4.4 Editorial Material

Sleep Apnea Related Risk of Motor Vehicle Accidents is Reduced by Continuous Positive Airway Pressure: Swedish Traffic Accident Registry Data

期刊

SLEEP
卷 38, 期 3, 页码 341-+

出版社

OXFORD UNIV PRESS INC
DOI: 10.5665/sleep.4486

关键词

CPAP; daytime sleepiness; driving distance; risk factors; traffic accident

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Study Objectives: Obstructive sleep apnea (OSA) is associated with an increased risk of motor vehicle accidents (MVAs). The rate of MVAs in patients suspected of having OSA was determined and the effect of continuous positive airway pressure (CPAP) was investigated. Design: MVA rate in patients referred for OSA was compared to the rate in the general population using data from the Swedish Traffic Accident Registry (STRADA), stratified for age and calendar year. The risk factors for MVAs, using demographic and polygraphy data, and MVA rate before and after CPAP were evaluated in the patient group. Setting: Clinical sleep laboratory and population based control (n = 635,786). Patients: There were 1,478 patients, male sex 70.4%, mean age 53.6 (12.8) y. Interventions: CPAP. Measurements and Results: The number of accidents (n = 74) among patients was compared with the expected number (n = 30) from a control population (STRADA). An increased MVA risk ratio of 2.45 was found among patients compared with controls (P < 0.001). Estimated excess accident risk was most prominent in the elderly patients (65-80 y, seven versus two MVAs). In patients, driving distance (km/y), EDS (Epworth Sleepiness score >= 16), short habitual sleep time (<= 5 h/night), and use of hypnotics were associated with increased MVA risk (odds ratios 1.2, 2.1, 2.7 and 2.1, all P <= 0.03). CPAP use >= 4 h/night was associated with a reduction of MVA incidence (7.6 to 2.5 accidents/1,000 drivers/y). Conclusions: The motor vehicle accident risk in this large cohort of unselected patients with obstructive sleep apnea suggests a need for accurate tools to identify individuals at risk. Sleep apnea severity (e.g., apnea-hypopnea index) failed to identify patients at risk.

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