A Screening Algorithm for Obstructive Sleep Apnea in Pregnancy.
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ABSTRACT:
SUBMITTER: Izci-Balserak B
PROVIDER: S-EPMC6812170 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We employed accepted, validated symptom-based screening measures to discern attributable risk of obstructive sleep apnea (OSA) to adverse pregnancy outcomes, taking into account potential maternal confounders. Commonly employed OSA screening measures (Berlin and Epworth scales) were performed in the second and third trimesters; maternal and neonatal outcome data were thereafter obtained. The relationship between OSA and outcomes of interest were explored in stratified and multivariate models controlling for potential confounders. The overall prevalence of OSA was 25.4%. Given a nonlinear increase by body mass index (BMI) strata (8.9%, 46%; p < 0.0001), stratified multivariate analysis was subsequently performed. Among nonobese (BMI <30) gravidae, frequency of preeclampsia was significantly higher among women with OSA (adjusted odds ratio = 6.58, 95% confidence interval = 1.04, 38.51; p = 0.035). Among the obese (BMI ≥30) gravidae, infant birth weight ratio (or birth weight by gestational age) was higher with OSA + screening than OSA - (1.099 versus 1.035; p = 0.04), and this association remained significant after adjustment for potential confounders (p = 0.05). OSA prevalence increases significantly among obese gravidae, raising concerns for the overall validity of commonly employed screening measures in pregnancy. Nevertheless, OSA status continues to exert an independent influence, as obese and nonobese gravidae are at increased risk for a limited number of adverse perinatal outcomes in multivariate models.
| S-EPMC3966067 | biostudies-literature
Project description:BackgroundThe American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used in patients with obstructive sleep apnea (OSA) without replacing polysomnography, which is the gold standard.ObjectiveThis study aims to develop a clinical decision support system for OSA diagnosis according to its standard definition (apnea-hypopnea index plus symptoms), identifying individuals with high pretest probability based on risk and diagnostic factors.MethodsA total of 47 predictive variables were extracted from a cohort of patients who underwent polysomnography. A total of 14 variables that were univariately significant were then used to compute the distance between patients with OSA, defining a hierarchical clustering structure from which patient phenotypes were derived and described. Affinity from individuals at risk of OSA phenotypes was later computed, and cluster membership was used as an additional predictor in a Bayesian network classifier (model B).ResultsA total of 318 patients at risk were included, of whom 207 (65.1%) individuals were diagnosed with OSA (111, 53.6% with mild; 50, 24.2% with moderate; and 46, 22.2% with severe). On the basis of predictive variables, 3 phenotypes were defined (74/207, 35.7% low; 104/207, 50.2% medium; and 29/207, 14.1% high), with an increasing prevalence of symptoms and comorbidities, the latter describing older and obese patients, and a substantial increase in some comorbidities, suggesting their beneficial use as combined predictors (median apnea-hypopnea indices of 10, 14, and 31, respectively). Cross-validation results demonstrated that the inclusion of OSA phenotypes as an adjusting predictor in a Bayesian classifier improved screening specificity (26%, 95% CI 24-29, to 38%, 95% CI 35-40) while maintaining a high sensitivity (93%, 95% CI 91-95), with model B doubling the diagnostic model effectiveness (diagnostic odds ratio of 8.14).ConclusionsDefined OSA phenotypes are a sensitive tool that enhances our understanding of the disease and allows the derivation of a predictive algorithm that can clearly outperform symptom-based guideline recommendations as a rule-out approach for screening.
| S-EPMC8277326 | biostudies-literature
Project description:Rationale: Obstructive sleep apnea (OSA) has been associated with metabolic dysregulation and systemic inflammation. This may be due to pathophysiologic effects of OSA on visceral adipose tissue. We sought to assess the transcriptional consequences of OSA on adipocytes by utilizing pathway-focused analyses. Methods: Patients scheduled to undergo ventral hernia repair surgery were recruited to wear a portable home sleep monitor for two nights prior to surgery. Visceral fat biopsies were obtained intra-operatively. RNA was extracted and whole-genome expression profiling was performed. Gene Set Enrichment Analysis (GSEA) was used to identify curated gene sets that were differentially enriched in OSA subjects. Network analysis was applied to a select set of highly enriched pathways. Results: 10 patients with OSA and 8 control subjects were recruited. There were no differences in age, gender, body mass index between the two groups, but the OSA subjects had a significantly higher respiratory disturbance index (19.2 vs. 0.6, P-value 0.05) and worse hypoxemia (minimum oxygen saturation 79.7% vs. 87.8%, P-value < 0.001). GSEA identified a number of gene sets up-regulated in adipose tissue of OSA patients including the pro-inflammatory NF-M-NM-:B pathway and the proteolytic ubiquitin/proteasome module. A critical metabolic pathway, the peroxisome proliferator-activated receptor (PPAR), was down-regulated in subjects with OSA. Network analysis linked members of these modules together and identified regulatory hubs. Conclusions: OSA is associated with alterations in visceral fat gene expression. Pathway-based network analysis highlighted perturbations in several key pathways whose coordinated interactions may contribute to the metabolic dysregulation observed in this complex disorder. Total RNA from visceral fat of 18 subjects (10 OSA, 8 Control) was hybridized to 18 Affymetrix Genechip Human Gene 1.0 ST microarrays.
