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. Author manuscript; available in PMC: 2022 Oct 3.
Published in final edited form as: WMJ. 2021 Apr;120(1):34–40.

Obstructive Sleep Apnea in Pregnancy: Early Lessons from our Sleep Pregnancy Clinic

Kathleen M ANTONY 1, Natalie M JACOBSON 2,3, A Lauren RICE 2,3, Abigail M WIEDMER 2,3, Hannah MOUREY 2,3, Mihaela H BAZALAKOVA 3
PMCID: PMC9527631  NIHMSID: NIHMS1836051  PMID: 33974763

Abstract

Problem considered:

Obstructive sleep apnea (OSA) is underdiagnosed during pregnancy, but there is strong theoretical and some empiric evidence that treatment may improve obstetric outcomes. Barriers to screening, testing, and treatment are common during pregnancy. The goal of this described intervention was to reduce these barriers and improve detection of OSA in pregnancy.

Research methods:

Representatives from sleep medicine and perinatology established a cross-disciplinary, collaborative Sleep Pregnancy Clinic, offering a streamlined referral process for multimodal screening, testing, and treatment of OSA during pregnancy. This is a retrospective analysis of our first 19 months of data.

Results:

Between June 2017 and December 2018, 134 pregnant women were referred for OSA testing and 63 (47.0%) completed objective sleep testing. Of women who completed testing, 38 (60.3%) met diagnostic criteria for OSA. This intervention resulted in a statistically significant increase in the number of diagnostic sleep apnea tests performed (average 22.4 tests per year before and 67 after the intervention (p=0.0012)).

Conclusions:

Despite a streamlined referral pipeline, completion rates of OSA testing in pregnant women remained below 50%. However, the overall number of women referred and those who completed testing significantly increased during this time period. Of those who completed testing, the majority were diagnosed with OSA. Since starting this clinic, we have created resources to familiarize patients with the equipment and worked to reduce other barriers. Assessment of these interventions and the impact of treatment on obstetric outcomes is ongoing, as is assessment of reasons women do not complete diagnostic testing.

Introduction

Obesity is the most common co-morbid condition of pregnancy, and OSA is a common co-morbidity of obesity.(1) When OSA occurs in pregnancy, it is independently associated with increased risk of gestational hypertension, preeclampsia, gestational diabetes, and possibly fetal growth restriction and other adverse neonatal outcomes.(2–13)

The prevalence of OSA during pregnancy is unclear, but evidence suggests it complicates 8–32% of pregnancies, depending on comorbidities such as obesity and gestational age at time of testing.(14–16) While the literature indicates OSA during pregnancy may be relatively frequent, it remains underdiagnosed.(3,15) There is also evidence, albeit limited, to suggest that continuous positive airway pressure (CPAP) (the first-line treatment for OSA), may have therapeutic benefit for blood pressure control in preeclampsia(17,18).

Given that treatment may reduce the risk of adverse pregnancy outcomes, specifically preeclampsia, which has limited proven prevention options,(19) identifying OSA during pregnancy is timely and critical. Therefore, we sought to identify and reduce barriers to identifying OSA in pregnant patients via a multimodal approach. We sought to increase screening of pregnant patients using the best screening tool available for pregnant women and reduce barriers to referral and referral completion. Thereafter, we aspired to increase treatment initiation for those who required treatment with an overarching goal of reducing adverse obstetric outcomes related to OSA.

Here, we describe the interventions we undertook with an aim of increasing the number of pregnant women completing indicated testing for OSA during pregnancy. We also report our findings on the characteristics of pregnant women who do versus do not complete referrals, and display the general trend in completed referrals both before and after our interventions.

Study Design/ Intervention

This project was a joint venture between the Division of Maternal-Fetal Medicine at the University of Wisconsin-Madison/ UnityPoint Health-Meriter and the Wisconsin Sleep Clinic at the University of Wisconsin-Madison. The analysis described here was determined consistent with quality improvement and did not meet criteria for human subject research, and was therefore deemed exempt from oversight by the Institutional Review Board for both UnityPoint Health-Meriter and the University of Wisconsin-Madison (May 2018).

