Skip to main content

Free Content Can we predict sleep‐disordered breathing in pregnancy? The clinical utility of symptoms

Download Article:

You have access to the full text article on a website external to Ingenta Connect.

Please click here to view this article on Wiley Online Library.

You may be required to register and activate access on Wiley Online Library before you can obtain the full text. If you have any queries please visit Wiley Online Library


Sleep‐disordered breathing (SDB) is reported commonly during pregnancy and is associated with an increased risk of adverse maternal and fetal outcomes, but the majority of these data are based upon self‐report measures not validated for pregnancy. This study examined the predictive value of screening questionnaires for SDB administered at two time‐points in pregnancy, and attempted to develop an ‘optimized predictive model’ for detecting SDB in pregnancy. A total of 380 women were recruited from an antenatal clinic in the second trimester of pregnancy. All participants completed the Berlin Questionnaire and the Multivariable Apnea Risk Index (MAP Index) at recruitment, with a subset of 43 women repeating the questionnaires at the time of polysomnography at 37 weeks' gestation. Fifteen of 43 (35%) women were confirmed to have a respiratory disturbance index (RDI) > 5 h−1. Prediction of an RDI > 5 h−1 was most accurate during the second trimester for both the Berlin Questionnaire (sensitivity 0.93, specificity 0.50, positive predictive value 0.50 and negative predictive value 0.93), and the MAP Index [area under the receiver operating characteristic (ROC) curve of 0.768]. A stepwise selection model identified snoring volume, a body mass index (BMI)≥32 kg m−2 and tiredness upon awakening as the strongest independent predictors of SDB during pregnancy; this model had an area under the ROC curve of 0.952. We conclude that existing clinical prediction models for SDB perform inadequately as a screening tool in pregnancy. The development of a highly predictive model from our data shows promise for a quick and easy screening tool to be validated for future use in pregnancy.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Document Type: Research Article

Publication date: 2013-12-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more