Indications for and Utilization of ACE Inhibitors in Older Individuals with Diabetes

Angiotensin-converting enzyme inhibitors (ACE) and angiotensin receptor blockers (ARB) improve cardiovascular outcomes in high-risk individuals with diabetes. Despite the marked benefit, it is unknown what percentage of patients with diabetes would benefit from and what percentage actually receive this preventive therapy. OBJECTIVES : To examine the proportion of older diabetic patients with indications for ACE or ARB (ACE/ARB). To generate national estimates of ACE/ARB use. DESIGN AND PARTICIPANTS : Survey of 742 individuals≥55 years (representing 8.02 million U.S. adults) self-reporting diabetes in the 1999 to 2002 National Health and Nutrition Examination Survey. MEASUREMENTS : Prevalence of guideline indications (albuminuria, cardiovascular disease, hypertension) and other cardiac risk factors (hyperlipidemia, smoking) with potential benefit from ACE/ARB. Prevalence of ACE/ARB use overall and by clinical indication. RESULTS : Ninety-two percent had guideline indications for ACE/ARB. Including additional cardiac risk factors, the entire (100%) U.S. noninstitutionalized older population with diabetes had indications for ACE/ARB. Overall, 43% of the population received ACE/ARB. Hypertension was associated with higher rates of ACE/ARB use, while albuminuria and cardiovascular disease were not. As the number of indications increased, rates of use increased, however, the maximum prevalence of use was only 53% in individuals with 4 or more indications for ACE/ARB. CONCLUSIONS : ACE/ARB is indicated in virtually all older individuals with diabetes; yet, national rates of use are disturbingly low and key risk factors (albuminuria and cardiovascular disease) are being missed. To improve quality of diabetes care nationally, use of ACE/ARB therapy by ALL older diabetics may be a desirable addition to diabetes performance measurement sets.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74734/1/j.1525-1497.2006.00351.x.pd

Trends in publications regarding evidence-practice gaps: A literature review

<p>Abstract</p> <p>Background</p> <p>Well-designed trials of strategies to improve adherence to clinical practice guidelines are needed to close persistent evidence-practice gaps. We studied how the number of these trials is changing with time, and to what extent physicians are participating in such trials.</p> <p>Methods</p> <p>This is a literature-based study of trends in evidence-practice gap publications over 10 years and participation of clinicians in intervention trials to narrow evidence-practice gaps. We chose nine evidence-based guidelines and identified relevant publications in the PubMed database from January 1998 to December 2007. We coded these publications by study type (intervention versus non-intervention studies). We further subdivided intervention studies into those for clinicians and those for patients. Data were analyzed to determine if observed trends were statistically significant.</p> <p>Results</p> <p>We identified 1,151 publications that discussed evidence-practice gaps in nine topic areas. There were 169 intervention studies that were designed to improve adherence to well-established clinical guidelines, averaging 1.9 studies per year per topic area. Twenty-eight publications (34%; 95% CI: 24% - 45%) reported interventions intended for clinicians or health systems that met Effective Practice and Organization of Care (EPOC) criteria for adequate design. The median consent rate of physicians asked to participate in these well-designed studies was 60% (95% CI, 25% to 69%).</p> <p>Conclusions</p> <p>We evaluated research publications for nine evidence-practice gaps, and identified small numbers of well-designed intervention trials and low rates of physician participation in these trials.</p

Testing for heterogeneity among the components of a binary composite outcome in a clinical trial

<p>Abstract</p> <p>Background</p> <p>Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome.</p> <p>Methods</p> <p>Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression.</p> <p>Results</p> <p>We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high.</p> <p>Conclusions</p> <p>It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes.</p

Antiarrhythmic versus antifibrillatory actions: Inference from experimental studies

Pathophysiology of the coronary circulation is a major contributor to altering the myocardial substrate, rendering the heart susceptible to the onset of arrhythmias associated with sudden cardiac death. Antiarrhythmic drug therapy for the prevention of sudden cardiac death has been provided primarily on the basis of trial and error and in some instances based on ill-suited preclinical evaluations. The findings of the Cardiac Arrhythmia Suppression Trial (CAST) requires a reexamination of the manner in which antiarrhythmic drugs are developed before entering into clinical testing. The major deficiency in this area of experimental investigation has been the lack of animal models that would permit preclinical studies to identify potentially useful or deleterious therapeutic agents. Further, CAST has emphasized the need to distinguish between pharmacologic interventions that suppresses nonlethal disturbances of cardiac rhythm as opposed to those agents capable of preventing lethal ventricular tachycardia or ventricular fibrillation. Preclinical models for the testing of antifibrillatory agents must consider the fact that the superimposition of transient ischemic events on an underlying pathophysiologic substrate makes the heart susceptible to lethal arrhythmias. Proarrhythmic events, not observed in the normal heart, may become manifest only when the myocardial substrate has been altered. We describe a model of sudden cardiac death that may more closely simulate the clinical state in humans who are at risk. The experimental results show a good correlation with clinical data regarding agents known to reduce the incidence of lethal arrhythmias as well as those showing proarrhythmic actions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30443/1/0000066.pd