A systematic review and meta-analysis of diabetes disease management programs

Context. Despite the rapid growth of disease management programs, there are still questions about their efficacy and effectiveness for improving patient outcomes and their ability to reduce costs associated with chronic disease. ^ Objective. To determine the effectiveness of disease management programs on improving the results of HbA1c tests, lipid profiles and systolic blood pressure (SBP) readings among diabetics. These three quantitative measures are widely accepted methods of determining the quality of a patient's diabetes management and the potential for future complications. ^ Data Sources. MEDLINE and CINAHL were searched from 1950 to June 2008 using MeSH terms designed to capture all relevant studies. Scopus pearling and hand searching were also done. Only English language articles were selected. ^ Study Selection. Titles and abstracts for the 2347 articles were screened against predetermined inclusion and exclusion criteria, yielding 217 articles for full screening. After full article screening, 29 studies were selected for inclusion in the review. ^ Data Extraction. From the selected studies, data extraction included sample size, mean change over baseline, and standard deviation for each control and experimental arm. ^ Results. The pooled results show a mean HbA1c reduction of 0.64%, 95% CI (-0.83 to -0.44), mean SBP reduction of 7.39 mmHg (95% CI to -11.58 to -3.2), mean total cholesterol reduction of 5.74 mg/dL (95% CI, -10.01 to -1.43), and mean LDL cholesterol reduction of 3.74 mg/dL (95% CI, -8.34 to 0.87). Results for HbA1c, SBP and total cholesterol were statistically significant, while the results for LDL cholesterol were not. ^ Conclusions. The findings suggest that disease management programs utilizing five hallmarks of care can be effective at improving intermediate outcomes among diabetics. However, given the significant heterogeneity present, there may be fundamental differences with respect to study-specific interventions and populations that render them inappropriate for meta-analysis. ^

Epidemiologic and methodological issues in serial measurements of blood pressure: The blood pressure study in Mexican children

The Blood Pressure Study in Mexican Children (BPSMC) is a short term longitudinal study of serial blood pressure collected in three observation periods by standardized examinations of 233 female children, 10 to 12 years of age, enrolled in public and private primary schools in Tlalpan, Mexico. Study objectives were: (1) to describe from baseline information the distribution and relationship of blood pressure to age and selected anthropometric factors, as well as to compare the BPSMC results with other blood pressure studies, (2) to examine the sources and amount of variation present in serial blood pressure of 123 children, and (3) to evaluate observer performance by means of intra- and inter-observer variability.^ Stepwise regression results from baseline revealed that of all anthropometric factors and age, weight was the best predictor for blood pressure.^ The results of serial blood pressure measurements show that, besides the known sources of blood pressure variability (subject, day, reading), the physiologic event of menarche has an important bearing upon the variability and characterization of blood pressure in young girls. The assessment of the effects of blood pressure variability and reliability upon the design and analysis of epidemiologic studies, became apparent among post-menarcheal girls; where blood pressure measurements taken from them have low reliability. Research is needed to propose alternatives for assessing blood pressure during puberty.^ Finally, observer performance of blood pressure and anthropometry were evaluated. Anthropometric measurements had reliabilities in excess of R = 0.96. Acceptable reliabilities (R = 0.88 to 0.95) were obtained for systolic and diastolic (phase 4 and 5) blood pressures. The BPSMC showed a 50 percent decrease in measurement error from the first to the third observation periods. ^

FEMALE SEXUAL MATURATION AND BLOOD PRESSURE (SECONDARY-SEX CHARACTERISTICS, GROWTH, DEVELOPMENT)

This study described the relationship of sexual maturation and blood pressure in a sample (n = 361) of white females, ages seven through 18, attending public schools in a defined area of Central Texas during October through December, 1984. Other correlates of blood pressure were also described for this sample.^ A survey was performed to obtain the data on height, weight, body mass, pulse rate, upper arm circumference and length, and blood pressure. Each subject self-assessed her secondary sex characteristics (breast and pubic hair) according to drawings of the Tanner stages of maturation. The subjects were interviewed to obtain data on personal health habits and menstrual status. Student age, ethnic group and place of residence were abstracted from school records. Parents or guardians of the subjects responded to a questionnaire pertaining to parental and subject health history and parents' occupation and educational attainment.^ In the simple linear regression analysis, sexual maturation and variables of body size were significantly (p < 0.001) and positively associated with systolic and fourth- and fifth-phase diastolic blood pressure. The demographic and socioeconomic variables were not sufficiently variant in this population to have differential effects on the relation between blood pressure and maturation. Stepwise multiple regression was used to assess the contribution of sexual maturation to the variance of blood pressure after accounting for the variables of body size. Sexual maturation (breast stage) along with weight, height and body mass remained in the multiple regression models for fourth- and fifth-phase diastolic blood pressure. Only height and body mass remained in the regression model for systolic blood pressure; sexual maturation did not contribute more to the explanation of the systolic blood pressure variance.^ The association of sexual maturation with blood pressure level was established in this sample of young white females. More research is needed first, to determine if this relationship prevails in other populations of young females, and second, to determine the relationship of sexual maturation sequence and change with the change of blood pressure during childhood and adolescence. ^

