Predictors of sleep-disordered breathing in pregnancy.

BACKGROUND: Sleep-disordered breathing (SDB) is common in pregnancy, but there are limited data on predictors. OBJECTIVES: The objective of this study was to develop predictive models of sleep-disordered breathing during pregnancy. STUDY DESIGN: Nulliparous women completed validated questionnaires to assess for symptoms related to snoring, fatigue, excessive daytime sleepiness, insomnia, and restless leg syndrome. The questionnaires included questions regarding the timing of sleep and sleep duration, work schedules (eg, shift work, night work), sleep positions, and previously diagnosed sleep disorders. Frequent snoring was defined as self-reported snoring ≥3 days per week. Participants underwent in-home portable sleep studies for sleep-disordered breathing assessment in early (6-15 weeks gestation) and mid pregnancy (22-31 weeks gestation). Sleep-disordered breathing was characterized by an apnea hypopnea index that included all apneas, plus hypopneas with ≥3% oxygen desaturation. For primary analyses, an apnea hypopnea index ≥5 events per hour was used to define sleep-disordered breathing. Odds ratios and 95% confidence intervals were calculated for predictor variables. Predictive ability of the logistic models was estimated with area under the receiver-operating-characteristic curves, along with sensitivities, specificities, and positive and negative predictive values and likelihood ratios. RESULTS: Among 3705 women who were enrolled, data were available for 3264 and 2512 women in early and mid pregnancy, respectively. The corresponding prevalence of sleep-disordered breathing was 3.6% and 8.3%, respectively. At each time point in gestation, frequent snoring, chronic hypertension, greater maternal age, body mass index, neck circumference, and systolic blood pressure were associated most strongly with an increased risk of sleep-disordered breathing. Logistic regression models that included current age, body mass index, and frequent snoring predicted sleep-disordered breathing in early pregnancy, sleep-disordered breathing in mid pregnancy, and new onset sleep-disordered breathing in mid pregnancy with 10-fold cross-validated area under the receiver-operating-characteristic curves of 0.870, 0.838, and 0.809. We provide a supplement with expanded tables, integrated predictiveness, classification curves, and an predicted probability calculator. CONCLUSION: Among nulliparous pregnant women, logistic regression models with just 3 variables (ie, age, body mass index, and frequent snoring) achieved good prediction of prevalent and incident sleep-disordered breathing. These results can help with screening for sleep-disordered breathing in the clinical setting and for future clinical treatment trials.

NuMoM2b Sleep-Disordered Breathing study: objectives and methods.

OBJECTIVE: The objective of the Sleep Disordered Breathing substudy of the Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-be (nuMoM2b) is to determine whether sleep disordered breathing during pregnancy is a risk factor for adverse pregnancy outcomes. STUDY DESIGN: NuMoM2b is a prospective cohort study of 10,037 nulliparous women with singleton gestations that was conducted across 8 sites with a central Data Coordinating and Analysis Center. The Sleep Disordered Breathing substudy recruited 3702 women from the cohort to undergo objective, overnight in-home assessments of sleep disordered breathing. A standardized level 3 home sleep test was performed between 6(0)-15(0) weeks' gestation (visit 1) and again between 22(0)-31(0) weeks' gestation (visit 3). Scoring of tests was conducted by a central Sleep Reading Center. Participants and their health care providers were notified if test results met "urgent referral" criteria that were based on threshold levels of apnea hypopnea indices, oxygen saturation levels, or electrocardiogram abnormalities but were not notified of test results otherwise. The primary pregnancy outcomes to be analyzed in relation to maternal sleep disordered breathing are preeclampsia, gestational hypertension, gestational diabetes mellitus, fetal growth restriction, and preterm birth. RESULTS: Objective data were obtained at visit 1 on 3261 women, which was 88.1% of the studies that were attempted and at visit 3 on 2511 women, which was 87.6% of the studies that were attempted. Basic characteristics of the substudy cohort are reported in this methods article. CONCLUSION: The substudy was designed to address important questions regarding the relationship of sleep-disordered breathing on the risk of preeclampsia and other outcomes of relevance to maternal and child health.

