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Abstract Background Atrial fibrillation (AF) has been linked to increased hyperthyroidism risk, but contributing factors are unclear. Objective We aimed to investigate whether AF could predict hyperthyroidism and related risk factors. Methods This retrospective cohort study was conducted in a tertiary medical institution and included patients aged 18 years or older with AF but without hyperthyroidism at diagnosis. The endpoint was defined as newly diagnosed hyperthyroidism during the follow-up period. Results The study cohort included 8552 participants. Patients who developed new hyperthyroidism were younger and the proportion of females was higher. They had fewer comorbidities, including diabetes (26% vs 29%, P = .121), hypertension (51% vs 58%, P < .001), coronary artery disease (17% vs 25%, P < .001), stroke (16% vs 22%, P < .001), and end-stage renal disease (ESRD) (6% vs 10%, P = .001). The CHADS2 score was lower in patients with hyperthyroidism (1.74 vs 2.05, P = .031), but there was no statistically significant difference in the CHA2DS2-VASc and HAS-BLED score. Cox regression analysis identified younger age, female gender, history of congestive heart failure, hypertension, diabetes, non-ESRD status, and lower CHADS2 score but not CHA2DS2-VASc as independent predictors of incident hyperthyroidism during follow-up. We also propose a novel, simple risk stratification score (SAD HEC2 score) with excellent predictive power for incident hyperthyroidism during follow-up. Conclusion Our results provide insight into clinical risk factors for the development of hyperthyroidism in AF patients, as identified by the novel SAD HEC2 score. AF appears to be a common precursor of hyperthyroidism.

BackgroundPatients with drug-refractory atrial fibrillation (AF) and pre-existing left atrial appendage occluder (LAAO) device may need pulmonary vein isolation (PVI). In this pioneer study, we investigated the impact of pre-existing LAAO on AF substrates and outcomes of PVI.MethodsFrom our AF registry, 65 drug-refractory patients with LAAO (72.1±11.4 years old; CHA2DS2-VASc score 3.7±2.1) were included for PVI. A balanced control group with 124 patients without LAAO receiving PVI (70.9±10.2 years old, CHA2DS2-VASc 3.6±1.9) were included for comparison.ResultsWe found PVI is feasible in patients with AF with pre-existing LAAO without new peridevice leak. Two patients with LAAO and one without LAAO had stroke during the procedure (2/65 vs 1/124, p=0.272). Complete isolation of left-sided PVs might not be achieved if the device covered the ridge joining the left atrial (LA) appendage to the body of LA. Local electrogram could be detected over LAAO and there was propagation of conduction over the occluder either under sinus rhythm or under atrial arrhythmia. LAAO might modulate LA substrate and induce peridevice fibrosis, peridevice LA flutter and complex fractionate atrial electrogram. The AF recurrent rate at 1 year was similar between the two groups (9.2% vs 8.8%).ConclusionsThis pioneer study first showed impacts of LAAO on LA substrate and PVI procedure.

Out-of-hospital cardiac arrest (OHCA) remains a major threat to public health worldwide. OHCA patients presenting initial shockable ventricular tachycardia/ventricular fibrillation (VT/VF) rhythm have a better survival rate. We sought to develop a simple SACAF score to discriminate VT/VF from non-VT/VF OHCAs based on the Taiwan multicenter hospital-based registry database. We analyzed the in- and pre-hospital data, including demographics, baseline comorbidities, response times, automated external defibrillator information, and the 12-lead ECG recording closest to the OHCA event in bystander-witnessed OHCA patients. Among the 461 study patients, male sex (OR 2.54, 95% CI = 1.32–4.88, P  = 0.005), age ≤ 65 years (OR 2.78, 95% CI = 1.64–4.70, P  < 0.001), cardiovascular diseases (OR 2.97, 95% CI = 1.73–5.11, P  < 0.001), and atrial fibrillation (AF) (OR 2.36, 95% CI = 1.17–4.76, P  = 0.017) were independent risk factors for VT/VF OHCA (n = 81) compared with non-VT/VF OHCA (n = 380). A composite SACAF score was developed (male S ex, A ge ≤ 65 years, C ardiovascular diseases, and AF ) and compared with the performance of a modified CHA 2 DS 2 -VASc score ( C ardiovascular diseases, H ypertension, A ge ≥ 75 years, D iabetes, previous S troke, V ascular disease, A ge 65–74 years, female S ex c ategory). The area under the receiver operating characteristic curve (AUC) of the SACAF was 0.739 (95% CI = 0.681–0.797, P  < 0.001), whereas the AUC of the modified CHA 2 DS 2 -VASc was 0.474 (95% CI = 0.408–0.541, P  = 0.464). A SACAF score of ≥ 2 was useful in discriminating VT/VF from non-VT/VF OHCAs with a sensitivity of 0.75 and a specificity of 0.60. In conclusion, the simple SACAF score appears to be useful in discriminating VT/VF from non-VT/VF bystander-witnessed OHCAs and the findings may also shed light on future mechanistic evaluation.

