Judith M. Kramer

Scientific evidence underlying the ACC/AHA clinical practice guidelines.

CONTEXT The joint cardiovascular practice guidelines of the American College of Cardiology (ACC) and the American Heart Association (AHA) have become important documents for guiding cardiology practice and establishing benchmarks for quality of care. OBJECTIVE To describe the evolution of recommendations in ACC/AHA cardiovascular guidelines and the distribution of recommendations across classes of recommendations and levels of evidence. DATA SOURCES AND STUDY SELECTION Data from all ACC/AHA practice guidelines issued from 1984 to September 2008 were abstracted by personnel in the ACC Science and Quality Division. Fifty-three guidelines on 22 topics, including a total of 7196 recommendations, were abstracted. DATA EXTRACTION The number of recommendations and the distribution of classes of recommendation (I, II, and III) and levels of evidence (A, B, and C) were determined. The subset of guidelines that were current as of September 2008 was evaluated to describe changes in recommendations between the first and current versions as well as patterns in levels of evidence used in the current versions. RESULTS Among guidelines with at least 1 revision or update by September 2008, the number of recommendations increased from 1330 to 1973 (+48%) from the first to the current version, with the largest increase observed in use of class II recommendations. Considering the 16 current guidelines reporting levels of evidence, only 314 recommendations of 2711 total are classified as level of evidence A (median, 11%), whereas 1246 (median, 48%) are level of evidence C. Level of evidence significantly varies across categories of guidelines (disease, intervention, or diagnostic) and across individual guidelines. Recommendations with level of evidence A are mostly concentrated in class I, but only 245 of 1305 class I recommendations have level of evidence A (median, 19%). CONCLUSIONS Recommendations issued in current ACC/AHA clinical practice guidelines are largely developed from lower levels of evidence or expert opinion. The proportion of recommendations for which there is no conclusive evidence is also growing. These findings highlight the need to improve the process of writing guidelines and to expand the evidence base from which clinical practice guidelines are derived.

Long-Term Adherence to Evidence-Based Secondary Prevention Therapies in Coronary Artery Disease

Background— Studies have examined the use of evidence-based therapies for coronary artery disease (CAD) in the short term and at hospital discharge, but few have evaluated long-term use. Methods and Results— Using the Duke Databank for Cardiovascular Disease for the years 1995 to 2002, we determined the annual prevalence and consistency of self-reported use of aspirin, &bgr;-blockers, lipid-lowering agents, and their combinations in all CAD patients and of angiotensin-converting enzyme inhibitors (ACEIs) in those with and without heart failure. Logistic-regression models identified characteristics associated with consistent use (reported on ≥2 consecutive follow-up surveys and then through death, withdrawal, or study end), and Cox proportional-hazards models explored the association of consistent use with mortality. Use of all agents and combinations thereof increased yearly. In 2002, 83% reported aspirin use; 61%, &bgr;-blocker use; 63%, lipid-lowering therapy use; 54%, aspirin and &bgr;-blocker use; and 39%, use of all 3. Consistent use was as follows: For aspirin, 71%; &bgr;-blockers, 46%; lipid-lowering therapy, 44%; aspirin and &bgr;-blockers, 36%; and all 3, 21%. Among patients without heart failure, 39% reported ACEI use in 2002; consistent use was 20%. Among heart failure patients, ACEI use was 51% in 2002 and consistent use, 39%. Except for ACEIs among patients without heart failure, consistent use was associated with lower adjusted mortality: Aspirin hazard ratio (HR), 0.58 and 95% confidence interval (CI), 0.54 to 0.62; &bgr;-blockers, HR, 0.63 and 95% CI, 0.59 to 0.67; lipid-lowering therapy, HR, 0.52 and 95% CI, 0.42 to 0.65; all 3, HR, 0.67 and 95% CI, 0.59 to 0.77; aspirin and &bgr;-blockers, HR, 0.61 and 95% CI, 0.57 to 0.65; and ACEIs among heart failure patients, HR, 0.75 and 95% CI, 0.67 to 0.84. Conclusions— Use of evidence-based therapies for CAD has improved but remains suboptimal. Although improved discharge prescription of these agents is needed, considerable attention must also be focused on understanding and improving long-term adherence.

Case reports of heart failure after therapy with a tumor necrosis factor antagonist.