Together, representatives from sleep medicine (M.H.B.) at Wisconsin Sleep/the University of Wisconsin-Madison and perinatology (K.M.A.) at the University of Wisconsin-Madison/UnityPoint Health-Meriter met with clinic managers from each site to establish a cross-disciplinary, collaborative Sleep Pregnancy Clinic. This clinic offers a streamlined referral process for multimodal screening, diagnostic testing, and treatment of OSA during pregnancy.

Simultaneously, the department of obstetrics and gynecology at the University of Wisconsin-Madison and UnityPoint Health-Meriter created taskforces aimed at optimizing care of pregnant women with obesity, and jointly generated clinical care guidelines based upon the best available evidence and national and society recommendations. Overviews of these guidelines were presented to obstetricians and gynecologists (both academic and private), certified nurse midwives, and family medicine physicians at faculty meetings and perinatal summit events. Electronic and physical (printed) copies of the guidelines were disseminated at these events, and the guidelines remain with other clinical guidelines both on UPH-Meriter’s website and within the shared files utilized for direct clinical care. These guidelines were also used to generate streamlined order sets and note templates in the electronic health record (UW Healthlink Epic, Hyperspace 2018, Epic Systems Corporation, Verona, WI) to facilitate order placement. One part of these updated guidelines prompted the obstetric care provider to complete OSA screening using at least one published and validated tool, thus ensuring that pregnant women with at least one risk factor (pre-pregnancy body mass index (BMI) greater than or equal to 30 kg/m2) were being screened for OSA.(20–22) Screening tools utilized included the four-variable tool by Facco and STOP-BANG for all women.(20–22) The four-variable tool by Facco was published in 2012. In this model, the age and BMI are summed and 15 points each are added if the woman has chronic hypertension or snores greater than or equal to 3 nights per week.(20) STOP-BANG was also included per the Sleep Clinic’s intake protocol and is commonly used by anesthesia.(23) STOP-BANG is an eight item questionnaire which assigns 1 point for each positive answer to questions about snoring, tiredness, observed apneas, hypertension, BMI >35 kg/m2, age >50, neck size >16 inches, and male sex. (21,22) Scores of 0–2 are low risk for sleep apnea with higher scores consistent with intermediate to high risk of sleep apnea.(21,22)

On the sleep clinic end, the decision was made to utilize portable four-channel home sleep apnea testing (HSAT) equipment (Respironics Alice PDx® which is currently used at Wisconsin Sleep for home diagnostics in nonpregnant patients as well), rather than in-lab polysomnography (PSG), in order to expedite testing, as prolonged wait-times up to 2–3 months are common for PSG testing, but HSATs are typically available same day or within a couple of weeks, if insurance prior authorization is needed. We also hypothesized that home testing might reduce barriers to test completion for some, although certainly not all, pregnant women, who might be hesitant to spend a night away from children, family members and in the potentially intimidating and cumbersome environment of the sleep lab. Finally, there is precedent for using portable OSA diagnostic devices in pregnancy, including with the largest prospective study of OSA during pregnancy to date, the nuMoM2b sleep disordered breathing substudy.(4)

While establishing this collaborative Sleep Pregnancy Clinic, patient-facing materials were developed. Some materials addressed barriers that pregnant women reported to completing sleep testing. For example, many pregnant women cited concerns about bulky or cumbersome testing equipment and noisy and uncomfortable treatment choices. To address these concerns, photographs were taken (UW Health Marketing and Communications) of a pregnant consenting volunteer wearing the home sleep apnea testing device and wearing a continuous positive airway pressure (CPAP) nasal pillows interface or mask, with the CPAP machine on a table next to her (for scale) (Figure 1A and B). We also created a brochure listing the symptoms of OSA, its significance during pregnancy, and the potential benefits of treatment (Figure 2).

