A 15 year old youth, who presented with out-of-hospital cardiac arrest due to documented ventricular fibrillation, was found to have nonobstructive hypertrophic cardiomyopathy. Electrophysiologic study demonstrated inducible sustained atrial fibrillation with a rapid ventricular response. This rhythm, associated with hypotension and evidence of myocardial ischemia, spontaneously degenerated into ventricular fibrillation. No ventricular arrhythmias were inducible by programmed ventricular stimulation. Therapy with metoprolol and verapamil slowed the ventricular rate during atrial fibrillation and maintained hemodynamic stability, both during follow-up electrophysiologic study and during a subsequent spontaneous episode.
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http://dx.doi.org/10.1016/s0735-1097(86)80484-3 | DOI Listing |
Acta Neurochir (Wien)
January 2025
Department of Neurosurgery, Helsinki University Hospital and University of Helsinki, Haartmaninkatu 4, Po Box 320, 00029 HUS, Helsinki, Finland.
Purpose: A substantial proportion of patients undergoing surgery for chronic subdural hematoma (CSDH) use anticoagulation medication due to atrial fibrillation (AF). We assessed the risk of postoperative thromboembolic and hemorrhagic complications in CSDH surgery patients with a history of anticoagulation for AF and their association with outcome.
Methods: This posthoc analysis of a nationwide multicenter randomized controlled trial conducted during 2020-2022 included CSDH patients undergoing surgery with a history of preoperative anticoagulation use for AF.
Routine use of genetic data in healthcare is much-discussed, yet little is known about its performance in epidemiological models including traditional risk factors. Using severe COVID-19 as an exemplar, we explore the integration of polygenic risk scores (PRS) into disease models alongside sociodemographic and clinical variables. PRS were optimized for 23 clinical variables and related traits previously-associated with severe COVID-19 in up to 450,449 UK Biobank participants, and tested in 9,560 individuals diagnosed in the pre-vaccination era.
View Article and Find Full Text PDFHeart Rhythm
January 2025
Cardiology Department, Tulane University School of Medicine, New Orleans, Louisiana, United States. Electronic address:
Background: Causal machine learning (ML) provides an efficient way of identifying heterogeneous treatment effect groups from hundreds of possible combinations, especially for randomized trial data.
Objective: The aim of this paper is to illustrate the potential of applying causal ML on the DECAAF II trial data. We proposed a causal ML model to predict the treatment response heterogeneity.
BMC Cardiovasc Disord
January 2025
ITACA Institute, Universitat Politècnica de València, València, Spain.
Background: Complexity and signal recurrence metrics obtained from body surface potential mapping (BSPM) allow quantifying atrial fibrillation (AF) substrate complexity. This study aims to correlate electrocardiographic imaging (ECGI) detected reentrant patterns with BSPM-calculated signal complexity and recurrence metrics.
Methods: BSPM signals were recorded from 28 AF patients (17 male, 11 women, 62.
Eur J Prev Cardiol
January 2025
Department of Invasive Cardiology, Medical University of Bialystok, Bialystok, Poland.
Aim: Air pollution remains the single largest environmental health risk factor, while atrial fibrillation (AF) is the most prevalent arrhythmia globally. The study aimed to investigate the relationship between short-term exposure to air pollution and acute AF admissions.
Methods: Individual data on AF hospitalization in the years 2011-2020 were collected from the National Health Fund in Poland (ICD-10: I48.
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