Context Although tumor necrosis factor (TNF) antagonists were once considered as a possible treatment for heart failure, recent trials showed no benefit, and one trial showed worsening heart failure with TNF antagonist treatment. Contribution This analysis of data from the U.S. Food and Drug Administrations MedWatch program on 47 patients who developed heart failure while receiving long-term TNF antagonist therapy showed that 81% had never experienced heart failure before taking TNF antagonists. Half of the patients with new-onset heart failure had no identifiable heart failure risk factors, and 10 patients were younger than 50 years of age. Implications Clinicians should be aware that heart failure may occur in patients receiving TNF antagonists. The Editors More than a decade ago, Levine and colleagues (1) demonstrated increased serum levels of tumor necrosis factor (TNF) in patients with advanced heart failure. Torre-Amione and colleagues (2) later showed that TNF levels correlated with the severity of heart failure. Other experimental findings (3, 4) supported the role of TNF in heart failure, and early clinical studies of blocking TNF in patients with heart failure demonstrated promising results (5-7). However, large-scale randomized, placebo-controlled trials of etanercept for treatment of heart failure were stopped early because they failed to demonstrate an improvement in clinical heart failure or mortality (8). A phase II trial in 150 patients (101 taking infliximab and 49 taking placebo) who had New York Heart Association class III to IV heart failure showed excess mortality (7 deaths vs. 0 deaths) and hospitalization for worsening heart failure in the infliximab group (9). At the time of our study, two TNF antagonists, etanercept and infliximab, were approved for use in the United States. Etanercept (Amgen, Thousand Oaks, California) is a recombinant, soluble TNF type 2 receptor that binds and inhibits TNF and is used to treat rheumatoid, juvenile rheumatoid, and psoriatic arthritis. Infliximab (Centocor, Malvern, Pennsylvania) is a chimeric monoclonal antibody against TNF- and is used to treat Crohn disease and, in combination with methotrexate, rheumatoid arthritis. Neither product is indicated for the prevention or treatment of heart failure. As of July 2001, 104 000 patients had been treated with etanercept and 170 000 patients had been treated with infliximab worldwide (10). Because controlled trials in patients with heart failure showed no benefit of TNF antagonists and, in the case of the infliximab trial, suggested worse outcome, we examined spontaneous adverse event reports to the U.S. Food and Drug Administration (FDA)s MedWatch system for evidence that TNF antagonists can exacerbate heart failure or promote new-onset heart failure. Methods The FDAs MedWatch program receives reports of adverse events related to FDA-licensed products after the products are marketed to the general population (11). Adverse event reports are submitted by manufacturers, physicians, other health care workers, consumers, and others. Except for manufacturers, reporting is voluntary, and the proportion of all adverse events reported to MedWatch is unknown (12). Using the high-level group term heart failures from the Medical Dictionary for Regulatory Activities, we searched MedWatch records for adverse event reports of heart failure among patients receiving etanercept or infliximab from the time of licensure through February 2002. We included both patients with new-onset heart failure and patients with exacerbation of preexisting heart failure after administration of a TNF antagonist. We excluded heart failure reports that were temporally associated with other heart failureinciting events (such as myocardial infarction, infection, pulmonary embolism, or atrial fibrillation). A cardiologist reviewed each report and determined that the available evidence supported the diagnosis of heart failure. Since patients younger than 50 years of age are relatively unlikely to develop heart failure due to traditional risk factors (that is, coronary artery disease, hypertension, and valvular abnormalities), we contacted reporting physicians of patients younger than 50 years of age to collect information on predisposing factors, tests of left ventricular function (for example, echocardiography), and clinical course and outcome. The funding sources had no role in the design, conduct, or reporting of this study. Results Forty-seven patients had heart failure after receiving TNF antagonists. Thirty-eight (81%) developed new-onset heart failure, and 9 (19%) experienced heart failure exacerbations (Table 1). The median age was 62 years (range, 19 to 87 years) for patients with new-onset heart failure and 70 years (range, 57 to 74 years) for patients with heart failure exacerbation. Twenty-eight of 38 patients who developed new-onset heart failure (74%) were age 50 years or older. Twenty-nine of 38 patients with new-onset heart failure (76%) and all patients with heart failure exacerbation were receiving a TNF antagonist for rheumatoid arthritis. Of the 38 patients who reported new-onset heart failure, 19 (50%) had no identifiable traditional risk factor for heart failure (previous myocardial infarction, coronary heart disease, hypertension, or diabetes). The median interval from the first dose of TNF antagonist to a diagnosis of new-onset heart failure or heart failure exacerbation was 3.5 months (range, 24 hours to 24 months) and 4 months (range, 24 hours to 20 months), respectively. Table 1. Summary Characteristics of Heart Failure Reported with Use of Tumor Necrosis Factor Antagonists All 10 patients younger than 50 years of age (range, 19 to 48 years of age) developed new-onset heart failure after receiving TNF antagonists. Table 2 provides clinical summaries of these cases. Six patients received infliximab, and 4 patients received etanercept. Echocardiography data were obtained in 9 of 10 patients and demonstrated decreased ejection fraction, with a median ejection fraction of 0.2 (range, 0.1 to 0.45); the remaining patient was included on a clinical basis alone. Three patients reported an underlying risk factor for heart failure: Two taking etanercept had diabetes, and 1 taking infliximab had hypertension. The median time to heart failure diagnosis in patients younger than 50 years of age was 3.5 months (range, 24 hours to 6 months) for those who received infliximab and 8.5 months (range, 5 months to 17 months) for those who received etanercept. Table 2. Characteristics of New-Onset Heart Failure in Patients Younger Than 50 Years of Age Nine of these 10 patients were reported to have discontinued TNF antagonist therapy after heart failure diagnosis. It was not known whether TNF antagonist therapy was discontinued in the remaining patient. Following heart failure treatment, 3 patients reported complete resolution of heart failure, 6 patients reported improvement, and 1 patient died. Three of the 6 patients whose heart failure improved had documented risk factors for heart failure. Discussion This is one of the first case series of new-onset heart failure temporally associated with TNF antagonists. The cases detailed here, taken together with recent data from clinical trials, suggest that TNF antagonists might induce heart failure in a subset of patients. However, because the incidence and history of heart failure are not well described in the populations receiving these drugs, these spontaneous reports alone are not sufficient to make causal inferences. Our understanding of the pathophysiology of chronic heart failure has evolved over the past two decades. Although originally thought to be due primarily to hemodynamic derangement, it is now considered a syndrome mostly influenced by activation of the sympathetic nervous system and neurohormonal axis (reninangiotensin system). Neurohormonal activation initially provides appropriate compensatory mechanisms for an acute decrease in cardiac output, but its long-term consequences are maladaptive. Inflammatory cytokines, such as TNF, are also overproduced in chronic heart failure and are thought to correspond to a similarly maladaptive inflammatory process (1, 2). However, although elevated circulating TNF levels are noted in patients with severe heart failure and this overproduction appears to be largely cardiac in origin (13), heart failure, unlike arthritis and Crohn disease, is not principally an inflammatory process. The syndrome of heart failure and the systemic response to myocardial injury are complex, with noninflammatory features particularly prominent. The recent failures of infliximab and etanercept (9, 14) to demonstrate benefit in heart failure illustrate this complexity. It is rare for inflammatory bowel diseases to have cardiac effects. However, cardiovascular disease is a recognized extra-articular complication of rheumatoid arthritis, usually due to an increase in premature coronary atherosclerosis or, more rarely, active vasculitis (15). Although we excluded cases of new or worsening heart failure with concomitant myocardial infarction, underlying rheumatoid arthritis or other comorbid conditions may have contributed to heart failure in some older patients. Finally, it is possible that some of these reported heart failure events occurred by chance. In the general U.S. population, the prevalence of heart failure is reported to be 2% among persons age 40 to 59 years and more than 5% among persons age 60 to 69 years (16). Given the number of persons exposed to TNF antagonist therapy, these prevalence figures suggest that coincidental heart failure among TNF antagonist recipients is a possibility. Nevertheless, the resolution or improvement of heart failure after withdrawal of TNF antagonists and administration of heart failure treatment in 9 younger patients (<50 years of age) shows that there may be a causal connection. Given the underreporting common in spontaneous

