Electrocardiogram breathing: A study of electrocardiogram derived respiration plus multiresolution wavelet analysis of heartbeat interval variability in sleep study patients

This dissertation presents a unique research opportunity by using recordings which provide electrocardiogram (ECG) plus a reference breathing signal (RBS). ECG derived breathing (EDR) is measured and correlated against RBS. Standard deviations of multiresolution wavelet analysis coefficients (SDMW) are obtained from heart rate and classified using RBS. Prior works by others used select patients for sleep apnea scoring with EDR but no RBS. Another prior work classified select heart disease patients with SDMW but no RBS. This study used randomly chosen sleep disorder patient recordings; central and obstructive apneas, with and without heart disease.^ Implementation required creating an application because existing systems were limited in power and scope. A review survey was created to choose a development environment. The survey is presented as a learning tool and teaching resource. Development objectives were rapid development using limited resources (manpower and money). Open Source resources were used exclusively for implementation. ^ Results show: (1) Three groups of patients exist in the study. Grouping RBS correlations shows a response with either ECG interval or amplitude variation. A third group exists where neither ECG intervals nor amplitude variation correlate with breathing. (2) Previous work done by other groups analyzed SDMW. Similar results were found in this study but some subjects had higher SDMW, attributed to a large number of apneas, arousals and/or disconnects. SDMW does not need RBS to show apneic conditions exist within ECG recordings. (3) Results in this study support the assertion that autonomic nervous system variation was measured with SDMW. Measurements using RBS are not corrupted due to breathing even though respiration overlaps the same frequency band.^ Overall, this work becomes an Open Source resource which can be reused, modified and/or expanded. It might fast track additional research. In the future the system could also be used for public domain data. Prerecorded data exist in similar formats in public databases which could provide additional research opportunities. ^

A comparison of breathing patterns of normal full term infants in supine versus right side-lying during quiet and active behavioral sleep states

This study investigated the effect of sleep position on breathing patterns of normal full term infants during quiet and active behavioral sleep states. Tidal volume, percent contribution of rib cage to tidal volume, and respiration rate were measured via respiratory inductive plethysmography (RIP) and pneumotachograph (PNT) in ten infants sleeping in supine versus right side-lying. Data was collected immediately following two consecutive feedings. Paired t tests and ANOVA comparisons showed no significant differences between the two postures (p $<$.05) in mean tidal volume (supine, M = 19.16, right side, M = 22.45), percent contribution of rib cage to tidal volume (supine, M = 30.55, right side M = 33.20), or respiration rate (supine, M = 49.13, right side, M = 49.37) during quiet sleep. Comparisons also showed no significant differences between the two postures (p $<$.05) in mean tidal volume (supine, M = 18.89, right side, M = 20.12), percent contribution of rib cage to tidal volume (supine, M = 6.43, right side, M = 6.97) or respiration rate (supine, M = 62.18, right side, M = 61.04) during active sleep. Therefore, no differences were found in the three respiratory variables measured between the supine and right side-lying positions. These findings suggest that infants may be positioned in either sleep position without detriment to respiratory function. This information may benefit occupational therapists and other health professionals involved in the education of parents on infant positioning and their respective advantages. ^

An Analytical Workflow for Metagenomic Data and its Application to the Study of Chronic Obstructive Pulmonary Disease (COPD)

Metagenomics is the culture-independent study of genetic material obtained directly from environmental samples. It has become a realistic approach to understanding microbial communities thanks to advances in high-throughput DNA sequencing technologies over the past decade. Current research has shown that different sites of the human body house varied bacterial communities. There is a strong correlation between an individual’s microbial community profile at a given site and disease. Metagenomics is being applied more often as a means of comparing microbial profiles in biomedical studies. The analysis of the data collected using metagenomics can be quite challenging and there exist a plethora of tools for interpreting the results. An automatic analytical workflow for metagenomic analyses has been implemented and tested using synthetic datasets of varying quality. It is able to accurately classify bacteria by taxa and correctly estimate the richness and diversity of each set. The workflow was then applied to the study of the airways microbiome in Chronic Obstructive Pulmonary Disease (COPD). COPD is a progressive lung disease resulting in narrowing of the airways and restricted airflow. Despite being the third leading cause of death in the United States, little is known about the differences in the lung microbial community profiles of healthy individuals and COPD patients. Bronchoalveolar lavage (BAL) samples were collected from COPD patients, active or ex-smokers, and never smokers and sequenced by 454 pyrosequencing. A total of 56 individuals were recruited for the study. Substantial colonization of the lungs was found in all subjects and differentially abundant genera in each group were identified. These discoveries are promising and may further our understanding of how the structure of the lung microbiome is modified as COPD progresses. It is also anticipated that the results will eventually lead to improved treatments for COPD.

Caffeine Intake and its Association with Disease Progression, Sleep Quality and Anxiety Symptoms and Nutritional Alterations in People Living with HIV in the Miami Adult Studies on HIV Cohort

Miami-Dade County has approximately 27,000 people living with HIV (PLWH), and the highest HIV incidence in the nation. PLWH have reported several types of sleep disturbances. Caffeine is an anorexic and lipolytic stimulant that may adversely affect sleep patterns, dietary intakes and body composition. High caffeine consumption (>250 mg. per day or the equivalent of >4 cups of brewed coffee) may also affect general functionality, adherence to antiretroviral treatment (ART) and HIV care. This study assess the relationship of high caffeine intake with markers of disease progression, sleep quality, insomnia, anxiety, nutritional intakes and body composition. A convenience sample of 130 PLWH on stable ART were recruited from the Miami Adult Studies on HIV (MASH) cohort, and followed for three months. After consenting, questionnaires on Modified Caffeine Consumption (MCCQ), Pittsburg Insomnia Rating Scale (PIRS), Pittsburg Sleep Quality Index (PSQI), Generalized Anxiety Disorder-7 (GAD-7), socio-demographics, drug and medication use were completed. CD4 count, HIV viral load, anthropometries, and body composition measures were obtained. Mean age was 47.89±6.37 years, 60.8% were male and 75.4% were African-Americans. Mean caffeine intake at baseline was 337.63 ± 304.97 mg/day (Range: 0-1498 mg/day) and did not change significantly at 3 months. In linear regression, high caffeine consumption was associated with higher CD4 cell count (β=1.532, P=0.049), lower HIV viral load (β=-1.067, P=0.048), higher global PIRS (β=1.776, P=0.046), global PSQI (β=2.587, P=0.038), and GAD-7 scores (β=1.674, P=0.027), and with lower fat mass (β=-0.994, P=0.042), energy intakes (β=-1.643, P=0.042) and fat consumption (β=-1.902, P=0.044), adjusting for relevant socioeconomic and disease progression variables. Over three months, these associations remained significant. The association of high caffeine with lower BMI weakened when excluding users of other anorexic and stimulant drugs such as cocaine and methamphetamine, suggesting that caffeine in combination, but not alone, may worsen their action. In summary, high caffeine consumption was associated with better measures of disease progression; but was also detrimental on sleep quality, nutritional intakes, BMI and body composition and associated with insomnia and anxiety. Large scale studies for longer time are needed to elucidate the contribution of caffeine to the well-being of PLWH.