Figure 1:

Figure 1:

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Images of a pregnant woman wearing the sleep device (Alice PDX 4 channel system) (A) and auto-continuous positive airway pressure (Auto-CPAP) (B) nasal pillows interface/mask, which are shown to patients during their obstetrical visit if they screen positive for possible sleep apnea, prompting a referral for testing.

Figure 2:

Figure 2:

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Patient-facing brochure listing the symptoms of OSA and its significance during pregnancy.

After the aforementioned clinical guideline and patient-facing materials were generated, the typical workflow comprised of 1) screening pregnant women with a prepregnancy BMI ≥ 30 kg/m2 for sleep apnea with screening questionnaires,(20–22) 2) displaying images of a pregnant woman wearing the sleep testing device and CPAP mask, 3) distributing brochures, and 4) placing referrals to the Wisconsin Sleep Clinic where they receive expedited triage per an established “pregnancy protocol” to home sleep testing with the Alice PDx 4 channel system (Koninklijke Philips N.V.).

Significant changes were made to the typical triage for OSA referrals at Wisconsin Sleep, in order to maximally expedite testing and clinical evaluation in the time-sensitive period of pregnancy. Specifically, whereas our triage normally requires evidence of documented symptoms (for example snoring, insomnia, and/or excessive daytime sleepiness) AND documented airway, cardiovascular and pulmonary examination by the referring provider, pregnancy referrals were triaged to home OSA testing directly, rather than sleep clinic visit to document symptoms and examination. Medical comorbidities of chronic hypertension and obesity were used as criteria for testing, akin to their use in the STOPBANG OSA questionnaire(21,22) and Berlin Questionnaire(24) in nonpregnant populations. Both the STOP Bang and Berlin Questionnaire are short questionnaires (with eight and ten questions, respectively) that emphasize obesity and hypertension as risk factors for sleep apnea in addition to subjective measures of sleepiness and snoring. Frequent (greater than 3 days per week on average), not just loud, snoring was admissible as a symptom. Triage questions where in lab PSG or clinic visit as the initial step were considered, for example with documented morbid obesity, previous CPAP noncompliance, presence of additional sleep disorders such as restless leg syndrome (RLS), etc. were forwarded to one sleep physician, M.H.B. for ultimate decision. Finally, the one circumstance where face-to-face clinic visits were mandated and typically expedited by M.H.B. clinic add-on if needed, were patients with Medicare insurance, given the latter’s strict requirements.

Referrals for the analysis period were tracked via entry into a clinical database created for the purpose of tracking referrals and results of sleep testing. Data were collected and managed using Research Electronic Data Capture (REDCap) electronic data capture tools hosted at the University of Wisconsin-Madison, School of Medicine and Public Health.(25) REDCap is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.

For the purpose of this analysis, OSA was defined as a respiratory effort index (REI) with portable HSAT (the vast majority of cases) or, in the case of in-lab PSG testing, apnea-hypopnea index (AHI) or respiratory disturbance index (RDI) >5 events/ hour.(26) Both 3% and 4% desaturation criteria were used, as Wisconsin Sleep uses 4% desaturation criteria as default, but sleep physicians can interpret studies using AASM 3% desaturation criteria per their discretion. REI, AHI or RDI of 5–15 per hour were classified as mild, 15–30/hour as moderate, and greater than 30 events/hour as severe, as is standard practice (ref). These severity designations remain widely used in research and clinical practice, with pre-determined symptoms or medical comorbidities required for insurance coverage for PAP therapy for OSA in the mild category. We offered CPAP therapy to all pregnant women with studies demonstrating AHI/RDI or REI> 5 events/hour. In the majority of cases there were both symptoms and comorbidities that justified CPAP therapy in the “mild” OSA category. In cases where insurance denied coverage, M.H.B initiated appeals to the home care company/insurance, but this was only needed in 3 instances in this particular cohort.

