Defining Age-related OSA Features in Robin Sequence Using Polysomnographic-based Analyses of Respiratory Arousal Responses and Gas-exchange Parameters.

INTRODUCTION: Robin sequence (RS) is a leading cause of obstructive sleep apnea (OSA) in newborns. Most studies have focused on understanding anatomic factors leading to OSA and changes in apnea-hypopnea index (AHI) on polysomnography (PSG) beyond the neonatal period. This study aims to define age-related OSA features between patients with RS, without RS and healthy controls using PSG-based analyses of respiratory arousal responses and gas-exchange parameters. DESIGN: Retrospective comparison of PSG features in a total of 48 children encompassing three groups: (a) infants with RS (n = 24, <1-year old), (b) non-RS older children (1-2 years old) with severe OSA (obstructive AHI (OAHI) of ≥10 events; n = 12), and (c) control infants and children (0-2 years old) without sleep apnea (OAHI ≤1.5/h, n = 12). We examined OSA sleep-stage specific and position-specific indexes, and the relationship between OSA severity and respiratory arousal indexes (OAHI/respiratory arousal indexes). RESULTS: OSA sleep-stage specific indexes (rapid eye movement [REM] vs non-REM[NREM]) as well as position-specific indexes (supine vs nonsupine) were similar in individuals with and without RS. Relative to the non-RS groups, infants with RS have more sustained hypoxemia (time with SpO2 < 90%) and reduced arousal responses to OSA demonstrated by higher OAHI/respiratory arousal indexes. OAHI/respiratory arousal indexes significantly correlated with the severity of hypoxemia in infants with RS. CONCLUSION: Infants with RS and OSA show reduced arousal responses to apneic events, which correlates with higher hypoxemia severity. OAHI/respiratory arousal indexes in RS may identify high-risk individuals with upper airway obstruction and reduced arousal protective responses.

Defining the patterns of PAP adherence in pediatric obstructive sleep apnea: a clustering analysis using real-world data.

STUDY OBJECTIVES: The implementation of positive airway pressure (PAP) therapy to treat obstructive sleep apnea in children is a complex process. PAP therapy data are highly heterogeneous in pediatrics, and the clinical management cannot be generalized. We hypothesize that pediatric PAP users can be subgrouped via clustering analysis to guide tailored interventions. METHODS: PAP therapy data for 250 children with obstructive sleep apnea were retrospectively examined using unsupervised hierarchical cluster analysis based on (1) PAP tolerance (average hours on days used) and (2) consistency of PAP use (percentage of days used). Clinical features in each cluster were defined, and a tree decision analysis was generated for clinical implementation. RESULTS: We were able to subclassify all 250 children (median age = 11.5 years) into five clusters: A (13.6%), B (29.6%), C (17.6%), D (16.4%), and E (22.8%). The clusters showed significant differences in PAP use patterns (Kruskal-Wallis P value < 1e-16). The most consistent PAP use patterns were seen in clusters A, B, and C. Major differences across clusters included the prevalence of obesity, PAP setting, developmental delay, and adenotonsillectomy. We also identified important differences in mask acceptance, OSA severity, and individual responses to PAP therapy based on objective apnea-hypopnea reductions in PAP downloads. CONCLUSIONS: A simple method to subset PAP use patterns in children can be implemented by analyzing cloud-based PAP therapy data. This novel approach may contribute to optimization of PAP therapy in children of all ages based on real-world evidence at the individual level.

Central breathing abnormalities in children with trisomy 21: Effect of age, sex, and concomitant OSA.

BACKGROUND: Trisomy 21 (TS21) is a condition with a high risk for sleep apnea. In the pediatric population, the risk also includes central breathing disorders. The aim of this study was to define the clinical and polysomnographic characteristics of central apnea in infants, children, and adolescents with TS21. METHODS: Retrospective review of baseline polysomnograms (PSGs) in children with TS21 in the sleep center at Children's National Medical Center in Washington DC. RESULTS: We included a total of 158 infants, children, and adolescents (0-18 years) with TS21 in this study. The median age was 4.82 years and 62% were male. The primary findings of the study are that (1) 12% of all pediatric subjects with TS21 included had a central apnea index (CAI) > 2/h; (2) the proportion of TS21 individuals with central breathing abnormalities progressively decreased with age being common in young individuals (≤2 years of age) but rare after 10 years of age; (3) additional sleep breathing disturbances (e.g., OSA and/or hypoxemia) are often present in children with TS21 and central apnea; and (4) the prevalence of central breathing abnormalities in TS21 is influenced by sex, being more likely to persist beyond early childhood (>2 years of age) in females than in males. CONCLUSION: Central breathing abnormalities are common in TS21 among young children (≤2 years of age) and in females older than 2 years of age. Central apnea is often associated with concomitant obstructive sleep apnea and/or hypoxemia in children with TS21.

Characteristics of hypertension in premature infants with and without chronic lung disease: a long-term multi-center study.

BACKGROUND: Many causes for neonatal hypertension in premature infants have been described; however in some cases no etiology can be attributed. Our objectives are to describe such cases of unexplained hypertension and to compare hypertensive infants with and without chronic lung disease (CLD). METHODS: We reviewed all cases of hypertension in premature infants referred from 18 hospitals over 16 years. Inclusion criteria were hypertension occurring at <6 months of age and birth at <37 weeks gestation; the main exclusion criterion was known secondary hypertension. Continuous variables were compared using analysis of variance. Nominal variables were compared using chi-square tests. RESULTS: A total of 97 infants met the inclusion criteria, of whom 37 had CLD. Among these infants, hypertension presented at a mean of 11.3 ± 3.2 chronological weeks of age and a postmenstrual age of 39.6 ± 3.6 weeks. Diagnostic testing was notable for plasma renin activity (PRA) being <11 ng/mL/h in 98% of hypertensive infants. Spironolactone was effective monotherapy in 51 of 56 cases of hypertension. Hypertension resolved in all infants, with an average treatment duration of 25 weeks. Significant differences between the two groups of infants were a 0.4 kg lower birthweight and a 2.5 weeks younger gestational age at birth in those with CLD (p < 0.01, p < 0.01, respectively). Hypertension presented in those with CLD 1.8 weeks later, but at the same postmenstrual age as those without CLD (p < 0.01, p = 0.45, respectively). CONCLUSION: Premature infants with unexplained hypertension, with and without CLD, presented at a postmenstrual age of 40 weeks with low PRA, transient time course, and a favorable response to spironolactone treatment.

MAROS: a decision support system for optimizing monitoring plans.

The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.

Groundwater monitoring plans at small-scale sites--an innovative spatial and temporal methodology.

An innovative methodology for improving existing groundwater monitoring plans at small-scale sites is presented. The methodology consists of three stand-alone methods: a spatial redundancy reduction method, a well-siting method for adding new sampling locations, and a sampling frequency determination method. The spatial redundancy reduction method eliminates redundant wells through an optimization process that minimizes the errors in plume delineation and the average plume concentration estimation. The well-siting method locates possible new sampling points for an inadequately delineated plume via regression analysis of plume centerline concentrations and estimation of plume dispersivity values. The sampling frequency determination method recommends the future frequency of sampling for each sampling location based on the direction, magnitude, and uncertainty of the concentration trend derived from representative historical concentration data. Although the methodology is designed for small-scale sites, it can be easily adopted for large-scale site applications. The proposed methodology is applied to a small petroleum hydrocarbon-contaminated site with a network of 12 monitoring wells to demonstrate its effectiveness and validity.