Obstetrics & Gynecology:
Perinatal Outcomes Associated With Obstructive Sleep Apnea in Obese Pregnant Women
Louis, Judette MD, MPH; Auckley, Dennis MD; Miladinovic, Branko PhD; Shepherd, Anna BSN; Mencin, Patricia BBA; Kumar, Deepak MD; Mercer, Brian MD; Redline, Susan MD, MPH
Department of Obstetrics and Gynecology, Division of Maternal Fetal Medicine, the Department of Internal Medicine, Division of Pulmonary Critical Care and Sleep Medicine, the Department of Research, and the Department of Pediatrics, Division of Neonatology, MetroHealth Medical Center-Case Western Reserve University School of Medicine, Cleveland, Ohio; the Center for Evidence Based Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida; and Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Department of Medicine, Division of Sleep Medicine, Boston, Massachusetts.
Corresponding author: Judette M. Louis, MD, MPH, MetroHealth Medical Center, Case Western Reserve University School of Medicine, Department of Obstetrics and Gynecology, Division of Maternal Fetal Medicine, Cleveland, OH 44109; e-mail: email@example.com.
Supported by the Robert Wood Johnson Foundation Physician Faculty Program and the Case Western Reserve University–Cleveland Clinic CTSA grant number UL1 RR024989 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and NIH roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH.
Presented at the 32nd annual meeting of the Society for Maternal-Fetal Medicine, February 6-11, 2012, Dallas, Texas.
Financial Disclosure Dr. Redline received a grant from ResMed Foundation and research equipment from Resmed Inc and Philips Respironics. The other authors did not report any potential conflicts of interest.
OBJECTIVE: To investigate the associations between obstructive sleep apnea (OSA) and maternal and neonatal morbidities in a cohort of obese gravid women.
METHODS: Participants were enrolled in a prospective observational study designed to screen for OSA and describe the possible risk factors for and outcomes of OSA among obese (body mass index [BMI, calculated as weight (kg)/[height (m)]2] 30 or higher) pregnant women. Women underwent an overnight sleep study using a portable home monitor. Studies were manually scored by a central masked sleep reading center using American Academy of Sleep Medicine diagnostic criteria. An apnea hypopnea index of 5 or more was considered diagnostic of OSA. Perinatal outcomes were compared between women with and without OSA.
RESULTS: Among 175 women, OSA prevalence was 15.4% (13 mild, 9 moderate, 5 severe). Compared with no OSA (apnea hypopnea index less than 5), the OSA group had a higher BMI (46.8±12.2 compared with 38.1±7.5; P=.002) and more chronic hypertension (55.6% compared with 32.4%, P=.02). Maternal complications included maternal death (n=1, amniotic fluid embolus [no OSA group]) and cardiac arrest (n=1, intraoperative at cesarean delivery [OSA group]). One previable birth and two stillbirths occurred in the no OSA group. Among live births, OSA was associated with more frequent cesarean delivery (65.4% compared with 32.8%; P=.003), preeclampsia (42.3% compared with 16.9%; P=.005), and neonatal intensive care unit admission (46.1% compared with 17.8%; P=.002). After controlling for BMI, maternal age, and diabetes, OSA (odds ratio [OR] 3.55, 95% confidence interval [CI] 1.1–11.3), previous preeclampsia (OR 2.79, 95% CI 1.09–7.19), and hypertension (OR 4.25, 95% CI 1.67–10.77) were associated with development of preeclampsia.
CONCLUSION: Obstructive sleep apnea among obese pregnant women is associated with more frequent preeclampsia, neonatal intensive care unit admissions, and cesarean delivery.
LEVEL OF EVIDENCE: II
In 2009–2010, 36% of adult women and 16% of children and adolescents in the United States were reported to have a body mass index (BMI) in the obese range (30 or more). This number is projected to increase to 42% in adults by the year 2030.1–3 With rates of both adult and adolescent obesity increasing, the prevalence of obesity among women of childbearing age (age 15–44 years) also can be expected to increase. Population and cohort studies consistently indicate that obesity is associated with an increased risk of comorbid conditions during pregnancy, cesarean delivery, anesthesia complications, venous thromboembolism, and maternal mortality.4–6 Obesity also has implications for the fetus, which may experience short-term consequences resulting from medically indicated preterm birth and macrosomia and also long-term implications related to fetal in utero programming.7 These sober facts have led to increased focus on the mitigation of obesity and its pregnancy-related morbidities.
