Search Results (30)

Objectives: With the growing importance of mobile technology and artificial intelligence (AI) in healthcare, the development of automated cardiac diagnostic systems has gained strategic significance. This review aims to summarize the current state of knowledge on the use of AI in the analysis of electrocardiographic (ECG) signals obtained from wearable devices, particularly smartwatches, and to outline perspectives for future clinical applications. Methods: A narrative literature review was conducted using PubMed, Web of Science, and Scopus databases. The search focused on combinations of keywords related to AI, ECG, and wearable technologies. After screening and applying inclusion criteria, 152 publications were selected for final analysis. Conclusions: Modern AI algorithms—especially deep neural networks—show promise in detecting arrhythmias, heart failure, prolonged QT syndrome, and other cardiovascular conditions. Smartwatches without ECG sensors, using photoplethysmography (PPG) and machine learning, show potential as supportive tools for preliminary atrial fibrillation (AF) screening at the population level, although further validation in diverse real-world settings is needed. This article explores innovation trends such as genetic data integration, digital twins, federated learning, and local signal processing. Regulatory, technical, and ethical challenges are also discussed, along with the issue of limited clinical evidence. Artificial intelligence enables a significant enhancement of personalized, mobile, and preventive cardiology. Its integration into smartwatch ECG analysis opens a path toward early detection of cardiac disorders and the implementation of population-scale screening approaches. Full article

This research proposes to systematically investigate the cardioprotective mechanisms of Pericarpium Trichosanthis injection (PTI) against acute myocardial ischemia through an integrated approach combining ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) constituent profiling, UNIFI database-assisted component identification, network pharmacology-guided target prediction, molecular docking verification, and in vivo experimental validation. The multimodal methodology is designed to comprehensively uncover the therapeutic benefits and molecular pathways underlying this traditional Chinese medicine formulation. Methods: UPLC-Q-TOF/MS and the UNIFI database were used in conjunction with a literature review to screen and validate the absorbed components of PTI. Using network pharmacology, we constructed protein-protein interaction (PPI) networks for pinpointing prospective therapeutic targets. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify potential signaling pathways. In vivo experiments were conducted to investigate the mechanisms by which PTI ameliorated isoproterenol-induced myocardial injury in rats. All animal experiments have adhered to ARRIVE guidelines. Results: UPLC-Q-TOF/MS revealed 11 core active components in PTI. Network pharmacology prioritization identified pseudoaspidin, ciryneol C, cynanoside M, daurinol, and n-butyl-β-D-fructopyranoside as central bioactive constituents within the compound-target interaction network. Topological analysis of the protein interactome highlighted AKT1, EGFR, MMP9, SRC, PTGS2, STAT3, BCL2, CASP3, and MAPK3 as the most interconnected nodes with the highest betweenness centrality. Pathway enrichment analysis established the PI3K/Akt signaling cascade as the principal mechanistic route for PTI’s cardioprotective effects. Molecular docking simulations demonstrated high-affinity interactions between characteristic components (e.g., cynanoside M, darutigenol) and pivotal targets including PTGS2, MAPK3, CASP3, and BCL2. In vivo investigations showed PTI treatment markedly attenuated myocardial tissue degeneration and collagen deposition (p < 0.05), normalized electrocardiographic ST-segment deviations, and suppressed pro-inflammatory cytokine production (IL-6, TNF-α). The formulation concurrently reduced circulating levels of cardiac injury indicators (LDH, cTnI) and oxidative stress parameters (ROS, MDA), Regarding apoptosis regulation, PTI reduced Bax, caspase-3, and caspase-9, while elevating Bcl-2 (p < 0.05), effectively inhibiting myocardial cell apoptosis with all therapeutic outcomes reaching statistical significance. These findings highlight PTI’s protective effects against myocardial injury through multi-target modulation of inflammation, oxidation, and apoptosis. Conclusions: PTI exerts its therapeutic effects in treating acute myocardial ischemia by regulating and suppressing inflammatory responses, and inhibiting cardiomyocyte apoptosis. Full article

