Multiple uncontrolled conditions and blood pressure medication intensification: an observational study

Abstract Background Multiple uncontrolled medical conditions may act as competing demands for clinical decision making. We hypothesized that multiple uncontrolled cardiovascular risk factors would decrease blood pressure (BP) medication intensification among uncontrolled hypertensive patients. Methods We observed 946 encounters at two VA primary care clinics from May through August 2006. After each encounter, clinicians recorded BP medication intensification (BP medication was added or titrated). Demographic, clinical, and laboratory information were collected from the medical record. We examined BP medication intensification by presence and control of diabetes and/or hyperlipidemia. 'Uncontrolled' was defined as hemoglobin A1c ≥ for diabetes, BP ≥ 140/90 mmHg (≥ 130/80 mmHg if diabetes present) for hypertension, and low density lipoprotein cholesterol (LDL-c) ≥ 130 mg/dl (≥ 100 mg/dl if diabetes present) for hyperlipidemia. Hierarchical regression models accounted for patient clustering and adjusted medication intensification for age, systolic BP, and number of medications. Results Among 387 patients with uncontrolled hypertension, 51.4% had diabetes (25.3% were uncontrolled) and 73.4% had hyperlipidemia (22.7% were uncontrolled). The BP medication intensification rate was 34.9% overall, but higher in individuals with uncontrolled diabetes and uncontrolled hyperlipidemia: 52.8% overall and 70.6% if systolic BP ≥ 10 mmHg above goal. Intensification rates were lowest if diabetes or hyperlipidemia were controlled, lower than if diabetes or hyperlipidemia were not present. Multivariable adjustment yielded similar results. Conclusions The presence of uncontrolled diabetes and hyperlipidemia was associated with more guideline-concordant hypertension care, particularly if BP was far from goal. Efforts to understand and improve BP medication intensification in patients with controlled diabetes and/or hyperlipidemia are warranted.http://deepblue.lib.umich.edu/bitstream/2027.42/78266/1/1748-5908-5-55.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78266/2/1748-5908-5-55.pdfPeer Reviewe

Sociodemographic Trends in National Ambulatory Care Visits for Hepatitis C Virus Infection

Poor and non-white patients are disproportionately infected with the hepatitis C virus (HCV). The objective of this research is to determine sociodemographic patterns of HCV-related ambulatory care visits over time. Data from the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey-Outpatient (NHAMCS-OPD) for the years 1997–2005 were analyzed in 3-year intervals. Demographic and other variables were compared for each period, and multivariable logistic regression was performed to examine whether the likelihood of a visit being HCV-related (versus non-HCV) was independently associated with (1) race and/or (2) Medicaid status over time. The total number of HCV-related ambulatory visits more than doubled from 3,583,585 during the years 1997–1999 to 8,027,166 during 2003–2005. During this time, the proportion of non-whites and Medicaid recipients presenting for HCV-related visits approximately doubled (non-whites: 16% vs. 33%, P = 0.04; Medicaid recipients: 10% vs. 25%, P = 0.07). In 2003–2005, HCV-related visits were more than twice as likely to occur among non-white patients vs. white patients (OR = 2.49; 95% CI: 1.60–3.86) and patients on Medicaid vs. non-Medicaid (3.49; 1.79–6.80). Our results show that HCV-associated ambulatory care visits are increasing, with a greater proportion of visits occurring among non-white patients and Medicaid recipients

An empirical approach towards the efficient and optimal production of influenza-neutralizing ovine polyclonal antibodies demonstrates that the novel adjuvant CoVaccine HT(TM) is functionally superior to Freund's adjuvant

