Search Results (449)

BACKGROUND: Sport practice may elevate the risk of cardiovascular events, including sudden cardiac death, in athletes with undiagnosed heart conditions. In Italy, pre-participation screening includes a resting ECG and either the Harvard Step Test (HST) or maximal exercise testing (MET), but the relative efficacy of the latter two tests for detecting arrhythmias and heart conditions remains unclear. METHODS: This study examined 511 paediatric athletes (8–18 years, 76.3% male) without known cardiovascular, renal, or endocrine diseases. All athletes underwent both HST and MET within 30 days. Absolute data and data relative to theoretical peak heart rates, arrhythmias (supraventricular and ventricular) and cardiovascular diagnoses were collected. RESULTS: HST resulted in a lower peak heart rate than MET (181.1 ± 9.8 vs. 187.5 ± 8.1 bpm, p < 0.001), but led to the detection of more supraventricular (18.6% vs. 13.1%, p < 0.001) and ventricular (30.5% vs. 22.7%, p < 0.001) arrhythmias, clustering during recovery (p = 0.014). This pattern was significant in males but not females. Among athletes diagnosed with cardiovascular diseases (22.3%), HST identified more ventricular arrhythmias (26.3% vs. 18.4%, p = 0.05), recovery-phase arrhythmias (20.2% vs. 14.0%, p = 0.035), and polymorphic arrhythmias (6.1% vs. 1.8%, p = 0.025). CONCLUSIONS: HST detects arrhythmias more effectively than MET in young male athletes, especially during recovery. More ventricular arrhythmias were highlighted even in athletes with cardiovascular conditions. Full article

Anderson–Fabry disease (AFD) is a rare X-linked lysosomal storage disorder characterized by the accumulation of globotriaosylceramide, leading to multi-organ involvement and significant morbidity. Cardiovascular manifestations, particularly arrhythmias, are common and pose a considerable risk to affected individuals. This overview examines current approaches to arrhythmic risk stratification in AFD, focusing on the identification, assessment, and management of cardiac arrhythmias associated with the disease. We explore advancements in diagnostic techniques, including echocardiography, cardiac MRI, and ambulatory ECG monitoring, to enhance the detection of arrhythmogenic substrate. Furthermore, we discuss the role of genetic and biochemical markers in predicting arrhythmic risk and the implications for personalized treatment strategies. Current therapeutic interventions, including enzyme replacement therapy and antiarrhythmic medications, are reviewed in the context of their efficacy and limitations. Finally, we highlight ongoing research and future directions with the aim of improving arrhythmic risk assessment and management in AFD. This overview underscores the need for a multidisciplinary approach to optimize care and outcomes for patients with AFD. Full article

Background/Objectives: QTc prolongation can result in lethal arrhythmia. Risk scores like the Tisdale score can be used for risk stratification for targeted pharmaceutical interventions. However, the practical usability across different medical specialties has not been sufficiently investigated. The aim of this study was to compare relevant risk factors for QTc prolongation and to investigate the use of the Tisdale score in cardiology and gastroenterology patients. Methods: For patients on a cardiology and a gastroenterology ward receiving a weekly pharmaceutical electronic chart review, risk factors for QTc prolongation, QTc-prolonging drugs, and electrocardiograms (ECGs) were retrospectively collected for a four-month period (07-10/2023), and the Tisdale score and its sensitivity and specificity were calculated. Results: A total of 627 chart reviews (cases) (335 cardiology, 292 gastroenterology) were performed. The median age was 66 (range 20–94) years, and 39% (245) of patients were female. The presence of established risk factors (hypokalemia, renal impairment, age ≥ 68 years, cardiac diseases) differed significantly between the specialties. A median of 2 (range 0–5) QTc-prolonging drugs were prescribed in both groups. Baseline and follow-up ECG were recorded in 166 (50%) cardiology cases, of which prolonged QTc intervals were detected in 38 (23%) cases. In the 27 (9%) gastroenterology cases with baseline and follow-up ECG, no QTc prolongations were detected. Across both specialties, the Tisdale score achieved a sensitivity of 74% and a specificity of 30%. Conclusions: The presence of established risk factors for QTc prolongation differed significantly between cardiology and gastroenterology cases. The Tisdale score showed acceptable sensitivity for risk stratification; however, the limited availability of ECGs for gastroenterology cases was a limiting factor. Full article

