Xiaolei Yang

Left ventricular remodeling (LVR) after anterior ST-segment elevation myocardial infarction (STEMI) is associated with adverse cardiovascular outcomes. We aimed to determine whether detailed electrocardiographic (ECG) features provide incremental predictive value beyond clinical characteristics for LVR after anterior STEMI. We retrospectively analyzed 1079 patients with anterior STEMI, including a derivation cohort of 831 patients (training, n = 665; internal validation, n = 166) and a temporal internal validation cohort of 248 patients. An exploratory cohort of 730 patients with non-anterior STEMI was also included. LVR was defined as a ≥20% increase in left ventricular end-diastolic volume from baseline to 6 months. After feature selection, two extreme gradient boosting models were constructed for risk prediction at hospital discharge: Model 1 included three clinical predictors, whereas Model 2 additionally included eight ECG features. No ECG features were retained in the exploratory non-anterior STEMI analysis. Model 2 had a higher area under the receiver operating characteristic curve (AUC) than Model 1 in both the internal validation cohort (0.869 vs. 0.787; p = 0.039) and the temporal validation cohort (0.792 vs. 0.638; p = 0.001). Model 2 also showed greater estimated net benefit in decision curve analysis and improved risk reclassification. Detailed ECG features may provide additional prognostic information beyond the clinical predictors examined in this study. The web-based calculator is intended for research use only, pending external validation.

Atrial fibrillation (AF) is a common arrhythmia associated with calcium (Ca ²⁺ ) dysregulation. Ca ²⁺ /calmodulin‐dependent protein kinase II‐δ (CaMKII‐δ) links Ca ²⁺ handling to arrhythmogenesis, but whether deubiquitination regulates its stability in AF remains unclear. We established an AF model by infusing angiotensin II (Ang II) for 3 weeks in atrial cardiomyocyte‐specific ubiquitin C‐terminal hydrolase L1 (UCHL1)‐knockout (CKO) and recombinant adeno‐associated virus serotype 9 (rAAV9)‐UCHL1‐overexpressing mice. UCHL1 was markedly upregulated in atria from Ang II‐infused mice and patients with AF. UCHL1‐CKO attenuated Ang II‐induced atrial remodeling and AF susceptibility, reduced CaMKII‐δ stability, and improved Ca ²⁺ handling, whereas UCHL1 overexpression produced the opposite effects. Mechanistically, UCHL1 bound to and deubiquitinated CaMKII‐δ at K251, preventing proteasomal degradation and thereby enhancing ryanodine receptor type 2 (RyR2) phosphorylation and Ca ²⁺ mishandling. The ubiquitination‐deficient CaMKII‐δ‐K251R mutant aggravated AF, whereas CaMKII‐δ knockdown or inhibition reduced the proarrhythmic effects of UCHL1 overexpression. Furthermore, the UCHL1 inhibitor 6RK73 reduced AF inducibility in mice. These findings identify UCHL1‐mediated stabilization of the CaMKII‐δ–RyR2 axis as a mechanism of AF and support UCHL1 as a potential therapeutic target.

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape for a broad spectrum of malignancies, substantially prolonging patient survival. However, the widespread clinical adoption of ICIs is challenged by a diverse array of cardiovascular immune-related adverse events (CV-irAEs). Among these, arrhythmias pose a considerable threat to patient safety and treatment continuity, given their insidious onset and potential lethality. Traditionally, these arrhythmias have been largely conceptualized as secondary complications of ICI-induced myocarditis, a perspective that has obscured their true clinical features. Emerging evidence indicates that ICI-associated arrhythmias exhibit distinct risk profiles and pathogenic mechanisms, suggesting that arrhythmias may be substantially more common than previously recognized and frequently manifest as standalone clinical entities rather than mere secondary complications. Accordingly, to mitigate cardiovascular risk and optimize long-term patient outcomes, this review synthesizes the epidemiology, risk factors, pathogenesis, and management strategies of ICI-associated arrhythmias, while highlighting the transformative potential of artificial intelligence-enhanced monitoring in advancing precision cardio-oncology.

