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Background: This study explores the impact of intensive blood pressure (BP) control on left ventricular hypertrophy (LVH) incidence and evaluates the prognostic implications of LVH status (pre-existing/new-onset/persistent/regression) using Systolic Blood Pressure Intervention Trial (SPRINT) Electrocardiogram Data., Methods: Poisson regression was used to assess new-onset LVH and LVH regression rates. Multivariable-adjusted Cox proportional hazard models determined the risk of adverse cardiovascular events (ACE), a composite of myocardial infarction (MI), non-MI acute coronary syndrome, stroke, heart failure, or cardiovascular death, alongside safety adverse events., Results: In 8,016 participants, intensive BP control significantly reduced new-onset LVH (8.27 vs. 14.79 per 1000-person years; adjusted p<0.001) and increased LVH regression (14.89 vs. 11.89 per 1000-person years; adjusted p<0.001). Elevated ACE risk was notable in participants with pre-existing LVH [adjusted HR: 1.94 (95% CI: 1.25-2.99); p = 0.003], new-onset LVH [adjusted 1.74 (95% CI: 1.16-2.60); p = 0.007], and persistent LVH[adjusted HR: 1.96 (95% CI: 1.11-3.46); p = 0.020], compared to those without LVH. Intriguingly, LVH regression attenuated this risk increment [adjusted HR: 1.57 (95% CI: 0.98-2.53); p = 0.062]. Achieving a BP target of < 120/80 mmHg nullified the increased ACE risk in those with pre-existing LVH., Conclusions: Intensive BP control is instrumental in both reducing the emergence of LVH and fostering its regression. Pre-existing, new-onset LVH and persistent LV remain a predictor of adverse cardiovascular prognosis, whereas LVH regression and achieving on-treatment BP < 120/80 mmHg in pre-existing LVH individuals may further mitigate residual cardiovascular risk., Clinical Trial Registration: URL: ClinicalTrials.gov Unique Identifier: NCT01206062., (© 2024. The Author(s).)

Backgrounds: Hematocrit is found an independent risk factor for acute kidney injury (AKI) in certain patients, but this effect in patients with acute myocardial infarction (AMI) is unclear. We aim to identify the relationship between hematocrit and AKI in patients with AMI., Methods: The patient data for the discovery and validation cohorts were extracted from the electronic Intensive Care Unit database and the Medical Information Mart for Intensive Care III database, respectively, to identify the relationship between hematocrit and AKI. With normal hematocrit as the reference, patients were divided into five groups based on the initial hematocrit value. The primary outcome was AKI during hospitalization. A multivariable logistic regression and a marginal effect analysis were used to evaluate the relationship between hematocrit and AKI., Results: In this study, a total of 9692 patients diagnosed with AMI were included, with 7712 patients in the discovery cohort and 1980 patients in the validation cohort. In the discovery cohort, hematocrit in 30-33%, 27-30% or < 27% were independent risk factors for AKI in the multivariate logistic analysis, with odds ratio (OR) of 1.774 (95% confidence interval [CI]: 1.203-2.617, p = 0.004), 1.834 (95% CI: 1.136-2.961, p = 0.013) and 2.577 (95% CI: 1.510-4.397, p < 0.001), respectively. Additionally, in the validation cohort, low hematocrit levels independently contributed to an increased risk of AKI among patients with AMI. During the analysis of marginal effects, a significant negative linear relationship between hematocrit levels and AKI was observed., Conclusions: Decreased hematocrit was an independent risk factor for AKI in patients with AMI. The relationship between hematocrit and AKI was negative linear., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 The Author(s). Published by IMR Press.)

Background: Substantial focus has been placed on atrial fibrillation (AF) treatment and associated stroke prevention rather than preventing AF itself. We employed Mendelian randomization (MR) approach to examine the causal relationships between 50 modifiable risk factors (RFs) and AF., Methods: Instrumental variables for genetically predicted exposures were derived from corresponding genome-wide association studies (GWASs). Summary-level statistical data for AF were obtained from a GWAS meta-analysis (discovery dataset, N = 1,030,836) and FinnGen (validation dataset, N = 208,594). Univariable and multivariable MR analyses were performed, primarily using inverse variance weighted method with a series of robust sensitivity analyses., Results: Genetic predisposition to insomnia, daytime naps, apnea, smoking initiation, moderate to vigorous physical activity and obesity traits, including body mass index, waist-hip ratio, central and peripheral fat/fat-free mass, exhibited significant associations with an increased risk of AF. Coffee consumption and ApoB had suggestive increased risks. Hypertension (odds ratio (OR) 95% confidence interval (CI): 5.26 (4.42, 6.24)), heart failure (HF) (OR 95% CI, 4.77 (2.43, 9.37)) and coronary artery disease (CAD) (OR 95% CI: 1.20 (1.16, 1.24)) were strongly associated with AF, while college degree, higher education attachment and HDL levels were associated with a decreased AF risk. Reverse MR found a bidirectional relationship between genetically predicted AF and CAD, HF and ischemic stroke. Multivariable analysis further indicated that obesity-related traits, systolic blood pressure and lower HDL levels independently contributed to the development of AF., Conclusions: This study identified several lifestyles and cardiometabolic factors that might be causally related to AF, underscoring the importance of a holistic approach to AF management and prevention., (© 2024 Stichting European Society for Clinical Investigation Journal Foundation. Published by John Wiley & Sons Ltd.)