2012-09-01 | E-GEOD-38792 | biostudies-arrayexpress
Project description:Study objectivesWe examined the validity of the STOP-Bang questionnaire and a modified STOP-Bang questionnaire to screen for obstructive sleep apnea (OSA) in women with obesity during the second trimester of pregnancy.MethodsNinety-nine pregnant women age 18 years or older with body mass index ≥ 40 kg/m2 completed the STOP-Bang questionnaire during their second trimester. The number of oxygen desaturation events (≥ 4% from baseline) was measured using overnight pulse oximetry, with OSA defined as ≥ 5 events/h. A Modified STOP-Bang score was derived by replacing the "Tired" item with Epworth Sleepiness Scale score ≥ 10. Seven candidate models were compared using information theoretic criteria: STOP-Bang, Modified STOP-Bang, and individual STOP-Bang items (Snore, Tired, Observed to stop breathing, high blood Pressure and Neck circumference). We used penalized logistic regression and negative binomial regression to derive predicted probabilities of having OSA and the predicted total event counts.ResultsThe predicted probability of meeting oximetry criteria for OSA increased with higher STOP-Bang scores, from < 10% for a score < 3 to 68% with a score of 6. The total number of disordered breathing events was 1.26 (95% confidence interval 1.06 to 1.50) times greater for a 1-unit increase in STOP-Bang. Of the candidate models, the best relative fit was the Snore item followed by STOP-Bang score (essentially equivalent). The predicted probability of having OSA was 5.0% for no snoring and 26.4% for snoring.ConclusionsSTOP-Bang has been shown to be a useful screening tool for OSA in pregnant women with obesity; however, the snoring question alone might be a simpler, effective predictor.Clinical trial registrationRegistry: ClinicalTrials.gov; Title: STOPBANG As A Screening Tool for Obstructive Sleep Apnoea in Pregnancy; URL: https://clinicaltrials.gov/ct2/show/NCT02542488; Identifier: NCT02542488.
| S-EPMC6510674 | biostudies-literature
Project description:IntroductionDiagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otolaryngology, resulting in long waitlists.MethodWe used data from our pediatric OSA clinic to identify predictors of tonsillectomy and/or adenoidectomy (AT). Before being seen in the clinic, parents completed the Pediatric Sleep Questionnaire (PSQ) and screening questionnaires for restless leg syndrome (RLS), nasal rhinitis, and gastroesophageal reflux disease (GERD). Tonsil size data were obtained from patient charts and graded using the Brodsky-five grade scale. Children completed an overnight oximetry study before being seen in the clinic, and a McGill oximetry score (MOS) was assigned based on the number and depth of oxygen desaturations. Logistic regression, controlling for otolaryngology physician, was used to identify significant predictors of AT. Three triage algorithms were subsequently generated based on the univariate and multivariate results to predict AT.ResultsFrom the OSA cohort, there were 469 eligible children (47% female, mean age = 8.19 years, SD = 3.59), with 89% of children reported snoring. Significant predictors of AT in univariate analysis included tonsil size and four PSQ questions, (1) struggles to breathe at night, (2) apneas, (3) daytime mouth breathing, and (4) AM dry mouth. The first triage algorithm, only using the four PSQ questions, had an odds ratio (OR) of 4.02 for predicting AT (sensitivity = 0.28, specificity = 0.91). Using only tonsil size, the second algorithm had an OR to predict AT of 9.11 (sensitivity = 0.72, specificity = 0.78). The third algorithm, where MOS was used to stratify risk for AT among those children with 2+ tonsils, had the same OR, sensitivity, and specificity as the tonsil-only algorithm.ConclusionTonsil size was the strongest predictor of AT, while oximetry helped stratify individual risk for AT. We recommend that referral letters for snoring children include graded tonsil size to aid in the triage based on our findings. Children with 2+ tonsil sizes should be triaged to otolaryngology, while the remainder should be referred to a pediatric sleep specialist.
