Department of Biobehavioral Health Sciences, College of Nursing, University of Illinois at Chicago, Chicago, Illinois.
School of Nursing, Shanghai Jiao Tong University, Shanghai, China.
Ann Am Thorac Soc. 2019 Oct;16(10):1286-1294. doi: 10.1513/AnnalsATS.201902-131OC.
Obstructive sleep apnea (OSA) is common in pregnancy and associated with maternal and fetal complications. Early detection of OSA may have important implications for maternal-fetal well-being. A screening tool combining several methods of assessment may better predict OSA among pregnant women compared with tools that rely solely on self-reported information. To develop a screening tool combining subjective and objective measures to predict OSA in pregnant women. This study is a secondary analysis using data collected from a completed cohort of pregnant women ( = 121 during the first and = 87 during the third trimester). Participants underwent full polysomnography and completed the Multivariable Apnea Prediction Questionnaire. The Obstructive Sleep Apnea/Hypopnea Syndrome Score and Facco apnea predictive model were obtained. Logistic regression analysis and area under the curve (AUC) were used to identify models predicting OSA risk. Participants' mean age was 27.4 ± 7.0 years. The prevalence of OSA during the first and third trimester was 10.7% and 24.1%, respectively. The final model predicting OSA risk consisted of body mass index, age, and presence of tongue enlargement. During the first trimester, the AUC was 0.86 (95% confidence interval [CI], 0.76-0.96). During the third trimester, the AUC was 0.87 (95% CI, 0.77-0.96). When the first-trimester data were used to predict third-trimester OSA risk, the AUC was 0.87 (95% CI, 0.77-0.97). This model had high sensitivity and specificity when used during both trimesters. The negative posttest probabilities (probability of OSA given a negative test result) ranged from 0.03 to 0.07. A new model consisting of body mass index, age, and presence of tongue enlargement provided accurate screening of OSA in pregnant women, particularly African-Americans. This tool can be easily and rapidly administered in busy clinical practices without depending on patients' awareness of experiencing apnea symptoms.
阻塞性睡眠呼吸暂停（OSA）在妊娠中很常见，与母婴并发症有关。早期发现 OSA 可能对母婴健康有重要意义。与仅依赖自我报告信息的工具相比，结合多种评估方法的筛查工具可能更能预测孕妇的 OSA。开发一种结合主观和客观测量的筛查工具来预测孕妇的 OSA。本研究是对一项已完成的孕妇队列研究数据的二次分析（第一孕期 = 121 例，第三孕期 = 87 例）。参与者接受了全面的多导睡眠图检查，并完成了多变量呼吸暂停预测问卷。获得了阻塞性睡眠呼吸暂停/低通气综合征评分和法科呼吸暂停预测模型。使用逻辑回归分析和曲线下面积（AUC）来确定预测 OSA 风险的模型。参与者的平均年龄为 27.4±7.0 岁。第一和第三孕期 OSA 的患病率分别为 10.7%和 24.1%。预测 OSA 风险的最终模型包括体重指数、年龄和舌体增大。在第一孕期，AUC 为 0.86（95%置信区间[CI]，0.76-0.96）。在第三孕期，AUC 为 0.87（95%CI，0.77-0.96）。当使用第一孕期数据预测第三孕期 OSA 风险时，AUC 为 0.87（95%CI，0.77-0.97）。该模型在两个孕期均具有较高的灵敏度和特异性。阴性后验概率（给定阴性检测结果的 OSA 概率）范围为 0.03 至 0.07。由体重指数、年龄和舌体增大组成的新模型为孕妇提供了准确的 OSA 筛查，尤其是非裔美国人。该工具可在繁忙的临床实践中轻松快速地进行，而无需依赖患者对出现呼吸暂停症状的意识。
