The role of BNP testing in heart failure

Brain natriuretic peptide (BNP) levels are simple and objective measures of cardiac function. These measurements can be used to diagnose heart failure, including diastolic dysfunction, and using them has been shown to save money in the emergency department setting. The high negative predictive value of BNP tests is particularly helpful for ruling out heart failure. Treatment with angiotensin-converting enzyme inhibitors, angiotensin-II receptor blockers, spironolactone, and diuretics reduces BNP levels, suggesting that BNP testing may have a role in monitoring patients with heart failure. However, patients with treated chronic stable heart failure may have levels in the normal range (i.e., BNP less than 100 pg per mL and N-terminal proBNP less than 125 pg per mL in patients younger than 75 years). Increases in BNP levels may be caused by intrinsic cardiac dysfunction or may be secondary to other causes such as pulmonary or renal diseases (e.g., chronic hypoxia). BNP tests are correlated with other measures of cardiac status such as New York Heart Association classification. BNP level is a strong predictor of risk of death and cardiovascular events in patients previously diagnosed with heart failure or cardiac dysfunction.

Approaches to training practitioners in the art and science of plant disease diagnosis

Allowing plant pathology students to tackle fictitious or real crop problems during the course of their formal training not only teaches them the diagnostic process, but also provides for a better understanding of disease etiology. Such a problem-solving approach can also engage, motivate, and enthuse students about plant pathologgy in general. This paper presents examples of three problem-based approaches to diagnostic training utilizing freely available software. The first provides an adventure-game simulation where Students are asked to provide a diagnosis and recommendation after exploring a hypothetical scenario or case. Guidance is given oil how to create these scenarios. The second approach involves students creating their own scenarios. The third uses a diagnostic template combined with reporting software to both guide and capture students' results and reflections during a real diagnostic assignment.

Prediction of functional capacity in chronic heart failure patients using myocardial tissue Doppler

Background. Exercise therapy improves functional capacity in CHF, but selection and individualization of training would be helped by a simple non-invasive marker of peak VO2. Peak VO2 in these pts is difficult to predict without direct measurement, and LV ejection fraction is a poor predictor. Myocardial tissue velocities are less load-dependent, and may be predictive of the exercise response in CHF pts. We sought to use tissue velocity as a predictor of peak VO2 in CHF pts. Methods. Resting 2D-echocardiography and tissue Doppler imaging were performed in 182 CHF pts (159 male, age 62±10 years) before and after metabolic exercise testing. The majority of these patients (129, 71%) had an ischemic cardiomyopathy, with resting EF of 35±13% and a peak VO2 of 13.5±4.7 ml/kg/min. Results. Neither resting EF (r=0.15) nor peak EF (r=0.18, both p=NS) were correlated with peak VO2. However, peak VO2 correlated with peak systolic velocity in septal (Vss, r=0.31) and lateral walls (Vsl, r=0.26, both p=0.01). In a general linear model (r2 = 0.25), peak VO2 was calculated from the following equation: 9.6 + 0.68*Vss - 0.09*age + 0.06*maximum HR. This model proved to be a superior predictor of peak VO2 (r=0.51, p=0.01) than the standard prediction equations of Wasserman (r= -0.12, p=0.01). Conclusions. Resting tissue Doppler, age and maximum heart rate may be used to predict functional capacity in CHF patients. This may be of use in selecting and following the response to therapy, including for exercise training.

Association between glutathione S-transferase M1 and T1 and the risk for coronary heart disease (CHD)

Deficiency of Glutathione S-transferases (GST) M1 and T1 are associated with chronic diseases (e.g. lung cancer, MS) and could be one factor for the risk for CHD.We conducted a pros-pective case-control study in 93 pts. with angiographically proven CHD and 161 controls matched for age ±2y and gender (resulting in n=91 pairs, of which 18 were female). Genes coding for functional GST M1 and T1 were analysed acoording to previously published methods. The association between GST M1, T1 was tested using Fisher's exact test; logistic regression analysis was performed to control for HDL-cholesterol, diabetes smoking, diabetes, hypertension. 41% of cases were smokers, 25% had diabetes and 68% hypertension, corresponding figures for controls were 31%, 13% and 33%. Mean HDL-cholesterol levels were comparable (pts: 46±14 mg/dl, controls: 43± 19 mg/dl). There was no overall significant correlation between functional GST T1 and M1 genotypes and CHD, however, there seems to be an association between GST M1, HDL-cholesterol and CHD. Larger studies are needed to verify these data.