Using Inverse Probability-Weighted Estimators in Comparative Effectiveness Analyses With Observational Databases

Inverse probability-weighted estimation is a powerful tool for use with observational data. In this article, we describe how this propensity score-based method can be used to compare the effectiveness of 2 or more treatments. First, we discuss the inherent problems in using observational data to assess comparative effectiveness. Next, we provide a conceptual explanation of inverse probability-weighted estimation and point readers to sources that address the method in more formal, technical terms. Finally, we offer detailed guidance about how to implement the estimators in comparative effectiveness analyses.

Rethinking Randomized Clinical Trials for Comparative Effectiveness Research: The Need for Transformational Change

Join the dialogue on health care reform. Comment on the perspectives published in Annals and offer ideas of your own. All thoughtful voices should be heard. While advances in medical science have led to continued improvements in medical care and health outcomes, evidence of the comparative effectiveness of alternative management options remains inadequate for informed medical care and health policy decision making. The result is frequently suboptimal and inefficient care as well as unsustainable costs. To enhance or at least maintain quality of care as health reform and cost containment occurs, better evidence of comparative clinical and cost-effectiveness is required (1). The American Recovery and Reinvestment Act of 2009 allocated a

Characteristics of Clinical Trials Registered in ClinicalTrials.gov, 2007-2010

1.1 billion down payment to support comparative effectiveness research (CER) (2). Although comparative effectiveness can be informed by synthesis of existing clinical information (systematic reviews, meta-analysis, and decision modeling) and analysis of observational data (administrative claims, electronic medical records, registries and other clinical cohorts, and casecontrol studies), randomized clinical trials (RCTs) are the most rigorous method of generating comparative effectiveness evidence and will necessarily occupy a central role in an expanded national CER agenda. However, as currently designed and conducted, many RCTs are ill suited to meet the evidentiary needs implicit in the IOM definition of CER: comparison of effective interventions among patients in typical patient care settings, with decisions tailored to individual patient needs (3). Without major changes in how we conceive, design, conduct, and analyze RCTs, the nation risks spending large sums of money inefficiently to answer the wrong questionsor the right questions too late. This article addresses several fundamental limitations of traditional RCTs for meeting CER objectives and offers 3 potentially transformational approaches to enhance their operational efficiency, analytical efficiency, and generalizability for CER. Enhancing Structural and Operational Efficiency As currently conducted, RCTs are inefficient and have become more complex, time consuming, and expensive. More than 90% of industry-sponsored clinical trials experience delayed enrollment (4). In a study comparing 28 industry-sponsored trials started between 1999 and 2002 with 29 trials started between 2003 and 2006, the time from protocol approval to database lock increased by a median of 70% (4). Several organizations have sought to streamline study start-up. In response to an analysis in Cancer and Leukemia Group B that found a median of 580 days from concept approval to phase 3 study activation (5), the National Cancer Institute established an operational efficiency working group to reduce study activation time by at least 50%, increase the proportion of studies reaching accrual targets, and improve timely study completion (6). The National Institutes of Healths Clinical and Translational Science Award recipients are documenting study start-up metrics as a first step to fostering improvements (7). The National Cancer Institute, the CEO Roundtable, Cancer Centers, and Cooperative Groups developed standard terms for clinical trial agreements as a starting point for negotiations between study sponsors and clinical sites (8). The Institute of Medicines Drug Forum also commissioned development of a template clinical research agreement (9). Through its Critical Path Program, the U.S. Food and Drug Administration (FDA) established the Clinical Trials Transformation Initiative (CTTI), a publicprivate partnership whose goal is to improve the quality and efficiency of clinical trials (10). The CTTI is hosted by Duke University and has broad representation from more than 50 member organizations, including academia, government, industry, clinical investigators, and patient advocates (11). The CTTI works by generating empirical data on how clinical trials are currently conducted and how they may be improved. Initial priorities for study include design principles, data quality and quantity (including monitoring), study start-up, and adverse event reporting. One of CTTIs projects is addressing site monitoring, an area that has been estimated to absorb 25% to 30% of phase 3 trial costs (12) and for which there is widespread agreement that improved efficiency is needed. The CTTI is determining the current range of monitoring practices for RCTs used by the National Institutes of Health, academic