Background: The implantable cardioverter-defibrillator (ICD) prevents sudden cardiac death in patients with ischemic cardiomyopathy (ICM). Catheter ablation has been shown to effectively reduce ventricular tachycardia (VT) recurrence, yet its efficacy in patients without an ICD implantation remains uncertain., Objective: We aimed to investigate the outcomes of ablation for VT in patients with ICM without a backup ICD., Methods: Patients with ICM who received ablation for VT without an ICD implantation were included in this study. Ablation was guided by either activation mapping or substrate mapping. Endocardial ablation was the primary strategy; epicardial access was considered when endocardial ablation failed. The primary end point was VT recurrence during follow-up; secondary end points included cardiovascular rehospitalization, all-cause mortality, and a composite of these events., Results: A total of 114 patients were included, with the mean age of 58.2 ± 11.1 years, 102 of whom (89.5%) were male. Twelve patients (10.5%) underwent endo-epicardial ablation, whereas the rest received endocardial ablation. With a median follow-up of 53.8 months (24.8-84.2 months), VT recurred in 45 patients (39.5%), and 6 patients (5.3%) died, including 2 sudden cardiac deaths. The recurrence rate of VT was significantly lower in patients undergoing endo-epicardial ablation than in those with endocardial ablation only (8.3% vs 43.1%; log-rank P = .032). After multivariate adjustment, epicardial ablation remained associated with a reduced risk of VT recurrence (hazard ratio, 0.14; 95% confidential interval, 0.02-0.98; P = .048)., Conclusion: Patients with ICM undergoing VT ablation without a backup ICD experienced a notably low rate of arrhythmic death. Most recurrences proved nonlethal., Competing Interests: Disclosures The authors declare no conflicts of interest., (Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Background: The stress hyperglycemia ratio (SHR), adjusted for average glycemic status, is suggested for assessing actual blood glucose levels. Its link with adverse outcomes is known in certain populations, yet its impact on sepsis patients' prognosis is unclear. This study explores the association between SHR and mortality in sepsis., Methods: We included 13,199 sepsis patients in this study and categorized SHR into distinct groups. Additionally, we utilized restricted cubic spline analysis to evaluate the correlation between SHR as a continuous variable and mortality. The primary outcome was 1-year all-cause mortality. Logistic regression and Cox proportional hazards models were employed to assess the associations between the SHR and both in-hospital mortality and 1-year mortality, respectively., Results: Among the study participants, 4,690 (35.5%) patients died during the 1-year follow-up. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and 1-year mortality. Using an SHR of 0.99 as the reference point, the hazard ratio for predicted 1-year mortality increased by 1.17 (95% CI 1.08 to 1.27) per standard deviation above 0.99, whereas each standard deviation increase predicted the hazard ratio of 0.52 (95% CI 0.39 to 0.69) below 0.99. Furthermore, we found that SHR could enhance the predictive performance of conventional severity scores., Conclusion: There exists a U shaped association between SHR and mortality in sepsis patients, where both low and high SHR values are associated with an increased risk of poor outcomes., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Women are frequently underrepresented in clinical trials and databases focusing on ventricular arrhythmias (VAs). However, understanding sex-based differences in risk factors and the prognosis of VAs is essential for tailoring personalized prevention and treatment strategies. This study aimed to investigate sex differences in the epidemiology, risk factors, and prognosis of VAs in patients with sepsis., Methods: We conducted a comprehensive analysis of 27,139 sepsis patients (mean [SD] age, 66.6 [16.2] years; 15,626 [57.6%] male), among whom 1136 (4.2%) developed VAs during their hospitalization. We evaluated VAs incidence and potential risk elements in both male and female patients, along with in-hospital mortality., Results: Men had a significantly higher likelihood of developing VAs compared to women (odds ratio [OR]: 1.70, 95% confidence interval [CI]: 1.50-1.94, p < 0.001). In the case of non-ischemic cardiomyopathy (NICM), the association with VAs was stronger in men than in women (relative risk ratio [RRR] = 1.63, 95% CI: 1.10-2.40, interaction p = 0.014). Furthermore, we observed significant sex-specific interactions in the relationship between incident VAs, congestive heart failure (CHF) (RRR = 1.35, 95% CI: 1.03-1.76, interaction p = 0.031), and pneumonia (RRR = 1.33, 95% CI: 1.02-1.74, interaction p = 0.036) when considering the adjusted model. The presence of VAs was associated with a nearly twofold increase in the risk of in-hospital mortality, a result that was observed in both sexes., Conclusions: In sepsis patients, the emergence of VAs independently escalates the risk of in-hospital mortality, with a notable correlation between male sex and an increased VAs risk. The impacts of CHF, NICM and pneumonia on incident VAs were significantly influenced by sex., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 The Author(s). Published by IMR Press.)