There has been no long-term clinical follow-up data of survivors or victims of sudden cardiac death (SCD). The Taiwan multi-center sudden arrhythmia death syndrome follow-up and clinical study (TFS-SADS) is a collaborative multi-center study with median follow-up time 43 months. In this cohort, the clinical characteristics of these SADS patients were compared with those with ischemic heart disease (IHD). In this SCD cohort, around half (42%) were patients with IHD, which was different from Caucasian SCD cohorts. Among those with normal heart, most had Brugada syndrome (BrS). Compared to those with SADS, patients with IHD were older, more males and more comorbidities, more arrhythmic death, and lower left ventricular ejection fraction. In the long-term follow-up, patients with SADS had a better survival than those with IHD (p < 0.001). In the Cox regression analysis to identify the independent predictors of mortality, older age, lower LVEF, prior myocardial infarction and history of out-of-hospital cardiac arrest were associated with higher mortality and beta blocker use and idiopathic ventricular fibrillation or tachycardia (IVF/IVT) with a better survival during follow-up. History of prior MI was associated with more arrhythmic death. Several distinct features of SCD were found in the Asia–Pacific region, such as higher proportion of SADS, poorer prognosis of LQTS and better prognosis of IVF/IVT. Patients with SADS had a better survival than those with IHD. For those with SADS, patients with channelopathy had a better survival than those with cardiomyopathy.

Background Atrial fibrillation (AF) and diabetes mellitus (DM) are associated with an increased risk of ischemic stroke, particularly in geriatric populations. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have demonstrated cardiovascular benefits, but their effects on stroke risk may vary by age. This study aimed to explore the age-dependent effects of SGLT2i on stroke risk in patients with AF and DM. Methods This historical longitudinal follow-up cohort study included 9,669 patients with AF and DM from the National Taiwan University Hospital database (2010–2020). Patients were stratified into three age groups (< 75, 75–89, and ≥ 90 years) to compare SGLT2i users and non-users within each age group. Cox proportional hazards models were used to evaluate stroke risk, adjusting for CHA₂DS₂-VASc score and oral anticoagulant use. Interaction analysis assessed age-specific SGLT2i effects. Results In patients aged < 75 years, SGLT2i use significantly reduced stroke risk (HR 0.63, 95% CI 0.44–0.88, P  < 0.05). Stroke risk was neutral in patients aged 75–89 years (HR 0.95, 95% CI 0.60–1.50), but significantly increased in those aged ≥ 90 years (HR 5.04, 95% CI 1.20–21.1, P  < 0.05). Interaction analysis confirmed a significant age-dependent effect (aged ≥ 90 years x SGLT2i use HR 6.39, 95% CI 1.49–27.40, P  < 0.05). Conclusions The impact of SGLT2i on stroke risk varies significantly by age. While protective in younger patients, SGLT2i may increase stroke risk in those aged ≥ 90 years. These findings highlight the importance of age-specific considerations in prescribing SGLT2i for patients with AF and DM. Graphical Abstract

Background Ventricular premature complex (VPC) is a common arrhythmia in clinical practice. VPC could trigger ventricular tachycardia/fibrillation or VPC-induced cardiomyopathy in susceptible patients. Existing screening methods require prolonged monitoring and are limited by cost and low yield when the frequency of VPC is low. Twelve-lead electrocardiogram (ECG) is low cost and widely used. We aimed to identify patients with VPC during normal sinus rhythm (NSR) using artificial intelligence (AI) and machine learning-based ECG reading. Methods We developed AI-enabled ECG algorithm using a convolutional neural network (CNN) to detect the ECG signature of VPC presented during NSR using standard 12-lead ECGs. A total of 2515 ECG records from 398 patients with VPC were collected. Among them, only ECG records of NSR without VPC (1617 ECG records) were parsed. Results A total of 753 normal ECG records from 387 patients under NSR were used for comparison. Both image and time-series datasets were parsed for the training process by the CNN models. The computer architectures were optimized to select the best model for the training process. Both the single-input image model (InceptionV3, accuracy: 0.895, 95% confidence interval [CI] 0.683–0.937) and multi-input time-series model (ResNet50V2, accuracy: 0.880, 95% CI 0.646–0.943) yielded satisfactory results for VPC prediction, both of which were better than the single-input time-series model (ResNet50V2, accuracy: 0.840, 95% CI 0.629–0.952). Conclusions AI-enabled ECG acquired during NSR permits rapid identification at point of care of individuals with VPC and has the potential to predict VPC episodes automatically rather than traditional long-time monitoring.