One area of increased investigation in pregnancy has been related to obstructive sleep apnea (OSA). Obstructive sleep apnea is a condition characterized by recurrent cycles of upper airway obstruction, nocturnal hypoxemia, reoxygenation, and sleep fragmentation, and is predominately an obesity-related comorbid condition.8,9 Obesity and weight gain are associated with the development and worsening of OSA.
Depending on the definition used, OSA prevalence among women of reproductive age has been estimated to be 0.7–5%. However, OSA remains underdiagnosed and understudied among women of reproductive age.10,11 Despite consistent data on the adverse cardiovascular effects of the disease in the nonpregnant population, data regarding the significance of the disease and its effects on reproduction remain scarce. Emerging data indicate an increased risk of gestational diabetes, preeclampsia, and small-for-gestational-age neonates in these women, but much of the currently available data are limited to case reports or studies that lack appropriate control groups, objective testing for OSA, or lack adjustment for obesity.12,13 It has become evident that obesity is an important confounding factor and the independent role of OSA is unclear. Therefore, we sought to examine the independent effects of OSA on maternal pregnancy outcomes and neonatal morbidities in a cohort of obese women. We hypothesized that women with OSA would have an increased risk of perinatal morbidities when compared with women of comparable weight without OSA.
MATERIALS AND METHODS
The patients in this study were enrolled in the Sleep Apnea in Pregnancy Screening Study, a prospective, observational, cohort study in which obese pregnant women were screened for sleep-related breathing disorders. The primary objective of this study was to develop a screening tool to detect OSA among obese pregnant women. The data presented in this article are the results of the preplanned secondary objective that was to identify the risk factors for OSA and to describe the pregnancy outcome among these women. The site for enrollment was a single urban tertiary care center that serves as a regional perinatal referral center. Recruitment occurred between September 2008 and August 2011. Approval from MetroHealth Medical Center's Institutional Review Board was obtained before the start of the study and each participant provided informed consent. Participants were offered enrollment if they were obese (prepregnancy BMI 30 or more), age 18 years or older, and were willing to be adherent to the study protocol. All gestational ages were included. Exclusion criteria were chronic use of narcotic or other drugs affecting the central nervous system and inability to maintain sleep beyond 2 hours. Because this was a study that relied on the use of a device, women with a documented history of nonadherence (missing more than three clinic visits) were also excluded (Fig. 1). To limit selection bias, participants were recruited from both general care and high-risk obstetrics clinics.
Enrollment.Fig. 1. L...Image Tools
Objective testing for OSA was performed using in-home portable polysomnography with the ARES Unicorder 5.2, a self-applied wireless physiologic recorder worn on the forehead. The device measures airflow using a nasal pressure cannula, blood hemoglobin SpO2 and pulse rate using reflectance oximetry, head movement and head position using actigraphy, and snoring levels using an acoustic microphone. After the patient had finished the study, the raw data were uploaded and the files were transferred by secure server to an independent blinded sleep reading center for manual scoring of the data. Apnea was defined as cessation of airflow for 10 seconds or more. Hypopnea was defined as a 50% or more reduction in airflow with an associated 3% or more decrease in oxygen saturation. Sleep time was estimated from artifact-free recording times. The apnea hypopnea index was calculated as the sum of all apnea plus hypopnea events divided by estimated sleep time.14
An apnea hypopnea index of less than 5 per hour was considered as “no OSA” and an apnea hypopnea index of 5 or more per hour was considered “OSA.” In addition, severity was described as: 5–15 per hour (mild); 16–29 per hour (moderate); and 30 or more per hour (severe).15 Participants with an apnea hypopnea index of 5 or more per hour were referred for an in-laboratory overnight polysomnogram for evaluation by a sleep medicine specialist, and their primary obstetric providers were notified. Although continuous positive airway pressure was recommended to all who tested positive for OSA, only one participant began continuous positive airway pressure during the pregnancy at 34 weeks of gestation. All the other participants were untreated.
