Acta cardiologica最新文献

{"title":"Triglyceride/high-density lipoprotein cholesterol ratio associates major adverse cardiac and cerebrovascular events: a 13-year prospective cohort study.","authors":"Qi Qi, Xinyu Wu, Xinyu Cui, Quanle Han, Jie Yu, Jie Deng, Xuechao Zhang, Yue Jiang, Nan Wang, Shouling Wu, Kangbo Li","doi":"10.1080/00015385.2025.2484855","DOIUrl":"https://doi.org/10.1080/00015385.2025.2484855","url":null,"abstract":"<p><strong>Background: </strong>Few studies have been conducted to investigate the association between the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and major adverse cardiac and cerebrovascular events (MACCEs) in a predominantly male cohort from China.</p><p><strong>Methods: </strong>A prospective cohort study was conducted on a total 95,837 individuals (males account for 79.67) extracted from the Kailuan study. All individuals were grouped according to the TG/HDL-C ratio quartile. The endpoints of this study were composite MACCEs and its subtypes [non-fatal myocardial (MI), non-fatal stroke and all-cause mortality]. The Kaplan-Meier method was employed to illustrate the cumulative incidence curve. The incidence rate was reported as per 1000 person-years. To explore the impact of varying quartiles of the TG/HDL-C ratio on the risk of MACCEs, Cox proportional hazard regression analysis was conducted. Furthermore, multivariate adjusted spline regression models were applied to examine the relationship between the TG/HDL-C ratio and the risk of MACCEs.</p><p><strong>Results: </strong>A total of 18,430 cases of composite MACCEs occurred during a 13.97-year follow-up. In brief, 1762 cases of MI, 6653 cases of stroke, and 12,524 cases of all-cause mortality were reported, respectively. The cumulative incidence and incidence rate of composite MACCEs, MI, and stroke increased with increment in the TG/HDL-C ratio (<i>p</i> < 0.001). In comparison to quartile 1, the hazard ratios of quartile 4 for composite MACCEs, MI, stroke, and all-cause mortality were 1.13 (95% CI 1.07-1.19), 1.55 (95% CI 1.30-1.84), 1.21 (95% CI 1.12-1.31), and 1.12 (95% CI 1.05-1.20), respectively. Multivariate adjusted spline regression models showed a nonlinear relationship between baseline TG/HDL-C ratio and risk of composite MACCEs (<i>p</i> for non-linearity < 0.01), MI (<i>p</i> for non-linearity < 0.01), stroke (<i>p</i> for non-linearity < 0.01), and all-cause mortality (<i>p</i> for non-linearity = 0.029).</p><p><strong>Conclusions: </strong>The TG/HDL-C ratio is significantly associated with an increased risk of MACCEs in a predominantly male cohort from northern China.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-9"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143959196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of obesity traits and uric acid levels with cardiovascular disease in Punjabi patients from Faisalabad, Pakistan.","authors":"Muhammad Umer Ghori, Muhammad Shareef Masoud, Muhammad Shafique, Misbah Hussain, Fazli Rabbi Awan","doi":"10.1080/00015385.2025.2490369","DOIUrl":"https://doi.org/10.1080/00015385.2025.2490369","url":null,"abstract":"<p><strong>Background: </strong>Cardiovascular diseases (CVDs) are one of the significant public health concerns worldwide. Understanding the relationship between Body Mass Index (BMI), Waist Circumference (WC), Waist-to-Hip Ratio (WHR) and uric acid levels are important in assessing cardiovascular risk. This study aimed to investigate the associations of BMI, WHR, WC and several biochemical parameters including uric acid levels with cardiovascular disease in patients from Faisalabad, Pakistan.</p><p><strong>Methods: </strong>This is a Retrospective Observational Study. A total of 403 cardiovascular patients were enrolled. Anthropometric measurements including BMI, WC and WHR were recorded. Serum samples were used to measure various biochemical parameters. SPSS ver. 21 was used to perform statistical analyses.</p><p><strong>Results: </strong>Results showed that BMI (29%↑), waist circumference (7%↑) and hip circumference (8%↑) were higher in obese CVD patients as compared to non-obese CVD patients. Additionally, uric acid levels were high (11%↑) in male CVD patients as compared to female CVD patients while total cholesterol (8%↑) and triglycerides (20%↑) levels were higher in female CVD patients as compared to male CVD patients. Pearson correlation and Linear regression analysis confirmed that uric acid was associated with total cholesterol, triglycerides, alanine transaminase, creatinine and urea levels (<i>p</i> < 0.05).</p><p><strong>Conclusion: </strong>This study confirms the associations between BMI, WC, WHR, uric acid levels and multiple biochemical parameters with health status in cardiovascular patients from Faisalabad, Pakistan.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-10"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143962955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ratio of red blood cell distribution width to albumin: a predictive biomarker of In-hospital mortality in heart failure patients.","authors":"Jingyi Lin, Lin Zhang, Shuaishuai Deng, Boxuan Feng, Li Liu, Guanwei Fan","doi":"10.1080/00015385.2025.2491151","DOIUrl":"https://doi.org/10.1080/00015385.2025.2491151","url":null,"abstract":"<p><strong>Background: </strong>The ratio of red blood cell distribution width (RDW) to albumin (ALB), known as RAR, functions as an innovative indicator related to prognosis. However, whether RAR can predict the in-hospital mortality (IHM) for heart failure (HF) patients remains ambiguous.