The National Sleep Research Resource: making data findable, accessible, interoperable, reusable and promoting sleep science.

This paper presents a comprehensive overview of the National Sleep Research Resource (NSRR), a National Heart Lung and Blood Institute-supported repository developed to share data from clinical studies focused on the evaluation of sleep disorders. The NSRR addresses challenges presented by the heterogeneity of sleep-related data, leveraging innovative strategies to optimize the quality and accessibility of available datasets. It provides authorized users with secure centralized access to a large quantity of sleep-related data including polysomnography, actigraphy, demographics, patient-reported outcomes, and other data. In developing the NSRR, we have implemented data processing protocols that ensure de-identification and compliance with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Heterogeneity stemming from intrinsic variation in the collection, annotation, definition, and interpretation of data has proven to be one of the primary obstacles to efficient sharing of datasets. Approaches employed by the NSRR to address this heterogeneity include (1) development of standardized sleep terminologies utilizing a compositional coding scheme, (2) specification of comprehensive metadata, (3) harmonization of commonly used variables, and (3) computational tools developed to standardize signal processing. We have also leveraged external resources to engineer a domain-specific approach to data harmonization. We describe the scope of data within the NSRR, its role in promoting sleep and circadian research through data sharing, and harmonization of large datasets and analytical tools. Finally, we identify opportunities for approaches for the field of sleep medicine to further support data standardization and sharing.

Preliminary Evaluation of an Order Template to Improve Diagnosis and Testosterone Therapy of Hypogonadism in Veterans.

BACKGROUND: Testosterone therapy is indicated for the treatment of hypogonadism. Evidence-based guidelines recommend testosterone treatment only for men with symptoms and signs of testosterone deficiency and consistently low serum testosterone concentrations; luteinizing hormone (LH) and follicle-stimulating hormone (FSH) measurements and discussion of risks and benefits of testosterone prior to therapy. However, the US Department of Veterans Affairs (VA) Office of the Inspector General (OIG) report found that health care providers were adhering poorly to guideline recommendations for the diagnosis and treatment of men with hypogonadism. METHODS: A prior authorization drug request (PADR) testosterone order template was implemented at VA Puget Sound Health Care System. A retrospective chart review was conducted in veterans who were prescribed testosterone and had no previous prescription in the prior year. Eligible veterans were evaluated 6 months before (pretemplate) and after (posttemplate) implementation of the template, and 3 months after removal of alternative testosterone ordering pathways (posttemplate/no alternative ordering pathways) that were discovered after PADR template implementation. We assessed the proportion of eligible veterans with documented symptoms of testosterone deficiency; appropriate diagnosis and evaluation of hypogonadism with ≥ 2 low serum testosterone and LH and FSH levels; and discussion of risks and benefits of testosterone treatment. RESULTS: In the pretemplate period, only 20 of 80 eligible veterans (25%) had a completed PADR for testosterone. In the posttemplate period, 18 of 45 (44%) eligible veterans had a completed PADR but only 7 (17%) had the testosterone order template completed. In the posttemplate/no alternative ordering pathways period, 13 (68%) and 11 (58%) of 19 eligible veterans had a completed PADR and testosterone order template, respectively. In all 3 periods, documentation of clinical symptoms and a discussion of risks and benefits were similar. In contrast, the proportion of veterans who had ≥ 2 low testosterone levels with LH and FSH levels measured in the posttemplate and posttemplate/no alternative ordering pathways periods were higher (41% and 37%, respectively) vs the pretemplate period (23%). Veterans with documented clinical symptoms, discussion of risks and benefits, and ≥ 2 low testosterone with gonadotropin measurements were 100%, 57%, and 71%, respectively, in the posttemplate/no alternative ordering pathways period. CONCLUSIONS: Implementation of a PADR order template may be a promising approach to improve the diagnosis of hypogonadism and appropriate testosterone therapy in accordance with established evidence-based clinical practice guidelines, particularly in veterans who are receiving new prescriptions.