A randomly selected subset of 19 women underwent concurrent ARES Unicorder monitoring and in-laboratory overnight full-montage polysomnogram. After the studies were conducted, the in-home ARES data were downloaded and transmitted to the sleep reading center. The in-laboratory polysomnogram was scored by the team of clinical sleep technicians using the same criteria as the sleep laboratory. The two teams were masked to the scoring result of the opposing team.
All participants received obstetric care by their physicians or nurse practitioners. No alteration of obstetrical care was recommended or mandated for study participants. Women with OSA were monitored in labor and delivery for 24 to 48 hours postdelivery if they demonstrated intrapartum hypoxemia.16 The medical records of all enrolled women and their newborns were reviewed after their discharge from the hospital, and information regarding antepartum course, delivery, and postdelivery complications (up to 6 weeks) was recorded. Chart abstraction was performed by an individual masked to study OSA status. Obtained maternal data included age, race, marital status, medical insurance, obstetric history, gestational age at enrollment, prepregnancy weight and BMI, total weight gain during pregnancy, parity, and comorbidities, which included hypertension, pregestational diabetes mellitus, gestational diabetes, asthma, and tobacco use.
American College of Obstetricians and Gynecologists clinical definitions used for diagnosis of the comorbidities mentioned include: chronic hypertension (blood pressure 140 mm Hg or more systolic or 90 mm Hg or more diastolic based on the average of two or more readings at each of two or more visits before 20 weeks of gestation or use of antihypertensive medication before pregnancy), pregestational diabetes mellitus (any of the following at the initial prenatal visit: fasting plasma glucose 126 mg/dL or more, hemoglobin A1c 6.5% or more, or random plasma glucose 200 mg/dL or more), gestational diabetes (at least one abnormal result on a 2-hour 75-g oral glucose tolerance test or at least two abnormal values on a 3-hour 100-g oral glucose tolerance test during pregnancy).17 Preeclampsia was defined as new-onset hypertension (systolic blood pressure 140 mm Hg or more or diastolic blood pressure 90 mm Hg or more) occurring at or after 20 weeks of gestation in a woman with previously normal blood pressure with documented proteinuria. Proteinuria was defined as total protein excretion of 300 mg or more in a 24-hour urine sample.18 Preterm delivery and severe preterm delivery were defined as delivery before 37 weeks and 0 days of gestation and before 32 weeks and 0 days of gestation, respectively, by best obstetrical estimate.
Clinical outcomes for neonatal respiratory disorders were determined as documented in the medical record by neonatal intensive care unit clinicians. Respiratory distress syndrome was typically defined as respiratory symptoms (eg, grunting, flaring, tachypnea, and retractions) with need for supplemental oxygen and neonatal intensive care unit admission for further respiratory support, and with the diagnosis verified by chest radiograph findings of a reticulogranular pattern and air bronchograms. Other respiratory outcomes included transient tachypnea of the newborn, pneumonia (chest radiograph verification required), pneumothorax, meconium aspiration, pulmonary hypoplasia, and respiratory failure.
The sample size was determined by the primary objective of the Sleep Apnea in Pregnancy Screening Study, which was to develop a tool to screen obese pregnant women for OSA. Assuming a 60% detection rate using the currently available screening questionnaires and an 80% detection rate using our newly developed questionnaire, the Sleep Apnea in Pregnancy Screening Study would need 182 participants (α=0.05, power=0.80) to detect a difference. An a priori power analysis was not performed for the secondary aim of the study; therefore, this analysis may be underpowered for the secondary outcomes. Study data were collected and managed using REDCap electronic data capture tools hosted at MetroHealth Medical Center.19 The agreement between ARES and full polysomnogram monitoring was measured using the Lin concordance correlation coefficient (rhoc) and Bradley-Blackwood test, which simultaneously compares the means and variances of two measurements. Good agreement was defined as rhoc in the range of 0.6–0.74 and a nonsignificant Bradley-Blackwood test result.20–22
Nominal data were analyzed with χ2 or Fisher exact test. Student t test was used for continuous data, and Wilcoxon rank-sum test was used for ordinal or non-normally distributed data. Normality was assessed using the Shapiro-Wilk test. Data analysis of outcome variables was limited to participants with a complete data set. Outcome variables were adjusted for age, race, and BMI because these variables are predicted of both OSA and perinatal morbidity. Multivariable logistic regression model was performed to study the association between preeclampsia and OSA after adjusting for the effect of potential confounders. The model goodness-of-fit was established using the Hosmer-Lemeshow test. We also sought to control and test for the logit model misspecification using linktest (absence of a linear relationship between the logit of the outcome and predictor variables) and multicollinearity among the predictor variables by assessing the tolerance levels for each variable. All analyses were performed with Stata 11.2 This study is registered in the National Institutes of Healh Clinical Trials registry (NCT01585844).