Background: Mechanical ventilation (MV) is widely used to relieve respiratory failure in patients with congestive heart failure (CHF). Prolonged MV (PMV) is associated with a poor prognosis. We aimed to establish a prediction model based on machine learning (ML) algorithms for the early identification of patients with CHF requiring PMV., Methods: Twelve commonly used ML algorithms were used to build the prediction model. The least absolute shrinkage and selection operator (LASSO) regression was employed to select the key features. We examined the area under the curve (AUC) statistics to evaluate the prediction performance. Data from another database were used to conduct external validation., Results: We screened out 10 key features from the initial 65 variables via LASSO regression to improve the practicability of the model. The CatBoost model showed the best performance for predicting PMV among the 12 commonly used ML algorithms, with favorable discrimination (AUC = 0.790) and calibration (Brier score = 0.154). Moreover, hospital mortality could be accurately predicted using the CatBoost model as well (AUC = 0.844). In the external validation, the CatBoost model also showed satisfactory prediction performance (AUC = 0.780), suggesting certain generalizability of the model. Finally, a nomogram with risk classification of PMV was shown in this study., Conclusion: The present study developed and validated a CatBoost model, which could accurately predict PMV in mechanically ventilated patients with CHF. Moreover, this model has a favorable performance in predicting hospital mortality in these patients., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Aims: Catheter ablation of ventricular tachycardia (VT) improves VT-free survival in 'classic' arrhythmogenic right ventricular cardiomyopathy (ARVC). This study aims to investigate electrophysiological features and ablation outcomes in patients with ARVC and biventricular (BiV) involvement., Methods and Results: We assembled a retrospective cohort of definite ARVC cases with sustained VTs. Patients were divided into the BiV (BiV involvement) group and the right ventricular (RV) (isolated RV involvement) group based on the left ventricular systolic function detected by cardiac magnetic resonance. All patients underwent electrophysiological mapping and VT ablation. Acute complete success was non-inducibility of any sustained VT, and the primary endpoint was VT recurrence. Ninety-eight patients (36 ± 14 years; 87% male) were enrolled, including 50 in the BiV group and 48 in the RV group. Biventricular involvement was associated with faster clinical VTs, a higher VT inducibility, and more extensive arrhythmogenic substrates (all P < 0.05). Left-sided VTs were observed in 20% of the BiV group cases and correlated with significantly reduced left ventricular systolic function. Catheter ablation achieved similar acute efficacy between these two groups, whereas the presence of left-sided VTs increased acute ablation failure (40 vs. 5%, P = 0.012). Over 51 ± 34 months [median, 48 (22-83) months] of follow-up, cumulative VT-free survival was 52% in the BiV group and 58% in the RV group (P = 0.353). A multivariate analysis showed that younger age, lower RV ejection fraction (RVEF), and non-acute complete ablation success were associated with VT recurrence in the BiV group., Conclusion: Biventricular involvement implied a worse arrhythmic phenotype and increased the risk of left-sided VTs, while catheter ablation maintained its efficacy for VT control in this population. Younger age, lower RVEF, and non-acute complete success predicted VT recurrence after ablation., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Autoimmune myocarditis, with increasing incidence and limited therapeutic strategies, is in urgent need to explore its underlying mechanisms and effective drugs. Pyroptosis is a programmed cell death that may contribute to the pathogenesis of myocarditis. Nonetheless, no direct evidence validated the role of pyroptosis in autoimmune myocarditis. Lupeol (Lup), a pentacyclic triterpene, possesses various biological activities such as antidiabetic properties. However, the effects of Lup on autoimmune myocarditis and pyroptosis remain unelucidated., Purpose: This study aimed to reveal the role of pyroptosis in autoimmune myocarditis and explore the protective effects of Lup, and its engaged mechanisms., Methods: The experimental autoimmune myocarditis (EAM) mouse model was established by immunization with a fragment of cardiac myosin in Balb/c mice. Lup and MCC950 were administered after EAM induction. The protective effects were assessed by inflammation score, cardiac injury, chronic fibrosis, and cardiac function. Mechanistically, the effects of Lup on the M1 polarization and pyroptosis of macrophages were evaluated. Transcriptome sequencing and molecular docking were subsequently employed, and the underlying mechanisms of Lup were further explored in vitro with small interfering RNA and adenovirus., Results: Administration of Lup and MCC950 alleviated EAM progression. Western blotting and immunofluorescence staining identified macrophages as the primary cells undergoing pyroptosis. Lup inhibited the expression of pyroptosis-associated proteins in macrophages during EAM in a dose-dependent manner. Furthermore, Lup suppressed pyroptosis in both bone marrow-derived macrophages (BMDMs) and THP-1-derived macrophages in vitro. In addition, Lup inhibited the M1 polarization of macrophages both in vivo and in vitro. Mechanistically, the protective effects of Lup were demonstrated via the suppression of the nuclear factor-κΒ (NF-κB) signaling pathway. Transcriptome sequencing and molecular docking revealed the potential involvement of peroxisome proliferator-associated receptor α (PPARα). Subsequently, we demonstrated that Lup activated PPARα to reduce the expression level of LACC1, thereby inhibiting the NF-κB pathway and pyroptosis., Conclusion: Our findings indicated the crucial role of macrophage pyroptosis in the pathogenesis of EAM. Lup ameliorated EAM by inhibiting the M1 polarization and pyroptosis of macrophages through the PPARα/LACC1/NF-κB signaling pathway. Thus, our results provided a novel therapeutic target and agent for myocarditis., Competing Interests: Declaration of Competing Interest All authors declared that no relevant conflicts of interest exist in this study., (Copyright © 2023 The Author(s). Published by Elsevier GmbH.. All rights reserved.)

