviden ce suggests that daytime sleep-
iness raises the risk of MVAs in both OSA patients and those with simple snoring
(Perez-Chada et al.
2005; Akkoyunlu et al. 2013; Lloberes et al. 2000; Masa et al.
2000; Shiomi et al. 2002; Alahmari et al. 2019). Early diagnosis and treatment of
OSA and education of the patient and family on the dangers of sleepy driving are
likely to reduce the prevalence of sleepiness-related crashes in OSA patients (Strohl
et al.
2013).
https://t.me/medicina_free
166 A. S. BaHammam et al.
Table 11.1 A summary of major studies that addressed obstructive sleep apnea and motor vehicle
accidents among drivers
Authors Country Type of study Study population Results
Hanning and
Welsh (
1996)
United
Kingdom
Questionnaire-
based survey
2247 drivers with “no
claim” history.
Questioned for a his-
tory of accidents,
snoring, and daytime
sleepiness
Snorers were more
likely to report day-
time sleepiness and
having had to pull off
from the road while
driving
Pack et al.
(
2006)
USA Questionnaire
followed by
actigraphy
and
in-lab PSG; an
experimental
study
1329 drivers; 247 at
high risk for OSA and
159 at low risk for
OSA
Short sleep duration
and severe OSA were
associated with
sleepiness and poor
performance on the
road. Of the study
population, 29% had
OSA, with severe
OSA in 5%
Ozoh et al.
(
2013)
Lagos Descriptive
cross-sectional
study using
questionnaires
500 male commercial
drivers.
Of the study popula-
tion, 49% had a high
risk for OSA and
14.4% had daytime
sleepiness. No rela-
tionship was
observed between
OSA, daytime sleep-
iness, and past his-
tory of MVAs
Dogan et al.
(
2006)
Turkey Descriptive
cross-sectional
study using a
questionnaire
340 drivers Of the study popula-
tion, 41.2% had
habitual snoring.
Habitual snorers had
OR = 1.6
(1.03–2.53) for
accidents
Lioberes et al.
(2000)
Spain A case-control
study with PSG
172 patients with OSA
and 40 controls
Self-reported sleepi-
ness among OSA
patients increased the
chance of accidents
(OR = 5; 95% CI
2.3–10.9)
Perez-Chada
et al. (
2005)
Argentina Questionnaire-
based study
738 long-haul truck
drivers
Snoring more than
3 times a week
(OR
1.73, 95%
CI = 1.23–2.44),
sleepiness while
driving (OR 1.92,
95%
CI = 1.08–1.96), and
ESS score > 10
(odds ratio 2.53, 95%
(continued)
https://t.me/medicina_free
11 Traffic Safety in Sleep Deprivation, Sleepiness, and Sleep Disorders 167
Table 11.1 (continued)
Authors Country Type of study Study population Results
CI = 1.61–3.97)
predicted accidents
or near-miss
accidents
Akkoyunlu
et al. (Cui
et al. 2006)
Turkey Questionnaire-
based study
520 city drivers The accident rate was
predicted by daytime
sleepiness among
those at high risk for
OSA
Masa et al.
(
2000)
Spain A case-control
study using PSG
145 habitually sleepy
drivers and controls
Those with a history
of MVA had a higher
respiratory distur-
bance index
(OR = 8.5; 95%
CI = 1.2–59)
Shiomi et al.
(
2009)
Japan A case-control
study using PSG
448 patients with OSA
and 106 simple
snorers
The accident rates
were higher in
patients with severe
OSA. Sleepiness
among OSA and
snorers predicted risk
of MVA
Braekman
et al.
(Alfawaz
et al.
2021;
Braeckman
et al. 2011)
Belgium A cross-sectional
cohort study
using
questionnaires
476 truck drivers Of the study popula-
tion (21.5%) were at
high risk for OSA
and 18% had scores
>10 on ESS
BaHammam
et al. (
2014)
Saudi
Arabia
A cross-sectional
study using
questionnaires
1219 city drivers The prevalence of
high risk for OSA
was higher among
drivers who had
MVAs in the past
6 months
11.2.2 MVAs and Central Hypersomnolence Disorders
MVAs are more likely in patients with central causes of hypersomnolence (Bartels
and Kusakcioglu 1965; George et al. 1996; Grubb 1969; Kotterba et al. 2004).
However, just a few research have been conducted on this subject. A French study
found that central diseases producing hypersomnolence (narcolepsy and primary
hypersomnia) enhanced the likelihood of having MVAs (Pizza et al. 2015) and that
the likelihood of having MVAs was related to daytime drowsiness (Pizza et al.