Interventions of relevance include the development of the clinic and rigorous referral tracking starting in June 2017, the use of photographs to show the home sleep apnea testing and treatment CPAP equipment being worn by a pregnant woman starting in September 2017, and the implementation of the standardized obesity order sets prompting the use of sleep apnea screening questionnaires in September 2018.

Descriptions of barriers encountered were as reported to Sleep Clinic scheduling personnel and were ascertained pragmatically and for clinical purposes.

We conducted two analyses. First, we analyzed demographic variables associated with sleep apnea study completion for women referred between June 2017 and December 2018. Demographic variables of women who did and who did not complete sleep studies were analyzed using Pearson’s chi-squared test and Student’s t-test as appropriate.

Second, we analyzed whether our rate of referral completion (determined by sleep test completion) or the number of sleep apnea tests in pregnant women increased prior to or after our interventions. This was accomplished via query of the electronic health record (UW Healthlink Epic, Hyperspace 2018, Epic Systems Corporation, Verona, WI) for the number of referrals and the number of completed clinic visits. Data for this analysis were analyzed by twelve-month interval from January 2012 through October 2019. All statistical analyses were performed utilizing Excel (Microsoft Excel, 2013, Redmond, WA) and STATA 16.0 (StataCorp, 2017, College Station, TX).

Results:

Between June 2017 and December 2018, 134 pregnant women were referred for OSA testing and 63 (47.0%) completed objective sleep testing (Figure 3). Of pregnant women who completed testing, 38 (60.3%) met diagnostic criteria for OSA. Among pregnant women with OSA, 30 (78.9%) had “mild,” 5 (13.2%) “moderate,” and 3 (7.9%) “severe” OSA. Women who did not complete objective sleep testing cited low suspicion for OSA, inconvenience, and concerns about the testing and treating equipment.

Figure 3:

Figure 3:

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Of 134 women referred for sleep testing, 63 (47.0) completed testing. Of those who completed testing, 60.3% met criteria for obstructive sleep apnea.

Table 1 shows the demographic and maternal characteristics of pregnant women who did or did not complete sleep testing. Pregnant women who did not complete sleep testing were less likely to be married and more likely to have a diagnosis of hypothyroidism. There was a non-statistically significant trend toward lower testing completion for referrals that occurred later in pregnancy.

Table 1:

Maternal characteristics by sleep test completion

Sleep test not completed Sleep test completed P value
n 71* n 63*
Age, years, mean ( SD) 32.8 (5.0) 34.3 (5.6) 0.106
Age, years by group, n (%)
 18–34 48 (67.6) 35 (55.6)
 ≥35 23 (32.4) 28 (44.4) 0.152
Race/Ethnicity, n(%)
 White 50 (74.6) 50 (79.4)
 Black or African American 10 (14.9) 5 (7.9)
 Hispanic 2 (3.0) 3 (4.8)
 Asian 2 (3.0) 2 (3.17)
 Other or not reported 3 (4.5) 3 (4.8) 0.782
Marital Status, n (%)
 Single 8 (14.3) 3 (5.17)
 Married or committed 15 (26.8) 38 (65.5)
 Divorced or separated 2 (3.6) 0 (0.0)
 Unknown 31 (55.4) 17 (29.3) <0.001
Parity 1.2 (1.5) 0.9 (1.2) 0.176
Trimester at time of referral
 First trimester 27 (40.3) 33 (54.1)
 Second trimester 26 (38.8) 24 (39.3)
 Third trimester 14 (20.9) 4 (6.6) 0.051
 BMI, kg/m2, mean (SD) 42.2 (8.7) 40.4 (8.7) 0.256
BMI, kg/m2, by group, n (%)
 <30 5 (7.9) 5 (8.0)
 30–39.99 22 (34.9) 23 (37.1)
 ≥40 36 (57.1) 34 (54.8) 0.965
Medical co-morbidities (n,%)
 Hypertension 27 (39.1) 20 (31.8) 0.376
 Pregestational diabetes 13 (18.3) 8 (12.7) 0.372
 Hypothyroidism 4 (6.0) 19 (31.2) <0.001
 Smoking 28 (41.8) 17 (27.4) 0.087
 Excess gestational weight gain (n,%) 18 (26.9) 26 (41.3) 0.083
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*

