trandolapril and Inflammation

Secretory phospholipase A(2) (sPLA(2)) may contribute to atherogenesis. To date, few prospective studies have examined the utility of sPLA(2) for risk stratification in coronary artery disease (CAD).. We measured plasma sPLA(2) activity at baseline in 3708 subjects in the PEACE randomized trial of trandolapril vs placebo in stable CAD. Median follow-up was 4.8 years. We used Cox regression to adjust for demographics, clinical risk factors, apolipoprotein B, apolipoprotein A1, and medications.. After multivariable adjustment, sPLA(2) was associated with an increased risk of cardiovascular death, myocardial infarction, or stroke (adjusted hazard ratio Q4:Q1 1.55, 95% CI 1.13-2.14) and cardiovascular death or heart failure (1.91, 1.20-3.03). In further multivariable assessment, increased activity levels of sPLA(2) were associated with the risk of cardiovascular death, myocardial infarction, or stroke (adjusted hazard ratio 1.47, 95% CI 1.06-2.04), independent of lipoprotein-associated phospholipase A(2) mass and C-reactive protein, and modestly improved the area under the curve (AUC) beyond established clinical risk factors (AUC 0.668-0.675, P = 0.01). sPLA(2), N-terminal pro-B-type natriuretic peptide, and high-sensitivity cardiac troponin T all were independently associated with cardiovascular death or heart failure, and each improved risk discrimination (P = 0.02, P < 0.001, P < 0.001, respectively).. sPLA(2) activity provides independent prognostic information beyond established risk markers in patients with stable CAD. These data are encouraging for studies designed to evaluate the role of sPLA(2) as a therapeutic target.

Topics: Aged; Angiotensin-Converting Enzyme Inhibitors; Biomarkers; Cardiovascular Diseases; Clinical Enzyme Tests; Coronary Disease; Double-Blind Method; Female; Heart Failure; Humans; Indoles; Inflammation; Male; Middle Aged; Multivariate Analysis; Myocardial Infarction; Necrosis; Phospholipases A2, Secretory; Predictive Value of Tests; Prognosis; Risk Assessment; Stroke

A major problem in treating inflammatory myopathies is the very limited information available about the processes taking place. For instance serum creatine kinase levels are often dismissed as a means of gaining an understanding of what is happening or a means of monitoring a patient. This paper shall show how serum creatine kinase levels may be used to explore the processes taking place that create muscle inflammation. This is achieved by a detailed longitudinal study. Firstly, considerable laboratory data is gathered such as serum creatine kinase levels and blood pressure information. Secondly, the data is quantified using a scientific model. We shall illustrate the approach through an extensive nine-year study of a particular polymyositis patient. We identify three basic processes that may contribute to muscle inflammation and show how they may be interpreted from specific patient data. Furthermore, details are given for controlling and monitoring the disease to maximise the reduction in the muscle attack while reducing significantly the muscle inflammation and keeping the drug concentration at a minimum to ensure minimum side-effects and how to identify and handle drug-drug, drug-natural product and adverse drug interactions. Examples are given for a natural product, azathioprine and trandolapril.

Topics: Animals; Azathioprine; Clinical Enzyme Tests; Creatine Kinase; Drug Interactions; Humans; Indoles; Inflammation; Models, Theoretical; Muscles; Muscular Diseases; Polymyositis; Time Factors