</p><p><strong>Methods: </strong>This study included HF patients derived from the Medical Information Mart for Intensive Care III (MIMIC-III) and IV (MIMIC-IV) databases. To examine the association between RAR and IHM, multiple Logistic regression models were conducted, complemented by subgroup analyses. Additionally, to ascertain the optimal threshold for RAR, restricted cubic spline (RCS) regressions were applied.</p><p><strong>Results: </strong>In the MIMIC-III (<i>n</i> = 9,413) and MIMIC-IV (<i>n</i> = 18,685) HF cohorts, the incidence of IHM was observed in 1,639 (17.41%) and 1,175 (6.29%) participants. Following adjustment for various covariates, RAR was shown to correlate with IHM (OR, 1.45 [95% CI, 1.08-1.39]). The areas under the curves for RAR were 0.683 (MIMIC-III) and 0.710 (MIMIC-IV), indicating superior predictive value than RDW and ALB. In subgroup analysis, younger HF patients with diabetes and without atrial fibrillation or anaemia showed higher ORs than older patients without diabetes or atrial fibrillation and those with anaemia, respectively. RCS indicated the OR for RAR was non-linear with IHM, and the optimal threshold for RAR prediction was between 4.5 and 5.</p><p><strong>Conclusion: </strong>An elevated RAR correlates with an increased risk of IHM in HF patients. Given that RAR can be readily derived from routine laboratory tests, it holds potential as a novel biomarker for identifying high-risk HF patients.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-11"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143955344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges in identifying AHRE predictors.","authors":"Şuara İrem Al, Bülent Görenek, Aytuğ Al","doi":"10.1080/00015385.2025.2491149","DOIUrl":"https://doi.org/10.1080/00015385.2025.2491149","url":null,"abstract":"","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-2"},"PeriodicalIF":2.1,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143957408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Congenital heart disease and volume loading: a critical evaluation of current predictive value.","authors":"İsa Ardahanlı, Ramazan Aslan, Murat Özmen","doi":"10.1080/00015385.2025.2491148","DOIUrl":"https://doi.org/10.1080/00015385.2025.2491148","url":null,"abstract":"","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-2"},"PeriodicalIF":2.1,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143952359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aortic thrombosis presenting as acute hypertensive pulmonary edema: a diagnostic challenge.","authors":"Wannes Heylen, Matthias De Boulle, Joeri Voet","doi":"10.1080/00015385.2025.2490380","DOIUrl":"https://doi.org/10.1080/00015385.2025.2490380","url":null,"abstract":"","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-3"},"PeriodicalIF":2.1,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143968561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus.","authors":"Zhijun Bu, Siyu Bai, Chan Yang, Guanhang Lu, Enze Lei, Youzhu Su, Zhaoge Han, Muyan Liu, Jingge Li, Linyan Wang, Jianping Liu, Yao Chen, Zhaolan Liu","doi":"10.1080/00015385.2025.2481662","DOIUrl":"https://doi.org/10.1080/00015385.2025.2481662","url":null,"abstract":"<p><strong>Background: </strong>Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model for these patients by interpretable machine learning (ML) methods.</p><p><strong>Methods: </strong>Data were sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.2). Predictors were selected by Least absolute shrinkage and selection operator (LASSO) regression and checked for multicollinearity with Spearman's correlation. Patients were randomly assigned to training and validation sets in an 8:2 ratio. Seven ML algorithms were used to construct models in the training set. Model performance was evaluated in the validation set using metrics such as area under the curve (AUC) with 95% confidence interval (CI), calibration curves, precision, recall, F1 score, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The significance of differences in predictive performance among models was assessed utilising the permutation test, and 10-fold cross-validation further validated the model's performance. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) were applied to interpret the models.</p><p><strong>Results: </strong>The study included 2,828 patients with AMI combined with DM. Nineteen predictors were identified through LASSO regression and Spearman's correlation. The Random Forest (RF) model was demonstrated the best performance, with an AUC of 0.823 (95% CI: 0.774-0.872), high precision (0.867), accuracy (0.873), and PPV (0.867). The RF model showed significant differences (<i>p</i> < 0.05) compared to the K-Nearest Neighbours and Decision Tree models. Calibration curves indicated that the RF model's predicted risk aligned well with actual outcomes. 