Comparing efficacy and safety in catheter ablation strategies for atrial fibrillation: protocol of a network meta-analysis of randomised controlled trials.

INTRODUCTION: Atrial fibrillation (AF) is the most common sustained arrhythmia. Catheter ablation (CA) of AF is an increasingly offered therapeutic approach, primary to relieve AF-related symptoms. Despite the development of new ablation approaches, there is no consensus regarding the most efficient ablation strategy. The objective of this network meta-analysis (NMA) is to compare the efficacy and safety of all different CA approaches for the treatment of patients with paroxysmal (PAF) and non-PAF (non-PAF). METHODS AND ANALYSIS: We will perform a systematic search to identify randomised controlled trials of different CA approaches for the treatment of PAF and non-PAF, through the final search date of 1 March 2020. Information sources will include major bibliographic databases (MEDLINE, Web of Science and CENTRAL) and clinical trial registries. Our primary outcomes will be the efficacy (recurrence-free survival) and safety of different CA approaches for the treatment of AF. Secondary outcomes will be all-cause mortality and procedural time. An NMA will be performed to determine the relative effects of different catheter ablation approaches (such as pulmonary vein isolation alone or in combination with ablation lines, ablation of complex fractionated atrial electrograms, etc). In PAF, a separate analysis will be performed including different energy sources (such as radiofrequency, cryogenic and laser energy). Risk of bias assessment and sensitivity analyses will be conducted to assess the robustness of the findings to potential bias. ETHICS AND DISSEMINATION: No ethical approval will be needed because data are collected from previous studies. The results will be presented through peer-review journals and conference presentation. PROSPERO REGISTRATION NUMBER: CRD42020169494.

Implementation and verification of an enhanced algorithm for the automatic computation of RR-interval series derived from 24 h 12-lead ECGs.

An important tool in early diagnosis of cardiac dysfunctions is the analysis of electrocardiograms (ECGs) obtained from ambulatory long-term recordings. Heart rate variability (HRV) analysis became a significant tool for assessing the cardiac health. The usefulness of HRV assessment for the prediction of cardiovascular events in end-stage renal disease patients was previously reported. The aim of this work is to verify an enhanced algorithm to obtain an RR-interval time series in a fully automated manner. The multi-lead corrected R-peaks of each ECG lead are used for RR-series computation and the algorithm is verified by a comparison with manually reviewed reference RR-time series. Twenty-four hour 12-lead ECG recordings of 339 end-stage renal disease patients from the ISAR (rISk strAtification in end-stage Renal disease) study were used. Seven universal indicators were calculated to allow for a generalization of the comparison results. The median score of the indicator of synchronization, i.e. intraclass correlation coefficient, was 96.4% and the median of the root mean square error of the difference time series was 7.5 ms. The negligible error and high synchronization rate indicate high similarity and verified the agreement between the fully automated RR-interval series calculated with the AIT Multi-Lead ECGsolver and the reference time series. As a future perspective, HRV parameters calculated on this RR-time series can be evaluated in longitudinal studies to ensure clinical benefit.

Rationale and study design of the prospective, longitudinal, observational cohort study "rISk strAtification in end-stage renal disease" (ISAR) study.

BACKGROUND: The ISAR study is a prospective, longitudinal, observational cohort study to improve the cardiovascular risk stratification in endstage renal disease (ESRD). The major goal is to characterize the cardiovascular phenotype of the study subjects, namely alterations in micro- and macrocirculation and to determine autonomic function. METHODS/DESIGN: We intend to recruit 500 prevalent dialysis patients in 17 centers in Munich and the surrounding area. Baseline examinations include: (1) biochemistry, (2) 24-h Holter Electrocardiography (ECG) recordings, (3) 24-h ambulatory blood pressure measurement (ABPM), (4) 24 h pulse wave analysis (PWA) and pulse wave velocity (PWV), (5) retinal vessel analysis (RVA) and (6) neurocognitive testing. After 24 months biochemistry and determination of single PWA, single PWV and neurocognitive testing are repeated. Patients will be followed up to 6 years for (1) hospitalizations, (2) cardiovascular and (3) non-cardiovascular events and (4) cardiovascular and (5) all-cause mortality. DISCUSSION/CONCLUSION: We aim to create a complex dataset to answer questions about the insufficiently understood pathophysiology leading to excessively high cardiovascular and non-cardiovascular mortality in dialysis patients. Finally we hope to improve cardiovascular risk stratification in comparison to the use of classical and non-classical (dialysis-associated) risk factors and other models of risk stratification in ESRD patients by building a multivariable Cox-Regression model using a combination of the parameters measured in the study. CLINICAL TRIALS IDENTIFIER: ClinicalTrials.gov NCT01152892 (June 28, 2010).