ObjectivesAtrial fibrillation (AF) in hypertrophic cardiomyopathy (HCM) is associated with increased mortality, mainly mediated by increased thromboembolic events and progressive heart failure. Many studies suggested inhibition of renin–angiotensin–aldosterone system (RAAS) could reduce new AF in various clinical conditions. However, evidence concerning the effects of RAAS inhibitors on AF prevention remains unclear in HCM. Our study is to investigate whether treatment with ACE inhibitors (ACEIs) or angiotensin-receptor blockers (ARBs) could lower the risk of new AF in HCM.MethodsWe conducted a retrospective study including subjects diagnosed HCM between January 1997 and December 2013 by using a nationwide database covering almost all Taiwanese from National Health Research Institute. All participants, aged 18 or older, had no ACEIs or ARBs exposure or AF diagnosis before enrolment. Propensity score matching and multivariate Cox hazard regression were employed to estimate the risk of new AF occurrence.ResultsTotal 18 266 subjects were included in the analysis with median follow-up duration 8.13 years. Patients taking ACEIs or ARBs are associated with lower risk of developing new AF than those without taking neither of medications (3.16% vs 5.65%, relative risk 0.56 (95% CI 0.49 to 0.64), HR 0.572 (95% CI 0.480 to 0.683)). The correlation is more prominent with longer ACEIs or ARBs treatment (HRs from T1 to T3: 0.741, 0.579, 0.337, P<0.001). These results remain consistent after propensity score adjustment.ConclusionIn patients with HCM, lower risk of new AF is observed in patients treated with either ACEIs or ARBs compared with those receiving neither of these medications.

Although Amiodarone, a class III antiarrhythmic drug, inhibits zebrafish cardiac valve formation, the detailed molecular pathway is still unclear. Here, we proved that Amiodarone acts as an upstream regulator, stimulating similar to versican b (s-vcanb) overexpression at zebrafish embryonic heart and promoting cdh-5 overexpression by inhibiting snail1b at atrioventricular canal (AVC), thus blocking invagination of endocardial cells and, as a result, preventing the formation of cardiac valves. A closer investigation showed that an intricate set of signaling events ultimately caused the up-regulation of cdh5. In particular, we investigated the role of EGFR signaling and the activity of Gsk3b. It was found that knockdown of EGFR signaling resulted in phenotypes similar to those of Amiodarone-treated embryos. Since the reduced phosphorylation of EGFR was rescued by knockdown of s-vcanb, it was concluded that the inhibition of EGFR activity by Amiodarone is s-vcanb-dependent. Moreover, the activity of Gsk3b, a downstream effector of EGFR, was greatly increased in both Amiodarone-treated embryos and EGFR-inhibited embryos. Therefore, it was concluded that reduced EGFR signaling induced by Amiodarone treatment results in the inhibition of Snail functions through increased Gsk3b activity, which, in turn, reduces snail1b expression, leading to the up-regulation the cdh5 at the AVC, finally resulting in defective formation of valves. This signaling cascade implicates the EGFR/Gsk3b/Snail axis as the molecular basis for the inhibition of cardiac valve formation by Amiodarone.

(1) Background: The role of using artificial intelligence (AI) with electrocardiograms (ECGs) for the diagnosis of significant coronary artery disease (CAD) is unknown. We first tested the hypothesis that using AI to read ECG could identify significant CAD and determine which vessel was obstructed. (2) Methods: We collected ECG data from a multi-center retrospective cohort with patients of significant CAD documented by invasive coronary angiography and control patients in Taiwan from 1 January 2018 to 31 December 2020. (3) Results: We trained convolutional neural networks (CNN) models to identify patients with significant CAD (>70% stenosis), using the 12,954 ECG from 2303 patients with CAD and 2090 ECG from 1053 patients without CAD. The Marco-average area under the ROC curve (AUC) for detecting CAD was 0.869 for image input CNN model. For detecting individual coronary artery obstruction, the AUC was 0.885 for left anterior descending artery, 0.776 for right coronary artery, and 0.816 for left circumflex artery obstruction, and 1.0 for no coronary artery obstruction. Marco-average AUC increased up to 0.973 if ECG had features of myocardial ischemia. (4) Conclusions: We for the first time show that using the AI-enhanced CNN model to read standard 12-lead ECG permits ECG to serve as a powerful screening tool to identify significant CAD and localize the coronary obstruction. It could be easily implemented in health check-ups with asymptomatic patients and identifying high-risk patients for future coronary events.