Aims: The aim of this study was to investigate the outcomes of catheter ablation (CA) in preventing arrhythmic events among patients with symptomatic Brugada syndrome (BrS) who declined implantable cardioverter defibrillator (ICD) implantation., Methods and Results: A total of 40 patients with symptomatic BrS were included in the study, of which 18 refused ICD implantation and underwent CA, while 22 patients received ICD implantation. The study employed substrate modification (including endocardial and epicardial approaches) and ventricular fibrillation (VF)-triggering pre-mature ventricular contraction (PVC) ablation strategies. The primary outcomes were a composite endpoint consisting of episodes of VF and sudden cardiac death during the follow-up period. The study population had a mean age of 43.8 ± 9.6 years, with 36 (90.0%) of them being male. All patients exhibited the typical Type 1 BrS electrocardiogram pattern, and 16 (40.0%) were carriers of an SCN5A mutation. The Shanghai risk scores were comparable between the CA and the ICD groups (7.05 ± 0.80 vs. 6.71 ± 0.86, P = 0.351). Ventricular fibrillation-triggering PVCs were ablated in 3 patients (16.7%), while VF substrates were ablated in 15 patients (83.3%). Epicardial ablation was performed in 12 patients (66.7%). During a median follow-up of 46.2 (17.5-73.7) months, the primary outcomes occurred more frequently in the ICD group than in the CA group (5.6 vs. 54.5%, Log-rank P = 0.012)., Conclusion: Catheter ablation is an effective alternative therapy for improving arrhythmic outcomes in patients with symptomatic BrS who decline ICD implantation. Our findings support the consideration of CA as an alternative treatment option in this population., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Life-threatening ventricular arrhythmias (LTVAs) are main causes of sudden cardiac arrest and are highly associated with an increased risk of mortality. A prediction model that enables early identification of the high-risk individuals is still lacking., Objective: We aimed to build machine learning (ML)-based models to predict in-hospital mortality in patients with LTVA., Methods: A total of 3140 patients with LTVA were randomly divided into training (n=2512, 80%) and internal validation (n=628, 20%) sets. Moreover, data of 2851 patients from another database were collected as the external validation set. The primary output was the probability of in-hospital mortality. The discriminatory ability was evaluated by the area under the receiver operating characteristic curve (AUC). The prediction performances of 5 ML algorithms were compared with 2 conventional scoring systems, namely, the simplified acute physiology score (SAPS-II) and the logistic organ dysfunction system (LODS)., Results: The prediction performance of the 5 ML algorithms significantly outperformed the traditional models in predicting in-hospital mortality. CatBoost showed the highest AUC of 90.5% (95% CI 87.5%-93.5%), followed by LightGBM with an AUC of 90.1% (95% CI 86.8%-93.4%). Conversely, the predictive values of SAPS-II and LODS were unsatisfactory, with AUCs of 78.0% (95% CI 71.7%-84.3%) and 74.9% (95% CI 67.2%-82.6%), respectively. The superiority of ML-based models was also shown in the external validation set., Conclusions: ML-based models could improve the predictive values of in-hospital mortality prediction for patients with LTVA compared with traditional scoring systems., (©Le Li, Ligang Ding, Zhuxin Zhang, Likun Zhou, Zhenhao Zhang, Yulong Xiong, Zhao Hu, Yan Yao. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.11.2023.)

Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is prevalent in hypertensive people, but the causal effect remains unclear. We employed Mendelian randomization (MR) approach to assess the causality between NAFLD and different blood pressure (BP) parameters., Method and Results: Instrumental variables for genetically predicted NAFLD, including chronically elevated serum alanine aminotransferase levels (cALT) and imaging and biopsy-confirmed NAFLD, were obtained from a genome-wide association study (N = 164,197). Multiple MR methods were implemented, including Inverse variance weighted, MR-Egger, Maximum likelihood, Weighted median, Simple median, Penalised weighted median, MR-RAPS, and cML-MA. Outliers were detected using MR-PRESSO, and pleiotropy was assessed using MR-Egger intercept and Phenoscanner. Heterogeneity was quantified using Cochran's Q and Rucker's Q' tests. Potential shared risk factors were analyzed to reveal the mediating effect. A higher genetic predisposition to cALT was causally associated with an increased risk of elevated BP levels, resulting in 0.65 mmHg (95% CI, 0.42-0.87), 0.38 mmHg (95% CI, 0.25-0.50) and 0.33 mmHg (95% CI, 0.22-0.44) higher for systolic BP, diastolic BP and pulse pressure, respectively. When more stringent criteria were used, imaging and biopsy-confirmed NAFLD showed a 1.12 mmHg (95% CI, 0.94-1.30) increase in SBP and a 0.55 mmHg (95% CI, 0.39-0.70) increase in DBP. Risk factor and mediation analyses suggested type 2 diabetes and fasting insulin levels might mediate the causal relationship between NAFLD and BP., Conclusion: The two-sample MR analyses showed robust causal effects of genetically predicted NAFLD on 3 different BP indices. The shared genetic profile between NAFLD and BP may suggest important therapeutic targets and early interventions for cardiometabolic risk factors., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2023 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Background: The stress hyperglycemia ratio (SHR) has demonstrated a noteworthy association with unfavorable cardiovascular clinical outcomes and heightened in-hospital mortality. Nonetheless, this relationship in critically ill patients remains uncertain. This study aims to elucidate the correlation between SHR and patient prognosis within the critical care setting., Methods: A total of 8978 patients admitted in intensive care unit (ICU) were included in this study. We categorized SHR into uniform groups and assessed its relationship with mortality using logistic or Cox regression analysis. Additionally, we employed the restricted cubic spline (RCS) analysis method to further evaluate the correlation between SHR as a continuous variable and mortality. The outcomes of interest in this study were in-hospital and 1-year all-cause mortality., Results: In this investigation, a total of 825 (9.2%) patients experienced in-hospital mortality, while 3,130 (34.9%) individuals died within the 1-year follow-up period. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and both in-hospital and 1-year mortality. Specifically, within the SHR range of 0.75-0.99, the incidence of adverse events was minimized. For each 0.25 increase in the SHR level within this range, the risk of in-hospital mortality rose by 1.34-fold (odds ratio [OR]: 1.34, 95% CI: 1.25-1.44), while a 0.25 decrease in SHR within 0.75-0.99 range increased risk by 1.38-fold (OR: 1.38, 95% CI: 1.10-1.75)., Conclusion: There was a U-shaped association between SHR and short- and long-term mortality in critical ill patients, and the inflection point of SHR for poor prognosis was identified at an SHR value of 0.96., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: High-sensitivity C-reaction protein (hsCRP), a biomarker of residual inflammatory risk, has been demonstrated with poor cardiovascular outcomes. We aimed to investigate the prognostic value of hsCRP in patients undergoing percutaneous coronary intervention (PCI) with or without diabetes mellitus (DM)., Methods: In this large-scale, prospective cohort study, we enrolled 8050 consecutive patients who underwent PCI for coronary artery stenosis. All subjects were stratified as high hsCRP (> 3 mg/L) and low hsCRP (≤ 3 mg/L) and were divided into four groups (hsCRP-L/non-DM, hsCRP-H/non-DM, hsCRP-L/DM, hsCRP-H/DM). The primary endpoint of the study was major adverse cardiovascular events (MACEs), including all-cause mortality, myocardial infarction, stroke, and unplanned vessel revascularization, evaluated at a 3 year follow-up., Results: After 35.7 months (interquartile range: 33.2 to 36.0 months) of median follow-up time, 674 patients suffered from MACEs. We found elevated hsCRP was highly associated with an increased risk of MACEs in both diabetic (hazard ratio [HR] = 1.68, 95% confidence interval CI 1.29-2.19, P < 0.001) and non-diabetic patients (HR = 1.31, 95% CI: 1.05-1.62, P = 0.007) after adjustment for other confounding factors. Kaplan-Meier survival analysis showed the highest incidence of MACEs in hsCRP-H/DM (P < 0.001). In addition, the results of the restricted cubic spline analysis suggested a positive linear relationship between hsCRP and MACEs., Conclusion: Elevated hsCRP is an independent risk factors of MACEs in patients undergoing PCI irrespective of glycemic metabolism status., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Observational studies have suggested a close association between atrial fibrillation (AF) and heart failure (HF), yet the causal effect remains uncertain. In this study, we employed a bidirectional Mendelian randomization analysis to investigate the causal effect of one disease on the other., Methods: Genetic instrumental variables were obtained from large-scale summary-level genome-wide association studies of AF (n = 1,030,836) and HF(n = 1,665,481), respectively. Two-sample Mendelian randomization was conducted to establish causal inferences. Inverse-variance weighted (IVW) was the primary estimate, while additional analyses including MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, and Weighted median were performed to validate robustness and identify pleiotropy., Results: After accounting for confounding variables, MR analysis suggested a potential causal relationship between AF and HF. An augmented genetic predisposition to atrial fibrillation was associated with an elevated risk of heart failure (odds ratio (OR) = 1.18, 95% confidence interval (CI):1.14-1.22). Likewise, genetically determined heart failure also increased the risk of heart failure (OR = 1.44, 95%CI:1.23-1.68). The robustness of the findings was corroborated through MR sensitivity analyses, and the causal estimates remained consistent when the instrument P-value threshold was tightened., Conclusions: Our bidirectional Mendelian randomization study supports a reciprocal causal relationship between AF and HF. The shared genetic profile of these conditions may provide crucial insights into potential therapeutic targets for the prevention and progression of both disorders. These findings underscore the necessity for further investigation into the underlying molecular mechanisms linking AF and HF, as well as the potential for personalized treatment strategies grounded in genetic profiling., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Aims: Life-threatening ventricular arrhythmias (LTVAs) are common manifestations of sepsis. The majority of sepsis patients with LTVA are unresponsive to initial standard treatment and thus have a poor prognosis. There are very limited studies focusing on the early identification of patients at high risk of LTVA in sepsis to perform optimal preventive treatment interventions. We aimed to develop a prediction model to predict LTVA in sepsis using machine learning (ML) approaches., Methods and Results: Six ML algorithms including CatBoost, LightGBM, and XGBoost were employed to perform the model fitting. The least absolute shrinkage and selection operator (LASSO) regression was used to identify key features. Methods of model evaluation involved in this study included area under the receiver operating characteristic curve (AUROC), for model discrimination, calibration curve, and Brier score, for model calibration. Finally, we validated the prediction model both internally and externally. A total of 27 139 patients with sepsis were identified in this study, 1136 (4.2%) suffered from LTVA during hospitalization. We screened out 10 key features from the initial 54 variables via LASSO regression to improve the practicability of the model. CatBoost showed the best prediction performance among the six ML