Supraventricular arrhythmias (SVAs), including the often-asymptomatic supraventricular extrasystole (SVE), pose significant challenges in early detection and precise diagnosis. These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart failure. In the study conducted, an innovative approach was introduced that combined a convolutional neural network (CNN) architecture to enable the early identification and characterization of SVEs within electrocardiogram (ECG) signals. The analysis leveraged a dataset comprising 78 half-hour recordings from the highly regarded MIT-BIH Arrhythmia Database, which included annotation headers serving as labels for each recording. Signals were down-sampled by a factor of 2 and split into windows of 512 samples, with 12,288 observations for training. Following the methodology, classic signal preprocessing techniques (filtering and data normalization) were used. The proposed model was based on the UNET 1D model. A binary cross-entropy loss function, Adam optimizer, and a batch size of 128 were obtained after a hyperparameter tuning. As a training-validation methodology, a 50-fold cross-validation technique was used. The approach demonstrated a Dice coefficient of 79.01%, a precision of 80.96%, and a recall rate of 86.60% in detecting SVE events. These findings were corroborated through meticulous comparison with the annotations provided by the MIT-BIH database. The results underscore the immense potential of CNN and deep learning techniques in the early detection of supraventricular arrhythmias. This approach not only offers a valuable tool for healthcare professionals engaged in telemonitoring and early intervention strategies but also represents a significant contribution to the field of cardiac health monitoring. By facilitating efficient and precise identification of SVEs, our research sets the stage for improved patient outcomes and the prevention of severe SVAs, marking substantial advancements in this critical domain. Full article

Atrial fibrillation (AF) is the most common persistent arrhythmia, and it is crucial to develop generalizable automatic AF detection methods. However, supervised AF detection is often limited in performance due to the difficulty in obtaining labeled data. To address the gap between limited labeled data and the requirements for model robustness and generalization in single-lead ECG AF detection, we proposed a semi-supervised contrastive learning method named MLMCL for AF detection. The MLMCL method utilizes the multi-level feature representations of the encoder to perform multiple contrastive learning to fully exploit temporal consistency, channel consistency, and label consistency. Meanwhile, it combines labeled and unlabeled data for pre-training to obtain robust features for downstream tasks. In addition, it uses the domain knowledge in the field of AF diagnosis for domain knowledge augmentation to generate hard samples and improve the distinguishability of ECG representations. In the cross-dataset testing mode, MLMCL had better performance and good stability on different test sets, demonstrating its effectiveness and robustness in the AF detection task. The comparison results with existing studies show that MLMCL outperformed existing methods in external tests. The MLMCL method can be extended and applied to multi-lead scenarios and has reference significance for the development of contrastive learning methods for other arrhythmia. Full article