Passive immunotherapies utilising polyclonal antibodies could have a valuable role in preventing and treating infectious diseases such as influenza, particularly in pandemic situations but also in immunocompromised populations such as the elderly, the chronically immunosuppressed, pregnant women, infants and those with chronic diseases. The aim of this study was to optimise current methods used to generate ovine polyclonal antibodies. Polyclonal antibodies to baculovirus-expressed recombinant influenza haemagglutinin from A/Puerto Rico/8/1934 H1N1 (PR8) were elicited in sheep using various immunisation regimens designed to investigate the priming immunisation route, adjuvant formulation, sheep age, and antigen dose, and to empirically ascertain which combination maximised antibody output. The novel adjuvant CoVaccine HT™ was compared to Freund’s adjuvant which is currently the adjuvant of choice for commercial production of ovine polyclonal Fab therapies. CoVaccine HT™ induced significantly higher titres of functional ovine anti-haemagglutinin IgG than Freund’s adjuvant but with fewer side effects, including reduced site reactions. Polyclonal hyperimmune sheep sera effectively neutralised influenza virus in vitro and, when given before or after influenza virus challenge, prevented the death of infected mice. Neither the age of the sheep nor the route of antigen administration appeared to influence antibody titre. Moreover, reducing the administrated dose of haemagglutinin antigen minimally affected antibody titre. Together, these results suggest a cost effective way of producing high and sustained yields of functional ovine polyclonal antibodies specifically for the prevention and treatment of globally significant diseases.Natalie E. Stevens, Cara K. Fraser, Mohammed Alsharifi, Michael P. Brown, Kerrilyn R. Diener, John D. Haybal

Performance of Risk-Based Criteria for Targeting Acute HIV Screening in San Francisco

Federal guidelines now recommend supplemental HIV RNA testing for persons at high risk for acute HIV infection. However, many rapid HIV testing sites do not include HIV RNA or p24 antigen testing due to concerns about cost, the need for results follow-up, and the impact of expanded venipuncture on clinic flow. We developed criteria to identify patients in a municipal STD clinic in San Francisco who are asymptomatic but may still be likely to have acute infection.Data were from patients tested with serial HIV antibody and HIV RNA tests to identify acute HIV infection. BED-CEIA results were used to classify non-acute cases as recent or longstanding. Demographics and self-reported risk behaviors were collected at time of testing. Multivariate models were developed and preliminarily evaluated using predictors associated with recent infection in bivariate analyses as a proxy for acute HIV infection. Multivariate models demonstrating ≥70% sensitivity for recent infection while testing ≤60% of patients in this development dataset were then validated by determining their performance in identifying acute infections.From 2004-2007, 137 of 12,622 testers had recent and 36 had acute infections. A model limiting acute HIV screening to MSM plus any one of a series of other predictors resulted in a sensitivity of 83.3% and only 47.6% of patients requiring testing. A single-factor model testing only patients reporting any receptive anal intercourse resulted in 88.9% sensitivity with only 55.2% of patients requiring testing.In similar high risk HIV testing sites, acute screening using "supplemental" HIV p24 antigen or RNA tests can be rationally targeted to testers who report particular HIV risk behaviors. By improving the efficiency of acute HIV testing, such criteria could facilitate expanded acute case identification

Understanding Liver Health Using the National Center for Health Statistics

The National Center for Health Statistics (NCHS) is the principal health statistics agency for the United States. It seeks to provide accurate, relevant, and timely data on health status and utilization of health care. As such, the NCHS represents a tremendous repository of behavioral, biological, and clinical data that can be employed to identify issues and effect change in public policy related to liver health and disease. By providing an understanding of the rich, publicly available data systems within the NCHS, investigators may capitalize on an efficient means to shape current knowledge of liver disease

Seagrass Canopy Photosynthetic Response Is a Function of Canopy Density and Light Environment: A Model for Amphibolis griffithii

A three-dimensional computer model of canopies of the seagrass Amphibolis griffithii was used to investigate the consequences of variations in canopy structure and benthic light environment on leaf-level photosynthetic saturation state. The model was constructed using empirical data of plant morphometrics from a previously conducted shading experiment and validated well to in-situ data on light attenuation in canopies of different densities. Using published values of the leaf-level saturating irradiance for photosynthesis, results show that the interaction of canopy density and canopy-scale photosynthetic response is complex and non-linear, due to the combination of self-shading and the non-linearity of photosynthesis versus irradiance (P-I) curves near saturating irradiance. Therefore studies of light limitation in seagrasses should consider variation in canopy structure and density. Based on empirical work, we propose a number of possible measures for canopy scale photosynthetic response that can be plotted to yield isoclines in the space of canopy density and light environment. These plots can be used to interpret the significance of canopy changes induced as a response to decreases in the benthic light environment: in some cases canopy thinning can lead to an equivalent leaf level light environment, in others physiological changes may also be required but these alone may be inadequate for canopy survival. By providing insight to these processes the methods developed here could be a valuable management tool for seagrass conservation during dredging or other coastal developments

Statistical power considerations in genotype-based recall randomized controlled trials

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for genemetformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design

Computational Modelling of Genome-Side Transcription Assembly Networks Using a Fluidics Analogy

Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets