Reviews in cardiovascular medicine最新文献

{"title":"Effects of Inclisiran, Alirocumab, Evolocumab, and Evinacumab on Lipids: A Network Meta-Analysis.","authors":"Lin Zhang, Bin Li, Wei Chen, Wei Li, Huayun Yang, Diguang Pan","doi":"10.31083/RCM25248","DOIUrl":"https://doi.org/10.31083/RCM25248","url":null,"abstract":"<p><strong>Background: </strong>Direct comparisons between the drugs are limited, and the dosing remains debatable. Therefore, the study aims to indirectly compare the efficacy and safety of inclisiran, alirocumab, evolocumab, and evinacumab in lipid-lowering through a network meta-analysis.</p><p><strong>Methods: </strong>Databases including PubMed, EMBASE, Web of Science, and the Cochrane Library were utilized to retrieve randomized controlled trials (RCTs). The search was conducted up to July 1, 2023. The Cochrane risk of bias tool was employed to appraise the quality of included studies. R software was used to conduct the Bayesian network meta-analysis.</p><p><strong>Results: </strong>Twenty-one RCTs with 10,835 patients were included. The network meta-analysis indicated that Evolocumab [mean difference (MD) = -60, 95% credibility interval (CrI) (-72, -49)] was the most effective (87%) in reducing low-density lipoprotein cholesterol (LDL-C), followed by alirocumab (71.4%) and inclisiran (47.2%), with placebo being the least effective (0.01%). In increasing high-density lipoprotein cholesterol (HDL-C), evolocumab [MD = 6.5, 95% CrI (3.2, 10)] ranked first (81.8%), followed by alirocumab (68.2%), with placebo again at the bottom (0.03%). In lowering total cholesterol, evolocumab [MD = -36, 95% CrI (-54, -19)] performed the best (86%), followed by alirocumab (64%), and placebo remained the least effective (0.04%). Regarding adverse events (AEs), evinacumab [odds ratio (OR) = 2, 95% CrI (1.17, 3.44)] ranked the highest (98.9%), followed by inclisiran (59.6%) and evolocumab (15.2%).</p><p><strong>Conclusions: </strong>Evolocumab appears to be the most effective in increasing HDL-C and reducing LDL-C and total cholesterol. Evinacumab shows the best safety profile with the lowest incidence of AEs.</p><p><strong>The prospero registration: </strong>CRD42024570445, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=570445.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"25248"},"PeriodicalIF":1.9,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategies to Reduce Left Anterior Descending Artery and Left Ventricle Organ Doses in Radiotherapy Planning for Left-Sided Breast Cancer.","authors":"Umut Diremsizoglu, Nezihan Topal, Aykut Oguz Konuk, Ibrahim Halil Suyusal, Dogacan Genc, Onur Ari, Hasan Furkan Cevik, Aysegul Ucuncu Kefeli, Maksut Gorkem Aksu, Emine Binnaz Sarper","doi":"10.31083/RCM26366","DOIUrl":"https://doi.org/10.31083/RCM26366","url":null,"abstract":"<p><strong>Background: </strong>One of the most significant long-term toxicities of breast cancer radiotherapy is major adverse cardiac events (MACE). In current radiotherapy practice, the mean heart dose is the most commonly used parameter. The aim of our study was to reduce the doses of organs at risk (OAR) in the left anterior descending artery (LAD) and left ventricle (LV) by including the LAD and LV in planning radiotherapy while maintaining adequate dose coverage for patients with left-sided breast cancer.</p><p><strong>Methods: </strong>We retrospectively analyzed left-sided breast cancer cases treated at the Kocaeli University Faculty of Medicine. Only patients with local and locally advanced breast cancer were included in the analysis. A total of 77 patients who were treated between 2020 and 2024 were included. The doses to the LAD and LV were added to the optimization algorithms. Two volumetric modulated arc therapy (VMAT) plans were created for each patient. A total of 154 plans were made, including standard and LAD and LV sparing plans.</p><p><strong>Results: </strong>There was no statistically significant difference in all VMAT plans regarding planning target volume (PTV) D2, D50, and D98 (dose receiving volume of PTV 2%, 50%, and 98%) (<i>p</i> > 0.05). However, a significant decrease was observed in heart V5 (the percentage of the heart receiving at least 5 gray (Gy)) and mean heart dose. A decrease in the mean heart dose was observed in the standard plan compared with the LAD and LV sparing plan (<i>p</i> < 0.001). Similarly, the heart V5 value decreased significantly (<i>p</i> < 0.001). Additionally, significant reductions were measured in all LAD and LV parameters after re-optimization.</p><p><strong>Conclusions: </strong>We achieved significant reductions in all heart, LAD, and LV parameters without making any changes to the planned treatment volume coverage by adding LAD and LV OARs to the optimization algorithms. The potential risk of MACE can be significantly reduced by implementing this strategy.