A total of 182 consenting women provided 175 complete portable polysomnogram data and were further evaluated. The prevalence of OSA was 15.4% (95% confidence interval [CI] 10.4–21.6%; 13 mild, nine moderate, five severe). Women with OSA had a median apnea hypopnea index of 12.9 events per hour of sleep and spent 6.5±2.5% of the night with SpO2 less than 90%. There was good agreement between the ARES apnea hypopnea index and polysomnogram apnea hypopnea index (rhoc=0.70, 95% CI 0.47–0.92; P<.001; Bradley-Blackwood P=.27).
Fourteen women transferred care from our institution and complete delivery data were not available. These women were excluded from further analysis. Demographic and clinical characteristics of the cohort are presented in Table 1. Compared with control group participants, the OSA group was older but similar in racial composition and insurance status. Women with OSA had a higher mean BMI (46.8±12.2 compared with 38.1±7.5; P=.002) and were more likely to have asthma diagnosed (48.1% compared with 22.9%; P=.007). They also had more frequent chronic hypertension (55.6% compared with 32.4%; P=.02), but the rate of pregestational diabetes (18.5% compared with 20.3%; P=.83) was similar between groups.
Perinatal and newborn outcomes for 158 evaluated participants with available outcome data are presented in Table 2. There was one previable birth at 22 weeks of gestation and two stillbirths; all three losses occurred in the control group. The cesarean delivery rate was 38% for the overall cohort. Among the 63 cesarean deliveries, indications included elective repeat cesarean (40%), arrest of labor (25%), abnormal fetal heart rate tracing (19%), fetal malpresentation (10%), suspected macrosomia (3%), and previous shoulder dystocia (3%). Women with OSA were more likely to have a cesarean delivery than the women in the control group (65.4% compared with 32.8%, P=.003) and more likely to have development of preeclampsia (42.3% compared with 16.9%, P=.005), but they had similar rates of preterm birth (17.6% compared with 18.5%; P=.91).
Severe maternal complications occurred in 6 of 158 women (3.8%), highlighting the high-risk nature of this population. These complications included maternal death (n=1, amniotic fluid embolus in the control group) and cardiac arrest (n=1, intraoperative at cesarean delivery in the OSA group). Operative complications included one reoperation for cystotomy and two cases of acute blood loss anemia requiring transfusion in the control group. Postpartum complications included one readmission for pulmonary embolus within 2 weeks after delivery in the OSA group.
Among live births, the two groups had a similar gestational age at delivery and birth weights. There were six neonates classified as small for gestational age (one in the OSA group and five in the control group) and two neonates were classified as large for gestational age (both in the control group). Obstructive sleep apnea was associated with more frequent neonatal intensive care unit admission (46% compared with 17.8%; P=.002) and hyperbilirubinemia (57.6% compared with 30.3%; P=.009) but similar rates of respiratory morbidity (Table 2). The primary indications for NICU admission included respiratory complications (n=26), prematurity (n=5), malformations (n=3), hypoglycemia (n=1), and observation (n=1). There was one case of hypoxic ischemic encephalopathy in the OSA group.
Results of the logistic regression examining factors associated with preeclampsia are presented in Table 3. The model provided a good fit (P=.90) and was correctly specified (P=.80). There was no evidence of multicollinearity (the tolerance was more than 79%). After controlling for maternal age, chronic hypertension, previous preeclampsia, BMI, and pregestational diabetes, OSA remained significantly associated with preeclampsia (odds ratio [OR] 3.55, 95% CI 1.12–11.3).