Some electronic health records lacked data

When assessing whether the total number of sleep clinic visits by pregnant women changed over time, the average number of annual referrals before this intervention was 44.4 referrals per year (standard deviation (SD) 3.8), rising to an average of 139.7 referrals per year (SD 34.9) following our intervention, a statistically significant increase (p<0.001). This intervention resulted in a statistically significant increase in the number of sleep tests performed (average 22.4 tests per year before (SD 5.3) and 67 (SD 16.6) after the intervention (p=0.0012)). However, the sleep study completion rate (as a percent of completed tests per referral) did not improve as referral completion was 50.3% (SD 10.2%) pre- and 48.0% (SD 2.4%) post-intervention (p=0.718). (Figure 4.)

Figure 4:

Figure 4:

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Referrals and sleep studies completed by pregnant women at the Wisconsin Sleep Center from January 2012-October 2019. There was a statistically significant increase in the number of referrals and completed studies performed on pregnant women after the intervention (average 22.4 tests per year before (SD 5.3) and 67 (SD 16.6) after the intervention (p=0.0012)).

Conclusions:

Here we describe in replicate detail the steps our clinics undertook to increase indicated testing for OSA during pregnancy. While completion rates of referrals, meaning referrals resulting in completion of sleep apnea testing, did not change, the overall number of pregnant women referred and tested for OSA significantly increased, both statistically and clinically. This increase occurred following the creation of a standardized protocol and order set for managing pregnant women with obesity inclusive of sleep apnea screening (as described above) and a streamlined referral process for objective sleep apnea testing. Of women who completed testing, the majority met diagnostic criteria for OSA with flexible use of both 4% and 3% desaturation criteria. This underlines the high prevalence of sleep disordered breathing in pregnancies complicated by obesity, and the importance of considering and pursuing evaluation of OSA in pregnancy. However the percentage of women who tested positive cannot be extrapolated to the non-tested population because there is likely ascertainment bias.

While the majority of pregnant women with OSA had “mild” sleep apnea, over 20% had “moderate or severe” sleep apnea. We would like to point out that this classification of sleep apnea severity, based on the number of respiratory events per hour (mild for AHI/RDI or REI 5–15/hr and moderate to severe for >15/hr), was formally adopted in 1999, based exclusively on PSG data and with scoring of respiratory events incorporating arousals, in addition to desaturations, to arrive at the AHI/RDI. Thus, designations of “mild” versus “moderate to severe” apnea severity remain empiric, have not been adjusted to reflect revised scoring criteria and 4 channel portable testing, and are unlikely to accurately define pathophysiological and clinical consequences of the unique physiology of OSA in pregnancy. In addition, use of 3% versus 4% desaturation criteria can easily change the diagnosis from snoring to OSA, or move a diagnostic test from the mild to the moderate to severe category.(27) These limitations remain a challenge in the field of sleep medicine in general, outside of OSA during pregnancy, and is beyond the scope of this publication, outside of advocating for the use of less restrictive and likely more physiologically relevant 3% diagnostic criteria in the evaluation of OSA in pregnancy.

Women who did and did not complete testing had demographic differences which we will use to inform our ongoing efforts to increase completion of diagnostic testing. Women who did not complete recommended sleep testing were less likely to be married. These women may be concerned that a sleep test would require them to be away from home which would pose challenges if there are additional children in the family that require care, thus assuaging these concerns will be a priority for future interventions; the sleep test used in our clinic is a home test, and we will emphasize that. We are also working to determine best ways of distributing the portable sleep apnea testing devices to women at their obstetric clinic, rather than requiring a trip to the sleep clinic to pick up the equipment, as the sleep clinic may not be near their home or work. Recommended sleep testing completion was also higher among women with hypothyroid disease, which may reflect worsened symptoms of fatigue. We also noted that completion of testing was (non-statistically) lowest in advanced pregnancy. We therefore suggest screening in early to mid-pregnancy. This would also allow any indicated treatment to commence, and potentially have an effect, earlier in the pregnancy.