institutions, and industry; assessing the quality objectives of monitoring; and determining the performance of various monitoring practices in meeting quality objectives. This project will provide criteria to help sponsors select the most appropriate monitoring methods for a trial, thereby improving quality while optimizing resources. Collectively, these efforts are generating empirical evidence and developing the mechanisms to improve clinical trial efficiency. In conjunction with other improvements, including those described below, the resulting changes in clinical trial practices will increase the feasibility of mounting the scale and scope of RCTs required to evaluate the comparative effectiveness of medical care. Analytical Efficiency: The Potential Role of Bayesian and Adaptive Approaches The traditional frequentist school has provided a solid foundation for medical statistics. But the artificial division of results into significant and nonsignificant is better suited for one-time dichotomous decisions, such as regulatory approval, and is not the best model for comparing interventions as evidence accumulates over time, as occurs in a dynamic medical care system. With traditional trials and analytical methods, it is difficult to make optimal use of relevant existing, ancillary, or new evidence as it arises during a trial, and thus such methods often are not well suited to facilitate clinical and policy decision making. Furthermore, real-world CER can be noisier than a standard RCT. Standard statistical techniques require increased sample sizes, in part because of the resulting additional variability and in part when trials compare several active treatments whose effectiveness differs by relatively small amounts. Designs that use features that change or adapt in response to information generated during the trial can be more efficient than standard approaches. Although many standard RCTs are adaptive in limited ways (for example, those with interim monitoring and stopping rules), the frequentist paradigm inhibits adaptation because of the requirement to prespecify all possible study outcomes, which in turn requires some rigidity in design. The Bayesian approach, using formal, probabilistic statements of uncertainty based on the combination of all sources of information both from within and outside a study, prespecifies how information from various sources will be combined and how the design will change while controlling the probability of false-positive and false-negative conclusions (13). Bayesian and adaptive analytical approaches can reduce the sample size, time, and cost required to obtain decision-relevant information by incorporating existing high-quality external evidence (such as information from pivotal trials, systematic reviews, models, and rigorously conducted observational studies) into CER trial design and drawing on observed within-trial end point relationships. If new interventions become available, adaptive RCT designs can allow these interventions to be added and less effective ones dropped without restarting the trial; therefore, at any given time, the trial is comparing the alternatives most relevant to current clinical practice. This dynamic learning adaptive feature (analogous to the Institute of Medicine Evidence-Based Medicine Roundtables learning health care system [14]) improves both the timeliness and clinical relevance of trial results. The following example shows how this model operates. A standard comparative effectiveness trial design of 4 alternative strategies for HIV infection treatment starts with the hypothesis of equal effectiveness of all 4 treatments. In contrast, as the trial progresses, the Bayesian approach answers the pragmatic questions: What is the probability that the favored therapy is the best of the 4 therapies? and What is the probability that the currently worst therapy will turn out to be best? (15). If this latter probability is low enough, the trialists can drop that treatment even if it is not, by conventional statistical testing, worse than other treatments. Newly developed HIV treatment strategies also can enter the trial, thus focusing patient resources on the most relevant treatment comparison. Bayesian and adaptive designs are particularly useful for rapidly evolving interventions (such as devices, procedures, practices, and systems interventions), especially when outcomes occur soon enough to permit adaptation of the trial design. They should also prove useful for clinical studies generated by such conditional coverage schemes as Medicares Coverage with Evidence Development policy by adding onto an existing evidence base and adapting studies into community care settings of interest to payers and patients (16, 17). Random allocation need not be equal between trial arms or patient subgroups. Probabilities of each intervention being the best can be updated and random allocation probabilities revised, so that more patients are allocated to the most promising strategies as evidence accumulates. This flexibility can also permit Bayesian trials to focus experimentation on clinically relevant subgroups, which could facilitate tailoring strategies to particular patients, a key element of CER. Experience with Bayesian adaptive approaches has been growing in recent years. Early-phase cancer trials are commonly performed using Bayesian designs (18). In 2005, the FDA released a draft guidance document for the u