Background: This study aims to retrospectively detect associations with postoperative complications in spinal surgeries during the hospitalization period using standardized, single-center data to validate a method for complication detection and discuss the potential future use of generated data. Methods: Data were generated in 2006–2019 from a standardized, weekly complications conference reviewing all neurosurgical operations at the University Hospital Luebeck. Paper-based data were recorded in a standardized manner during the conference and transferred with a time delay of one week into a proprietary complication register. A total of 5575 cases were grouped based on the diagnosis, surgical localization, approach, instrumentation, previous operations, surgery indication, age, ASA score, and pre-existing conditions. Retrospective analysis was performed using a logistic regression detecting complication associations. The results were compared to the literature validating the method of complication detection. Results: Mean cohort age: 58.83 years. Overall complication rate: 10.9%. Mortality rate: 0.25%. The statistically significant complication associations were age; an age of >60; the localization (cervical, thoracic); a cervical tumor or trauma diagnosis; lumbar degenerative conditions, tumor, trauma, or infection; a cervical hemi-/laminectomy and vertebral body replacement; a lumbar hemi-/laminectomy, posterior spondylodesis, and 360° fusion; lumbar instrumentation, with an ASA score of three and four; a ventral and combined/360° approach; a lumbar combined/360° revision; two, three and ≥four pre-existing conditions; hypertension; osteoporosis; arrhythmia; an oncological condition; kidney dysfunction; stroke; and thrombosis. Conclusions: Documenting risk profiles for spinal procedures is important in identifying postoperative complications. The available data provide a comprehensive overview within a single center for spinal surgeries. Standardized complication recording during an established complication conference in the clinical routine enables the detection of significant complications. It is desirable to standardize the registration of postoperative complications to facilitate comparability across different institutions. The results may contribute to national or international databases used for automated AI risk profiling. Full article

Background/Objectives: In Europe, the prevalence of AF is expected to increase 2.5-fold over the next 50 years with a lifetime risk of 1 in 3–5 individuals after the age of 55 years and a 34% rise in AF-related strokes. The PREFATE project investigates evidence gaps in the early detection of atrial fibrillation in high-risk populations within primary care. This study aims to estimate the prevalence of device-detected atrial fibrillation (DDAF) and assess the feasibility and impact of systematic screening in routine primary care. Methods: The prospective cohort study (NCT 05772806) included 149 patients aged 65–85 years, identified as high-risk for AF. Participants underwent 14 days of cardiac rhythm monitoring using the Fibricheck^® app (CE certificate number BE16/819942412), alongside evaluations with standard ECG and transthoracic echocardiography. The primary endpoint was a new AF diagnosis confirmed by ECG or Holter monitoring. Statistical analyses examined relationships between AF and clinical, echocardiographic, and biomarker variables. Results: A total of 18 cases (12.08%) were identified as positive for possible DDAF using FibriCheck^® and 13 new cases of AF were diagnosed during follow-up, with a 71.4-fold higher probability of confirming AF in FibriCheck^®-positive individuals than in FibriCheck^®-negative individuals, resulting in a post-test odds of 87.7%. Significant echocardiographic markers of AF included reduced left atrial strain (<26%) and left atrial ejection fraction (<50%). MVP ECG risk scores ≥ 4 strongly predicted new AF diagnoses. However, inconsistencies in monitoring outcomes and limitations in current guidelines, particularly regarding AF burden, were observed. Conclusions: The study underscores the feasibility and utility of AF screening in primary care but identifies critical gaps in diagnostic criteria, anticoagulation thresholds, and guideline recommendations. Full article

Cardiac troponin-I (cTnI) is a highly sensitive and specific marker of myocardial injury detectable in plasma by immunoassay techniques. Inclusion criteria over a 3-year period required a diagnosis of cardiac disease accompanied by electrocardiographic (ECG) and cardiac ultrasound examinations (n = 23) in adult horses (≥2 years of age). A second group of normal adult ponies (n = 12) was studied as a reference group. Heparinized jugular venous blood samples were collected and centrifuged within 30 min, and the plasma was separated and frozen at −70 °C for subsequent batched cTnI analysis. The lower limit of detection was 0.01 ng/mL, and the upper limit was 100 ng/mL of plasma. Normal equine plasma cTnI concentrations ranged from 0.01 to 0.03 ng/mL (n = 12). Horses with non-arrhythmogenic murmurs (n = 4) included tricuspid (0.05 ng/mL cTnI), mitral (0.07), and aortic insufficiencies (0.01, 0.02). Horses with benign atrial fibrillation (n = 8) had a cTnI range of <0.01–0.09 ng/mL, with four horses having cTnI concentrations falling slightly outside the reference range (0.04, 0.05, 0.06, and 0.09). Horses with ventricular arrhythmias (ventricular premature contractions or ventricular tachycardia) and documentable myocardial toxicities or immunological reactions (n = 5) had cTnI concentrations of 0.05, 0.21, 0.31, 15.18, and >100 ng/mL. Horses with ventricular arrhythmias but no documentation of myocardial toxicity (n = 3) had cTnI concentrations of 0.34, 0.46, and 80.42 ng/mL. When grouped by arrhythmia type and compared using the Mann–Whitney Rank Sum Test, the median ventricular arrhythmia cTnI (0.40 ng/mL) was significantly higher than the median atrial fibrillation cTnI (0.04 ng/mL, p < 0.001). It was concluded that horses with myocardial toxicities and ventricular arrhythmias often had severe elevations in plasma cTnI. Full article