10-fold cross-validation confirmed the superior performance of RF model, with an average AUC of 0.828 (95% CI: 0.800-0.842). Significant Variables in RF model indicated that the top eight significant predictors were urine output, maximum anion gap, maximum urea nitrogen, age, minimum pH, maximum international normalised ratio (INR), mean respiratory rate, and mean systolic blood pressure.</p><p><strong>Conclusion: </strong>This study demonstrates the potential of ML methods, particularly the RF model, in predicting in-hospital mortality risk for AMI patients with DM. The SHAP and LIME methods enhance the interpretability of ML models.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-18"},"PeriodicalIF":2.1,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The value of handheld ultrasound in point-of-care or at home EF prediction.","authors":"Yue Jiang, Lingyan Zhang, Zhaoyang Liu, Lei Wang","doi":"10.1080/00015385.2025.2490382","DOIUrl":"10.1080/00015385.2025.2490382","url":null,"abstract":"<p><p>In this paper, AI-enabled handheld ultrasound is used in point-of-care or at home, and evaluate the accuracy of it for left ventricular ejection fraction (LVEF) evaluation. It provides a simple, convenient, and practical tool for the patients with heart disease, especially those with heart failure. The AI model used for this AI-enabled handheld ultrasound is a machine learning model trained with tens of thousands of ultrasound four-chamber cardiograms. The LVEF evaluation accuracy of the AI model was compared by the experts performing ultrasound four-chamber cardiogram detection in 100 patients on high-end ultrasound in the hospital. In the 100 clinical trials, the sensitivity, specificity, and accuracy of the AI model were 91%, 95%, and 98%, respectively. Then 10 cases were used to compare the LVEF results of hospital tests with the predicted results of the AI model. The difference between the two is less than 10%. Finally, over the course of one month, the AI-enabled handheld ultrasound was employed to conduct regular evaluations of left LVEF for point-of-care purposes on a group of 10 patients diagnosed with heart failure. The LVEF evaluation accuracy of AI-enabled handheld ultrasound is more than 96%, which was higher than that of experts in high-end ultrasound in hospitals. The easy-to-use AI-enabled handheld ultrasound can evaluate the LVEF in the point of care or at home and get the same accuracy as the high-end ultrasound equipment in the hospital. It may play an important role in monitoring cardiac function at home for the ambulatory heart failure patients.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"1-7"},"PeriodicalIF":2.1,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anomalous left coronary artery from pulmonary artery with an intramural and inter-arterial course.","authors":"Damandeep Singh, Niraj Nirmal Pandey, Mayank Yadav, Pannasamudra Mohankumar Shivaprasad, Lamk Kadiyani","doi":"10.1080/00015385.2024.2448867","DOIUrl":"10.1080/00015385.2024.2448867","url":null,"abstract":"","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"190-192"},"PeriodicalIF":2.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142930386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the prognostic significance of platelet-to-lymphocyte ratio (PLR) for coronary artery lesions in Kawasaki disease.","authors":"Tiantuo Huang, Qi Peng, Yue Cao, Xiaochen Fan","doi":"10.1080/00015385.2025.2471656","DOIUrl":"10.1080/00015385.2025.2471656","url":null,"abstract":"<p><strong>Objective: </strong>We aimed to examine the correlation between the platelet-to-lymphocyte ratio (PLR) and coronary artery lesions (CALs) in individuals diagnosed with Kawasaki disease (KD) and to evaluate its prognostic significance.</p><p><strong>Methods: </strong>Our study entailed a detailed retrospective examination and analysis of clinical records for patients diagnosed with KD at the First Affiliated Hospital of Anhui Medical University from January 2017 to January 2023. In our methodological approach, we applied various statistical techniques - including univariate analyses, binary logistic regression, and receiver operating characteristic (ROC) curve analysis - to meticulously assess the relationship between the PLR and the incidence of CALs in this patient cohort. Our objective was to elucidate potential predictive markers for CALs development in KD patients, thereby contributing valuable insights into the prognosis and management of this condition.</p><p><strong>Results: </strong>In the conducted research, a total of 364 patients were analysed, among which 63 individuals (17.3%) exhibited CALs upon admission. Through the application of binary logistic regression analysis, our findings underscored PLR as a statistically significant predictor for the presence of CALs. Furthermore, the ROC curve analysis demonstrated an AUC (area under the curve) value of 0.707 (95%CI 0.641-0.772, <i>p</i> < .001) for the prognostic capacity of PLR concerning CALs.</p><p><strong>Conclusions: </strong>The outcomes of our investigation indicate that PLR acts as a significant risk indicator for CALs. Such insights pave the way for improved risk stratification and potentially guide therapeutic decision-making in patients with KD.</p>","PeriodicalId":6979,"journal":{"name":"Acta cardiologica","volume":" ","pages":"181-187"},"PeriodicalIF":2.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}