We have found a 15.4% prevalence of OSA among obese pregnant women. These women who experienced frequent obesity-related comorbid conditions had a high rate of cesarean delivery and preeclampsia. Additionally, the neonatal intensive care unit admission rate was high in this cohort of women.
Our findings are consistent with previous published studies in pregnant women. In a case control study of women with polysomnogram-confirmed OSA, preeclampsia was more prevalent among those women with OSA compared with normal weight and obese control group participants (30% compared with 10% and 12%, respectively; P<.01).13 Another large population-based study of 759 Chinese women with confirmed OSA demonstrated an increased risk of gestational hypertension (OR 3.18, 95% CI 2.14–4.73) and preeclampsia (OR 1.60, 95% CI 2.16–11.26) associated with OSA.23 Other large studies have relied on symptom-based screening in clinic-based populations and found a similar twofold odds of development of preeclampsia in the presence of sleep apnea symptoms.24However, most previous studies have not considered a comprehensive set of risk factors, such as previous preeclampsia, ethnicity, and gestational weight gain in addition to comorbid conditions.25 Our findings appear to suggest that OSA may have an independent association with preeclampsia after controlling for these major confounding variables.
In the general population, obesity and obesity-related comorbid conditions such as chronic hypertension, diabetes, weight gain, and older age are well-identified risk factors for OSA.26,27 Our data appear to confirm the presence of those same risk factors in this younger population. In our cohort, the women with OSA were heavier and had more chronic hypertension, consistent with the reports in the general population. Conversely, we did not find an increased prevalence of pregestational diabetes mellitus or gestational diabetes in our cohort, perhaps because of the high prevalence of obesity overall in the United States. This is contrary to a recently published report of 759 pregnant women not selected on the basis of obesity. In that study, OSA was associated with gestational diabetes (OR 1.6, 95% CI 1.07–2.8).23 However, that population-based study estimated BMI and obesity using International Classification of Diseases, 9th Revision, Clinical Modification diagnoses, which could result in misclassification. In fact, the reported obesity rate in that cohort was just 5%. Other reports of the association between sleep-related breathing disorders and pregnancy-related diabetes have relied on symptom-based screening and not objective testing.1,24,28 Our inability to find a difference in the frequency of diabetes among women with OSA may be related to the obesity of our overall cohort and to the small number of participants. Nonetheless, this highlights the importance of obesity as a significant confounding variable when studying pregnancy outcomes among women with OSA.
We were surprised to find the increased neonatal intensive care unit admission rates among the offspring of women with OSA despite similar frequencies of preterm birth between groups. Many of these admissions were secondary to respiratory morbidity in the neonate. The relationship between respiratory morbidity and cesarean delivery has been well-described. Epidemiologic and observation studies have demonstrated that term neonates with transient tachypnea of the newborn have a fourfold increased odds of being delivered by cesarean.29 Gestational age also influences neonatal respiratory morbidity. In an analysis of data from a large observational cohort of 13,258 women undergoing elective cesarean delivery at 19 centers across the United States, respiratory morbidity incidence decreased with increasing term gestational age between 37 weeks and 39 weeks.30 Compared with women delivering at 39 weeks of gestation, women who delivered at 38 or 37 weeks of gestation were 1.5-times to 2-times as likely to have a delivery complicated by neonatal intensive care unit admission and 1.7-times to 2.5-times as likely to have a newborn with respiratory morbidity. This reported relationship may further explain our findings. The women with OSA were less likely to be admitted for spontaneous labor and were more likely to undergo induction of labor and had higher cesarean delivery rates. They delivered at term but, on average, 1 week earlier than the group without OSA. Nonetheless, there may be alternative explanations. As we move forward and study the pathophysiologic mechanisms of OSA, it will be important to bear in mind the potential consequences of early term birth.
