Dataset Information

Gestational Obstructive Sleep Apnea: Biomarker Screening Models and Lack of Postpartum Resolution.

ABSTRACT: STUDY OBJECTIVES:To measure prevalence and severity of third trimester obstructive sleep apnea and evaluate postpartum resolution. To assess a novel biomarker for screening for obstructive sleep apnea in pregnancy. METHODS:This prospective observational study was performed at Wake Forest School of Medicine obstetrics clinics between April 2014 and December 2015. Fractional exhaled nitric oxide measurements and sleep studies were obtained and compared at 32 0/7 to 35 6/7 weeks gestation and postpartum. Exhaled nitric oxide and risk factors for the development of gestational sleep apnea were evaluated for predictive ability independently and in screening models. RESULTS:Of 76 women enrolled, 73 performed valid sleep studies in pregnancy and 65 had an additional valid study 6 to 15 weeks postpartum. Twenty-four women (37%) had gestational sleep apnea compared with 23 (35%) with postpartum sleep apnea (P > .99). Eight of 11 women (73%) retested 6 to 8 months postpartum had persistent sleep apnea. Exhaled nitric oxide had moderate discrimination screening for sleep apnea in pregnancy (area under the receiver operating characteristic curve = 0.64). A model utilizing exhaled nitric oxide, pregnancy-specific screening, and Mallampati score improved ability to identify women at risk for gestational sleep apnea (sensitivity = 46%, specificity = 91% and likelihood ratio = 5.11, area under receiver operating characteristic curve = 0.75). CONCLUSIONS:Obstructive sleep apnea is common in the early postpartum period and often persisted at least 6 months. Exhaled nitric oxide as a sole biomarker to screen for sleep apnea in pregnancy has only modest discrimination. Combined with additional parameters sensitivity and specificity improved. CLINICAL TRIAL REGISTRATION:Registry: ClinicalTrials.gov, Identifier: NCT02100943, Title: Exhaled Nitric Oxide as a Biomarker of Gestational Obstructive Sleep Apnea and Persistence Postpartum, URL: https://clinicaltrials.gov/ct2/show/NCT02100943.

SUBMITTER: Street LM

PROVIDER: S-EPMC5886432 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Gestational Obstructive Sleep Apnea: Biomarker Screening Models and Lack of Postpartum Resolution.

Street Linda M LM Aschenbrenner Carol A CA Houle Timothy T TT Pinyan Clark W CW Eisenach James C JC

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine 20180415 4

<h4>Study objectives</h4>To measure prevalence and severity of third trimester obstructive sleep apnea and evaluate postpartum resolution. To assess a novel biomarker for screening for obstructive sleep apnea in pregnancy.<h4>Methods</h4>This prospective observational study was performed at Wake Forest School of Medicine obstetrics clinics between April 2014 and December 2015. Fractional exhaled nitric oxide measurements and sleep studies were obtained and compared at 32 0/7 to 35 6/7 weeks gest ...[more]

PMID: 29609706

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Project description:BACKGROUND:Obstructive sleep apnea syndrome (OSAS) is common in adults. People with OSAS have a higher risk of experiencing traffic accidents and occupational injuries (OIs). We aimed to clarify the diagnostic performance of a three-channel screening device (ApneaLinkTM) compared with the gold standard of full-night attended polysomnography (PSG) among hospital outpatients not referred for sleep-related symptoms. Furthermore, we aimed to determine whether manual revision of the ApneaLinkTM autoscore enhanced diagnostic performance. METHODS:We investigated 68 patients with OI and 44 without OI recruited from the University Hospital Basel emergency room, using a cross-sectional study design. Participating patients spent one night at home with ApneaLinkTM and within 2 weeks slept for one night at the sleep laboratory. We reanalyzed all ApneaLinkTM data after manual revision. RESULTS:We identified significant correlations between the ApneaLinkTM apnea-hypopnea index (AHI) autoscore and the AHI derived by PSG (r = 0.525; p <0.001) and between the ApneaLinkTM oxygen desaturation index (ODI) autoscore and that derived by PSG (r = 0.722; p <0.001). The ApneaLinkTM autoscore showed a sensitivity and specificity of 82% when comparing AHI ≥5 with the cutoff for AHI and/or ODI ≥15 from PSG. In Bland Altman plots the mean difference between ApneaLinkTM AHI autoscore and PSG was 2.75 with SD ± 8.80 (β = 0.034), and between ApneaLinkTM AHI revised score and PSG -1.50 with SD ± 9.28 (β = 0.060). CONCLUSIONS:The ApneaLinkTM autoscore demonstrated good sensitivity and specificity compared with the gold standard (full-night attended PSG). However, Bland Altman plots revealed substantial fluctuations between PSG and ApneaLinkTM AHI autoscore respectively manually revised score. This spread for the AHI from a clinical perspective is large, and therefore the results have to be interpreted with caution. Furthermore, our findings suggest that there is no clinical benefit in manually revising the ApneaLinkTM autoscore.