Amyloidosis is a rare pathology characterized by protein deposits in various organs and tissues. Cardiac amyloidosis (CA) can be caused by various protein deposits, but transthyretin amyloidosis (ATTR) and immunoglobulin light chain (AL) are the most frequent pathologies. Protein misfolding can be induced by several factors such as oxidative stress, genetic mutations, aging, chronic inflammation, and neoplastic disorders. In ATTR cardiomyopathy (ATTR-CM), the amyloid fibrils can be found in the myocardium interstitial space and are associated with arrhythmias and heart failure. In pathological situations, the transthyretin (TTR) configuration is destroyed by proteolytic action, leading to monomers that further misfold and aggregate to form the amyloid fibrils. ^99mTc-Pyrophosphate (^99m-Tc-PYP), ^99mTc 3,3-diphosphono-1,2-propanodicarboxylic acid (^99m-Tc-DPD) and ^99m-Tc hydroxy-methylene-Dyphosphonate (^99m-Tc-HMDP) are used to detect myocardium amyloid deposits due to their ability to detect calcium ions that are present in the amyloid fibrils through dystrophic calcification. ATTR-CM therapy acts on different stages of the amyloidogenic process, including liver TTR synthesis, TTR tetramer destabilization, and misfolding of the monomers. The main aim of this narrative review is to present ATTR-CM, starting with molecular changes regarding the protein misfolding process and radionuclide aspects and finishing with pharmacological approaches. Full article

Background/Objectives: Atrial fibrillation (AF) is the most frequent arrhythmia in the adult population associated with a high rate of severe consequences leading to significant morbidity and mortality worldwide. Therefore, its prompt recognition is of high clinical importance. AF detection often remains challenging due to unspecific symptoms and a lack of reliable biomarkers for its prediction. Herein, novel bioanalytical methodologies, such as metabolomics, offer new opportunities for a better understanding of the underlying pathological mechanisms of cardiovascular diseases, including AF. The metabolome, considered a complete set of small molecules present in the organism, directly reflects the current phenotype of the studied system and is highly sensitive to any changes, including arrhythmia’s onset. A growing body of evidence suggests that metabolite profiling has prognostic value in AF prediction, highlighting its potential role not only in early diagnosis but also in guiding therapeutic interventions. By identifying specific metabolites as a disease biomarker or recognising particular metabolomic pathways involved in the AF pathomechanisms, metabolomics could be of great clinical value for further clinical decision-making, risk stratification, and an individual personalised approach. The presented narrative review aims to summarise the current state of knowledge on metabolomics in AF with a special emphasis on its implications for clinical practice and personalised medicine. Full article

