Clinical Cardiology最新文献

{"title":"Predictive Value of Machine Learning for the Risk of In-Hospital Death in Patients With Heart Failure: A Systematic Review and Meta-Analysis","authors":"Liyuan Yan,&nbsp;Jinlong Zhang,&nbsp;Le Chen,&nbsp;Zongcheng Zhu,&nbsp;Xiaodong Sheng,&nbsp;Guanqun Zheng,&nbsp;Jiamin Yuan","doi":"10.1002/clc.70071","DOIUrl":"10.1002/clc.70071","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The efficiency of machine learning (ML) based predictive models in predicting in-hospital mortality for heart failure (HF) patients is a topic of debate. In this context, this study's objective is to conduct a meta-analysis to compare and assess existing prognostic models designed for predicting in-hospital mortality in HF patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A systematic search of databases was conducted, including PubMed, Embase, Web of Science, and Cochrane Library up to January 2023. To ensure comprehensiveness, we performed an additional search in June 2023. The Prediction Model Risk of Bias Assessment Tool was employed to assess the validity and reliability of ML models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our analysis incorporated 28 studies involving a total of 106 predictive models based on 14 different ML techniques. In the training data set, these models showed a combined C-index of 0.781, sensitivity of 0.56, and specificity of 0.94. In the validation data set, the models exhibited a combined C-index of 0.758, sensitivity of 0.57, and specificity of 0.84. Logistic regression (LR) was the most frequently used ML algorithm. LR models in the training set had a combined C-index of 0.795, sensitivity of 0.63, and specificity of 0.85, and these measures for LR models in the validation set were 0.751, 0.66, and 0.79, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our study indicates that although ML is increasingly being leveraged to predict in-hospital mortality for HF patients, the predictive performance remains suboptimal. Although these models have relatively high C-index and specificity, their ability to predict positive events is limited, as indicated by their low sensitivity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"48 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11670054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Devices for Arrhythmia Detection: What Is Still Missing?","authors":"Naoya Kataoka,&nbsp;Teruhiko Imamura","doi":"10.1002/clc.70074","DOIUrl":"10.1002/clc.70074","url":null,"abstract":"<p>Various digital devices have been developed to detect atrial fibrillation (AF). Manninger and colleagues demonstrated that intermittent electrocardiogram (ECG)-based digital devices are increasingly being integrated into clinical practice, whereas photoplethysmography (PPG)-based devices are less commonly utilized for the diagnosis and screening of AF [<span>1</span>].</p><p>In the three proposed clinical scenarios—(1) symptomatic low-risk patients, (2) asymptomatic high-risk patients, and (3) symptomatic high-risk patients—many clinicians demonstrated a preference for diagnostic tools other than PPG-based devices [<span>1</span>]. The authors highlighted this trend and emphasized the need for enhanced education regarding novel PPG-based digital technologies. However, ECG-based tools, which provide greater diagnostic accuracy than PPG-based devices, may be more suitable in scenarios (1) and (3), where patients already exhibit clear symptoms of AF.</p><p>The debate over the type of device (PPG-based vs. ECG-based) may not be the most critical issue at present. While PPG-based devices demonstrate high accuracy in AF screening [<span>2</span>], the duration of arrhythmia monitoring is arguably more significant. Devices that impose minimal burden on patients are likely to be preferred for prolonged monitoring.</p><p>The clinical implications of aggressive intervention for AF detected by wearable devices remain uncertain. The prevalence of AF in the general population is quite low (approximately 1%) [<span>2</span>], and among those diagnosed, only 30% experience adverse outcomes such as thromboembolism or heart failure. Consequently, the number needed to treat to achieve a meaningful clinical benefit from wearable devices is exceptionally high [<span>3</span>]. Therefore, optimizing patient selection for the implementation of PPG-based devices warrants greater consideration.</p><p>The authors have nothing to report.