2015). At study inclusion, the risk of MVAs was high in both treated and untreated
participants (untreated, OR = 2.21; 95% CI = [1.30–3.76], treated OR = 2.04; 95%
CI = [1.26–3.30]). However, the risk of MVAs for patients treated for at least 5 years
was not different from the risk for healthy participa nts (OR = 1.23; 95%
https://t.me/medicina_free
CI = [0.56– 2.69]), implying that long-term treatment may potentially reverse the
risk of MVAs (Pizza et al. 2015).
168 A. S. BaHammam et al.
11.2.3 Medication and the Dangers of MVAs
Several studies have found that people with insomnia and those on various sleep
drugs are more prone to accidents as a result of weariness, poor attentiveness, and
sleepiness behind the wheel (Daley et al. 2009; Leger et al. 2006; Williamson et al.
2011). Several studies investigated the long-term impact of hypnotic medications on
driving performance. Participants were given hypnotic medication before going to
bed, and their driving abilities were assessed the next day. According to the findings
of these investigations, benzodiazepine hypnotics and zopiclone considerably
decreased driving performance, although zolpidem and zaleplon had less of an effect
(Verster et al.
2004, 2006, 2011). Ramelteon, a melatonin receptor antagonist, has
been demonstrated to dramatically decrease driving performance the following
morning (Mets et al.
2011).
Current evidence corroborates epidemiological data indicating an increased risk
of accidents among people who take benzodiazepine hypnotics and zopiclone
(Barbone et al. 1998 ).
11.2.4 Countermeasures That May Help to Reduce
Drowsiness When Driving
Given that tiredness is a major cause of MVAs, it is critical to evaluate the
countermeasures that may prevent sleepiness and lower the risk of MVAs. A variety
of countermeasures can be used to decrease tiredness among sleep-deprived drivers
or while driving at strange hours. The installation of rumble strips in the middle of
the road, particularly on small roads, has been shown to rouse sleeping drivers
(Anund et al.
2011). When evaluated 2 h after administration, modafinil (300 mg)
was found to reduce lane deviation in sleep-deprived subjects, with no effect on
vehicle speed beyond permitted limits (Gurtman et al. 2008). However, modafinil
can cause exhilaration, impairing one’s ability to properly appraise the risk of
driving in such settings (Gurtman et al.
2008). Caffeine (200 mg) and napping
have been shown to reduce errors while driving at night without affecting future
sleep (Philip et al. 2006; Sagaspe et al. 2007a). After 64 h of continuous wakeful-
ness, the effects of three stimulants, modafinil (400 mg), caffeine (600 mg), and
dextroamphetamine (20 mg), on alertness and vigilance were examined. Caffeine
had an instant impact, while dextroamphetamine had a longer effect, and modafinil
was found to be equal to placebo (Killgore et al. 2008). Caffeine had the highest rate
of adverse effects, although dextroamphetamine negatively influenced post-test
https://t.me/medicina_free
sleep (Killgore et al. 2008). A recent study suggested that a small dose of caffeine
has positive effects on alertness in patients with narcolepsy (Aldosari et al. 2020).
Some studies have suggested that driving at night with a blue light in the automobile
can be beneficial (Taillard et al.
2012). Scheduled naps while driving at night have
also increased attentiveness and reduced error s (Signal et al. 2009).
11 Traffic Safety in Sleep Deprivation, Sleepiness, and Sleep Disorders 169
11.2.5 The Effect of Treatment for Sleep Disorders
on the Risk of MVAs
One important concern is whether treating sleep disturbances can help to prevent
MVAs. It has been stated numerous times in the literature that optimal and effective
treatment of sleep disturbances can enhance awareness and minimize the likelihood
of accidents (George 2001; Gurubhagavatula et al. 2008). It has been discovered that
treating narcolepsy and primary hypersomnia lowers the risk of MVAs (Pizza et al.
2015; Philip et al. 2014). A comprehensive review and meta-analysis of OSA,
CPAP, and accidents discovered that using CPAP reduced the probability of an
accident in drivers with moderate to severe OSA (RR = 0.278, 95% CI: 0:22 to 0:35,
p 0.001); self-reported tiredness, one of the symptoms of OSA, was also reduced
(Tregear et al. 2009) (Figs. 11.1 and 11.2).
A poll was conducted to ascertain sleep physicians’ perspectives on fitness-to-
drive in individuals with sleep disorders (Mets et al. 2012). Most sleep doctors
agreed that patients with untreated OSA, narcolepsy, or insomnia should not drive
Fig. 11.1 A 2-min window showing an example of obstructive apnea. Airflow is absent despite
persistent respiratory paradoxical effort. The event is followed by arousal and desaturation
https://t.me/medicina_free
Соседние файлы в папке Библиотека им академика М.И. Перельмана