Background: The clinical utility of doxorubicin, a potent chemotherapeutic agent, is severely limited by its dose‐dependent cardiotoxicity. Hypoxia‐inducible factor 1α (HIF1α) is a key regulator of cardiovascular adaptation, but its role and mechanism in doxorubicin‐induced cardiotoxicity (DIC) remain unclear. Methods: Using in vitro (AC16 cells) and in vivo (mouse) models of DIC, we used genetic (knockout, knockdown) and pharmacological (FG4592) approaches to modulate HIF1α. Cardiac function, apoptosis, endoplasmic reticulum (ER) morphology, and ER‐phagy flux were assessed. Molecular mechanisms were investigated using chromatin immunoprecipitation and promoter activity assays. Results: HIF1α exhibited a dynamic, biphasic expression pattern during DIC progression. Stabilization of HIF1α by FG4592 alleviated doxorubicin‐induced cardiac dysfunction, atrophy, fibrosis, and apoptosis, whereas HIF1α knockout exacerbated these injuries. The protective effects of FG4592 were strictly dependent on HIF1α. Mechanistically, HIF1α transcriptionally activated the ER‐phagy receptor gene testis‐expressed protein 264 ( TEX264 ) by directly binding to its promoter. This activation enhanced ER‐phagy, and suppressed ER stress–mediated apoptosis. Crucially, ablation of TEX264 abolished the cardioprotective effects of both HIF1α and FG4592. Conclusions: This study identifies a novel HIF1α/TEX264/ER‐phagy axis that is suppressed in DIC and is central to cardiomyocyte survival. Targeting this pathway, particularly with the clinically available HIF1α stabilizer FG4592, represents a promising therapeutic strategy against DIC.

Background: Hypertrophic cardiomyopathy (HCM) significantly increases the risk of new-onset atrial fibrillation (AF) through distinct pathogenic mechanisms. This study develops a machine learning (ML) model to improve AF prediction in patients with HCM and investigates electrophysiological abnormalities and non-traditional factors as preclinical predictors. The findings aim to inform early warning systems and precision management strategies for AF in this patient cohort. Methods: This retrospective cohort study consecutively enrolled patients diagnosed with HCM who had no prior history of AF from 2014 to 2023. A two-step feature selection procedure involving the Boruta algorithm and LASSO regression was implemented, and four machine-learning based algorithms were trained and compared against the reference model of the HCM-AF score. The Shapley Additive Explanations (SHAP) method was utilized for interpretability. Results: A total of 225 patients (annual incidence ratio 3.42%, 225/1014) developed new-onset AF during the median follow-up period of 6.50 years. Twelve clinical variables were identified through the feature selection process, with the random forest model demonstrating the best overall performance with area under the receiver-operating characteristic curve (AUC) 0.770 and 95% confidence interval (CI) of 0.699-0.840, outperforming the reference model (AUC 0.692, 95% CI 0.598-0.786) (Delong’s P = 0.012). The SHAP analysis revealed that indices of heart failure, age, left atrial size, followed by a history of cardiac implantable electronic devices, frequent atrial premature contractions, P-wave terminal force in lead V ₁ , P-wave duration, PR interval, and left ventricular remodeling were associated with a significantly higher model-predicted risk of AF. Conclusions: The Random Forest model outperformed the HCM-AF score with robust predictive ability, validating P-wave indices as preclinical AF biomarkers through ML model for the first time. This integrated model offers a practical tool for early AF risk stratification in HCM, highlighting the clinical value of early symptomatic monitoring. Future multicenter validation is needed.

Background: Temperature extremes are established triggers of cardiovascular events in the general population, while cancer patients face elevated atrial fibrillation (AF) risk due to disease- and treatment-related factors. However, whether cancer confers additional vulnerability to temperature-related AF events remains unclear. This study aimed to examine the association between extreme temperatures and AF hospitalizations in cancer patients compared with non-cancer controls. Methods: Data were derived from the real-world study of the Chinese AF registry (2014–2023), comprising 1,665,014 AF hospitalizations. This study is an exploratory, cancer-focused secondary analysis of the RWS-CAF registry. Overall associations between ambient temperature and AF hospitalization in the full registry have been reported separately. We used a time-stratified case-crossover design with distributed lag nonlinear models to assess temperature-AF associations. Cancer patients ( n = 243482) were compared with demographically matched non-cancer controls, and unmatched analyses were performed in the full cohort. Subgroup analyses examined effect modification by age, sex, and geographic region. Results: Extreme cold (1st percentile, − 5.6 °C) was associated with higher AF hospitalization risk in cancer patients (RR 1.80, 95% CI 1.60–2.03) compared with matched non-cancer controls (RR 1.27, 95% CI 1.21–1.34; P _interaction < 0.001). The nonoptimal temperature-attributable fraction was also higher in the cancer group (19.7%) than in matched non-cancer patients (10.2%), with cold exposure accounting for the majority of the burden. Among cancer patients, the cold-related RR was higher in males (1.86, 1.62–2.15) than in females (1.37, 1.26–1.50; P _interaction < 0.001), and the cold-related RR was higher in northern than in southern China ( P _interaction = 0.002). Lag-specific analyses suggested earlier onset and more persistent cold-related risk elevation in the cancer group. Conclusions: Patients with cancer appeared more vulnerable to cold-related AF hospitalization than those without cancer, with stronger associations observed in men and in northern regions. These findings support the possibility that cancer modifies the temperature–AF relationship and warrant confirmation in studies with prespecified analyses and more detailed oncologic characterization.

