Taking aim at HDL-C. Raising levels to reduce cardiovascular risk

Although statin therapy has revolutionized management of coronary heart disease (CHD), the lowering of low-density lipoprotein cholesterol (LDL-C) levels is not the whole story. Increased plasma concentrations of high-density lipoprotein cholesterol (HDL-C) have a cardioprotective effect that is just as important for reducing risk of heart attack and stroke. In this article, Dr McGovern examines the evidence that provides the rationale for HDL-C as a therapeutic target for cardiovascular risk reduction.     

Propensity analysis of outcome in coronary artery bypass graft surgery patients >75 years old

Purpose  

We looked at the complications and hospital resources of an elderly population undergoing first-time isolated coronary artery bypass graft surgery (CABG) in comparison to a younger counterpart for a propensity matched cohort.     

Evaluation of the Cepheid Xpert C. difficile/Epi and Meridian Bioscience illumigene C. difficile Assays for Detecting Clostridium difficile Ribotype 033 Strains

Clostridium difficile PCR ribotype 033 (RT033) is found in the gastrointestinal tracts of production animals and, occasionally, humans. The illumigene C. difficile assay (Meridian Bioscience, Inc.) failed to detect any of 52 C. difficile RT033 isolates, while all strains signaled positive for the binary toxin genes but were reported as negative for C. difficile by the Xpert C. difficile/Epi assay (Cepheid).     

Comparative effects on lipid levels of combination therapy with a statin and extended-release niacin or ezetimibe versus a statin alone (the COMPELL study)

International guidelines recommend lower target cholesterol levels and treatment of low high-density lipoprotein cholesterol (HDL-C) and elevated triglycerides for patients at moderately high to high coronary heart disease (CHD) risk. Combination therapy is often required to achieve multiple lipid treatment goals, and > or =50% reduction in low-density lipoprotein cholesterol (LDL-C) is needed in some patients to achieve aggressive LDL-C targets. In this context, we evaluated comparative effects on lipid levels of combination therapy at low to moderate doses with a statin plus extended-release niacin (niacin ER), a statin plus ezetimibe, and a highly potent statin alone. This was an open-label, multicenter, 12-week study in 292 patients (50% women) who qualified for drug therapy based on number of CHD risk factors. Patients were randomized to four parallel arms, titrated from low to moderate or high doses: atorvastatin/niacin ER, rosuvastatin/niacin ER, simvastatin/ezetimibe, or rosuvastatin alone. Baseline mean values were, for LDL-C 197 mg/dL (5.1 mmol/L), HDL-C 49 mg/dL (1.3 mmol/L), triglycerides 168 mg/dL (1.9 mmol/L). There were no significant differences among treatment groups in the change from baseline in LDL-C at pre-specified timepoints during treatment. All groups lowered LDL-C by approximately 50% or more (range -49 to -57%), achieving mean levels of 82-98 mg/dL (2.1-2.5 mmol/L). Changes in non-HDL-C (range -46 to -55%) mirrored those for LDL-C and did not differ among treatment groups. Statin/niacin ER combination regimens also increased HDL-C and large HDL (HDL2) and lowered triglycerides and lipoprotein (a) significantly more than other regimens. No drug-related myopathy or hepatotoxicity was observed. In this study, low to moderate dose combination therapy with a statin and niacin ER provided broad control of lipids and lipoproteins independently associated with CHD.     

Mixed binary-continuous copula regression models with application to adverse birth outcomes

Bivariate copula regression allows for the flexible combination of two arbitrary, continuous marginal distributions with regression effects being placed on potentially all parameters of the resulting bivariate joint response distribution. Motivated by the risk factors for adverse birth outcomes, many of which are dichotomous, we consider mixed binary-continuous responses that extend the bivariate continuous framework to the situation where one response variable is discrete (more precisely, binary) whereas the other response remains continuous. Utilizing the latent continuous representation of binary regression models, we implement a penalized likelihood–based approach for the resulting class of copula regression models and employ it in the context of modeling gestational age and the presence/absence of low birth weight. The analysis demonstrates the advantage of the flexible specification of regression impacts including nonlinear effects of continuous covariates and spatial effects. Our results imply that racial and spatial inequalities in the risk factors for infant mortality are even greater than previously suggested.