Model-Derived Markers of Autonomic Cardiovascular Dysfunction in Sleep-Disordered Breathing.
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ABSTRACT:
SUBMITTER: Khoo MCK
PROVIDER: S-EPMC5270554 | biostudies-other | 2016 Dec
REPOSITORIES: biostudies-other
Publications
Model-Derived Markers of Autonomic Cardiovascular Dysfunction in Sleep-Disordered Breathing.
Khoo Michael C K MCK Chalacheva Patjanaporn P
Sleep medicine clinics 20161027 4
Evidence indicates that sleep-disordered breathing leads to elevated sympathetic tone and impaired vagal activity, promoting hypertension and cardiometabolic disease. Low-cost but accurate monitoring of autonomic function is useful for the aggressive management of sleep apnea. This article reviews the development and application of multivariate dynamic biophysical models that enable the causal dependencies among respiration, blood pressure, heart rate variability, and peripheral vascular resista ...[more]
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Project description:(1) Purpose: this study proposes a method of prediction of cardiovascular diseases (CVDs) that can develop within ten years in patients with sleep-disordered breathing (SDB). (2) Methods: For the design and evaluation of the algorithm, the Sleep Heart Health Study (SHHS) data from the 3367 participants were divided into a training set, validation set, and test set in the ratio of 5:3:2. From the data during a baseline period when patients did not have any CVD, we extracted 18 features from electrography (ECG) based on signal processing methods, 30 ECG features based on artificial intelligence (AI), ten clinical risk factors for CVD. We trained the model and evaluated it by using CVD outcomes result, monitored in follow-ups. The optimal feature vectors were selected through statistical analysis and support vector machine recursive feature elimination (SVM-RFE) of the extracted feature vectors. Features based on AI, a novel proposal from this study, showed excellent performance out of all selected feature vectors. In addition, new parameters based on AI were possibly meaningful predictors for CVD, when used in addition to the predictors for CVD that are already known. The selected features were used as inputs to the prediction model based on SVM for CVD, determining the development of CVD-free, coronary heart disease (CHD), heart failure (HF), or stroke within ten years. (3) Results: As a result, the respective recall and precision values were 82.9% and 87.5% for CVD-free; 71.9% and 63.8% for CVD; 57.2% and 55.4% for CHD; 52.6% and 40.8% for HF; 52.4% and 44.6% for stroke. The F1-score between CVD and CVD-free was 76.5%, and it was 59.1% in class four. (4) Conclusion: In conclusion, our results confirm the excellence of the prediction model for CVD in patients with SDB and verify the possibility of prediction within ten years of the CVDs that may occur in patients with SDB.
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Project description:RationaleEpidemiologic studies on the consequences of sleep-disordered breathing invariably use the apnea-hypopnea index as the primary measure of disease severity. Although hypopneas constitute a majority of disordered breathing events, significant controversy remains about the best criteria used to define these events.ObjectivesThe current investigation sought to assess the most appropriate definition for hypopneas that would be best correlated with cardiovascular disease.MethodsA community sample of middle-aged and older adults was recruited as part of the Sleep Heart Health Study. Full-montage polysomnography was conducted and hypopneas were defined using different thresholds of oxyhemoglobin desaturation with and without arousals. Prevalent cardiovascular disease was assessed based on self-report. Logistic regression analysis was used to characterize the independent association between the hypopnea index and prevalent cardiovascular disease.Measurements and main resultsUsing a sample of 6,106 adults with complete data on cardiovascular disease status and polysomnography, the current study found that hypopneas associated with an oxyhemoglobin desaturation of 4% or more were associated with prevalent cardiovascular disease independent of confounding covariates. The adjusted prevalent odds ratios for quartiles of the hypopnea index using a 4% desaturation criterion were as follows: 1.00 (<1.10 events/h), 1.10 (1.01-3.20 events/h), 1.33 (3.21-7.69 events/h), and 1.41 (>7.69 events/h). Hypopnea measures based on less than 4% oxyhemoglobin desaturation or presence of arousals showed no association with cardiovascular disease.ConclusionsHypopneas comprise a significant component of sleep-disordered breathing in the general community. By varying the criteria for defining hypopneas, this study demonstrates that hypopneas with a desaturation of at least 4% are independently associated with cardiovascular disease. In contrast, no association was observed between cardiovascular disease and hypopneas associated with milder desaturations or arousals.
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Project description:Academic success involves the ability to use cognitive skills in a school environment. Poor academic performance has been linked to disrupted sleep associated with sleep-disordered breathing (SDB). In parallel, poor sleep is associated with increased risk for obesity, and weight management problems have been linked to executive dysfunction, suggesting that interactions may be operational between SDB and obesity to adversely affect neurocognitive outcomes.To test whether mediator relationships exist between body weight, SDB, and cognition.Structural equation modeling was conducted on data from 351 children in a community-based cohort assessed with the core subtests of the Differential Abilities Scales after an overnight polysomnogram. Body mass index, apnea-hypopnea index, and cognitive abilities were modeled as latent constructs.In a sample of predominantly white children 6 to 10 years of age, SDB amplified the adverse cognitive and weight outcomes by 0.55- to 0.46-fold, respectively. Weight amplified the risk by 0.39- to 0.40-fold for SDB and cognitive outcomes, respectively. Poor ability to perform complex mental processing functions increased the risk of adverse weight and SDB outcomes by 2.9- and 7.9-fold, respectively.Cognitive functioning in children is adversely affected by frequent health-related problems, such as obesity and SDB. Furthermore, poorer integrative mental processing may place a child at a bigger risk for adverse health outcomes.
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Project description:There are limited data on the effect of bronchopulmonary dysplasia (BPD) on sleep disordered breathing (SDB). We hypothesized that both the severity of prematurity and BPD would increase the likelihood of SDB in early childhood. Our secondary aim was to evaluate the association of demographic factors on the development of SDB.This is a retrospective study of patient factors and overnight polysomnogram (PSG) data of children enrolled in our BPD registry between 2008 and 2015. Association between PSG results and studied variables was assessed using multiple linear regression analysis.One-hundred-forty children underwent at least one sleep study on room air. The mean respiratory disturbance index (RDI) was elevated at 9.9 events/hr (SD: 10.1). The mean obstructive apnea-hypopnea index (OAHI) was 6.5 (9.1) events/hr and the mean central event rate of 3.0 (3.7) events/hr. RDI had decreased by 22% or 1.5 events/hour (95%CI: 0.6, 1.9) with each year of age (P?=?0.005). Subjects with more severe respiratory disease had 38% more central events (P?=?0.02). Infants exposed to secondhand smoke had 2.4% lower (P?=?0.04) oxygen saturation nadirs and a pattern for more desaturation events. Non-white subjects were found to have 33% higher OAHI (P?=?0.05), while white subjects had a 61% higher rate of central events (P?<?0.001).RDI was elevated in a selected BPD population compared to norms for non-preterm children. BPD severity, smoke exposure, and race may augment the severity of SDB. RDI improved with age but was still elevated by age 4, suggesting that this population is at risk for the sequelae of SDB.
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