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"48 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heart Failure Is Closely Associated With the Expression Characteristics of Type I Interferon-Related Genes","authors":"Jianfeng Zhuo,&nbsp;Yan Zhong,&nbsp;Xiaojuan Luo,&nbsp;Sijie Qiu,&nbsp;Xinmei Li,&nbsp;Yunyu Liang,&nbsp;Yu Wu,&nbsp;Xiyu Zhang","doi":"10.1002/clc.70063","DOIUrl":"10.1002/clc.70063","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The association between the expression of type I interferon related genes (TIIRGs) and EFrHF is not well understood. This study aimed to investigate the correlation between the expression patterns of TIIRGs and EFrHF using bioinformatics analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>An analysis was conducted to examine the expression and distribution of TIIRGs in cardiomyocytes. Afterwards, GSE5406 was utilized as the validation set, including 16 without heart failure, 86 with idiopathic dilated cardiomyopathy (IDCM), and 108 individuals with ischemic cardiomyopathy (ICM). We conducted a comparative analysis of the variations in TIIRGs gene expression across various forms of heart failure.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>There were eight genes that showed substantial changes between patients with EFrHF and those without heart failure. A risk model for EFrHF was developed utilizing JAK1 and EIF2AK2, with an area under the curve (AUC) of 0.909. Five genes exhibited notable disparities between IDCM and ICM. Through multivariate analysis, it was shown that JAK1 and IFNA16/IFNA14 were identified as independent risk variables for distinguishing between the two pathogenic categories. The model, utilizing JAK1 and IFNA16/IFNA14, successfully differentiated between IDCM and ICM with an area under the curve (AUC) of 0.722. In the validation set GSE5406, the expression of JAK1 was dramatically downregulated, while EIF2AK2 was significantly upregulated in heart failure (HF) tissues. The model utilizing JAK1 and EIF2AK2 successfully differentiated between those with an illness and those without (AUC = 0.877).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The expression of TIIRGs is strongly associated with the presence and specific subtypes of HF in a pathological context.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"48 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142863523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stratification of Early Arrhythmic Risk in Patients Admitted for Acute Coronary Syndrome: The Role of the Machine Learning-Derived “PRAISE Score”","authors":"Luca Cumitini,&nbsp;Ailia Giubertoni,&nbsp;Lidia Rossi,&nbsp;Domenico D'Amario,&nbsp;Leonardo Grisafi,&nbsp;Paola Abbiati,&nbsp;Fabrizio D'Ascenzo,&nbsp;Gaetano Maria De Ferrari,&nbsp;Giuseppe Patti","doi":"10.1002/clc.70035","DOIUrl":"10.1002/clc.70035","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The PRAISE (PRedicting with Artificial Intelligence riSk aftEr acute coronary syndrome) score is a machine learning-based model for predicting 1-year adverse cardiovascular or bleeding events in patients with acute coronary syndrome (ACS). Its role in predicting arrhythmic complications in ACS remains unknown.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Atrial fibrillation (AF) and ventricular arrhythmias (VA) were recorded by continuous electrocardiographic monitoring until discharge in a cohort of 365 participants with ACS prospectively enrolled. We considered two separate timeframes for VA occurrence: ≤ 48 and &gt; 48 h. The objective was to evaluate the ability of the PRAISE score to identify ACS patients at higher risk of in-hospital arrhythmic complications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ROC curve analysis indicated a significant association between PRAISE score and risk of both AF (AUC 0.89, <i>p</i> = 0.0001; optimal cut-off 5.77%) and VA (AUC 0.69, <i>p</i> = 0.0001; optimal cut-off 2.17%). Based on these thresholds, high/low AF PRAISE score groups and high/low VA PRAISE score groups were created, respectively. Patients with a high AF PRAISE score more frequently developed in-hospital AF (19% vs. 1%). Multivariate analysis showed a high AF PRAISE score risk as an independent predictor of AF (HR 4.30, <i>p</i> = 0.016). Patients with high VA PRAISE scores more frequently developed in-hospital VA (25% vs. 8% for VA ≤ 48 h; 33% vs. 3% for VA &gt; 48 h). Multivariate analysis demonstrated a high VA PRAISE score risk as an independent predictor of both VA ≤ 48 h (HR 2.48, <i>p</i> = 0.032) and VA &gt; 48 h (HR 4.93, <i>p</i> = 0.014).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The PRAISE score has a comprehensive ability to identify with high specificity those patients at risk for arrhythmic events during hospitalization for ACS.