Background: Electrocardiographic (ECG) screening is crucial in pre-participation evaluations (PPEs) for elite athletes, aiding in the early detection of cardiac adaptations and potential risks. Elite female gymnasts experience unique cardiovascular adaptations due to intensive training, yet limited longitudinal data exist on their ECG evolution. This study introduces Oracle Crystal Ball, a predictive tool for forecasting ECG abnormalities and assessing PPE cost-effectiveness to optimize screening protocols. Methods: This retrospective cohort study analyzed ECG and cardiovascular parameters in twelve elite female gymnasts who underwent up to 14 PPEs over several years at the National Institute of Sports Medicine, Romania. Longitudinal ECG trends, training variables, and biochemical markers were examined using statistical analyses, including logistic regression, repeated measures ANOVA, and time-series forecasting (ARIMA). Monte Carlo simulations assessed the cost-effectiveness of 6-month vs. 12-month PPE schedules. Results: The athletes exhibited significant cardiovascular adaptations, including progressive declines in resting heart rate and training-induced ECG changes. Junctional escape rhythms and T-wave inversions (V1–V3) increased with age, requiring refined ECG interpretation. Predictive modeling demonstrated the feasibility of individualized risk stratification, while a cost-effectiveness analysis revealed that a 12-month PPE schedule was financially advantageous without reducing diagnostic accuracy. Conclusions: Longitudinal ECG monitoring and predictive analytics improve risk assessment in elite gymnasts. Oracle Crystal Ball enhances athlete-specific screening, minimizing unnecessary tests while ensuring early detection of clinically significant ECG changes. A 12-month PPE schedule is a cost-effective alternative for elite athletes. Full article

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, associated with significant morbidity, mortality, and healthcare burden. Despite advances in AF management, challenges persist in early detection, risk stratification, and treatment optimization, necessitating innovative solutions. Artificial intelligence (AI) has emerged as a transformative tool in AF care, leveraging machine learning and deep learning algorithms to enhance diagnostic accuracy, improve risk prediction, and guide therapeutic interventions. AI-powered electrocardiographic screening has demonstrated the ability to detect asymptomatic AF, while wearable photoplethysmography-based technologies have expanded real-time rhythm monitoring beyond clinical settings. AI-driven predictive models integrate electronic health records and multimodal physiological data to refine AF risk stratification, stroke prediction, and anticoagulation decision making. In the realm of treatment, AI is revolutionizing individualized therapy and optimizing anticoagulation management and catheter ablation strategies. Notably, AI-enhanced electroanatomic mapping and real-time procedural guidance hold promise for improving ablation success rates and reducing AF recurrence. Despite these advancements, the clinical integration of AI in AF management remains an evolving field. Future research should focus on large-scale validation, model interpretability, and regulatory frameworks to ensure widespread adoption. This review explores the current and emerging applications of AI in AF, highlighting its potential to enhance precision medicine and patient outcomes. Full article

Background: Obstructive sleep apnea (OSA) is a prevalent yet underdiagnosed condition associated with a major healthcare burden. Current diagnostic tools, such as full-night polysomnography (PSG), pose a limited accessibility to diagnosis due to their elevated costs. Recent advances in Artificial Intelligence (AI), including Machine Learning (ML) and deep learning (DL) algorithms, offer novel potential tools for an accurate OSA screening and diagnosis. This systematic review evaluates articles employing AI-powered models for OSA screening and diagnosis in the last decade. Methods: A comprehensive electronic search was performed on PubMed/MEDLINE, Google Scholar, and SCOPUS databases. The included studies were original articles written in English, reporting the use of ML algorithms to diagnose and predict OSA in suspected patients. The last search was performed in June 2024. This systematic review is registered in PROSPERO (Registration ID: CRD42024563059). Results: Sixty-five articles, involving data from 109,046 patients, met the inclusion criteria. Due to the heterogeneity of the algorithms, outcomes were analyzed into six sections (anthropometric indexes, imaging, electrocardiographic signals, respiratory signals, and oximetry and miscellaneous signals). AI algorithms demonstrated significant improvements in OSA detection, with accuracy, sensitivity, and specificity often exceeding traditional tools. In particular, anthropometric indexes were most widely used, especially in logistic regression-powered algorithms. Conclusions: The application of AI algorithms to OSA diagnosis and screening has great potential to improve patient outcomes, increase early detection, and lessen the load on healthcare systems. However, rigorous validation and standardization efforts must be made to standardize datasets. Full article