Background/Objectives: Catheter ablation for atrial fibrillation (AF) is a well-established therapeutic approach for maintaining sinus rhythm, though its efficacy remains suboptimal in certain patients. The left atrium (LA) volume, commonly assessed through transthoracic echocardiography (TTE), is a recognized predictor of AF recurrence after pulmonary vein isolation (PVI). However, the complex three-dimensional structure of the LA makes precise measurement challenging with traditional TTE techniques. Electroanatomic mapping (EAM) offers a more accurate evaluation of LA geometry and volume, which may enhance the prediction of ablation outcomes. Methods: This prospective study included 197 patients with AF who were referred for PVI to our center (Hospital Universitario Central de Asturias, Spain) between 2016 and 2020. All participants underwent pre-ablation TTE and EAM to assess the electric active volume (EAV) of the LA. Clinical follow-up included regular Holter monitoring and electrocardiograms to detect AF recurrences. Results: The mean age was 56.3 ± 9.67 years, and 34% had persistent AF. The mean LA volumes measured by TTE and the EAV by EAM were 62.86 ± 15.58 mL and 126.75 ± 43.35 mL, respectively, with a moderate positive correlation (r = 0.49, p < 0.001). AF recurrences were observed in 51.27% of patients over a 36 ± 15-month follow-up period. Cox regression analyses (univariate and multivariate), Kaplan–Meier curves and log-rank tests were used to illustrate freedom from atrial arrhythmia during follow-up. Both EAV by EAM and TTE volumes were significant predictors of AF recurrence in the univariate analysis (HR 1.002 [1.001–1.003], p = 0.033 and HR 1.001 [1.006–1.012], p < 0.01, respectively). Among clinical variables, persistent AF was significantly associated with a higher risk of recurrence (HR 1.17 [1.096–1.268], p = 0.02). Conclusions: EAV of the LA assessment by EAM demonstrates a significant correlation with TTE measurements and is a predictor of AF post-ablation recurrence. In patients selected for catheter ablation, EAV by EAM provides additional insights that could contribute to therapeutic decision-making and risk stratification of AF recurrences. Full article

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, impacting approximately 6.1 million adults in the United States, with projections to increase two-fold by 2030. AF significantly increases the risk of stroke and other adverse cardiovascular events, leading to increased morbidity and mortality. The 2023 ACC/AHA/ACCP/HRS guidelines present a paradigm shift in AF management, moving from a duration-based classification to a more comprehensive, patient-centered approach. This includes a novel AF classification system that emphasizes early detection and intervention, including risk factors and lifestyle modification tailored to each patient’s risk profile. Moreover, the recommendations advocate for a multidisciplinary care model, ensuring coordinated management involving primary care providers and specialists. Primary care providers play a crucial role in initiating risk factor management and lifestyle interventions, even before the development of AF. This review aims to thoroughly examine the guidelines for the diagnosis and management of AF and equip general internists with the necessary insights to navigate the evolving landscape of AF care effectively. Full article

Cancer therapy-related cardiac dysfunction (CTRCD) has emerged as a significant concern with the rise of effective cancer treatments like anthracyclines and targeted therapies such as trastuzumab. While these therapies have improved cancer survival rates, their unintended cardiovascular side effects can lead to heart failure, cardiomyopathy, and arrhythmias. The pathophysiology of CTRCD involves oxidative stress, mitochondrial dysfunction, and calcium dysregulation, resulting in irreversible damage to cardiomyocytes. Inflammatory cytokines, disrupted growth factor signaling, and coronary atherosclerosis further contribute to this dysfunction. Advances in cardio-oncology have led to the early detection of CTRCD using cardiac biomarkers like troponins and imaging techniques such as echocardiography and cardiac magnetic resonance (CMR). These tools help identify asymptomatic patients at risk of cardiac events before the onset of clinical symptoms. Preventive strategies, including the use of cardioprotective agents like beta-blockers, angiotensin-converting enzyme inhibitors, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter-2 inhibitors have shown promise in reducing the incidence of CTRCD. This review summarizes the mechanisms, detection methods, and emerging treatments for CTRCD, emphasizing the importance of interdisciplinary collaboration between oncologists and cardiologists to optimize care and improve both cancer and cardiovascular outcomes. Full article

