Ahmad Yonis Badawy PROFESSOR Pulmonaty Medicine Department Sleep disorderd breathing unit

1. Prevalence and Predictors of Sleep related Accidents in Egyptian Commercial Drivers with Sleep Disordered Breathing Ahmad Yonis Badawy PROFESSOR Pulmonaty Medicine Department Sleep disorderd breathing unit Mansoura University - EGYPT

2. AUTHORS • NesreenElsayedMorsy: Assistant lecturer of Chest Medicine, Faculty of Medicine, Mansoura University-EGYPT • Ahmad Yonis Badawy: Professor of Chest Medicine, Faculty of Medicine, Mansoura University-EGYPT • Sayed Ahmad abdelhafeez: Professor of Chest Medicine, Faculty of Medicine, Mansoura University-EGYPT • AbdElhadyElgilany: Professor of Public Health and Preventive Medicine, Faculty of Medicine, Mansoura University-EGYPT • Mohsen Mohammed Elshafey: Professor of Chest Medicine, Faculty of Medicine, Mansoura University-EGYPT

3. Acknowledgement This study was supported by a grant of Egyptian Academy of Scientific Research and Technology (Ministry of Scientific Research) in collaboration with Mansoura University.

4. INTRODUCTION

5. INTRODUCTION UnfortunatelyEgypt is ranked the 3rd country in the world with highest mortality rates (41.6 deaths/100.000 population) due to road traffic accidents (RTA) based on a revision of the 2007 statistics done by WHOand WHO Global Status Report on Road Safety, 2009

6. INTRODUCTION According to the Central Authority for Public Mobilization and Statistics the commonest cause of accidents was inattention of the driver (18%) which is failure to pay attention to a particular task (due to distracting influences or to an inability related to a physiologic factor such as sleepiness)

7. INTRODUCTION Several risk factors for the occurrence of sleepiness at the wheel exist, including: • long periods of wakefulness • time of day while driving • alcohol and drug consumption • work hours • reduced sleep time • sleep disorders resulting in excessive daytime sleepiness, such as obstructive sleep apnea syndrome (OSAS)

8. INTRODUCTION Untreatedsleep disordered breathing is common in commercial drivers and associated with 2 to 7 folds increased risk of motor vehicle crashes.

9. REVIEW OF LITERATURES

10. Sleep Disordered Breathing

11. Sleep Related Breathing Disorders The sleep related breathing disorders are characterized by abnormalities of respiration during sleep. In some of these disorders, respiration is also abnormal during wakefulness.

12. Sleep Related Breathing Disorders Classification according to ICSD-3

13. Sleep Related Breathing Disorders Classification according to ICSD-3 Isolated Symptoms and Normal Variants Snoring Catathrenia

15. SBD and COGNITION

16. Patients with OSAS show deficits across a wide range of cognitive functions including: • attention • memory • psychomotor speed • visuospatial abilities • constructional abilities • executive functions • language abilities (Andreou & Agapitou, 2007)

19. Why sleepy drivers risky for accidents

21. AIM OF THE WORK

22. AIM OF THE WORK Estimate the prevalence and the predictors of sleep related road traffic accidents in commercial drivers attending Mansoura Sleep Disordered Breathing Unit (EGYPT).

23. METHODOLOGY

24. METHODOLOGY Cross-sectional descriptive study including 110 commercial drivers attending to sleep disordered breathing unit clinic (pulmonology department - faculty of medicine - mansoura university – EGYPT) during the period of November 2013 to October 2014 where they had diagnostic in lab attended full night PSG . we assess history of sleep related accident or near accidents followed by a nested case-control study where case is those with history of accidents and control without history of accidents

25. Sleep lab

26. METHODOLOGY The following data was collected: The behavioral history of driving including: mean daily driving hours; mean daily sleep duration, Shift work, Tea/coffee while driving was taken. The clinical examination was done using: Epworth sleepiness scale (ESS), Functional outcome of sleep questionnaire (FOSQ), Berlin questionnaire, STOP Bang questionnaire, OSAS score and wake erect Pulse oximetry (SPO2).

27. METHODOLOGY The polysomnographic results reviewed using: • Apnea Hypopnea Index (AHI), • Basal and lowest oxygen saturation • oxygen desaturation index • Sleep efficiency % • slow wave sleep% • REM % • Arousal index Final diagnosis: obstructive sleep apnea syndrome (OSAS) or obesity hypoventilation syndrome (OHS).

28. METHODOLOGY Then variables analyzed by SPSS version 16. Bivariate analysis was done followed by multivariate logistic regression to detect independent variables of accidents.

29. RESULTS

30. RESULTS Prevalence of accidents or near accidents in those with SDB versus those without SDB

31. RESULTS Behavioral predictors of accidents or near accidents in those with SDB

32. RESULTS Clinical predictors of accidents or near accidents in those with SDB

33. RESULTS Polysomnographic Predictors of accidents or near accidentsin those with SDB

34. RESULTS Multiple logistic regression analysis of independent predictors of Accidents or near accidents in those with SDB

35. CONCLUSION RED SEA BOTTOM

36. CONCLUSION The prevalence of accidents or near accidents was found to be high (46.7%) in drivers with SDB .

37. CONCLUSION • lower Sleep efficiency% • lower mean daily sleep hours • lower slow wave sleep% • lower REM% could be of predictive importance in detection of SDB related accidents among commercial drivers.