Since its first pathological description over 65 years ago, hypertrophic cardiomyopathy (HCM), with a worldwide prevalence of 1:500, has emerged as the most common genetically determined cardiac disease. Diagnostic work-up has dramatically improved over the last decades, from clinical suspicion and abnormal electrocardiographic findings to hemodynamic studies, echocardiography, contrast-enhanced cardiac magnetic resonance, and genetic testing. The implementation of screening programs and the use of implantable cardioverter defibrillators (ICDs) for high-risk individuals have notably reduced arrhythmic sudden deaths, altering the disease’s mortality profile. Therapeutic breakthroughs, including surgical myectomy, alcohol septal ablation, and the novel introduction of “myosin inhibitors”, have revolutionized symptom management and reduced progression to advanced heart failure (HF) and death. Despite this progress, refractory HF—both with preserved and reduced systolic function—has become the predominant cause of HCM-related mortality. While most patients with HCM experience a favorable clinical course with low morbidity and mortality, timely identification and targeted treatment of high-risk subgroups progressing toward progressive HF remain a pressing challenge, even for expert clinicians. Full article

Ventricular pre-excitation (VP) is a cardiac disorder characterized by the presence of an accessory pathway (AP) that bypasses the atrioventricular node (AVN), which, although often asymptomatic, exposes individuals to an increased risk of re-entrant supraventricular tachycardias and sudden cardiac death (SCD) due to rapid atrial fibrillation (AF) conduction. This condition is particularly significant in sports cardiology, where preparticipation ECG screening is routinely performed on athletes. Professional athletes, given their elevated risk of developing malignant arrhythmias, require careful assessment. Early identification of VP and proper risk stratification are crucial for determining the most appropriate management strategy and ensuring the safety of these individuals during competitive sports. Non-invasive tools, such as resting electrocardiograms (ECGs), ambulatory ECG monitoring, and exercise stress tests, are commonly employed, although their interpretation can sometimes be challenging. This review aims to provide practical tips and electrocardiographic clues for detecting VP beyond the classical triad (short PR interval, delta wave, and prolonged QRS interval) and offers guidance on non-invasive risk stratification. Although the diagnostic gold standard remains invasive electrophysiological study, appropriate interpretation of the ECG can help limit unnecessary referrals for young, often asymptomatic, athletes. Full article

PRKAG2 cardiomyopathy is a rare genetic disorder that manifests early in life with an autosomal dominant inheritance pattern. It harbors left ventricular hypertrophy (LVH), ventricular pre-excitation and progressively worsening conduction system defects. Its estimated prevalence among patients with LVH ranges from 0.23 to about 1%, but it is likely an underdiagnosed condition. We report the association of the PRKAG2 missense variant c.1006G>A p. (Val336Ile) with LVH, conduction abnormalities (short PR interval and incomplete right bundle branch bock) and early-onset arterial hypertension (AH) in a 44-year-old Caucasian patient. While cardiac magnetic resonance (CMR) showed a mild hypertrophic phenotype with maximal wall thickness of 17 mm in absence of tissue alterations, the electric phenotype was relevant including brady–tachy syndrome and recurrent syncope. The same variant has been detected in the patient’s sister and daughter, with LVH + early-onset AH and electrocardiographic (ECG) alterations + lipothymic episodes, respectively. Paying close attention to the coexistence of LVH and ECG alterations in the proband has been helpful in directing genetic tests to exclude primary cardiomyopathy. Hence, identifying the genetic basis in the patient allowed for familial screening as well as a proper follow-up and therapeutic management of the affected members. A review of the PRKAG2 cardiomyopathy literature is provided alongside the case report. Full article

