Abstract
Background: Gestational obstructive sleep apnea (OSA) is associated with adverse maternal and fetal outcomes. Timely diagnosis and treatment are crucial to improve pregnancy outcomes. Conventional OSA screening questionnaires are less accurate, and various prediction models have been studied specifically during pregnancy. Methods: A systematic review and meta-analysis were performed for multivariable prediction models of both development and validation involving diagnosis of OSA during pregnancy. Results: Of 1262 articles, only 6 studies (3713 participants) met the inclusion criteria and were included for review. All studies showed high risk of bias for the construct of models. The pooled C-statistics (95%CI) for development prediction models was 0.817 (0.783, 0850), I2 = 97.81 and 0.855 (0.822, 0.887), I2 = 98.06 for the first and second–third trimesters, respectively. Only multivariable apnea prediction (MVAP), and Facco models were externally validated with pooled C-statistics (95%CI) of 0.743 (0.688, 0.798), I2 = 95.84, and 0.791 (0.767, 0.815), I2 = 77.34, respectively. The most common predictors in the models were body mass index, age, and snoring, none included hypersomnolence. Conclusions: Prediction models for gestational OSA showed good performance during early and late trimesters. A high level of heterogeneity and few external validations were found indicating limitation for generalizability and the need for further studies.
Highlights
Obstructive sleep apnea (OSA) is a common disorder, characterized by repetitive upper airway collapse during sleep apnea and/or hypopnea leading to oxygen desaturation, arousal, sleep fragmentation, sympathetic activation, and endothelial dysfunction [1,2,3]
Despite evidence showing that early diagnosis and treatments of gestational obstructive sleep apnea (OSA) could improve pregnancy outcomes [10,11], diagnosis of gestational OSA is challenging given the difficulty in access to standard polysomnography (PSG) and together with unawareness of OSA in pregnancy
Search terms were constructed according to the PICO principles: pregnancy (MeSH), “pregnant women”, parturient, gestation*, obstetric”; “sleep questionnaire”, screening, “prediction model”, predictors, “prediction tool”, “risk score”; “polysomnography”, PSG, sleep test, “home sleep test”, “Watch-peripheral arterial tonometry (PAT); and obstructive sleep apnea (MeSH), “obstructive sleep apnea’, “sleep apnea”, OSA, “sleep-disordered breathing”, snoring
Summary
Obstructive sleep apnea (OSA) is a common disorder, characterized by repetitive upper airway collapse during sleep apnea and/or hypopnea leading to oxygen desaturation, arousal, sleep fragmentation, sympathetic activation, and endothelial dysfunction [1,2,3]. Long-term cardiovascular consequences are shown both in men and women, despite the lower OSA prevalence in women [4]. Snoring and witnessed apnea, the hallmark of OSA symptomatology were less reported in premenopausal women when compared to post-menopausal women [6,7]. Gestational OSA had been shown to increase adverse maternal and fetal outcomes such as preeclampsia, gestational hypertension/diabetes, and preterm birth [8]. Gestational obstructive sleep apnea (OSA) is associated with adverse maternal and fetal outcomes. Diagnosis and treatment are crucial to improve pregnancy outcomes. Conventional OSA screening questionnaires are less accurate, and various prediction models have been studied during pregnancy. Methods: A systematic review and meta-analysis were performed for multivariable prediction models of both development and validation involving diagnosis of OSA during pregnancy. The pooled C-statistics (95%CI) for development prediction models was 0.817
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