BLOOD PRESSURE CHANGES IN RELATION TO DEMOGRAPHIC, ANTHROPOMETRIC, AND SEXUAL MATURATION VARIABLES IN U.S. HEALTH EXAMINATION SURVEY OF CHILDREN AND YOUTHS (UNITED STATES)

The determinants of change in blood pressure during childhood and adolescence were studied in a cohort of U.S. national probability sample of 2146 children examined on two occasions during the Health Examination Survey. Significant negative correlations between the initial level and the subsequent changes in blood pressure were observed. The multiple regression analyses showed that the major determinants of systolic blood pressure (SBP) change were change in weight, baseline SBP, and baseline upper arm girth. Race, time interval between examinations, baseline age, and height change were also significant determinants in SBP change. For the change in diastolic blood pressure (DBP), baseline DBP, baseline weight, and weight change were the major determinants. Baseline SBP, time interval and race were also significant determinants. Sexual maturation variables were also considered in the subgroup analysis for girls. Weight change was the most important predictor of the change in SBP for the group of girls who were still in the pre-menarchal or pre-breast maturation status at the time of the follow-up examination, and who had started to menstruate or to develop breast maturation at sometime between the two examinations. Baseline triceps skinfold thickness or initial SBP were more important variables than weight change for the group of girls who had already experienced menarche or breast maturation at the time of the initial survey. For the total group, pubic hair maturation was found to be a significant predictor of SBP change at the 5% significance level. The importance of weight change and baseline weight for the changes in blood pressure warrants further study. ^

Descriptive analysis of Ben Taub Pediatric Weight Management Program

The purpose of this study is to descriptively analyze the current program at Ben Taub Pediatric Weight Management Program in Houston, Texas, a program designed to help overweight children ages three to eighteen to lose weight. In Texas, approximately one in every three children is overweight or obese. Obesity is seen at an even greater level within Ben Taub due to the hospital's high rate of service for underserved minority populations (Dehghan et al, 2005; Tyler and Horner, 2008; Hunt, 2009). The weight management program consists of nutritional, behavioral, physical activity, and medical counseling. Analysis will focus on changes in weight, BMI, cholesterol levels, and blood pressure from 2007–2010 for all participants who attended at least two weight management sessions. Recommendations will be given in response to the results of the data analysis.^

Comparison of two statistical methods for rare variant association analysis

Studies have shown that rare genetic variants have stronger effects in predisposing common diseases, and several statistical methods have been developed for association studies involving rare variants. In order to better understand how these statistical methods perform, we seek to compare two recently developed rare variant statistical methods (VT and C-alpha) on 10,000 simulated re-sequencing data sets with disease status and the corresponding 10,000 simulated null data sets. The SLC1A1 gene has been suggested to be associated with diastolic blood pressure (DBP) in previous studies. In the current study, we applied VT and C-alpha methods to the empirical re-sequencing data for the SLC1A1 gene from 300 whites and 200 blacks. We found that VT method obtains higher power and performs better than C-alpha method with the simulated data we used. The type I errors were well-controlled for both methods. In addition, both VT and C-alpha methods suggested no statistical evidence for the association between the SLC1A1 gene and DBP. Overall, our findings provided an important comparison of the two statistical methods for future reference and provided preliminary and pioneer findings on the association between the SLC1A1 gene and blood pressure.^

A cross-sectional analysis of the association between polycyclic aromatic hydrocarbons and diesel particulate matter exposures and hypertension among individuals of Mexican origin residing in Houston, TX

