SANPSY-USR 3413, SANPSY-CNRS, Bordeaux University, 33000, Bordeaux, France.
HP2 Laboratory, INSERM U1042, Grenoble Alpes University, Grenoble, France.
Sci Rep. 2020 Oct 1;10(1):16267. doi: 10.1038/s41598-020-72430-8.
To evaluate the value of apnoea + hypopnoea index versus self-reported sleepiness at the wheel in anticipating the risk of sleepiness-related accidents in patients referred for obstructive sleep apnoea. A cross-sectional analysis of the French national obstructive sleep apnoea registry. 58,815 subjects referred for a suspicion of obstructive sleep apnoea were investigated by specific items addressing sleepiness at the wheel and sleepiness-related accidents. Apnoea + hypopnoea index was evaluated with a respiratory polygraphy or full polysomnography. Subjects had a median age of 55.6 years [45.3; 64.6], 65% were men, with a median apnoea + hypopnoea index of 22 [8; 39] events/h. Median Epworth sleepiness scale score was 9 [6; 13], 35% of the patients reported sleepiness at the wheel (n = 20,310), 8% (n = 4,588) reported a near-miss accident and 2% (n = 1,313) reported a sleepiness-related accident. Patients reporting sleepiness at the wheel whatever their obstructive sleep apnoea status and severity exhibited a tenfold higher risk of sleepiness-related accidents. In multivariate analysis, other predictors for sleepiness-related accidents were: male gender, ESS, history of previous near-miss accidents, restless leg syndrome/periodic leg movements, complaints of memory dysfunction and nocturnal sweating. Sleep apnoea per se was not an independent contributor. Self-reported sleepiness at the wheel is a better predictor of sleepiness-related traffic accidents than apnoea + hypopnoea index.
评估呼吸暂停+低通气指数与自我报告的驾驶时困倦在预测阻塞性睡眠呼吸暂停患者与困倦相关的事故风险中的价值。法国国家阻塞性睡眠呼吸暂停登记处的横断面分析。通过专门针对驾驶时困倦和困倦相关事故的项目,对 58815 名疑似阻塞性睡眠呼吸暂停的患者进行了调查。使用呼吸多导睡眠图或全睡眠图评估呼吸暂停+低通气指数。患者的中位年龄为 55.6 岁[45.3; 64.6],65%为男性,呼吸暂停+低通气指数的中位数为 22 [8; 39]次/小时。中位 Epworth 嗜睡量表评分为 9 [6; 13],35%的患者报告有驾驶时困倦(n=20310),8%(n=4588)报告有险些发生事故,2%(n=1313)报告有与困倦相关的事故。无论阻塞性睡眠呼吸暂停的状态和严重程度如何,报告驾驶时困倦的患者发生与困倦相关的事故的风险增加了十倍。在多变量分析中,与困倦相关的事故的其他预测因素包括:男性、ESS、先前险些发生事故的病史、不宁腿综合征/周期性肢体运动、记忆功能障碍和夜间出汗的抱怨。睡眠呼吸暂停本身并不是一个独立的贡献因素。自我报告的驾驶时困倦是预测与困倦相关的交通事故的更好指标,而不是呼吸暂停+低通气指数。