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clc.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142853094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Safety and Efficacy of Two Ultrathin Biodegradable Polymer Sirolimus-Eluting Stents in Real-World Practice: Genoss DES Stents Versus Orsiro Stents From a Prospective Registry","authors":"Ho Sung Jeon,&nbsp;Young Jin Youn,&nbsp;Jung-Hee Lee,&nbsp;Young Jun Park,&nbsp;Jung-Woo Son,&nbsp;Jun-Won Lee,&nbsp;Min-Soo Ahn,&nbsp;Sung Gyun Ahn,&nbsp;Jang-Young Kim,&nbsp;Byung-Su Yoo,&nbsp;Junghan Yoon","doi":"10.1002/clc.70060","DOIUrl":"10.1002/clc.70060","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The Orsiro and Genoss DES stents are biodegradable polymer drug-eluting stents (DESs) with ultrathin struts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To investigate the safety and efficacy of these two ultrathin DESs in real-world practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>From a single-center prospective registry, we included 751 and 931 patients treated with the Genoss DES and Orsiro stents, respectively. After propensity score matching, we compared 483 patients in each group with respect to a device-oriented composite outcome (DOCO), which comprised cardiac death, target vessel myocardial infarction, and clinically indicated target lesion revascularization up to 2 follow-up years.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>After propensity score matching, there were no significant between-group differences in clinical and angiographic characteristics. During the median follow-up period of 730 days (interquartile range, 427–730 days), there was no significant between-group difference in the DOCO rate (3.1% in the Genoss DES group vs. 2.9% in the Orsiro group, log-rank <i>p</i> = 0.847).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study demonstrated comparable safety and efficacy between the Orsiro and Genoss DES stents during a 2-year follow-up period in real-world practice. However, this result should be confirmed in a large randomized controlled trial.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Trial Registration</h3>\u0000 \u0000 <p>ClinicalTrials.gov Identifier: NCT02038127.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clc.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anticoagulation Monitoring During ECMO Support: Monitor or Flip a Coin?","authors":"Sasa Rajsic,&nbsp;Benedikt Treml","doi":"10.1002/clc.70061","DOIUrl":"10.1002/clc.70061","url":null,"abstract":"<p>Should we rely on anticoagulation monitoring in ECMO patients or simply flip a coin? The increasing use of anti-factor Xa activity to monitor the effect of UFH appears appropriate, given its moderate correlation with the UFH infusion rates, and it may play a role in preventing thromboembolic events. However, to avoid bleeding complications, more sophisticated tools, and careful clinical decision-making remain essential.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clc.70061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142845903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship Between Left Ventricular Ejection Fraction and ICD-10 Codes Among Patients Hospitalized With Heart Failure","authors":"Ty J. Gluckman,&nbsp;Shih-Ting Chiu,&nbsp;Deanna Rider,&nbsp;Pu-kai Tseng,&nbsp;James O. Mudd,&nbsp;Joshua D. Remick,&nbsp;Craig Granowitz,&nbsp;Amy Carroll,&nbsp;Slaven Sikirica,&nbsp;Mario E. Canonico,&nbsp;Judith Hsia,&nbsp;Marc P. Bonaca","doi":"10.1002/clc.70055","DOIUrl":"10.1002/clc.70055","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>While left ventricular ejection fraction (LVEF) represents an important means by which to classify patients with heart failure (HF), relatively little is known about the distribution of LVEFs among patients hospitalized for HF based on their International Classification of Disease (ICD)-10 code.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We performed a retrospective cross-sectional analysis of patients admitted to a large integrated health system within the western US between January 1, 2018 and October 1, 2022 with a principal diagnosis of HF (defined by ICD-10 codes: I50.2, systolic HF; I50.3, diastolic HF; I50.4, combined systolic and diastolic HF; I11.0, hypertensive heart disease with HF; and I13.0 and I13.2, hypertensive heart disease with HF and chronic kidney disease).