A Screening Algorithm for Obstructive Sleep Apnea in Pregnancy.

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.