Objectives: The association between anti-Ro/SSA antibodies and the appearance of cardiac rhythm disorders in adults is discussed. We aim to study this relationship, together with active treatments and comorbidities, and its impact on daily clinical practice in adults with systemic autoimmune diseases (SADs). Methods: This cross-sectional single-center study was conducted in a tertiary hospital between January 2021 and March 2022. A sample of adult patients followed up in the SAD Unit with a diagnosis of a SAD and previously tested for anti-Ro/SSA and anti-La/SSB were recruited. All of them underwent a 12-lead electrocardiogram. Results: 167 patients were included. 90 (53.9%) were positive for anti-Ro60, 101 (60.5%) for anti-Ro52, and 45 (26.9%) for anti-La/SSB; 52 (31.3%) were triple-negative. 84% were women, and the mean age was 59 years (standard deviation 12.8). The most common SAD was primary Sjögren’s syndrome (34.8%), followed by systemic lupus erythematosus (24.6%) and rheumatoid arthritis (22.8%). A statistically significant relationship was found between anti-Ro52 positivity and cardiac rhythm disorders (relative risk = 2.007 [1.197–3.366]), specifically QTc prolongation (relative risk = 4.248 [1.553–11.615]). Multivariate regressions showed a significant association, with diabetes mellitus being the most related comorbidity. The association between anti-Ro52 antibodies and atrioventricular conduction disorders was not significant. Conclusions: The presence of anti-Ro52 antibodies in adult patients with SADs is associated with an increased risk of QTc prolongation. Electrocardiographic screening of patients with SAD, anti-Ro52 antibodies, and other risk factors, like diabetes mellitus or QT-prolonging drugs, seems advisable. Those with baseline electrocardiogram abnormalities or additional risk factors should undergo electrocardiographic monitoring. Full article

Introduction: Cardiac transthyretin amyloidosis (ATTR) is a progressive, fatal disease leading to heart failure due to accumulation of amyloid fibrils in the interstitial space and may occur as a hereditary (ATTRv) or wild-type (ATTRwt) form. Guidelines recommend the use of ACE inhibitors (ACEis) and beta-blockers (BBs) as heart failure therapy (HFT) in all patients with symptomatic heart failure and reduced ejection fraction, independent of the underlying etiology. However, the prognostic benefit of ACEis and BBs in ATTR has not been elucidated in detail yet. We thus sought to retrospectively investigate the outcome of patients with ATTRwt or ATTRv under HFT. Methods: Medical records of 403 patients with cardiac ATTR (ATTRwt: n = 268, ATTRv: n = 135) were screened for long-term medication as well as clinical, laboratory, electrocardiographic and echocardiographic data. Patients were assessed between 2005 and 2020 at the University Hospital Heidelberg. Kaplan–Meier analysis was used to analyze potential differences in survival among different subgroups. Results: The mean follow-up was 28 months. In total, 43 patients (32%) with ATTRv and 140 patients (52%) with ATTRwt received HFT. Survival was significantly shorter in patients receiving HFT in ATTRv (46 vs. 83 months, p = 0.0007) vs. non-HFT. A significantly better survival was observed in patients with comorbidities (coronary artery disease, arterial hypertension) and HFT among ATTRwt patients (p = 0.004). No significant differences in survival were observed in the other subgroups. Conclusions: Survival analysis revealed a potential benefit of HFT in patients with ATTRwt and cardiac comorbidities such as coronary artery disease and/or arterial hypertension. In contrast, HFT should be used with caution in patients with ATTRv. Full article