Background. Research has shown that elevations of only 10 mmHg diastolic blood pressure (BP) and 5 mmHg systolic BP are associated with substantial (as large as 50%) increases in risks for cardiovascular disease, a leading cause of death, worldwide. Epidemiological studies have found that particulate matter (PM) increases blood pressure (BP) and many biological mechanisms which may suggest that the organic matter of PM contributes to the increase in BP. To understand components of PM which may contribute to the increase in BP, this study focuses on diesel particulate matter (DPM) and polycyclic aromatic hydrocarbons (PAHs). To our knowledge, there have been only four epidemiological studies on BP and DPM, and no epidemiological studies on BP and PAHs. ^ Objective. Our objective was to evaluate the association between prevalent hypertension and two ambient exposures: DPM and PAHs amongst the Mano a Mano cohort. ^ Methods. The Mano a Mano cohort which was established by the M.D. Anderson Cancer Center in 2001, is comprised of individuals of Mexican origin residing in Houston, TX. Using geographical information systems, we linked modeled annual estimates of PAHs and DPM at the census track level from the U.S. Environmental Protection Agency's National-Scale Air Toxics Assessment to residential addresses of cohort members. Mixed-effects logistic regression models were applied to determine associations between DPM and PAHs and hypertension while adjusting for confounders. ^ Results. Ambient levels of DPM, categorized into quartiles, were not statistically associated with hypertension and did not indicate a dose response relationship. Ambient levels of PAHs, categorized into quartiles, were not associated with hypertension, but did indicate a dose response relationship in multiple models (for example: Q2: OR = 0.98; 95% CI, 0.73–1.31, Q3: OR = 1.08; 95% CI, 0.82–1.41, Q4: OR = 1.26; 95% CI, 0.94–1.70). ^ Conclusion. This is the first assessment to analyze the relationship between ambient levels of PAHs and hypertension and it is amongst a few studies investigating the association between ambient levels of DPM and hypertension. Future analyses are warranted to explore the effects DPM and PAHs using different categorizations in order to clarify their relationships with hypertension.^

The role of cardiorespiratory fitness and weight status on 24-hr ambulatory blood pressure among adolescents

BACKGROUND: This observational research study investigated the association of cardiorespiratory fitness and weight status with repeated measures of 24-hr ambulatory blood pressure (24-hr ABP). Little is known about these associations and few data exist examining the interaction between cardiorespiratory fitness and weight status and the contributions of each on 24-hr ABP in youth. ^ METHODS: This research study used secondary analysis data from the "Adolescent Blood Pressure and Anger: Ethnic Differences" study. This current study sample included 374 African-American, Anglo-American, and Mexican-American adolescents 11-16 years of age. Mixed-effects models were used for testing the relationship between weight status and cardiorespiratory fitness and repeated measures of ambulatory blood pressure over 24 hours (24-hr ABP). Weight status was categorized into "normal weight" (BMI<85th percentile), "overweight" (85th≤BMI<95th), and "obese" (BMI≥95th). Cardiorespiratory fitness, determined by heart rate recovery (HRR), was defined as the difference between heart rate at peak exercise and heart rate at two minutes post-exercise, as measured by a height-adjusted step test and stratified into two groups: low and high fitness, using a median split. Ambulatory blood pressure (ABP) was monitored for a 24-hr period on a school day using the Spacelabs ambulatory monitor (Model 90207). Blood pressure and heart rate were recorded at 30 minute intervals throughout the day of recording and at 60 minute intervals during sleep. ^ RESULTS: No significant associations were found between weight status and mean 24-hr systolic blood pressure (SBP) or mean arterial pressure (MAP). A significant and inverse association between weight status and mean 24-hr diastolic blood pressure (DBP) was revealed. Cardiorespiratory fitness was significantly and inversely associated with mean 24-hr ABP. High fitness adolescents had significantly lower mean 24-hr SPB, DBP, and MAP measurements than low fitness adolescents. Compared to low fitness adolescents, high fitness adolescents had 1.90 mmHg, 1.16 mmHg, and 1.68 mmHg lower mean 24-hr SBP, DBP, and MAP, respectively. Additionally, high fitness appeared to afford protection from higher mean 24-hr SBP and MAP, irrespective of weight status. Among normal weight adolescents, low fitness resulted in higher mean 24-hr SBP and MAP, compared to their fit counterparts. Among adolescents categorized as high fitness, increasing weight status did not appear to result in higher mean 24-hr SBP or MAP. Cardiorespiratory fitness, rather than weight status, appeared to be a more dominant predictor of mean 24-hr SBP and MAP. ^ CONCLUSIONS: To our knowledge, this research is the first study to investigate the independent and combined contributions of cardiorespiratory fitness and weight status on 24-hr ABP, all objectively measured. The results of this study may potentially guide and inform future research. It appears that early cardiovascular disease (CVD) prevention should focus on improving cardiorespiratory fitness levels among all adolescents, particularly those adolescents least fit, regardless of their weight status, while obesity prevention efforts continue.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Pressure core barrel characteristics and composition of gases at DSDP Site 76-533