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"26366"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868904/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Model-Based Prediction of In-Hospital Acute Kidney Injury Risk in Acute Aortic Dissection Patients.","authors":"Zhili Wei, Shidong Liu, Yang Chen, Hongxu Liu, Guangzu Liu, Yuan Hu, Bing Song","doi":"10.31083/RCM25768","DOIUrl":"https://doi.org/10.31083/RCM25768","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to identify the risk factors for in-hospital acute kidney injury (AKI) in patients with acute aortic dissection (AAD) and to establish a machine learning model for predicting in-hospital AKI.</p><p><strong>Methods: </strong>We extracted data on patients with AAD from the Medical Information Mart for Intensive Care (MIMIC)-IV database and developed seven machine learning models: support vector machine (SVM), gradient boosting machine (GBM), neural network (NNET), eXtreme gradient boosting (XGBoost), K-nearest neighbors (KNN), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and the optimal model was interpreted using Shapley Additive explanations (SHAP) visualization analysis.</p><p><strong>Results: </strong>A total of 325 patients with AAD were identified from the MIMIC-IV database, of which 84 patients (25.85%) developed in-hospital AKI. This study collected 42 features, with nine selected for model building. A total of 70% of the patients were randomly allocated to the training set, while the remaining 30% were allocated to the test set. Machine learning models were built on the training set and validated using the test set. In addition, we collected AAD patient data from the MIMIC-III database for external validation. Among the seven machine learning models, the CatBoost model performed the best, with an AUC of 0.876 in the training set and 0.723 in the test set. CatBoost also performed strongly during the validation, achieving an AUC of 0.712. SHAP visualization analysis identified the most important risk factors for in-hospital AKI in AAD patients as maximum blood urea nitrogen (BUN), body mass index (BMI), urine output, maximum glucose (GLU), minimum BUN, minimum creatinine, maximum creatinine, weight and acute physiology score III (APSIII).</p><p><strong>Conclusions: </strong>The CatBoost model, constructed using risk factors including maximum and minimum BUN levels, BMI, urine output, and maximum GLU, effectively predicts the risk of in-hospital AKI in AAD patients and shows compelling results in further validations.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"25768"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143542787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic and Prognostic Value of Cardiac Magnetic Resonance for Cardiotoxicity Caused by Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis.","authors":"Jialian Li, Yanwei Li, Li Tao, Chuan Zhang, Zhong Zuo","doi":"10.31083/RCM25508","DOIUrl":"https://doi.org/10.31083/RCM25508","url":null,"abstract":"<p><strong>Background: </strong>The complex process of cardiac magnetic resonance (CMR) and the uncertainty of each parameter in the diagnosis and prognosis of cardiotoxicity limit its promotion in the cardiac evaluation of patients treated with immune checkpoint inhibitors (ICI).</p><p><strong>Methods: </strong>A comprehensive search was conducted across PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Cochrane databases for relevant articles published up until September 28, 2024.</p><p><strong>Results: </strong>After screening, 8 articles were included in this study. The analysis revealed that following ICI treatment, the left ventricular global longitudinal strain (GLS) increased significantly [weighted mean difference (WMD) 2.33; 95% confidence interval (CI) 1.26, 3.41; <i>p</i> < 0.01], while the global radial strain (GRS) decreased [WMD -4.73; 95% CI -6.74, -2.71; <i>p</i> < 0.01]. Additionally, T1 and T2 values increased [standardized mean difference (SMD) 1.14; 95% CI 0.59, 1.68; <i>p</i> < 0.01] and [SMD 1.11; 95% CI 0.64, 1.58; <i>p</i> < 0.01], respectively. An elevated T2 was associated with a higher occurrence of major adverse cardiovascular events (MACE), with a hazard ratio of 1.36 (95% CI 1.12, 1.64).</p><p><strong>Conclusions: </strong>Our findings demonstrate that T1, T2, and GLS increase, while GRS decreases following ICI administration. By consolidating these critical metrics, we propose a streamlined, abbreviated (non-contrast) CMR protocol that can be completed within 15 minutes, thereby facilitating the integration of CMR in cardio-oncology.</p><p><strong>The prospero registration: </strong>CRD42023437238, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023437238.