algorithms, with excellent discrimination (AUROC = 0.874) and calibration (Brier score = 0.157). The remarkable performance of the model was presented in the external validation cohort ( n = 9492), with an AUROC of 0.836, suggesting certain generalizability of the model. Finally, a nomogram with risk classification of LTVA was shown in this study., Conclusion: We established and validated a machine leaning-based prediction model, which was conducive to early identification of high-risk LTVA patients in sepsis, thus appropriate methods could be conducted to improve outcomes., Competing Interests: Conflict of interest: The authors declare that they have no competing interests., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Female patients are underrepresented in randomized controlled clinical trials and registries of ventricular arrhythmia (VA). Personalized prevention and therapies require an understanding of sex differences in risk factors and prognosis of VA., Objective: We aimed to assess sex differences in the incidence, risk factors, and mortality of VA in congestive heart failure (HF) patients., Methods: This study included 10,889 patients (mean [SD] age, 73.8 [13.4] years; 5917 [53.8%] male) with congestive HF, of which 1555 (14.3%) patients developed VA during hospitalization. VA incidence, potential risk factors, and in-hospital mortality were evaluated in both sexes., Results: Men were more strongly associated with incident VA compared with women (odds ratio [OR]: 2.006, 95% CI: 1.790-2.248, p < 0.001). Thirteen potential predictors, which accounted for 91.0% of the risk of VA in men and 88.2% in women, were included in this study. There were significant interactions by sex in the association between incident VA, atrial fibrillation (AF) (relative risk ratio = 0.730, 95% CI: 0.571-0.933, interaction p = 0.012), and non-ischemic cardiomyopathy (NICM) (relative risk ratio = 1.391, 95% CI: 1.029-1.872, interaction p = 0.030). Congestive HF patients developed with VA had an approximately 1.5-fold risk of in-hospital mortality, which was not affected by sex., Conclusions: In congestive HF patients, incident VA was an independent risk factor of in-hospital mortality, and male sex was strongly associated with an increased risk of VA. Awareness of sex differences in the association of AF and NICM with VA may enhance therapeutic decisions, thus improving their clinical outcomes., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Mechanically ventilated patients with congestive heart failure (CHF) are at high-risk of mortality. We aimed to develop and validate a prediction model based on machine learning (ML) algorithms to predict hospital mortality in mechanically ventilated patients with CHF., Methods: Least absolute shrinkage and selection operator (LASSO) regression was used to identify the key features. Hyperparameters optimization (HPO) was conducted to modify the prediction model. The area under the receiver operating characteristic curve (AUC), accuracy, calibration curve and decision curve analysis were used to evaluate prediction performance. The final model was validated using an external validation set from another database. The prediction results were represented by a nomogram., Results: A total of 4530 qualified patients were included. Among 11 ML-algorithms, CatBoost showed the best prediction performance (AUC = 0.833). And 10 key features (10/63) were selected based on the LASSO regression. After HPO, the prediction performance of the CatBoost model based on the key features was significantly improved (AUCs: 0.805 vs. 0.821). Additionally, the CatBoost model also showed the satisfactory prediction performance in the external validation set (AUC = 0.806)., Conclusion: The present study developed and validated a CatBoost model, which could accurately predict hospital mortality in mechanically ventilated patients with CHF., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Backgrounds: Decreased urine output (UO) is associated with adverse outcomes in certain patients, but this effect in patients admitted for cardiovascular diseases is still unproven. Moreover, the relationship between increased UO and prognosis is also unclear., Objective: To investigate the relationship between decreased or increased UO and outcomes in patients with the cardiovascular intensive care unit (CICU)., Methods: This study was a retrospective cohort analysis based on the medical information mart for intensive care III (MIMIC-III) database. The patients' data were extracted from the Beth Israel Deaconess Medical Center (Boston, MA) between 2001 and 2012. With the initial 24-h UO range from 0.5 to 1.0 ml/kg/h as the reference, participants were divided into the several groups. The primary outcome was 30-day mortality. The secondary outcomes were 90-day mortality, ICU mortality, hospital mortality, use of mechanical ventilation (MV), and vasopressor agents in the first 24-h of ICU. The association between UO and mortality was assessed by multivariable logistic regression., Results: A total of 13,279 patients admitted to CICU were included. Low UO (< 0.5 ml/kg/h) was strongly associated with 30-day mortality (unadjusted OR = 3.993, 95% CI: 3.447-4.625, p < 0.001), and very high UO (≥ 2.0 ml/kg/h) was also a significantly risk factor for 30-day mortality (Unadjusted OR = 2.069, 95% CI: 1.701-2.516, p < 0.001) compared with the reference. The same effects also were shown in the multivariable logistic regression, adjusted by age, gender, vital signs, common comorbidities, and use of diuretics, with an adjusted OR of 2.023 (95% CI: 1.693-2.417, p < 0.001) for low UO and 1.771 (95% CI: 1.389-2.256, p < 0.001) for very high UO. Moreover, both decreased UO and increased UO were risk factors for 90-day mortality, ICU mortality, hospital mortality, use of MV and vasopressor agents., Conclusion: The decreased and increased UO both were significantly associated with short-term mortality, the relationship between UO and mortality was U-shape rather than linear., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Zhang, Xiong, Hu, Liu, Tu and Yao.)