A pressure core barrel (PCB), developed by the Deep Sea Drilling Project, was used successfully to recover, at in situ pressure, sediments of the Blake Outer Ridge, offshore the southeastern United States. The PCB is a unique, wire-line tool, 10.4 m long, capable of recovering 5.8 m of core (5.8 cm in diameter), maintained at or below in situ pressures of 34.4 million Pascals (MPa), and 1.8 m of unpressurized core (5.8 cm in diameter). All excess internal pressure above the operating pressure of 34.4 MPa is automatically vented off as the barrel is retrieved. The PCB was deployed five times at DSDP Site 533 where geophysical evidence suggests the presence of gas hydrates in the upper 600 m of sediment. Three cores were obtained holding average in situ pressures of 30 MPa. Two other cores did not maintain in situ pressures. Three of the five cores were intermittently degassed at varying intervals of time, and portions of the vented gas were collected for analysis. Pressure decline followed paths indicative of gas hydrates and/or dissolved gas. The released gas was dominantly methane (usually greater than 90%), along with higher molecular-weight hydrocarbon gases and carbon dioxide. During degassing the ratio of methane to ethane did not vary significantly. On the other hand, concentrations of higher molecular-weight hydrocarbon gases increased, as did carbon dioxide concentrations. The results from the PCB experiments provide tentative but equivocal evidence for the presence of .gas hydrates at Site 533. The amount of gas hydrate indicated is small. Nevertheless, this work represents the first successful study of marine gas hydrates utilizing the PCB.

Table 1 Microorganisms, identified with DOGE analysis. 16S rDNA sequences, obtained from sequencing of DOGE bands, were assigned to the corresponding microorganisms

Microorganisms play an important role in the transformation of material within the earth's crust. The storage of CO2 could affect the composition of inorganic and organic components in the reservoir, consequently influencing microbial activities. To study the microbial induced processes together with geochemical, petrophysical and mineralogical changes, occurring during CO2 storage, long-term laboratory experiments under simulated reservoir P-T conditions were carried out. Clean inner core sections, obtained from the reservoir region at the CO2 storage site in Ketzin (Germany) from a depth of about 650 m, were incubated in high pressure vessels together with sterile synthetic formation brine under in situ P-T conditions of 5.5 MPa and 40°C. A 16S rDNA based fingerprinting method was used to identify the dominant species in DNA extracts of pristine sandstone samples. Members of the alpha- and beta-subdivisions of Proteobacteria and the Actinobacteria were identified. So far sequences belonging to facultative anaerobic, chemoheterotrophic bacteria (Burkholderia fungorum, Agrobacterium tumefaciens) gaining their energy from the oxidation of organic molecules and a genus also capable of chemolithoautotrophic growth (Hydrogenophaga) was identified. During CO2 incubation minor changes in the microbial community composition were observed. The majority of microbes were able to adapt to the changed conditions. During CO2 exposure increased concentrations of Ca**2+, K**+, Mg**2+ and SO4**2- were observed. Partially, concentration rises are (i) due to equilibration between rock pore water and synthetic brine, and (ii) between rock and brine, and are thus independent on CO2 exposure. However, observed concentrations of Ca**2+, K**+, Mg**2+ are even higher than in the original reservoir fluid and therefore indicate mineral dissolution due to CO2 exposure.

Mesopelagic fish abundance and particle size spectrum analysis from Maria S. Merian cruise MSM26, spring 2013

One of the goals of EU BASIN is to understand variability in production across the Atlantic and the impact of this variability on higher trophic levels. One aspect of these investigations is to examine the biomes defined by Longhurst (2007). These biomes are largely based on productivity measured with remote sensing. During MSM 26, mesopelagic fish and size-spectrum data were collected to test the biome classifications of the north Atlantic. In most marine systems, the size-spectrum is a decay function with more, smaller organisms and fewer larger organisms. The intercept of the size-spectrum has been linked to overall productivity while the slope represents the "rate of decay" of this productivity (Zhou 2006, doi:10.1093/plankt/fbi119). A Laser In-Situ Scattering Transmissometer was used to collect size-spectrum data and net collections were made to capture mesopelagic fish. The relationship among the mesopelagic fish size and abundance distributions will be compared to the estimates of production from the size-spectrum data to evaluate the biomes of the stations occupied during MSM 26.

Analysis of Pacific oyster larval proteome and its response to high-CO2

Most calcifying organisms show depressed metabolic, growth and calcification rates as symptoms to high-CO(2) due to ocean acidification (OA) process. Analysis of the global expression pattern of proteins (proteome analysis) represents a powerful tool to examine these physiological symptoms at molecular level, but its applications are inadequate. To address this knowledge gap, 2-DE coupled with mass spectrophotometer was used to compare the global protein expression pattern of oyster larvae exposed to ambient and to high-CO(2). Exposure to OA resulted in marked reduction of global protein expression with a decrease or loss of 71 proteins (18% of the expressed proteins in control), indicating a wide-spread depression of metabolic genes expression in larvae reared under OA. This is, to our knowledge, the first proteome analysis that provides insights into the link between physiological suppression and protein down-regulation under OA in oyster larvae.