When OSA is diagnosed, systematic reviews and meta-analyses have demonstrated increased risk of adverse pregnancy outcomes among women with OSA.(2–4,6–12) Assessment of the impact of OSA on obstetric outcomes in our population is ongoing, as is assessment of whether treatment is beneficial. Here we demonstrate that, while the overall referral completion rate was low, of the women who completed testing, over half were diagnosed with OSA, and treatment was recommended. CPAP remains first line therapy for OSA.(3) While large trials of CPAP tolerance and efficacy in pregnancy are lacking, the findings of small studies suggest that treatment may improve obstetric outcomes with regards to preeclampsia.(17,18)

Strengths of this study include the detailed review of the sleep testing results and treatment plan to ensure that all women with sleep apnea were accurately diagnosed, evaluated in sleep clinic and treatment initiated expeditiously. Limitations include the use of the electronic health record to extract referrals retrospectively. The electronic health record occasionally lacks diagnostic codes for pregnancy, particularly for women whose prenatal care is not within the same healthcare system or electronic health record as the system where the sleep test occurs. This would be expected to reduce the capture of pregnant women seen at the sleep clinic. To account for this source of bias, our analyses of referral completion and sleep clinic visits exclusively utilized data from the electronic health record query and did not include data from our clinical database, as this would introduce understandable ascertainment bias. Retrospective analysis occasionally also lacks relevant clinical information. Some referrals lacked demographic characteristics as seen in table 1. Another important limitation is the performance of sleep apnea screening questionnaires during pregnancy. Most screening tools used for the nonpregnant population perform poorly during pregnancy including the Berlin and STOP-BANG questionnaires, and the Epworth Sleepiness Scale, although each have some useful components.(14,23,28,29) We opted for Facco’s four variable tool, which had the highest accuracy for predicting sleep apnea in pregnancy at the time our intervention was designed, although it has more recently been demonstrated to have poor specificity among women with BMI ≥40 kg/m2.(20,29) Our assessment of reported barriers were obtained by the Sleep Clinic Schedulers and were limited by ascertainment bias due to the retrospective approach.

Future analyses of our clinical database will focus on assessing obstetric outcomes associated with sleep apnea diagnosis in this population, evaluating the currently utilized sleep screening tools, and measuring the impact of treatment on established obstetric outcomes. We will also plan a patient focused exploration of the barriers to OSA testing via systematically performed interviews of recently delivered postpartum and will study the percentage of tests performed that yielded positive test results before and after the intervention. Our intention with this manuscript is to demonstrate one feasible workflow to allow other clinics to emulate this model, improve the number of women referred and screened for OSA during pregnancy, and hopefully reduce adverse obstetric events associated with OSA.

Acknowledgements:

We would like to thank the University of Wisconsin School of Medicine and Public Health Departments of Obstetrics and Gynecology and Neurology, Unity Point Health-Meriter’s Center for Perinatal Care, and Wisconsin Sleep for their support in the development of this obstetric sleep clinic. Via the use of REDCap for clinical tracking, the project described was supported by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR002373. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We thank the Department of Biology Course Biology 152 for fostering collaboration between undergraduate students and clinical research mentors. We would also like to thank the following individuals: Jeffrey Piers for his assistance in querying the electronic health record to track referrals and referral completion; Angela Bahr for volunteering to model the sleep testing device and positive airway pressure mask treatment; and Robert Koehler for reviewing the literature and procuring articles.