Background: Ivabradine reduces heart rate by inhibiting the “funny current” expressed on the sinoatrial node and improves mortality and morbidity in patients with systolic heart failure and sinus tachycardia. The funny current is known to be expressed also on the atrioventricular node according to experimental studies. However, the impact of ivabradine on PR interval remained unknown. Methods: Patients with a left ventricular ejection fraction of less than 50% who received 1 month of ivabradine were screened. Electrocardiographic and echocardiographic data, particularly concerning heart rate, the PR interval, and trans-mitral flow pattern, were collected at baseline and 1-month follow-up. The primary endpoint was defined as the composite of cardiovascular death and hospital readmission for worsening heart failure following ivabradine administration. Results: In the cohort of 29 enrolled patients (median age: 66 years, 62% male), the median baseline heart rate was 86 beats per minute and the median PR interval was 168 milliseconds. Following ivabradine administration, a significant decrease of 20 beats per minute in the heart rate and a significant increase of 24 milliseconds in the PR interval were observed. The truncated interval of the A-wave, detected in the trans-mitral flow, consistently demonstrated a negative correlation with the PR interval both before and after the administration of ivabradine. During a median of 1.8 years of follow-up, six patients reached the primary endpoint. A combination of heart rate reduction and PR prolongation following ivabradine administration, both of which were independent factors associated with the primary endpoint (p < 0.05 for both), was associated with greater freedom from the primary endpoint compared with either/neither of them (p = 0.002). Conclusions: Ivabradine seems to prolong PR interval, which is a novel surrogate marker of favorable clinical outcomes in patients with systolic heart failure. This effect may be associated with the dynamics of the trans-mitral flow pattern, in conjunction with heart rate and the PR interval. Clinical implications of PR interval-guided ivabradine therapy remains the future concern. Full article

Background and Objectives: The risk of developing cardiovascular diseases (CVD) in patients suffering from rheumatoid arthritis (RA) is two times higher compared to the general population. The objective of this retrospective study was to determine which cardiovascular complications can appear in men vs. women with rheumatoid arthritis. Early diagnosis and initiation of therapeutic measures to reduce the progression rate of rheumatoid arthritis, while also maintaining an active lifestyle, are the most important problems in young patients. Materials and Methods: We included a number of 200 patients, divided into two groups according to gender (124 women and 76 men) with rheumatoid arthritis, presenting various stages of disease concomitant with cardiovascular complications. We assessed traditional and non-traditional risk factors, as well as electrocardiographic and echocardiographic findings in both groups. Results: All patients presented an atherogenic coefficient over two, indicating a significant risk of atherogenesis. Men had elevated levels of total cholesterol compared with women (≥200 mg/dL; 77.6%—men vs. 25.8%—women, p < 0.001). The participants presented cardiac arrhythmias, especially in the active stage of RA. Women had an increased risk of atrial fibrillation by 2.308 times compared to men (p = 0.020). One of the most important complications found in young women was pulmonary arterial hypertension (p = 0.007). Conclusions: In daily clinical practice, the screening of RA is carried out in sufficiently. This disease is often undiagnosed, and the risk factors remain unassessed. As a result, RA patients continue to present an increased risk of developing CVD. Full article