Background: The uric acid-to-albumin ratio (UAR) is a novel inflammatory marker linked to cardiovascular disease. This study aimed to evaluate the predictive value of UAR for left atrial thrombus or spontaneous echo contrast (LAT/SEC) in non-valvular atrial fibrillation (NVAF), explore its mediating mechanisms, and assess the incremental value beyond the CHA₂DS₂-VASc score. Methods: This retrospective study included 514 patients with NVAF undergoing transesophageal echocardiography (TEE). Multivariable logistic regression, restricted cubic splines (RCS), generalized additive models (GAMs), receiver operating characteristic (ROC) curves, and mediation analyses were employed to evaluate the relationship between UAR and LAT/SEC. Reclassification indices assessed UAR’s incremental value beyond the CHA₂DS₂-VASc score. Results: The prevalence of LAT/SEC was 17.32%. UAR was independently associated with LAT/SEC (OR: 1.43, 95% CI: 1.25– 1.66; P < 0.001) in a nonlinear manner (P for non-linearity = 0.031). A threshold effect was identified at 12.11, below which the risk increased more significantly (OR: 1.61, 95% CI: 1.36– 1.92; P < 0.001). UAR showed better predictive performance (AUC=0.712) than UA (0.684) and albumin (0.612). Incorporating UAR into the CHA₂DS₂-VASc model improved risk stratification. Mediation analysis indicated that left atrial diameter (LAD) and left ventricular ejection fraction (LVEF) accounted for 8.26% and 9.75% of the association, respectively. Conclusion: UAR is an independent predictor of LAT/SEC in patients with NVAF, outperforming its individual components and providing significant incremental value beyond the CHA₂DS₂-VASc score. It may serve as a readily accessible biomarker for optimizing risk stratification and clinical anticoagulation decisions. Image A is an infographic with three sections: Study Population, Exposure and Outcome, linked by arrows. Study Population features a heart icon, ECG trace and five person icons, indicating 514 NVAF cases from 2019.1 to 2022.6. Exposure shows an arm with a blood draw and a marker icon, labeled UAR (uric acid/albumin). Outcome displays a heart icon, ECG trace and five person icons, noting 89 LAT/SEC cases in NVAF patients during admission. Image B is a dose-response graph with UAR on the X-axis and Odds ratio (95% CI) on the Y-axis. The curve rises with UAR and the 95% CI band widens at higher UAR. Text indicates P for overall < 0.001 and P for nonlinear = 0.031. Image C is a decision curve analysis graph with High Risk Threshold on the X-axis and Net Benefit on the Y-axis. The legend includes UAR + CHA2DS2-VASc, CHA2DS2-VASc, All and None. The UAR + CHA2DS2-VASc curve is generally above the CHA2DS2-VASc curve, both nearing zero at higher thresholds.A three-part infographic on NVAF: UAR exposure, LAT/SEC outcome and odds and decision-curve graphs.