| S-EPMC8281470 | biostudies-literature
Project description:Rationale: Obstructive sleep apnea (OSA) has been associated with metabolic dysregulation and systemic inflammation. This may be due to pathophysiologic effects of OSA on visceral adipose tissue. We sought to assess the transcriptional consequences of OSA on adipocytes by utilizing pathway-focused analyses. Methods: Patients scheduled to undergo ventral hernia repair surgery were recruited to wear a portable home sleep monitor for two nights prior to surgery. Visceral fat biopsies were obtained intra-operatively. RNA was extracted and whole-genome expression profiling was performed. Gene Set Enrichment Analysis (GSEA) was used to identify curated gene sets that were differentially enriched in OSA subjects. Network analysis was applied to a select set of highly enriched pathways. Results: 10 patients with OSA and 8 control subjects were recruited. There were no differences in age, gender, body mass index between the two groups, but the OSA subjects had a significantly higher respiratory disturbance index (19.2 vs. 0.6, P-value 0.05) and worse hypoxemia (minimum oxygen saturation 79.7% vs. 87.8%, P-value < 0.001). GSEA identified a number of gene sets up-regulated in adipose tissue of OSA patients including the pro-inflammatory NF-κB pathway and the proteolytic ubiquitin/proteasome module. A critical metabolic pathway, the peroxisome proliferator-activated receptor (PPAR), was down-regulated in subjects with OSA. Network analysis linked members of these modules together and identified regulatory hubs. Conclusions: OSA is associated with alterations in visceral fat gene expression. Pathway-based network analysis highlighted perturbations in several key pathways whose coordinated interactions may contribute to the metabolic dysregulation observed in this complex disorder.
2012-09-01 | GSE38792 | GEO
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.
| S-EPMC5976202 | biostudies-literature
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.
| S-EPMC6733412 | biostudies-literature
Project description:Background: Obstructive sleep apnea (OSA) is prevalent in pregnancy and it is associated with adverse pregnancy-related outcomes such as gestational diabetes, pre-eclampsia, and low birth weight. Maternal systemic inflammation is proposed to be one of the main intermediate mechanisms. However, the effects of OSA on systemic inflammation are unknown in normal pregnancy. Methods: Women in the 3rd trimester underwent hospital polysomnography to evaluate whether OSA increases systemic inflammation in normal pregnancy and its potential association with adverse fetal outcomes. OSA was defined as an apnea-hypopnea index (AHI) of ≥ 5 h-1. Plasma cytokines levels (TNF-α, IL-1β, IL-6, IL-8, and IL-10) were determined by multiple immunoassays. Results: We included 11 patients with OSA and 22 women with AHI < 5 h-1, who were homogeneous in age, and body mass index (BMI). Women with OSA had significant higher levels of TNF-α, IL-1β, IL-8, and IL-10. We found significant correlations between AHI during REM and TNF-α (r = 0.40), IL-1β (r = 0.36), IL-6 (r = 0.52), IL-8 (r = 0.43), between obstructive apnea index and TNF-α (r = 0.46) and between AHI and IL-1β (r = 0.43). We also found that CT90% was related to IL-8 (r = 0.37). There were no significant differences in neonatal characteristics; however, we found inverse correlations between TNF-α and IL-8 with birth weight (both r = -0.48), while IL-8 showed a significant inverse relationship with neonatal gestational age (r = -0.48). Conclusions: OSA in our normal pregnancy population was associated with higher systemic inflammation, which was related to obstructive events, especially during REM sleep. Moreover, systemic inflammation was inversely correlated with neonatal birth weight and age.
| S-EPMC8593073 | biostudies-literature
Project description:ObjectiveObstructive sleep apnea (OSA) is common among bariatric surgery patients and is associated with perioperative risk. Preoperative screening is recommended, but some screening tools lack validation, and their relative performance is unclear in this population. The study objective was to compare the ability of four existing tools (STOP-BANG, NO-OSAS, No-Apnea, and the Epworth Sleepiness Scale [ESS]) to screen for moderate to severe OSA in a diverse bariatric cohort.MethodsData from patients presenting for first-time bariatric surgery who underwent a sleep study within 1 year of the initial encounter were retrospectively reviewed. Performance of the four tools for detecting moderate to severe OSA was compared based on the area under the receiver operating characteristic curves (AUC).ResultsOf the included 214 patients (83.2% female, median age 39 years), 45.3% had moderate to severe OSA. Based on AUC, STOP-BANG (0.75 [95% CI: 0.68-0.81], N = 185), NO-OSAS (0.76 [95% CI: 0.69-0.82], N = 185), and No-Apnea (0.69 [95% CI: 0.62-0.76], N = 190) had similar performance (P > 0.16). Compared with STOP-BANG and NO-OSAS, ESS (0.61 [95% CI: 0.54-0.68], N = 198) had a significantly lower AUC (P < 0.01). Hispanic/Latino self-identification, sex, or obesity class did not significantly modify test performance.ConclusionsSTOP-BANG and NO-OSAS may be preferable to No-Apnea and ESS when screening bariatric surgery patients for moderate to severe OSA. Efforts to screen bariatric patients for OSA are recommended.
| S-EPMC7760780 | biostudies-literature