Background and Objectives: Subcutaneous implantable cardioverter-defibrillators (S-ICDs) provide protection against sudden cardiac death from outside the cardiovascular system. ECG screening is a prerequisite for implantation, but the reproducibility of its results post-operatively in the device is only partial. We aimed to compare the results of ECG screening with device-based sensing vector analysis. Materials and Methods: We screened the hospital records of all S-ICD recipients in our clinic. All of them had pre-operative ECG screening performed (primary, secondary, and alternate vectors). The results were compared with device-based vector analysis to determine the relation of the pre- and post-operative vector availability. Results: Complete ECG screening and device-based vector analysis were obtained for 103 patients. At least two acceptable vectors were found in 97.1% of the patients pre-operatively and in 96.1% post-operatively. When comparing vectors in terms of agreement (OK or FAIL) pre- and post-operatively, in 89.3% of the patients, the result for the primary vector was the same in both situations; for the secondary, it was in 84.5%, and for the alternate, it was in 74.8% of patients, respectively. In 55.3% of patients, all three vectors were labeled the same (OK or FAIL); in 37.9%, two vectors had the same result, and in 6.8%, only one vector had the same result pre- and post-operatively. The number of available vectors was the same pre- and post-operatively in 62.1% of patients, while in 15.5%, it was lower, and in 22.3% of patients, it was higher than observed during screening. Conclusions: Routine clinical pre-operative screening allowed for a good selection of candidates for S-ICD implantation. All patients had at least one vector available post-operatively. The final number of vectors available in the device-based analysis in most patients was at least the same (or higher) than during screening. The repeatability of the positive result for a single vector was high. Full article

Several studies conducted on humans demonstrate the increase in cardiac troponins and the onset of arrhythmias in the course of systemic inflammatory response syndrome (SIRS). The aim of the current study was to assess the blood concentration of cardiac troponin I (cTnI) and electrocardiographic findings in SIRS-affected cats. Seventeen shorthair cats hospitalized with SIRS were enrolled (Group 1). SIRS diagnosis was performed based on the detection of at least two of the four criteria such as abnormal body temperature, abnormal heart rate (i.e., tachycardia or bradycardia), abnormal respiratory rate (i.e., tachypnea or bradypnea), and alterations of white blood cell number (i.e., leukocytes or band neutrophils). Ten cats screened for elective surgery such as neutering or dental procedures were evaluated as a control population (Group 2). They were considered healthy based on history, physical examination, hematological and biochemical profile, urinalysis, coprological exam, thyroxine assay, blood pressure measurement, and echocardiography. A physical examination, complete blood cell count, biochemistry test (including an electrolyte panel), electrocardiographic examination, and cTnI assay were carried out in each cat enrolled. Traumatic events, gastrointestinal, neoplastic, respiratory, and neurological disorders were identified as causes of SIRS in Group 1. In Group 1, a significantly higher concentration of cTnI than that in Group 2 was recorded (p = 0.004). In 37.5% of cats with SIRS, ventricular premature complexes occurring in couplets with multiform configuration were detected. Similarly, to humans, data herein reported would indicate possible cardiac damage present in cats with SIRS diagnosis. Full article

Cardiovascular diseases are currently the leading cause of death worldwide. Thus, there is a need for non-invasive ambulatory (Holter) ECG monitors with automatic measurements of ECG intervals to evaluate electrocardiographic abnormalities of patients with cardiac diseases. This work presents the implementation of algorithms in an FPGA for beat-to-beat heart rate and RT interval measurements based on the continuous wavelet transform (CWT) with splines for a prototype of an ambulatory ECG monitor of three leads. The prototype’s main elements are an analog–digital converter ADS1294, an FPGA of Xilinx XC7A35T-ICPG236C of the Artix-7 family of low consumption, immersed in a low-scale Cmod-A7 development card integration, an LCD display and a micro-SD memory of 16 Gb. A main state machine initializes and manages the simultaneous acquisition of three leads from the ADS1294 and filters the signals using a FIR filter. The algorithm based on the CWT with splines detects the QRS complex (R or S wave) and then the T-wave end using a search window. Finally, the heart rate (60/RR interval) and the RT interval (from R peak to T-wave end) are calculated for analysis of its dynamics. The micro-SD memory stores the three leads and the RR and RT intervals, and an LCD screen displays the beat-to-beat values of heart rate, RT interval and the electrode connection. The algorithm implemented on the FPGA achieved satisfactory results in detecting different morphologies of QRS complexes and T wave in real time for the analysis of heart rate and RT interval dynamics. Full article