Background: Heart failure (HF) management increasingly relies on innovative solutions to enhance monitoring and care. Wearable devices, originally popularized for fitness tracking, show promise in clinical decision-making for HF. This study explores the application and potential for the broader integration of wearable technology in HF management, emphasizing remote monitoring and personalized care. Methods: A comprehensive literature review was performed to assess the role of wearables in HF management, focusing on functionalities like vital sign tracking, patient engagement, and clinical decision support. Clinical outcomes and barriers to adopting wearable technology in HF care were critically analyzed. Results: Wearable devices increasingly track physiological parameters relevant to HF, such as heart rate, physical activity, and sleep. They can identify at-risk patients, promote lifestyle changes, facilitate early diagnosis, and accurately detect arrhythmias that lead to decompensation. Additionally, wearables may assess fluid status, identifying early signs of decompensation to prevent hospitalization and supporting therapeutic adjustments. They also enhance physical activity and optimize cardiac rehabilitation programs, improving patient outcomes. Both wearable and implanted cardiac devices enable continuous, non-invasive monitoring through small devices. However, challenges like data integration, regulatory approval, and reimbursement impede their widespread adoption. Conclusions: Wearable technology can transform HF management through continuous monitoring and early interventions. Collaboration among involved parties is essential to overcome integration challenges and validate most of these devices in clinical practice. Full article

Background: The wearable cardioverter defibrillator (WCD) has emerged as a valuable tool used for temporary protection from sudden cardiac death. However, since the WCD uses surface electrodes to detect arrhythmias, it is susceptible to inappropriate detection. Although shock conversion rates for the WCD are reported to be high for detected events, its efficacy in clinical practice tends to be degraded by patient noncompliance. Reasons for this include wearer discomfort and frequent false alarms, which may interrupt sleep and generate anxiety. Up to now, data on the incidence of false alarms emitted by the WCD and their predictors are rare. Objectives: The aim of our study was to assess the relationship between both artifact sensing and episode misclassification burden and wearing compliance in patients with a WCD (ZOLL LifeVest™ 4000 system, ZOLL CMS GmbH, Cologne, Germany). Methods and Results: We conducted a single-center retrospective observational study, analyzing patients with a WCD prescribed at our institution. A total of 134 patients (mean age 51.7 ± 13.8 years, 79.1% male) were included. Arrhythmia recordings were analyzed and categorized as non-sustained ventricular tachycardia, sustained ventricular tachycardia or fibrillation, artifact sensing or misclassified episodes. Indication for WCD prescription was both primary and secondary prophylaxis. A total of 3019 false WCD alarms were documented in 78 patients (average number of false alarms 38.7 ± 169.5 episodes per patient) over a mean WCD wearing time of 71.5 ± 70.9 days (daily WCD wearing time 20.2 ± 5.0 h). In a total of 78 patients (58.2% of the study population), either artifact sensing (76.9%), misclassified episodes (6.4%), or both (16.7%) occurred. Misclassified episodes included sinus tachycardias, atrial flutter, atrial fibrillation, premature ventricular contractions (PVCs), and intermittent bundle branch block. A multiple linear regression identified loop diuretics (regression coefficient [B] −0.11; 95% CI −0.21–(−0.0001); p = 0.049), angiotensin receptor–neprilysin inhibitors (ARNIs) (B −0.11; 95% CI 0.22–(−0.01); p = 0.033), and a higher R-amplitude of the WCD baseline electrocardiogram (ECG) (B −0.17; 95% CI −0.27–(−0.07); p = 0.001) as independent predictors for a lower number of artifact episodes per day. In addition, atrial fibrillation (B 0.05; 95% CI 0.01–0.08; p = 0.010), and calcium antagonists (B 0.07; 95% CI 0.02–0.12; p = 0.012) were independent predictors for increased numbers of misclassified episodes per day, while beta-blockers seemed to reduce them (B −0.06; 95% CI −0.10–(−0.01); p = 0.013). Patients terminated 61.0% of all false alarms manually by pressing the response button on average 1.9 times per false alarm with overall 3.6 manual terminations per affected patient per month. Conclusions: In conclusion, false alarms from the ZOLL LifeVest™ system were frequent, with artifact sensing being the most common cause. Hence, the occurrence of false alarms represents a significant side effect of WCD therapy, and efforts should be made to minimize false alarms. Full article