Inhibition of myeloperoxidase to treat left ventricular dysfunction in non-ischaemic cardiomyopathy.

Aims: Non-ischaemic cardiomyopathy (NICMP), an incurable disease terminating in systolic heart failure (heart failure with reduced ejection fraction [HFrEF]), causes immune activation, however anti-inflammatory treatment strategies so far have failed to alter the course of this disease. Myeloperoxidase (MPO), the principal enzyme in neutrophils, has cytotoxic, pro-fibrotic and nitric oxide oxidizing effects. Whether MPO inhibition ameliorates the phenotype in NICMP remains elusive.

Sparse Group Penalties for bi-level variable selection.

Many data sets exhibit a natural group structure due to contextual similarities or high correlations of variables, such as lipid markers that are interrelated based on biochemical principles. Knowledge of such groupings can be used through bi-level selection methods to identify relevant feature groups and highlight their predictive members. One of the best known approaches of this kind combines the classical Least Absolute Shrinkage and Selection Operator (LASSO) with the Group LASSO, resulting in the Sparse Group LASSO.

Interpretability of bi-level variable selection methods.

Variable selection is usually performed to increase interpretability, as sparser models are easier to understand than full models. However, a focus on sparsity is not always suitable, for example, when features are related due to contextual similarities or high correlations. Here, it may be more appropriate to identify groups and their predictive members, a task that can be accomplished with bi-level selection procedures.

Heart rate variability: reference values and role for clinical profile and mortality in individuals with heart failure.

Aims: To establish reference values and clinically relevant determinants for measures of heart rate variability (HRV) and to assess their relevance for clinical outcome prediction in individuals with heart failure.

Methods: Data from the MyoVasc study (NCT04064450; N = 3289), a prospective cohort on chronic heart failure with a highly standardized, 5 h examination, and Holter ECG recording were investigated. HRV markers were selected using a systematic literature screen and a data-driven approach.

A systematic review and evaluation of statistical methods for group variable selection.

This review condenses the knowledge on variable selection methods implemented in R and appropriate for datasets with grouped features. The focus is on regularized regressions identified through a systematic review of the literature, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 14 methods are discussed, most of which use penalty terms to perform group variable selection.

FEV Predicts Cardiac Status and Outcome in Chronic Heart Failure.

Background: COPD is an established predictor of clinical outcome in patients with chronic heart failure (HF). However, little evidence is available about the predictive value of FEV in chronic HF.

Research Question: Is pulmonary function related to the progression of chronic HF?

Study Design And Methods: The MyoVasc study (ClinicalTrials.

Chronic venous insufficiency, cardiovascular disease, and mortality: a population study.

Aims: Evidence regarding the health burden of chronic venous insufficiency (CVI), its clinical determinants, and impact on outcome is scarce.

Methods And Results: Systematic phenotyping of CVI according to established CEAP (Clinical-Etiologic-Anatomic-Pathophysiologic) classification was performed in 12 423 participants (age range: 40-80 years) of the Gutenberg Health Study from April 2012 to April 2017. Prevalence was calculated age- and sex-specifically.