The electrocardiogram (ECG) is one of the most accessible and comprehensive diagnostic tools used to assess cardiac patients at the first point of contact. Despite advances in computerized interpretation of the electrocardiogram (CIE), its accuracy remains inferior to physicians. This study evaluated the diagnostic performance of an artificial intelligence (AI)-powered ECG system and compared its performance to current state-of-the-art CIE. An AI-powered system consisting of 6 deep neural networks (DNN) was trained on standard 12‑lead ECGs to detect 20 essential diagnostic patterns (grouped into 6 categories: rhythm, acute coronary syndrome (ACS), conduction abnormalities, ectopy, chamber enlargement and axis). An independent test set of ECGs with diagnostic consensus of two expert cardiologists was used as a reference standard. AI system performance was compared to current state-of-the-art CIE. The key metrics used to compare performances were sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score. A total of 932,711 standard 12‑lead ECGs from 173,949 patients were used for AI system development. The independent test set pooled 11,932 annotated ECG labels. In all 6 diagnostic categories, the DNNs achieved high F1 scores: Rhythm 0.957, ACS 0.925, Conduction abnormalities 0.893, Ectopy 0.966, Chamber enlargement 0.972, and Axis 0.897. The diagnostic performance of DNNs surpassed state-of-the-art CIE for the 13 out of 20 essential diagnostic patterns and was non-inferior for the remaining individual diagnoses. Our results demonstrate the AI-powered ECG model's ability to accurately identify electrocardiographic abnormalities from the 12‑lead ECG, highlighting its potential as a clinical tool for healthcare professionals.

Recommendations on cardiac resynchronization therapy (CRT) in patients with atrial fibrillation or flutter (AF) are based on less robust evidence than those in sinus rhythm (SR). We aimed to assess the efficacy of CRT upgrade in the BUDAPEST-CRT Upgrade trial population by their baseline rhythm. Heart failure patients with reduced ejection fraction (HFrEF) and previously implanted pacemaker (PM) or implantable cardioverter defibrillator (ICD) and ≥20% right ventricular (RV) pacing burden were randomized to CRT with defibrillator (CRT-D) upgrade (n = 215) or ICD (n = 145). Primary [HF hospitalization (HFH), all-cause mortality, or <15% reduction of left ventricular end-systolic volume] and secondary outcomes were investigated. At enrolment, 131 (36%) patients had AF, who had an increased risk for HFH as compared with those with SR [adjusted hazard ratio (aHR) 2.99; 95% confidence interval (CI) 1.26–7.13; P = 0.013]. The effect of CRT-D upgrade was similar in patients with AF as in those with SR [AF adjusted odds ratio (aOR) 0.06; 95% CI 0.02–0.17; P < 0.001; SR aOR 0.13; 95% CI 0.07–0.27; P < 0.001; interaction P = 0.29] during the mean follow-up time of 12.4 months. Also, it decreased the risk of HFH or all-cause mortality (aHR 0.33; 95% CI 0.16–0.70; P = 0.003; interaction P = 0.17) and improved the echocardiographic response (left ventricular end-diastolic volume difference −49.21 mL; 95% CI −69.10 to −29.32; P < 0.001; interaction P = 0.21). In HFrEF patients with AF and PM/ICD with high RV pacing burden, CRT-D upgrade decreased the risk of HFH and improved reverse remodelling when compared with ICD, similar to that seen in patients in SR. In AF patients CRT-D upgrade reduced the risk of mortality or HF hospitalization as compared with ICD, additionally echocardiographic parameters, symptoms, and NT-proBNP levels improved. However, the risk of HF hospitalization was higher in AF patients when compared with SR. AF, atrial fibrillation or flutter; aOR, adjusted odds ratio; aHR, adjusted hazard ratio; CI, confidence interval; CRT-D, cardiac resynchronization therapy with defibrillator; ICD, implantable cardioverter defibrillator; HF, heart failure; HFrEF, heart failure with reduced ejection fraction; LVESV, left ventricular end-systolic volume; NT-proBNP, N-terminal pro b-type natriuretic peptide; PCI, percutaneous coronary intervention; PM, pacemaker; RV, right ventricular; SR, sinus rhythm.

Micro ribonucleic acids (miRNAs) are short non-coding RNA molecules responsible for regulation of gene expression. They are involved in many pathophysiological processes of a wide spectrum of diseases. Recent studies showed their involvement in atrial fibrillation. They seem to become potential screening biomarkers for atrial fibrillation and even treatment targets for this arrhythmia. The aim of this review article was to summarize the latest knowledge about miRNA and their molecular relation to the pathophysiology, diagnosis and treatment of atrial fibrillation.