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"25508"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiac Sarcoidosis: Clinical Insights, Diagnosis, and Management Strategies.","authors":"Nicola Farina, Giacomo De Luca, Giovanni Peretto, Alex Bartoli, Antonio Esposito, Marco Matucci-Cerinic, Lorenzo Dagna, Corrado Campochiaro","doi":"10.31083/RCM26605","DOIUrl":"https://doi.org/10.31083/RCM26605","url":null,"abstract":"<p><p>Cardiac sarcoidosis (CS) is a multifaceted inflammatory disease that affects the heart, leading to complications such as arrhythmias, heart failure, and sudden cardiac death. Endomyocardial biopsy is the diagnostic gold standard, but its low sensitivity and risks limit its utility. Imaging modalities, such as cardiac magnetic resonance and positron emission tomography, are critical for diagnosing and managing CS. Additionally, CS treatment primarily involves corticosteroids and immunosuppressive agents to reduce inflammation and control disease progression, although biologics such as tumor necrosis factor-alpha (TNF-α) inhibitors are considered in refractory or steroid-dependent cases. This narrative review revises the existing knowledge on the diagnosis and treatment of CS, providing a comprehensive overview of current strategies.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"26605"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Signalling Pathways in Myocardial Fibrosis in Hypertrophic Cardiomyopathy.","authors":"Patryk Skórka, Jakub Piotrowski, Estera Bakinowska, Kajetan Kiełbowski, Andrzej Pawlik","doi":"10.31083/RCM27152","DOIUrl":"https://doi.org/10.31083/RCM27152","url":null,"abstract":"<p><p>Hypertrophic cardiomyopathy (HCM) is the most prevalent hereditary cardiovascular disorder, characterised by left ventricular hypertrophy and cardiac fibrosis. Cardiac fibroblasts, transformed into myofibroblasts, play a crucial role in the development of fibrosis. However, interactions between fibroblasts, cardiomyocytes, and immune cells are considered major mechanisms driving fibrosis progression. While the disease has a strong genetic background, its pathogenetic mechanisms remain complex and not fully understood. Several signalling pathways are implicated in fibrosis development. Among these, transforming growth factor-beta and angiotensin II are frequently studied in the context of cardiac fibrosis. In this review, we summarise the most current evidence on the involvement of signalling pathways in the pathogenesis of HCM. Additionally, we discuss the potential role of monitoring pro-fibrotic molecules in predicting clinical outcomes in patients with HCM.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"27152"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fibulin 1 and 2 Levels in Patients with Heart Failure: Comparison of Different Heart Failure Stages and Exploring the Temporal Changes During Acute Exacerbation.","authors":"Burcu Cihan Talay, Emrullah Kızıltunç, Canan Yılmaz, Zakir Osmanov, Serkan Ünlü, Mustafa Candemir, Burak Sezenöz, Özden Seçkin Göbüt, Salih Topal, Sedat Türkoğlu","doi":"10.31083/RCM26364","DOIUrl":"https://doi.org/10.31083/RCM26364","url":null,"abstract":"<p><strong>Background: </strong>Fibulin 1 and Fibulin 2 are members of the extracellular matrix (ECM) glycoprotein family. ECMs drive prognosis through remodeling, a key step in the pathogenesis of heart failure (HF). We aimed to compare Fibulin 1 and 2 levels in different stages of HF and to investigate their relationship with other prognostic factors of HF.</p><p><strong>Methods: </strong>Patients with HF were divided into two groups according to left ventricular ejection fraction (LVEF): reduced and non-reduced LVEF. The control and patient groups consisted of individuals with Stages A and B HF, Stages C and D HF, respectively. Fibulin levels were measured at different stages of HF and in the control group. Additionally, Fibulin levels were measured at admission, discharge, and in the first month in patients who were hospitalized due to decompensated HF.</p><p><strong>Results: </strong>Serum Fibulin 1 and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels were significantly higher in the patient group than in the control group. Serum Fibulin 2 levels were similar between the groups. Although serum Fibulin 2 levels were similar at repeated measurements, serum Fibulin 1 and NT-proBNP levels significantly decreased at discharge and remained similar at 1 month compared with admission. There was a significant positive correlation between Fibulin 1 and NT-proBNP levels and a significant negative correlation between Fibulin 1 levels and LVEF. Fibulin 2 levels were not correlated with LVEF and NT-proBNP.</p><p><strong>Conclusions: </strong>Our study demonstrated that serum Fibulin 1 levels differ among different HF stages and have a similar temporal change as observed for NT-proBNP levels. A similar association was not observed for Fibulin 2 in our study.