Breast cancer (BC)-related atrial fibrillation (AF) contributes to an overall poor prognosis and raises great concerns. However, beyond cancer treatment-related AF, it is unknown whether BC itself is sufficient to directly induce AF. This study aimed to explore the role of BC in the development of AF, focusing on the tumour itself rather than therapy-related cardiotoxicity. A retrospective analysis was conducted on 1224 female BC patients before therapy and 18 159 healthy female participants. The prevalence of AF was assessed, and markers of atrial remodelling, including P-wave indices on electrocardiogram (ECG), were measured. An orthotopic BC model was established by implanting E0771 cells to mammary fat pads of female C57BL/6 mice. An electrophysiological study was employed to assess atrial arrhythmia vulnerability. Masson’s trichrome staining, coculture assays and molecular biological techniques were used to determine the mechanisms of BC-induced AF. BC patients (n = 1217) were individually matched 1:1 to non-cancer female controls (n = 1217) by propensity score matching. Even before treatment, BC patients had a significantly higher prevalence of AF (6.41%) than controls (0.90%). BC patients exhibited more marked atrial remodelling evaluated by abnormal P-wave terminal force in ECG lead V1 (7.37% vs 3.90%, P < .001), compared to non-cancer female controls. Similarly, BC mice, as well as mice administered with tumour-conditioned media or plasma from BC mice, developed atrial fibrosis and had increased AF susceptibility. After screening tumour-secreted factors, both BC patients with AF and BC mice displayed elevated levels of soluble ADAM10 (sADAM10) in tumour tissue and plasma. Moreover, sADAM10 promoted the cleavage of Ephrin B2 into soluble Ephrin B2 (sEphrin B2) in atrial cardiofibroblasts (ACFs), which then bound with EphB3 and EphB4 receptors and activated the atrial fibrosis pathway. Cardiac fibroblast-specific knockdown of Ephrin B2 suppressed AF development in BC mice. The plasma levels of sEphrin B2 were especially higher in pre-treatment breast cancer patients with AF compared to controls, in parallel with increasing sADAM10 levels (R² = 0.67, P < .0001). The inhibition of tumour-originated sADAM10 with its specific inhibitor (GI254023X) or its shRNA attenuated atrial fibrosis and AF susceptibility in BC mice. BC patients before treatment present a significantly higher prevalence of AF and atrial remodelling, which correlate with elevated levels of tumour-originated sADAM10 and ACF-secreted sEphrin B2. Tumour-originated sADAM10 directly promotes AF pathogenesis by inducing atrial fibrosis, independent of cancer treatment. These findings imply that the inhibition of sADAM10 represents a potentially new therapeutic option for BC-associated AF.

Background: The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) has emerged as a novel biomarker for cardiovascular outcomes. However, its role in atrial fibrillation (AF) remains unclear. This meta-analysis aimed to evaluate the diagnostic efficacy of MHR in predicting AF risk. Methods: We systematically searched PubMed, Embase, and Web of Science up to March 20, 2025. The primary outcome was to assess the diagnostic accuracy of MHR for predicting AF using summary receiver operating characteristic (SROC) curve analysis. The secondary outcome was to explore the relationship between MHR and AF risk. Pooled odds ratio (OR), sensitivity, specificity, and area under the curve (AUC) were calculated. Results: A total of 13 studies comprising 5,499 participants were included. Elevated MHR was independently associated with an increased AF risk (OR = 1.21; 95% CI, 1.11–1.31; P < 0.001). The pooled sensitivity and specificity were 0.85 (95% CI, 0.71–0.93) and 0.68 (95% CI, 0.60–0.75), yielding an area under the SROC curve of 0.80 (95% CI, 0.76–0.83). Subgroup analyses revealed significant diagnostic performance variations by AF phenotype: MHR had the highest sensitivity (0.91; 95% CI 0.74–1.00) and AUC (0.94; 95% CI 0.91–0.96) in non-procedural AF, followed by post-ablation recurrence (sensitivity = 0.86, AUC = 0.83) and new-onset AF (sensitivity = 0.80, AUC = 0.83). Large-sample studies (>600) showed lower sensitivity (0.71 vs. 0.90) but higher specificity (0.78 vs. 0.60) than small-sample studies (≤600). No significant publication bias was detected ( p = 0.45). Conclusions: MHR demonstrates moderate diagnostic accuracy for AF risk prediction and is better suited as a screening or complementary biomarker than a standalone diagnostic tool. Its diagnostic performance varies significantly by AF phenotype and clinical context. Given the limited number of studies, significant heterogeneity, and unstandardized MHR cut-offs, large-scale prospective studies with standardized protocols are warranted to validate these findings and facilitate targeted clinical application. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/ , identifier CRD420251030225.