Background: Mycobacterium bovis bacillus Calmette-Guérin (BCG) is an attenuated live vaccine that provides insufficient protection against tuberculosis (TB), the underlying mechanisms for which remain unknown. Assuming that the BCG vaccine inherits immune evasive strategies from virulent parent M. bovis strains, we aimed to identify the associated genes and assess their effects on the vaccine efficacy., Methods: Three genes, BCG&#95;3174, BCG&#95;1782, and BCG&#95;2432c, associated with immune evasion were first identified via bioinformatics analysis and then confirmed in the genome of M. bovis and 12 commercial BCG vaccine substrains using Polymerase Chain Reaction (PCR) and DNA sequencing. These genes were disrupted to develop mutant strains, and their effects on autophagy and their protective efficacy were further compared with the BCG vaccine in vitro and in vivo., Results: Of the three identified genes, only the disruption of BCG&#95;2432c, namely ΔBCG&#95;2432c, conferred stronger protection against intranasal TB in vaccinated mice, when compared with the BCG vaccine. ΔBCG&#95;2432c showed a stronger ability to trigger intracellular ROS-mediated complete autophagic flux in infected THP-1 cells that resulted in higher antigen presentation. The improved protection could be attributed to early and increased IFN-γ + CD4 + T EM and IL-2 + CD4 + T CM cells in the spleens and lungs of ΔBCG&#95;2432c-vaccinated mice., Conclusions: The insufficient efficacy of the BCG vaccine is attributable to the important autophagy-inhibition gene BCG&#95;2432c that blocks the autophagosome-lysosome pathway of antigen presentation. ΔBCG&#95;2432c provides a promising platform to either replace the current BCG vaccine or develop vaccines that are more effective against TB., (© 2021 European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Background and Objective: Research on automatic auscultation diagnosis of COVID-19 has not yet been developed. We therefore aimed to engineer a deep learning approach for the automated grading diagnosis of COVID-19 by pulmonary auscultation analysis., Methods: 172 confirmed cases of COVID-19 in Tongji Hospital were divided into moderate, severe and critical group. Pulmonary auscultation were recorded in 6-10 sites per patient through 3M littmann stethoscope and the data were transferred to computer to construct the dataset. Convolutional neural network (CNN) were designed to generate classifications of the auscultation. F1 score, the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity and specificity were quantified. Another 45 normal patients were served as control group., Results: There are about 56.52%, 59.46% and 78.85% abnormal auscultation in the moderate, severe and critical groups respectively. The model showed promising performance with an averaged F1 scores (0.9938 95% CI 0.9923-0.9952), AUC ROC score (0.9999 95% CI 0.9998-1.0000), sensitivity (0.9938 95% CI 0.9910-0.9965) and specificity (0.9979 95% CI 0.9970-0.9988) in identifying the COVID-19 patients among normal, moderate, severe and critical group. It is capable in identifying crackles, wheezes, phlegm sounds with an averaged F1 scores (0.9475 95% CI 0.9440-0.9508), AUC ROC score (0.9762 95% CI 0.9848-0.9865), sensitivity (0.9482 95% CI 0.9393-0.9578) and specificity (0.9835 95% CI 0.9806-0.9863)., Conclusions: Our model is accurate and efficient in automatically diagnosing COVID-19 according to different categories, laying a promising foundation for AI-enabled auscultation diagnosing systems for lung diseases in clinical applications., Competing Interests: Declaration of Competing Interest All authors declare no competing interests., (Copyright © 2021. Published by Elsevier B.V.)

Sympathetic overactivation plays an important role in promoting a variety of pathophysiological processes in cardiovascular diseases (CVDs), including ventricular remodeling, vascular endothelial injury and atherosclerotic plaque progression. Device-based sympathetic nerve (SN) regulation offers a new therapeutic option for some CVDs. Renal denervation (RDN) is the most well-documented method of device-based SN regulation in clinical studies, and several large-scale randomized controlled trials have confirmed its value in patients with resistant hypertension, and some studies have also found RDN to be effective in the control of heart failure and arrhythmias. Pulmonary artery denervation (PADN) has been clinically shown to be effective in controlling pulmonary hypertension. Hepatic artery denervation (HADN) and splenic artery denervation (SADN) are relatively novel approaches that hold promise for a role in cardiovascular metabolic and inflammatory-immune related diseases, and their first-in-man studies are ongoing. In addition, baroreflex activation, spinal cord stimulation and other device-based therapies also show favorable outcomes. This review summarizes the pathophysiological rationale and the latest clinical evidence for device-based therapies for some CVDs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Li, Hu, Xiong and Yao.)

Genome-wide association studies (GWAS) have identified more than 2000 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, most of which are located in the non-coding region. However, the causal SNPs functioning as gene regulatory elements still remain largely undisclosed. Here, we applied a Dinucleotide Parallel Reporter sequencing (DiR-seq) assay to evaluate 288 breast cancer risk SNPs in nine different breast cancer cell lines. Further multi-omics analysis with the ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing), DNase-seq (DNase I hypersensitive sites sequencing) and histone modification ChIP-seq (Chromatin Immunoprecipitation sequencing) nominated seven functional SNPs in breast cancer cells. Functional investigations show that rs4808611 affects breast cancer progression by altering the gene expression of NR2F6 . For the other site, rs2236007, the alteration promotes the binding of the suppressive transcription factor EGR1 and results in the downregulation of PAX9 expression. The downregulated expression of PAX9 causes cancer malignancies and is associated with the poor prognosis of breast cancer patients. Our findings contribute to defining the functional risk SNPs and the related genes for breast cancer risk prediction.