Footnotes

Conflict of Interest Disclosures: The authors report no disclosures.

Paper Presentation Information: Data from this paper were presented as poster presentations at the Wisconsin Association for Perinatal Care (WAPC) 2019 Annual Conference, Abstract # 10, Oshkosh, WI, April 7–9, 2019 and the Wisconsin Perinatal Quality Collaborative Annual Summit, Brookfield, WI, Sept 17, 2019.

References

  • 1.Catalano PM, Shankar K. Obesity and pregnancy: mechanisms of short term and long term adverse consequences for mother and child. BMJ. 2017;360:j1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Pamidi S, Pinto LM, Marc I, Benedetti A, Schwartzman K, Kimoff RJ. Maternal sleep-disordered breathing and adverse pregnancy outcomes: A systematic review and metaanalysis. Am J Obstet Gynecol. Elsevier Inc; 2014;210(1):52.e1–52.e14. [DOI] [PubMed] [Google Scholar]
  • 3.Bazalakova M Sleep Disorders in Pregnancy. Semin Neurol. 2017;37(6):661–8. [DOI] [PubMed] [Google Scholar]
  • 4.Facco FL, Parker CB, Reddy UM, Silver RM, Koch MA, Louis JM, et al. Association between Sleep-Disordered Breathing and Hypertensive Disorders of Pregnancy and Gestational Diabetes Mellitus. Obstet Gynecol. 2017;129(1):31–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bourjeily G, Danilack VA, Bublitz MH, Muri J, Rosene-montella K, Lipkind H. Maternal obstructive sleep apnea and neonatal birth outcomes in a population based sample. Sleep Med Elsevier Ltd; 2020;66:233–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Brown NT, Turner JM, Kumar S. The intrapartum and perinatal risks of sleep-disordered breathing in pregnancy: a systematic review and metaanalysis. Am J Obstet Gynecol. Elsevier; 2018;219(2):147–161.e1. [DOI] [PubMed] [Google Scholar]
  • 7.Antony KM, Racusin DA, Aagaard KM, Dildy GA. Chapter 3: Maternal Physiology. In: Gabbe SG, editor. Obstetrics: Normal and Problem Pregnancies. 7th ed. Philadelphia, PA: Elsevier; 2017. p. 38–63. [Google Scholar]
  • 8.Ding XX, Wu Y Le, Xu SJ, Zhang SF, Jia XM, Zhu RP, et al. A systematic review and quantitative assessment of sleep-disordered breathing during pregnancy and perinatal outcomes. Sleep Breath. 2014;18(4):703–13. [DOI] [PubMed] [Google Scholar]
  • 9.Xu T, Feng Y, Peng H, Guo D, Li T. Obstructive Sleep Apnea and the Risk of Perinatal Outcomes: A Meta-Analysis of Cohort Studies. Sci Rep. 2014;4:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Li L, Zhao K, Hua J, Li S. Association between sleep-disordered breathing during pregnancy and maternal and fetal outcomes: An updated systematic review and meta-analysis. Front Neurol. 2018;9(MAY):1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Warland J, Dorrian J, Morrison JL, O’Brien LM. Maternal sleep during pregnancy and poor fetal outcomes: A scoping review of the literature with meta-analysis. Sleep Med Rev Elsevier Ltd; 2018;41(2018):197–219. [DOI] [PubMed] [Google Scholar]
  • 12.Liu L, Su G, Wang S, Zhu B. The prevalence of obstructive sleep apnea and its association with pregnancy-related health outcomes: a systematic review and meta-analysis. Sleep Breath. Sleep and Breathing; 2019;23(2):399–412. [DOI] [PubMed] [Google Scholar]
  • 13.August EM, Salihu HM, Biroscak BJ, Rahman S, Bruder K, Whiteman VE. Systematic review on sleep disorders and obstetric outcomes: Scope of current knowledge. Am J Perinatol. 2013;30(4):323–34. [DOI] [PubMed] [Google Scholar]