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Over nearly 5 years, 61,238 HF hospitalizations occurred, of which 49,772 (81%) had a LVEF available by echocardiography within the preceding 3 months. Whereas most patients hospitalized with systolic HF (<i>n</i> = 2220) as well as systolic and diastolic heart failure (<i>n</i> = 1582) had an LVEF ≤ 40% (86.2% and 74.8%, respectively), most patients hospitalized with diastolic HF (<i>n</i> = 1542) had an LVEF ≥ 50% (94.0%) (Figure). A much greater range of LVEFs were noted for those with hypertensive heart disease with HF (<i>n</i> = 18,092) and hypertensive heart disease with HF and CKD (<i>n</i> = 26,336) (Figure).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>While there was relatively good concordance between LVEF and the ICD-10 code-defined HF type for systolic HF, diastolic HF, and systolic and diastolic HF, these codes represent a small subset (~10%) of total HF hospitalizations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clc.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142834351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal Trends in Mortality Related to Stroke and Atrial Fibrillation in the United States: A 21-Year Retrospective Analysis of CDC-WONDER Database","authors":"Owais Ahmad,&nbsp;Hanzala Ahmed Farooqi,&nbsp;Isra Ahmed,&nbsp;Adeena Jamil,&nbsp;Rayyan Nabi,&nbsp;Irfan Ullah,&nbsp;Abdul Wali Khan,&nbsp;Raheel Ahmed,&nbsp;Mahboob Alam,&nbsp;Bernardo Cortese,&nbsp;Mamas A. Mamas","doi":"10.1002/clc.70058","DOIUrl":"10.1002/clc.70058","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Atrial Fibrillation (AF) is one of the most strongly associated risk factors for stroke. Our study aims to analyze changes in mortality from 1999 to 2020 in patients with AF and stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using the Centre for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC-WONDER), we retrospectively analyzed annual age-adjusted mortality rates (AAMR) per million from 1999 to 2020 in stroke patients with AF. Temporal trends were analyzed, and Annual Percentage Change (APC) was calculated using the JoinPoint regression model across variations in demographics (sex, race) and regional subgroups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Around 490 000 deaths were reported between 1999 and 2020 from stroke and AF across the 25–85+ age group. AAMR initially decreased until 2008 (APC = –0.9), followed by an increase till 2020 (APC = 1.1). Women had a higher AAMR than men throughout the years. Non-Hispanic white patients had a marginally higher AAMR than all other races and ethnicities. The highest AAMR was observed in the western region. States like Vermont, Oregon, Washington, Alaska, Minnesota, and West Virginia were in the top 90th percentile, while Nevada, Louisiana, Florida, New York, New Mexico, and Arizona were in the bottom 10th percentile. Nonmetropolitan areas had consistently higher AAMRs throughout the 2 decades.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>An overall rise in mortality has been observed in stroke and AF patients, with a greater surge in 2019. The need for healthcare policy changes, especially in areas with high mortality and awareness of healthier lifestyle factors, can be an essential preventative measure to help mitigate growing mortality rates.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/clc.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exome Sequencing Identified Susceptible Genes for High Residual Risks in Early-Onset Coronary Atherosclerotic Disease","authors":"Runda Wu,&nbsp;Ya Su,&nbsp;Jianquan Liao,&nbsp;Juan Shen,&nbsp;Yuanji Ma,&nbsp;Wei Gao,&nbsp;Zheng Dong,&nbsp;Yuxiang Dai,&nbsp;Kang Yao,&nbsp;Junbo Ge","doi":"10.1002/clc.70066","DOIUrl":"10.1002/clc.70066","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Despite the tremendous improvement in therapeutic medication and intervention for coronary atherosclerotic disease (CAD), residual risks remain. Exome sequencing enables identification of rare variants and susceptibility genes for residual risks of early-onset coronary atherosclerotic disease (EOCAD) with well-controlled conventional risk factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We performed whole-exome sequencing of subjects who had no conventional risk factors, defined as higher body mass index, smoking, hypertension and dyslipidemia, screened from 1950 patients with EOCAD (age ≤ 45 years, at least 50% stenosis of coronary artery by angiography), and selected control subjects from 1006 elder (age ≥ 65 years) with &lt; 30% coronary stenosis. Gene-based association analysis and clinical phenotypic comparison were conducted.