Northwestern University, Feinberg School of Medicine, Department of Obstetrics and Gynecology, Chicago, IL 60611, USA.
J Clin Sleep Med. 2012 Aug 15;8(4):389-94. doi: 10.5664/jcsm.2030.
The Berlin Questionnaire and Epworth Sleepiness Scale (ESS) are commonly used to screen for sleep apnea in non-pregnant populations. We sought to evaluate the Berlin and ESS in pregnancy and to determine whether an alternative screening approach could better detect sleep apnea in pregnant women.
Pregnant women at high risk for sleep apnea (women with chronic hypertension, pre-gestational diabetes, obesity, and/or a prior history of preeclampsia) completed a sleep survey composed of the Berlin and ESS, and participated in an overnight sleep evaluation with the Watch-PAT100 (WP100), a wrist-mounted device designed to diagnose sleep apnea, defined as an apnea hypopnea index ≥ 5. Using multivariable statistics, demographic, clinical, and subjective symptoms that were independently associated with sleep apnea were determined and a prediction rule for the presence of sleep apnea was developed. The predictive capacity of this newly developed system was compared to that of the Berlin and ESS using receiver-operating curve (ROC) statistics.
Of the 114 women who participated and had a valid WP100 study, 100 completed the Berlin and 96 the ESS. The Berlin and ESS did not accurately predict sleep apnea in this high-risk pregnancy cohort, with ROC area under the curves (AUC) of 0.54 (p = 0.6) and 0.57 (p = 0.3), respectively. Conversely, a model incorporating frequent snoring, chronic hypertension, age, and body mass index performed significantly better (AUC 0.86, p > 0.001).
The Berlin and ESS are not appropriate tools to screen for sleep apnea in high-risk pregnant women. Conversely, our four-variable model more accurately predicts sleep apnea in pregnancy.
柏林问卷和嗜睡量表(ESS)常用于筛查非妊娠人群的睡眠呼吸暂停。我们旨在评估妊娠期间的柏林问卷和 ESS,并确定替代筛查方法是否能更好地检测妊娠妇女的睡眠呼吸暂停。
患有睡眠呼吸暂停高危因素的孕妇(患有慢性高血压、孕前糖尿病、肥胖症和/或既往子痫前期病史的孕妇)完成了一份由柏林问卷和 ESS 组成的睡眠调查问卷,并参加了 Watch-PAT100(WP100)的夜间睡眠评估,这是一种腕戴式设备,用于诊断睡眠呼吸暂停,定义为呼吸暂停低通气指数≥5。使用多变量统计学,确定与睡眠呼吸暂停独立相关的人口统计学、临床和主观症状,并制定了睡眠呼吸暂停的预测规则。使用接受者操作特征(ROC)统计数据比较新开发系统的预测能力与柏林问卷和 ESS 的预测能力。
在 114 名参与并进行了有效的 WP100 研究的女性中,有 100 名完成了柏林问卷,96 名完成了 ESS。柏林问卷和 ESS 并不能准确预测这一高危妊娠队列中的睡眠呼吸暂停,ROC 曲线下面积(AUC)分别为 0.54(p=0.6)和 0.57(p=0.3)。相反,纳入频繁打鼾、慢性高血压、年龄和体重指数的模型表现明显更好(AUC 0.86,p>0.001)。
柏林问卷和 ESS 不适用于筛查高危孕妇的睡眠呼吸暂停。相反,我们的四变量模型更能准确预测妊娠期间的睡眠呼吸暂停。