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A sleep apnea related risk of vehicle accident is reduced by CPAP - Swedish traffic accident data acquisition (STRADA) registry

Mahssa Karimi ; Jan A Hedner ; Henrike Häbel (Institutionen för matematiska vetenskaper, matematisk statistik ; SuMo Biomaterials) ; Olle Nerman (Institutionen för matematiska vetenskaper, matematisk statistik) ; Ludger Grote
22nd Congress of the European Sleep Research Society, 16–20 September 2014, Tallinn, Estonia. Journal of Sleep Research (0962-1105). Vol. 23 (2014), Suppl 1, p. 67-67.
[Artikel, refereegranskad vetenskaplig]

Objectives: Obstructive sleep apnea (OSA) is associated with excessive daytime sleepiness (EDS) and two to seven times increased risk of motor vehicle accidents (MVAs) compared with the general population. The MVA rate in patients with suspected OSA, clinical features and the effect of treatment on risk prediction was investigated. Methods: Clinical sleep laboratory patients were cross-analyzed with a matched control group from the general population. The 10-year incidence of MVA among patients (n = 1478, 70.4% males, mean age 54 (13) years) and accidents (n = 21118) in the general population was analyzed. Risk factors associated with MVA risk were determined in patients with OSA. Results: Observed accidents among patients (n = 74) were compared with the expected number (n = 29.91, risk ratio 2.47, P < 0.001) predicted from the control population. Observed MVAs were more prevalent among younger (18–44 years) patiens but estimated OSA related excess accident risk was most prominent in elderly (65–80 years, risk ratio 3.5) drivers. Risk factors within the OSA patient cohort (high traffic exposure≥15 000 km/year, Epworth Sleepiness Score ≥16, habitual sleep time ≤5 h/night and use of hypnotics) were associated with increased accident risk (odds ratio 1.2, 2.1, 2.7 and 2.1, respectively, all P ≤ 0.03. Compliance with CPAP (≥4 h/night), was associated with a reduction of MVA frequency (7.6 to 2.5 accidents/1000 drivers/year). Conclusions: The motor vehicle accident risk in this large cohort of unselected sleep apnea patients suggests a need for accurate tools to identify individuals at risk. Conventional metrics of sleep apnea severity (e.g. apnea-hypopnea-index) failed to identify patients at risk.


Supplement: 1, Special Issue: SI, Meeting Abstract: 262



Denna post skapades 2015-03-31. Senast ändrad 2016-03-21.
CPL Pubid: 214692

 

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Institutioner (Chalmers)

Institutionen för medicin, avdelningen för invärtesmedicin och klinisk nutrition (GU)
Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)
SuMo Biomaterials

Ämnesområden

Neurologi

Chalmers infrastruktur