Effect of Gender on the Outcomes of Contemporary Percutaneous Coronary Intervention

CONTEXT Recent reports highlight gaps between guidelines-based treatment recommendations and evidence from clinical trials that supports those recommendations. Strengthened reporting requirements for studies registered with ClinicalTrials.gov enable a comprehensive evaluation of the national trials portfolio. OBJECTIVE To examine fundamental characteristics of interventional clinical trials registered in the ClinicalTrials.gov database. METHODS A data set comprising 96,346 clinical studies from ClinicalTrials.gov was downloaded on September 27, 2010, and entered into a relational database to analyze aggregate data. Interventional trials were identified and analyses were focused on 3 clinical specialties-cardiovascular, mental health, and oncology-that together encompass the largest number of disability-adjusted life-years lost in the United States. MAIN OUTCOME MEASURES Characteristics of registered clinical trials as reported data elements in the trial registry; how those characteristics have changed over time; differences in characteristics as a function of clinical specialty; and factors associated with use of randomization, blinding, and data monitoring committees (DMCs). RESULTS The number of registered interventional clinical trials increased from 28,881 (October 2004-September 2007) to 40,970 (October 2007-September 2010), and the number of missing data elements has generally declined. Most interventional trials registered between 2007 and 2010 were small, with 62% enrolling 100 or fewer participants. Many clinical trials were single-center (66%; 24,788/37,520) and funded by organizations other than industry or the National Institutes of Health (NIH) (47%; 17,592/37,520). Heterogeneity in the reported methods by clinical specialty; sponsor type; and the reported use of DMCs, randomization, and blinding was evident. For example, reported use of DMCs was less common in industry-sponsored vs NIH-sponsored trials (adjusted odds ratio [OR], 0.11; 95% CI, 0.09-0.14), earlier-phase vs phase 3 trials (adjusted OR, 0.83; 95% CI, 0.76-0.91), and mental health trials vs those in the other 2 specialties. In similar comparisons, randomization and blinding were less frequently reported in earlier-phase, oncology, and device trials. CONCLUSION Clinical trials registered in ClinicalTrials.gov are dominated by small trials and contain significant heterogeneity in methodological approaches, including reported use of randomization, blinding, and DMCs.

Early and Long-term Outcomes of Heart Failure in Elderly Persons, 2001-2005

Limited information exists regarding the outcomes of newer percutaneous coronary intervention (PCI) technologies in women. This study sought to determine whether female gender is an independent risk factor for PCI mortality and/or complications in contemporary practice. Using information from the National Cardiovascular Network (NCN) Database on 109,708 (33% women) PCI cases from 22 hospitals between January 1994 and January 1998, we examined the association of gender with unadjusted and risk-adjusted procedural outcomes. Women undergoing PCI were older, smaller, and had more comorbid illness than men, but less extensive coronary disease. Temporal trends in PCI device selection were similar in men and women. Compared with men, women had higher unadjusted procedural mortality rates (1.8% vs 1.0%, p <0.001), more strokes (0.4% vs 0.2%, p <0.001), and higher vascular complication rates (5.4% vs 2.7%, p <0.001). However, after adjusting for baseline clinical risk factors, and importantly, body surface area, women and men had similar PCI mortality risks (adjusted odds ratio 1.07, 95% confidence interval 0.92 to 1.24). Gender was not an independent risk factor for mortality among subgroups receiving coronary stent or atherectomy devices after risk adjustment. However, women undergoing PCI remained at higher risk for stroke, vascular complications, and repeat in-hospital revascularization than men, even after risk adjustment. We conclude that in contemporary practice, a patients body size rather than gender, conveys independent risk for mortality after PCI.

Balancing the Benefits and Risks of Inhaled Long-Acting Beta-Agonists — The Influence of Values

BACKGROUND The treatment of chronic heart failure has improved during the past 2 decades, but little is known about whether the improvements are reflected in trends in early and long-term mortality and hospital readmission. METHODS In a retrospective cohort study of 2 540 838 elderly Medicare beneficiaries hospitalized with heart failure between January 1, 2001, and December 31, 2005, we examined early and long-term all-cause mortality and hospital readmission and patient- and hospital-level predictors of these outcomes. RESULTS Unadjusted in-hospital mortality declined from 5.1% to 4.2% during the study (P < .001), but 30-day, 180-day, and 1-year all-cause mortality remained fairly constant at 11%, 26%, and 37%, respectively. Nearly 1 in 4 patients were readmitted within 30 days of the index hospitalization, and two-thirds were readmitted within 1 year. Controlling for patient- and hospital-level covariates, the hazard of all-cause mortality at 1 year was slightly lower in 2005 than in 2001 (hazard ratio, 0.98; 95% confidence interval, 0.97-0.99). The hazard of readmission did not decline significantly from 2001 to 2005 (hazard ratio, 0.99; 95% confidence interval, 0.98-1.00). CONCLUSIONS Early and long-term all-cause mortality and hospital readmission rates remain high and have improved little with time. The need to identify optimal management strategies for these clinically complex patients is urgent.

Underuse of Aspirin in a referral population with documented coronary artery disease

In December 2008, the FDA reviewed the risks and benefits of inhaled long-acting beta-agonists for the treatment of asthma in adults and children. Dr. Judith Kramer writes that the challenge of protecting the publics health is heightened by variability in the values placed on benefits and risks.