Project description:Rationale: Sleep-disordered breathing (SDB) is associated with increased risk of adverse pregnancy outcomes, including gestational diabetes mellitus (GDM). GDM is a significant cause of maternal and infant morbidities. Assessing these risk factors concurrently may facilitate both the identification of women at GDM risk and the initiation of GDM prevention strategies.Objectives: To investigate whether SDB events, including SDB in rapid eye movement (REM) sleep and other sleep parameters, are associated with increased risk of GDM and to evaluate the performance of the models investigating associations between breathing and sleep parameters and GDM risk.Methods: In this case-control study, 46 women with newly diagnosed GDM and 46 healthy control subjects, who were individually matched for age, gestational age, body mass index, race, and parity, completed overnight polysomnographic studies and sleep questionnaires after being screened for GDM during the late-second to mid-third trimesters. Conditional logistic regression analysis was used to identify models investigating associations between risk factors and GDM risk. The Bayesian information criterion (BIC) was employed to compare models; the model with the lowest BIC is preferred.Results: Obstructive sleep apnea (OSA; defined as an apnea-hypopnea index [AHI] >5 events/h) was present in 22% of subjects with GDM and 9% of control subjects (P < 0.001). Women with OSA had a higher GDM risk (odds ratio [OR], 4.71; 95% confidence interval [CI], 1.05-21.04). In individual models, GDM risk was also significantly higher among women with higher overall AHI (events/h OR, 1.81; 95% CI, 1.01-3.27), higher AHI in REM (events/h OR, 2.09; 95% CI, 1.02-4.31), higher oxygen desaturation index greater than or equal to 4% (ODI4; events/h OR, 2.21; 95% CI, 1.03-4.73), and higher Sleep Apnea Symptom Score (OR, 2.72; 95% CI, 1.11-6.69). The percentage of non-REM sleep was significantly associated with decreased risk of GDM (percentage of non-REM sleep OR, 0.88; 95% CI, 0.78-0.99). The BIC supports the conclusion that there is a strong association between AHI in REM and GDM risk compared with the other significant models.Conclusions: SDB events, including REM-related OSA, are linked to increased GDM risk. GDM risk is also influenced by intercorrelated sleep variables.

Project description:Rationale: 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.Objectives: To develop a screening tool combining subjective and objective measures to predict OSA in pregnant women.Methods: This study is a secondary analysis using data collected from a completed cohort of pregnant women (n = 121 during the first and n = 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.Results: 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.Conclusions: 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.

Project description:BackgroundObesity is prevalent among pregnant women in the United States; obstructive sleep apnea is highly comorbid with obesity and is associated with adverse pregnancy outcomes. Screening for obstructive sleep apnea in pregnant women has remained a challenge because of a lack of validated screening tools.ObjectiveThe purpose of this study was to evaluate established obstructive sleep apnea screening tools, a sleepiness scale, and individual component items in a cohort of pregnant women with extreme obesity in mid pregnancy with the use of objective testing to determine obstructive sleep apnea status and to describe the prevalence of obstructive sleep apnea among women with extreme obesity.Study designAdult pregnant subjects, between 24 and 35 weeks gestation, with a body mass index ≥40 kg/m2 at the time of enrollment completed obstructive sleep apnea screening tools (Berlin Questionnaire, American Society of Anesthesiologists checklist, and STOP-BANG questionnaire) and the Epworth Sleepiness Scale; they also underwent physical examination of the neck, mouth, and airway. The published obstructive sleep apnea in pregnancy prediction score was calculated for each subject. Obstructive sleep apnea status for each subject was determined by the results of an overnight, unattended type III home sleep apnea test.ResultsTwenty-four percent of pregnant women with extreme obesity had obstructive sleep apnea on home sleep apnea testing in mid pregnancy (Apnea-Hypopnea Index, ≥5 events per hour]. Established obstructive sleep apnea screening tools performed very poorly to screen for obstructive sleep apnea in this cohort. Age, body mass index, neck circumference, frequently witnessed apneas, and highly likely to fall asleep while driving were associated most strongly with obstructive sleep apnea status in this cohort.ConclusionWe found that 24% of pregnant women with body mass index ≥40 kg/m2 between 24 and 35 weeks gestation have obstructive sleep apnea, defined as Apnea-Hypopnea Index ≥5 events per hour on an overnight type III home sleep apnea test. We found the Berlin Questionnaire, American Society of Anesthesiologists checklist, STOP-BANG, obstructive sleep apnea in pregnancy score by Facco et al, and the Epworth Sleepiness Scale were not useful screening tools for obstructive sleep apnea in a cohort of obese pregnant women. However, age, body mass index, neck circumference, frequently witnessed apneas, and likely to fall asleep while driving were associated with obstructive sleep apnea in this cohort. Further studies are needed to adjust the criteria and thresholds within the available screening tools to better predict obstructive sleep apnea in pregnant women with obesity.

Dataset Information

Gestational Obstructive Sleep Apnea: Biomarker Screening Models and Lack of Postpartum Resolution.

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Gestational Obstructive Sleep Apnea: Biomarker Screening Models and Lack of Postpartum Resolution.

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