  • 14.Antony KM, Agrawal A, Arndt ME, Murphy AM, Alapat PM, Guntupalli KK, et al. Obstructive sleep apnea in pregnancy: reliability of prevalence and prediction estimates. J Perinatol. Nature Publishing Group; 2014. Aug;34(8):587–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Louis JM, Koch MA, Reddy UM, Silver RM, Parker CB, Facco FL, et al. Predictors of sleep-disordered breathing in pregnancy. Am J Obstet Gynecol. Elsevier Inc.; 2018;218(5):521.e1–521.e12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Facco FL, Ouyang DW, Grobman WA. Sleep Disordered Breathing in a High-Risk Cohort Prevalence and Severity across Pregnancy. Am J Perinatol. 2014;31:899–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Whitehead C, Tong S, Wilson D, Howard M, Walker SP. Treatment of early-onset preeclampsia with continuous positive airway pressure. Obstet Gynecol. 2015;125(5):1106–9. [DOI] [PubMed] [Google Scholar]
  • 18.Edwards N, Blyton DM, Kirjavainen T, Kesby GJ, Sullivan CE, Kgv GV, et al. Nasal Continuous Positive Airway Pressure Reduces Sleep-induced Blood Pressure Increments In Preeclampsia. Am J Respir Crit Care Med. 2000;162:252–7. [DOI] [PubMed] [Google Scholar]
  • 19.The American College of Obstetricians and Gynecologists. Gestational hypertension and preeclampsia. ACOG Practice Bulletin No. 202. Obstet Gynecol. 2019;133(1):1–25. [DOI] [PubMed] [Google Scholar]
  • 20.Facco FL, Ouyang DW, Zee PC, Grobman W a. Development of a pregnancy-specific screening tool for sleep apnea. J Clin Sleep Med. 2012. Jan;8(4):389–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Chung F, Yegneswaran B, Liao P, Chung SA, Vairavanathan S, Islam S, et al. STOP Questionnaire: A Tool to Screen Patients for Obstructive Sleep Apnea. Anesthesiology. 2008;(108):812–21. [DOI] [PubMed] [Google Scholar]
  • 22.Chung F, Subramanyam R, Liao P, Sasaki E, Shapiro C, Sun Y. High STOP-Bang score indicates a high probability of obstructive sleep apnoea. Br J Anaesth. The Author(s). Published by Elsevier Ltd on behalf of the British Journal of Anaesthesia.; 2012;108(5):768–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Pearson F, Batterham AM, Cope S. The STOP-BANg questionnaire as a screening tool for obstructive sleep apnea in pregnancy. J Clin Sleep Med. 2019;15(5):705–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131(7):485–91. [DOI] [PubMed] [Google Scholar]
  • 25.Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform Elsevier Inc.; 2009;42(2):377–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, et al. Rules for Scoring Respiratory Events in Sleep : Update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. J Clin Sleep Med. 2012;8(5):597–619. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Budhiraja R, Javaheri S, Parthasarathy S, Berry RB, Quan SF. The Association Between Obstructive Sleep Apnea Characterized by a Minimum 3 Percent Oxygen Desaturation or Arousal Hypopnea Definition and Hypertension. J Clin Sleep Med United States; 2019. Sep;15(9):1261–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Tantrakul V, Numthavaj P, Guilleminault C, McEvoy M, Panburana P, Khaing W, et al. Performance of screening questionnaires for obstructive sleep apnea during pregnancy: A systematic review and meta-analysis. Sleep Med Rev Elsevier Ltd; 2017;36:96–106. [DOI] [PubMed] [Google Scholar]
  • 29.Dominguez JE, Grotegut CA, Cooter M, Krystal AD, Habib AS. Screening extremely obese pregnant women for obstructive sleep apnea. Am J Obstet Gynecol. Elsevier Inc.; 2018;219(6):613.e1–613.e10. [DOI] [PMC free article] [PubMed] [Google Scholar]

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