Many studies reported that spontaneous fluctuation of the blood oxygen level-dependent signal exists in multiple frequency components and changes over time. By assuming a reliable energy contrast between low- and high-frequency bands for each voxel, we developed a novel spectrum contrast mapping (SCM) method to decode brain activity at the voxel-wise level and further validated it in designed experiments. SCM consists of the following steps: first, the time course of each given voxel is subjected to fast Fourier transformation; the corresponding spectrum is divided into low- and high-frequency bands by given reference frequency points; then, the spectral energy ratio of the low- to high-frequency bands is calculated for each given voxel. Finally, the activity decoding map is formed by the aforementioned energy contrast values of each voxel. Our experimental results demonstrate that the SCM (1) was able to characterize the energy contrast of task-related brain regions; (2) could decode brain activity at rest, as validated by the eyes-closed and eyes-open resting-state experiments; (3) was verified with test-retest validation, indicating excellent reliability with most coefficients > 0.9 across the test sessions; and (4) could locate the aberrant energy contrast regions which might reveal the brain pathology of brain diseases, such as Parkinson's disease. In summary, we demonstrated that the reliable energy contrast feature was a useful biomarker in characterizing brain states, and the corresponding SCM showed excellent brain activity-decoding performance at the individual and group levels, implying its potentially broad application in neuroscience, neuroimaging, and brain diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Yu, Cai, Li, Xiong, Yang, He, Tang, Zhang, Du, Yan, Chang and Wang.)

Idiopathic ventricular arrhythmia (IVA) is a term used to describe a spectrum of ventricular arrhythmia without structural heart disease (SHD). IVAs contain premature ventricular contractions (PVCs), nonsustained monomorphic ventricular tachycardia (VT), and sustained VT. Electrocardiography is a fundamental and important tool to diagnose and localize IVAs. More detailed, IVAs originating from different origins exhibit characterized ECGs due to their specific anatomic backgrounds. As catheter ablation becomes widely used to eliminate these arrhythmias, its high success rate is based on accurate localization of their origins. Therefore, these ECG characteristics show great importance for precise localization of their origins and subsequently successful ablation. This review aims to sum up ECG characteristics of IVAs based on anatomy and give brief introduction of mechanisms and treatment of IVAs., (© 2020 The Authors. Annals of Noninvasive Electrocardiology published by Wiley Periodicals LLC.)

Background: Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple heart abnormalities that covers a wide range of arrhythmias, with better-than-human accuracy, has not yet been developed. We therefore aimed to engineer a deep learning approach for the automated multilabel diagnosis of heart rhythm or conduction abnormalities by real-time ECG analysis., Methods: We used a dataset of ECGs (standard 10 s, 12-channel format) from adult patients (aged ≥18 years), with 21 distinct rhythm classes, including most types of heart rhythm or conduction abnormalities, for the diagnosis of arrhythmias at multilabel level. The ECGs were collected from three campuses of Tongji Hospital (Huazhong University of Science and Technology, Wuhan, China) and annotated by cardiologists. We used these datasets to develop a convolutional neural network approach to generate diagnoses of arrythmias. We collected a test dataset of ECGs from a new group of patients not included in the training dataset. The test dataset was annotated by consensus of a committee of board-certified, actively practicing cardiologists. To evaluate the performance of the model we assessed the F1 score and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, as well as quantifying sensitivity and specificity. To validate our results, findings for the test dataset were compared with diagnoses made by 53 ECG physicians working in cardiology departments who had a wide range of experience in ECG interpretation (range 0 to >12 years). An external public validation dataset of 962 ECGs from other hospitals was used to study generalisability of the diagnostic model., Findings: Our training and validation dataset comprised 180 112 ECGs from 70 692 patients, collected between Jan 1, 2012, and Apr 30, 2019. The test dataset comprised 828 ECGs corresponding to 828 new patients, recorded between Sept 11, 2012, and Aug 30, 2019. At the multilabel level, our deep learning approach to diagnosing heart abnormalities resulted in an exact match in 658 (80%) of 828 ECGs, exceeding the mean performance of physicians (552 [67%] for physicians with 0-6 years of experience; 571 [69%] for physicians with 7-12 years of experience; 621 [75%] for physicians with more than 12 years of experience). Our model had an overall mean F1 score of 0·887 compared with 0·789 for physicians with 0-6 years of experience, 0·815 for physicians with 7-12 years of experience, and 0·831 for physicians with more than 12 years of experience. The model had a mean AUC ROC score of 0·983 (95% CI 0·980-0·986), sensitivity of 0·867 (0·849-0·885) and specificity of 0·995 (0·994-0·996). Promising F1 scores were also obtained from the external public database using our proposed model without any model modifications (mean F1 scores of 0·845 in multilabel and 0·852 in single-label ECGs)., Interpretation: Our model is more accurate than physicians working in cardiology departments at distinguishing a range of distinct arrhythmias in single-label and multilabel ECGs, laying a promising foundation for computational decision-support systems in clinical applications., Funding: National Natural Science Foundation of China and Hubei Science and Technology Project., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Recently, many studies have shown that pretreatment serum albumin can be closely linked to the prognosis of cancer patients, including those with renal cell carcinoma (RCC). However, not all studies have reached the same conclusion. We therefore conducted a systematic review and meta-analysis to evaluate the prognostic value of pretreatment serum albumin in RCC patients. A total of 17 studies involving 6,447 patients were included in our meta-analysis. Our results indicated that a lower pretreatment serum albumin level yielded a worse overall survival (hazard ratio [HR]=2.46, 95% confidence interval [CI] 1.92-3.13), cancer-specific survival (HR=2.22, 95% CI 1.87-2.64), and relapse-free survival/progression-free survival (HR=1.75, 95% CI 1.28-2.38). Generally, these findings were particularly pronounced when stratified by tumor type, analysis type, cut-off value, and HR-obtaining method. In conclusion, a decreased pretreatment serum albumin level implies a poor prognosis for RCC patients, and can be monitored for risk stratification and individualized treatment in RCC patients., Competing Interests: The authors report no conflicts of interest in this work.