Deploying Elemental Iodine in a Vapor Form to Disinfect Water and to Clear Biofilms.

Traditionally, iodine has been delivered as a solution, tablet or resin to disinfect water. In this study we evaluated the "I2 vapor infusion" (I2VP) technology which passes an airstream through a matrix containing elemental iodine (I2) to produce I2 vapor as an innovative method of iodine delivery for water disinfection. Pressured air was provided either by a compressor or hand pump. Testing was performed with water inoculated with either Gram-negative (Escherichia, Salmonella) or Gram-positive (Enterococcus) bacteria or with pre-formed Acinetobacter or Staphylococcus biofilms. Bacterial colony forming units were used to assess efficacy of the device. In distilled water all bacteria and biofilms were eliminated after brief exposures (<90 s). Culturable bacteria were also eliminated from pond and municipal sewer water, but the technology was mostly ineffective against dairy lagoon water with high turbidity and organic particulate. Longer duration infusion and higher air volumes used to overcome interference from organic matter were also associated with higher concentrations of residual iodine. We conclude that I2 vapor infusion has the potential to be useful for emergency water treatment and potentially for reducing microbiological contamination of some waste streams.

Population Health Management during Student Pharmacist Introductory Experiential Education to Expand Clinical Pharmacist Impact.

OBJECTIVE: To evaluate the impact of incorporating pre-advanced pharmacy practice experience (pre-APPE) student pharmacists into three different population health management (PHM) projects. METHODS: The prospective quality improvement projects incorporated three third-year student pharmacists who developed and conducted individual PHM projects over the course of three to seven months. The projects included hypoglycemia screening, hepatitis C virus and human immunodeficiency virus screening, and statin use evaluations for atherosclerotic cardiovascular disease risk reduction. Under the guidance of a clinical pharmacist, students developed project materials, conducted patient chart reviews, and contacted patients to make interventions such as recommendations for therapy, ambulatory patient monitoring, patient education, and arranging provider follow-up. Student impact was evaluated through the number of patients screened, the number of eligible patients contacted, and the total number of interventions or recommendations made. Student time spent was tracked throughout the projects. RESULTS: Out of 244 patients screened, 198 patients met inclusion criteria and 162 patients were contacted or assessed by a student pharmacist. Students made a total of 319 interventions, including patient education (132), patient monitoring (132), pharmacotherapy recommendations (28), and arranging follow-up (27). On average students screened 33 patients per month, and, per patient, required 8.6 minutes for eligibility assessment and approximately 6 minutes for telephone interviews. CONCLUSION: This report demonstrates that pre-APPE student pharmacists are well-equipped to design and implement PHM projects. Utilization of student pharmacists in similar PHM programs can expand the pharmacist's impact on patient care in the ambulatory care setting.

The National Sleep Research Resource: towards a sleep data commons.

Objective: The gold standard for diagnosing sleep disorders is polysomnography, which generates extensive data about biophysical changes occurring during sleep. We developed the National Sleep Research Resource (NSRR), a comprehensive system for sharing sleep data. The NSRR embodies elements of a data commons aimed at accelerating research to address critical questions about the impact of sleep disorders on important health outcomes. Approach: We used a metadata-guided approach, with a set of common sleep-specific terms enforcing uniform semantic interpretation of data elements across three main components: (1) annotated datasets; (2) user interfaces for accessing data; and (3) computational tools for the analysis of polysomnography recordings. We incorporated the process for managing dataset-specific data use agreements, evidence of Institutional Review Board review, and the corresponding access control in the NSRR web portal. The metadata-guided approach facilitates structural and semantic interoperability, ultimately leading to enhanced data reusability and scientific rigor. Results: The authors curated and deposited retrospective data from 10 large, NIH-funded sleep cohort studies, including several from the Trans-Omics for Precision Medicine (TOPMed) program, into the NSRR. The NSRR currently contains data on 26 808 subjects and 31 166 signal files in European Data Format. Launched in April 2014, over 3000 registered users have downloaded over 130 terabytes of data. Conclusions: The NSRR offers a use case and an example for creating a full-fledged data commons. It provides a single point of access to analysis-ready physiological signals from polysomnography obtained from multiple sources, and a wide variety of clinical data to facilitate sleep research.

Effect of Manual Editing of Total Recording Time: Implications for Home Sleep Apnea Testing.

STUDY OBJECTIVES: Type 3 home sleep apnea tests may underestimate the apnea-hypopnea index (AHI) due to overestimation of total sleep time (TST). We aimed to evaluate the effect of manual editing of the total recording time (TRT) on the TST and AHI. METHODS: Thirty 15-channel in-home polysomnography studies (AHI 0 to 30 events/h) scored using American Academy of Sleep Medicine criteria were rescored by two blinded polysomnologists after data from electroencephalogram, electrooculogram, and electromyogram were masked. In method 1, periods of probable wakefulness and artifact were manually edited and removed from analysis. Method 2 identified TST as the TRT without manual editing. Paired t-tests were used to compare the TST and AHI between these methods. Sensitivity and specificity of each method were calculated for gold standard AHI cutoffs of ≥ 5 and ≥ 15 events/h. RESULTS: TST (mean [standard deviation, SD]) by polysomnography, method 1, and method 2 was 366.0 (70.1), 447.1 (59.0), and 542 (61.9) min, respectively. The corresponding AHI was 12.5 (8.2), 10.8 (7.0), and 9.1 (6.1) events/h, respectively. Compared to polysomnography, both alternative methods overestimated the TST (method 1: mean difference [SD] 81.1 [56.1] min, method 2: 176.0 [89.7] min; both p < 0.001) and underestimated the AHI (method 1: mean difference [SD] -1.6 [3.3], method 2: -3.3 [3.9]; both p < 0.001). The sensitivity was 100% and 70.0% for method 1, and 91.3% and 40.0% for method 2 for identifying sleep-disordered breathing using AHI cutoffs of ≥ 5 and ≥ 15 events/h, respectively. CONCLUSIONS: Manual editing of TRT reduces the overestimation of TST and improves the sensitivity for identifying studies with sleep-disordered breathing. COMMENTARY: A commentary on this article appears in this issue on page 9.

Association Between Sleep-Disordered Breathing and Hypertensive Disorders of Pregnancy and Gestational Diabetes Mellitus.

OBJECTIVE: To estimate whether sleep-disordered breathing during pregnancy is a risk factor for the development of hypertensive disorders of pregnancy and gestational diabetes mellitus (GDM). METHODS: In this prospective cohort study, nulliparous women underwent in-home sleep-disordered breathing assessments in early (6-15 weeks of gestation) and midpregnancy (22-31 weeks of gestation). Participants and health care providers were blinded to the sleep test results. An apnea-hypopnea index of 5 or greater was used to define sleep-disordered breathing. Exposure-response relationships were examined, grouping participants into four apnea-hypopnea index groups: 0, greater than 0 to less than 5, 5 to less than 15, and 15 or greater. The study was powered to test the primary hypothesis that sleep-disordered breathing occurring in pregnancy is associated with an increased incidence of preeclampsia. Secondary outcomes were rates of hypertensive disorders of pregnancy, defined as preeclampsia and antepartum gestational hypertension, and GDM. Crude and adjusted odds ratios and 95% confidence intervals (CIs) were calculated from univariate and multivariate logistic regression models. RESULTS: Three thousand seven hundred five women were enrolled. Apnea-hypopnea index data were available for 3,132 (84.5%) and 2,474 (66.8%) women in early and midpregnancy, respectively. The corresponding prevalence of sleep-disordered breathing was 3.6% and 8.3%. The prevalence of preeclampsia was 6.0%, hypertensive disorders of pregnancy 13.1%, and GDM 4.1%. In early and midpregnancy the adjusted odds ratios for preeclampsia when sleep-disordered breathing was present were 1.94 (95% CI 1.07-3.51) and 1.95 (95% CI 1.18-3.23), respectively; hypertensive disorders of pregnancy 1.46 (95% CI 0.91-2.32) and 1.73 (95% CI 1.19-2.52); and GDM 3.47 (95% CI 1.95-6.19) and 2.79 (95% CI 1.63-4.77). Increasing exposure-response relationships were observed between apnea-hypopnea index and both hypertensive disorders and GDM. CONCLUSION: There is an independent association between sleep-disordered breathing and preeclampsia, hypertensive disorders of pregnancy, and GDM.

Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource.

ABSTRACT: Professional sleep societies have identified a need for strategic research in multiple areas that may benefit from access to and aggregation of large, multidimensional datasets. Technological advances provide opportunities to extract and analyze physiological signals and other biomedical information from datasets of unprecedented size, heterogeneity, and complexity. The National Institutes of Health has implemented a Big Data to Knowledge (BD2K) initiative that aims to develop and disseminate state of the art big data access tools and analytical methods. The National Sleep Research Resource (NSRR) is a new National Heart, Lung, and Blood Institute resource designed to provide big data resources to the sleep research community. The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization. Each deidentified study record minimally includes the summary results of an overnight sleep study; annotation files with scored events; the raw physiological signals from the sleep record; and available clinical and physiological data. NSRR is designed to be interoperable with other public data resources such as the Biologic Specimen and Data Repository Information Coordinating Center Demographics (BioLINCC) data and analyzed with methods provided by the Research Resource for Complex Physiological Signals (PhysioNet). This article reviews the key objectives, challenges and operational solutions to addressing big data opportunities for sleep research in the context of the national sleep research agenda. It provides information to facilitate further interactions of the user community with NSRR, a community resource.

Prevalence and associations of respiratory-related leg movements: the MrOS sleep study.

OBJECTIVES: Obstructive respiratory events often terminate with an associated respiratory-related leg movement (RRLM). Such leg movements are not scored as periodic leg movements (periodic limb movements during sleep, PLMS), although the criteria for distinguishing RRLM from PLMS differ between the American Academy of Sleep Medicine (AASM) and the World Association of Sleep Medicine (WASM)/ International Restless Legs Syndrome Study Group (IRLSSG) scoring manuals. Such LMs may be clinically significant in patients with obstructive sleep apnea (OSA). The prevalence and correlation of RRLM in men with OSA were examined. METHODS: A case-control sample of 575 men was selected from all men with an apnea-hypopnea index (AHI, ≥3% desaturation criteria) ≥ 10 and good data from piezoelectric leg movement sensors at the first in-home sleep study in the MrOS cohort (mean age = 76.8 years). Sleep studies were rescored for RRLMs using five different RRLM definitions varying in both latency of leg movement onset from respiratory event termination and duration of the leg movement. The quartile of RRLM% (the number of RRLM/the number of hypopneas + apneas) was derived. RESULTS: The nonparametric densities of RRLM% were most influenced by alterations in the latency rather than the duration of the LM. The most liberal RRLM definition (latency 0-5 s, duration 0.5-10 s) led to a median RRLM% of 23.4 (interquartile range 12.41, 37.12) in this sample. The average AHI and arousal index increased as the quartile of RRLM% increased, as well as the prevalence of chronic obstructive pulmonary disease (COPD). The prevalence of those with a history of hypertension decreased as RRLM% increased. The non-Caucasian race was associated with lower RRLM%. CONCLUSION: Within an elderly sample with moderate to severe OSA, piezoelectric-defined RRLM% is associated with a number of sleep-related and demographic factors. Further study of the optimal definition, predictors, and consequences of RRLM is warranted.