Another unexpected finding of our study was the occurrence of maternal death and the cardiac arrest in this small group of patients. However, it does highlight the risk of pregnancy in the obese woman. Maternal mortality rates have plateaued in recent decades. Obesity is a risk factor for precipitating or exacerbating all of the most common causes of maternal death after live birth in the United States (hemorrhage, hypertensive disorders of pregnancy, cardiovascular conditions, cardiomyopathy, infection, and thrombotic pulmonary embolism).31 Comorbid conditions also play a role. In population-based studies of near-miss morbidity and mortality, the most common comorbidities are hypertensive disorders of pregnancy (34.7%), previous cesarean delivery (15.7%), diabetes mellitus (10.5%), and pre-existing hypertension (10.2%).32
Our study has several limitations that require consideration. Our cohort was limited to obese patients, so we could not comment on the implications of the disease in women who are not obese. Despite limiting ourselves to obese individuals, the women with OSA, on average, had a BMI that was greater than that of women in the control group. Therefore, there still may be an obesity-related effect that we did not fully account for in our analyses. In that case, we may be overestimating the effect of OSA. In 86% of the participants, OSA was diagnosed based on a 1-night study. Night-to-night variability in apnea hypopnea index has been described and, as a result, there may have been some misclassification of OSA. Some patients transferred their care out of the system and we were unable to obtain data on their deliveries. Those women were mostly in the control group. If they had severe outcomes, too, we may be overestimating the observed effect size. Finally, our cohort included only a limited number of women with severe OSA. This, coupled with a relatively small number of observed cases of preeclampsia, neonatal intensive care unit admission, and hypertension, prevented evaluation of the effect of severity of disease on pregnancy outcomes, suggesting that both the adjusted and unadjusted ORs should be interpreted with caution. Nonetheless, these results are an important preliminary investigation of the morbidity to be expected in obese women with OSA. In conclusion, obese women with OSA have high rates of other obesity-related comorbid conditions and poor pregnancy outcomes. An optimal approach to decrease morbidity in women with OSA should be directed at treatment of obesity before pregnancy, which might also improve comorbid OSA. Nonetheless, weight loss is often difficult. Evidence of OSA operating as an independent risk factor for adverse maternal and neonatal outcomes also supports the need to address better ways to screen and treat OSA in pregnancy.
1. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA 2012;307:491–7.
2. Finkelstein EA, Khavjou OA, Thompson H, Trogdon JG, Pan L, Sherry B, et al.. Obesity and severe obesity forecasts through 2030. Am J Prevent Med 2012;42:563–70.
3. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. JAMA 2012;307:483–90.
4. Ovesen P, Rasmussen S, Kesmodel U. Effect of prepregnancy maternal overweight and obesity on pregnancy outcome. Obstet Gynecol 2011;118:305–12.
5. Vricella LK, Louis JM, Mercer BM, Bolden N. Impact of morbid obesity on epidural anesthesia complications in labor. Am J Obstet Gynecol 2011;205:370.e1-6.
6. Goffman D, Madden RC, Harrison EA, Merkatz IR, Chazotte C. Predictors of maternal mortality and near-miss maternal morbidity. J Perinatol 2007;27:597–601.
7. Catalano PM, Ehrenberg HM. The short- and long-term implications of maternal obesity on the mother and her offspring. BJOG 2006;113:1126–33.
8. Romero-Corral A, Caples SM, Lopez-Jimenez F, Somers VK. Interactions between obesity and obstructive sleep apnea. Chest 2010;137:711–9.
9. Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleep-disordered breathing. JAMA 2000;284:3015–21.
10. Bixler EO, Vgontzas AN, Lin HM, Ten Have T, Rein J, Vela-Bueno A, et al.. Prevalence of sleep-disordered breathing in women: effects of gender. Am J Respir Crit Care Med 2001;163:608–13.
11. Young T, Palta M, Dempsey J, Skatrud J, Weber S, Badr S. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993;328:1230–5.
12. Venkata C, Venkateshiah SB. Sleep-disordered breathing during pregnancy. J Am Board Fam Med 2009;22:158–68.
13. Louis JM, Auckley D, Sokol RJ, Mercer BM. Maternal and neonatal morbidities associated with obstructive sleep apnea complicating pregnancy. Am J Obstet Gynecol 2010;202:261.e1-5.
14. Iber C, Redline S, Kaplan Gilpin A, Quan S, Zhang L, Gottlieb D, et al.. Polysomnography performed in the unattended home versus the attended laboratory setting–Sleep Heart Health Study methodology. Sleep 2004;1:536–40.