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Subjects without defined conventional risk factors accounted for 4.72% of young patients. Totally, 6 genes might be associated with residual risk of EOCAD, namely <i>CABP1</i> (OR = 22.19, <i>p</i> = 0.02), <i>HLA-E</i> (OR = 22.19, <i>p</i> = 0.02), <i>TOE1</i> (OR = 33.6, <i>p</i> = 0.002), <i>HPSE2</i> (OR = 11.1, <i>p</i> = 0.04), <i>CHST14</i> (OR = 22.19, <i>p</i> = 0.02) as well as <i>KLHL8</i> (OR = 22.19, <i>p</i> = 0.02). Phenotypic analysis displayed the levels of low-density lipoprotein cholesterol in carriers of mutations from <i>CABP1</i>, <i>HLA-E</i>, <i>TOE1</i>, and <i>HPSE2</i> were significantly elevated compared to noncarriers. Notably, extracellular matrix-associated <i>CHST14</i> and fibrinogen-associated <i>KLHL8</i> both displayed possible correlation with increased neutrophil proportion and decreased monocyte percentage (both <i>p</i> &lt; 0.05), exerting potential effects on the residual inflammatory risks of EOCAD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The study identified six genes related to dyslipidemia and inflammation pathways with potential association with residual risk of EOCAD, which will contribute to precision-based prevention in these patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Trial Registration</h3>\u0000 \u0000 <p>The GRAND study was registered at www.clinicaltrials.gov on July 14, 2015, and the registry number is NCT 02496858.</p>\u0000 </section>\u0000 </div>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11645474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142823535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to “How to consider the indication of implantable cardioverter defibrillator in the elderly patients”","authors":"Michael Gotzmann MD,&nbsp;Marie Lewenhardt MD,&nbsp;Fabienne Kreimer MD","doi":"10.1002/clc.24208","DOIUrl":"10.1002/clc.24208","url":null,"abstract":"<p>We would like to thank Naoya Kataoka and Teruhiko Imamura for their comments on our publication. While we strongly agree with some of their comments, we would like to take the opportunity to point out some aspects of our publication that may not have been described clearly enough.</p><p>We would like to clarify that in our study not only deceased patients with previous implantable cardioverter defibrillator (ICD) therapy were defined as patients with “benefit of ICD implantation,” but also patients with adequate ICD therapy who did not die during the observation period. In fact, of the 89 patients who received adequate ICD therapy, only 21 patients died during the study period.<span>¹</span> We would also like to point out that the investigation period of 4.2 years on average was not short. We therefore do not believe that an extended investigation period would have changed the results of the analysis.</p><p>In principle, however, we agree with Naoya Kataoka and Teruhiko Imamura on several points. The surgical risk and the risk of infection play a significant role in the risk-benefit assessment of device therapy. In our study, however, we limited ourselves to a few endpoints and focused in particular on the major endpoint “death from any cause.”</p><p>Another important aspect is that comorbidities have a significant impact on the benefit of ICD therapy. A younger multimorbid patient may have a worse prognosis than an older patient. Nonetheless, we believe that considering age when deciding whether ICD therapy is appropriate can be a very simple but important contribution. As the benefits of ICD therapy in older patients have been repeatedly questioned in the past, this is particularly important.<span>^2-4</span> At the same time, in an increasingly aging society, a considerable proportion of old and very old patients are treated with an ICD. In Germany and the United States, the proportion of patients over 80 years of age who receive an ICD for primary prophylactic indications is approximately 14%, without convincing data being available. Our study revealed that the benefit of ICD therapy in this patient group remains to be critically assessed.</p><p>In other words, comorbidities are undeniably important factors for the potential benefit of ICD therapy, but also age, so taking comorbidities into account could help to make a benefit-risk assessment before ICD implantation.</p>","PeriodicalId":10201,"journal":{"name":"Clinical Cardiology","volume":"47 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11638679/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142817466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}