Empagliflozin in patients post myocardial infarction rationale and design of the EMPACT-MI trial

Background : Patients with acute myocardial infarction (MI) are at risk for developing heart failure (HF) and subsequently are at an increased risk of mortality. Sodium-glucose cotransporter-2 inhibitors have been proven to improve outcomes in patients with HF with reduced ejection fraction, and, in the case of empagliflozin, in HF with preserved ejection fraction even without diabetes, but their efficacy and safety in the post-MI population has not yet been evaluated. Methods : The EMPACT-MI trial will evaluate the safety and efficacy of empagliflozin compared with placebo in patients hospitalized for MI with or at high risk of new onset HF, in addition to standard care. EMPACT-MI is a streamlined, multinational, randomized, double-blind, placebo-controlled trial randomizing 5,000 participants at approximately 480 centers in 22 countries. Eligible patients presenting with spontaneous MI must have new signs or symptoms of pulmonary congestion requiring treatment or new left ventricular dysfunction (LVEF<45%), and at least one additional risk factor for development of future HF. Eligible and consenting patients are randomized to empagliflozin 10mg or placebo daily in addition to standard of care within 14 days of hospital admission for MI. The primary composite endpoint is time to first hospitalization for HF or all-cause mortality. Conclusions : EMPACT-MI will inform clinical practice regarding the role of empagliflozin in patients after an MI with high risk for the development of future HF and mortality

Baseline characteristics of patients enrolled in the EMPACT‐MI trial

Aims: Empagliflozin has been shown to reduce the risk of adverse cardiovascular outcomes in patients with type 2 diabetes and in those with heart failure. The impact of empagliflozin in post-acute myocardial infarction (AMI) patients is unknown. Methods and results: The Study to Test the Effect of Empagliflozin on Hospitalization for Heart Failure and Mortality in Patients with Acute Myocardial Infarction (EMPACT-MI) trial screened 6610 participants with AMI and randomized 6522 to empagliflozin or placebo in addition to standard of care. The median (interquartile) age was 64 (56–71) years and 75.1% of patients were male. Major comorbidities included hypertension (69.1%), type 2 diabetes (31.7%), prior myocardial infarction (13.0%), and atrial fibrillation (10.9%). The majority (74.3%) of patients presented with an ST-elevation myocardial infarction. Overall, 56.9% of patients had acute signs or symptoms of congestion requiring treatment and 78.3% had left ventricular systolic dysfunction with ejection fraction <45%. Clinical characteristics, including baseline demographics, rates of revascularization, and cardiovascular medications at discharge were largely comparable to recent trials of the post-AMI population. Conclusion: The EMPACT-MI trial will establish the benefit and risks of empagliflozin treatment in patients with AMI

Effect of empagliflozin on heart failure outcomes after acute myocardial infarction: insights from the EMPACT-MI trial

Background: Empagliflozin reduces the risk of heart failure events in patients with type 2 diabetes at high cardiovascular risk, chronic kidney disease, and in those with prevalent heart failure irrespective of ejection fraction. While EMPACT-MI showed empagliflozin does not reduce the risk of the composite of hospitalization of heart failure and all-cause mortality, the impact of empagliflozin on first and recurrent heart failure events in patients after myocardial infarction is unknown. Methods: EMPACT-MI was a double-blind, randomized, placebo-controlled, event-driven trial that randomized 6522 patients hospitalized for acute myocardial infarction at risk for heart failure based on newly developed left ventricular ejection fraction of <45% and/or signs or symptoms of congestion to receive empagliflozin 10 mg daily or placebo within 14 days of admission. In prespecified secondary analyses, treatment groups were analyzed for heart failure outcomes. Results: Over a median of follow-up of 17.9 months, the risk for first heart failure hospitalization and total heart failure hospitalizations was significantly lower in the empagliflozin compared with the placebo group (118 (3.6%) vs. 153 (4.7%) patients with events, HR 0.77 [95% CI 0.60, 0.98], P=0.031 for first heart failure hospitalization and 148 vs. 207 events, RR 0.67 [95% CI 0.51, 0.89], P=0.006 for total heart failure hospitalizations). Subgroup analysis showed consistency of empagliflozin benefit across clinically relevant patient subgroups for first and total heart failure hospitalizations. Post-discharge need for new use of diuretics, renin-angiotensin modulators, and mineralocorticoid receptor antagonists were less in patients randomized to empagliflozin than placebo (all p<0.05). Conclusions: In patients after acute myocardial infarction with left ventricular dysfunction or congestion, empagliflozin reduced the risk of heart failure

Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future

Purpose Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. Design Meta-analysis of prevalence data. Participants A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. Methods AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). Main Outcome Measures Prevalence of early and late AMD, BCVA, and number of AMD cases. Results Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%–5.0%) in those aged 55–59 years to 17.6% (95%

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques

Selected genes in the KIRC data.

<p>Median variance of selected genes plotted against the number of selected genes in 50 resampling datasets. We used a smoothing spline on the scatterplot for better visualization of the association.</p

Prediction error for the KIRC and AML data.

<p>The 0.632+ estimator for the prediction error in terms of the Brier Score. The solid black line is the prediction error of the Kaplan-Meier estimate which does not include clinical information nor RNA-Seq data, the dashed black line the prediction error of the clinical model. A: CoxBoost model used for prediction on KIRC data. B: Lasso used for prediction on KIRC data. C: CoxBoost model used for prediction on AML data. D: Lasso model used for prediction on AML data.</p

RNA-Seq of KIRC data.

<p>A: Scatterplot for all DESeq-normalized counts: Mean vs. variance. The larger the mean value, the larger the variance. The red dot is a randomly chosen gene called B3GNT3. B: Histogram of DESeq-normalized counts for gene B3GNT3. The distribution is skewed and has extreme values. C: 1000 highest gene-gene correlations for the original data compared to the same gene-gene correlations for data in which we truncated the extreme values.</p

Areas under the curve for the simulation study.

<p>A: 10 genes have a linear effect on the patient outcome. B: 20 genes have a linear effect. C: 10 genes have a logarithmic effect. D: 20 genes have a logarithmic effect.</p