15. Iber C, Ancoli-Israel S, Chesson AL Jr, Quan SF, American Academy of Sleep Medicine. The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. Westchester (IL): American Academy of Sleep Medicine; 2007.
16. Louis J, Auckley D, Bolden N. Management of Obstructive Sleep Apnea in Pregnant Women. Obstet Gynecol 2012;119:864–8.
17. Gestational diabetes. Practice Bulletin No. 30. American College of Obstetricians and Gynecologists. Obstet Gynecol 2001;98:525–38.
18. Diagnosis and management of preeclampsia and eclampsia. Practice Bulletin No. 33. American College of Obstetricians and Gynecologists. Obstet Gynecol 2002;99:159–67.
19. 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 2009;42:377–81.
20. Bradley EL, Blackwood LG. Comparing paired data–-a simultaneous test for means and variances. Am Stat 1989;43:234–5.
21. Cicchetti DV. The precision of reliability and validity estimates re-visited: distinguishing between clinical and statistical significance of sample size requirements. J Clin Exp Neuropsychol 2001;23:695–700.
22. Lin L, Hedayat AS, Sinha B, Yang M. Statistical methods in assessing agreement: Models, issues, and tools. J Am Stat Assoc 2002;97:257–70.
23. Chen YH, Kang JH, Lin CC, Wang IT, Keller JJ, Lin HC. Obstructive sleep apnea and the risk of adverse pregnancy outcomes. Am J Obstet Gynecol 2012;206:136–e1-5.
24. Bourjeily G, Raker CA, Chalhoub M, Miller MA. Pregnancy and fetal outcomes of symptoms of sleep-disordered breathing. Eur Respir J 2010;36:849–55.
25. Schutte JM, Steegers EA, Schuitemaker NW, Santema JG, de Boer K, Pel M, et al.. Rise in maternal mortality in the Netherlands. BJOG 2010;117:399–406.
26. Young T, Skatrud J, Peppard PE. Risk factors for obstructive sleep apnea in adults. JAMA 2004;291:2013–6.
27. Yaggi HK, Strohl KP. Adult obstructive sleep apnea/hypopnea syndrome: definitions, risk factors, and pathogenesis. Clin Chest Med 2010;31:179–86.
28. Centers for Disease Control and Prevention. State-specific obesity prevalence among adults—United States, 2009. Atlanta (GA): Centers for Disease Control and Prevention; 2010.
29. Tutdibi E, Gries K, Bücheler M, Misselwitz B, Schlosser RL, Gortner L. Impact of labor on outcomes in transient tachypnea of the newborn: Population-based study. Pediatrics 2010;125:e577–83.
30. Tita AT, Landon MB, Spong CY, Lai Y, Leveno KJ, Varner MW, et al.. Timing of elective repeat cesarean delivery at term and neonatal outcomes. N Engl J Med 2009;360:111–20.
31. Berg CJ, Callaghan WM, Syverson C, Henderson Z. Pregnancy-related mortality in the United States, 1998 to 2005. Obstet Gynecol 2010;116:1302–9.
32. Hawkins JL, Chang J, Palmer SK, Gibbs CP, Callaghan WM. Anesthesia-Related Maternal Mortality in the United States: 1979–2002. Obstet Gynecol 2011;117:69–74.
Figure. No available...Image Tools
This article has been cited 3 time(s).
Sleep and BreathingSleep-disordered breathing and daytime napping are associated with maternal hyperglycemiaSleep and Breathing
Diabetes CareSleep-Disordered Breathing and Gestational Diabetes Mellitus A meta-analysis of 9,795 participants enrolled in epidemiological observational studiesDiabetes Care
SleepPositive Airway Pressure as a Therapy for Preeclampsia?Sleep
© 2012 The American College of Obstetricians and Gynecologists
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Looking for ABOG articles? Visit our ABOG MOC II collection. The selected Green Journal articles are free through the end of the calendar year.
ACOG MEMBER SUBSCRIPTION ACCESS
If you are an ACOG Fellow and have not logged in or registered to Obstetrics & Gynecology, please follow these step-by-step instructions to access journal content with your member subscription.
Data is temporarily unavailable. Please try again soon.
Readers Of this Article Also Read