Publications by authors named "K Dickstein"
Aims: Iron deficiency (ID) is highly prevalent in patients with heart failure (HF) and associated with morbidity and poor prognosis, but pathophysiological mechanisms are unknown. We aimed to identify novel biological pathways affected by ID.
Methods And Results: We studied 881 patients with HF from the BIOSTAT-CHF cohort.
Article Synopsis
- The study aims to use machine learning clustering to categorize distinct patient types among those with ischaemic heart failure and reduced ejection fraction (HFrEF) to improve personalized treatment approaches.
- Analysis of 8,591 HFrEF patients revealed five unique clusters based on clinical and biological traits, with varying risks for hospitalization and death, highlighting the need for tailored management strategies.
- The findings indicate that specific clusters correlate with different outcomes, suggesting that treatments like mineralocorticoid receptor antagonists may be more beneficial for certain patient groups, ultimately enhancing patient care in the future.
Aims: Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in selected patients with heart failure (HF) and electrical dyssynchrony. This treatment receives class IA recommendations in European Society of Cardiology (ESC) guidelines. However, despite these strong recommendations, CRT implantation practice varies greatly in Europe.
View Article and Find Full Text PDFBackground: Outcomes of hospitalized patients with heart failure (HF) and characteristics of advanced HF stage may vary across left ventricular ejection fraction (LVEF) and world regions.
Objectives: This study sought to analyze characteristics of hospitalized advanced HF patients across LVEF spectrum, world regions, and country income.
Methods: Among 18,553 hospitalized patients with acute HF (7,902 new-onset HF and 10,651 decompensated chronic HF) enrolled in the global registry REPORT-HF (International Registry to Assess Medical Practice With Longitudinal Observation for Treatment of Heart Failure), we analyzed characteristics and outcomes of patients with advanced HF, defined as previously diagnosed HF; severe symptoms before current admission (NYHA functional class III/IV); and ≥1 HF-related hospitalization in the preceding 12 months, excluding the current.
Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset.
Eur Heart J Digit Health
September 2024
Aims: We aimed to externally validate the SEMMELWEIS-CRT score for predicting 1-year all-cause mortality in the European Cardiac Resynchronization Therapy (CRT) Survey I dataset-a large multi-centre cohort of patients undergoing CRT implantation.
Methods And Results: The SEMMELWEIS-CRT score is a machine learning-based tool trained for predicting all-cause mortality in patients undergoing CRT implantation. This tool demonstrated impressive performance during internal validation but has not yet been validated externally.