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"26364"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating Circulating Plasma Interleukin-10 Enhanced Risk Predictability of Mortality in Acute Type A Aortic Dissection Surgery.","authors":"Yi-Fei Diao, Zhi-Bin Chen, Jia-Xi Gu, Xin-Yang Xu, Wen-Feng Lin, Chun-Ze Yuan, Jia-Qi Xiong, Ming-Hui Li, Bu-Qing Ni, Sheng Zhao, Yong-Feng Shao, Ying-Yuan Zhang, Hong Liu","doi":"10.31083/RCM26334","DOIUrl":"https://doi.org/10.31083/RCM26334","url":null,"abstract":"<p><strong>Background: </strong>Acute type A aortic dissection (TAAD) is a life-threatening cardiovascular emergency with a high mortality rate. The peri-operative factors influencing in-hospital mortality among surgically treated TAAD patients remain unclear. This study aimed to identify key peri-operative risk factors associated with in-hospital mortality.</p><p><strong>Methods: </strong>Peri-operative laboratory data, surgical strategies, and TAAD-related risk factors, associated with mortality, were collected. Machine learning techniques were applied to evaluate the impact of various parameters on in-hospital mortality. Based on the findings, a nomogram model was developed and validated using area under the receiver operating characteristic curve (AUC) analysis, calibration plots, and internal validation methods.</p><p><strong>Results: </strong>A total of 199 patients with TAAD were included in the study cohort, which was divided into derivation and validation cohorts. Using the least absolute shrinkage and selection operator (LASSO) regression method, 66 features were narrowed down to six key predictors. These included age, lymphocyte count, use of continuous renal replacement therapy (CRRT), cardiopulmonary bypass (CPB) time, duration of mechanical ventilation, and postoperative interleukin-10 (IL-10) levels, all of which were identified as significant risk factors for in-hospital mortality following TAAD surgery.</p><p><strong>Conclusions: </strong>We developed and validated a predictive model, presented as a nomogram, to estimate in-hospital survival in patients with TAAD. Post-operative IL-10 was identified as an independent prognostic factor for patients with TAAD. The combination of IL-10 with five additional indicators significantly improved the predictive accuracy, demonstrating superiority over the use of any single variable alone.</p><p><strong>Clinical trial registration: </strong>This study protocol was registered at ClinicalTrials.gov (NCT04711889). https://clinicaltrials.gov/study/NCT04711889.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"26334"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction and Verification of a Frailty Risk Prediction Model for Elderly Patients with Coronary Heart Disease Based on a Machine Learning Algorithm.","authors":"Jiao-Yu Cao, Li-Xiang Zhang, Xiao-Juan Zhou","doi":"10.31083/RCM26225","DOIUrl":"https://doi.org/10.31083/RCM26225","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to develop a machine learning-based predictive model for assessing frailty risk among elderly patients with coronary heart disease (CHD).</p><p><strong>Methods: </strong>From November 2020 to May 2023, a cohort of 1170 elderly patients diagnosed with CHD were enrolled from the Department of Cardiology of a tier-3 hospital in Anhui Province, China. Participants were randomly divided into a development group and a validation group, each containing 585 patients in a 1:1 ratio. Least absolute shrinkage and selection operator (LASSO) regression was employed in the development group to identify key variables influencing frailty among patients with CHD. These variables informed the creation of a machine learning prediction model, with the most accurate model selected. Predictive accuracy was subsequently evaluated in the validation group through receiver operating characteristic (ROC) curve analysis.</p><p><strong>Results: </strong>LASSO regression identified the activities of daily living (ADL) score, hemoglobin, low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), depression, cardiac function classification, cerebrovascular disease, diabetes, solitary living, and age as significant predictors of frailty among elderly patients with CHD in the development group. These variables were incorporated into a logistic regression model and four machine learning models: extreme gradient boosting (XGBoost), random forest (RF), light gradient boosting machine (LightGBM), and adaptive boosting (AdaBoost). AdaBoost demonstrated the highest accuracy in the development group, achieving an area under the ROC curve (AUC) of 0.803 in the validation group, indicating strong predictive capability.</p><p><strong>Conclusions: </strong>By leveraging key frailty determinants in elderly patients with CHD, the AdaBoost machine learning model developed in this study has shown robust predictive performance through validated indicators and offers a reliable tool for assessing frailty risk in this patient population.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"26225"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Impact of Glucose Levels on Patient Outcome after Transcatheter Aortic Valve Replacement.","authors":"Haitham Abu Khadija, Mohammad Alnees, Gera Gandelman, Mahdi Awwad, Tal Schiller, Yazan Hamdan, Omar Ayyad, Alena Kirzhner, Gal Sella, Yazid Kashquosh, Nadin Kakoush, Alex Blatt, Jacob George","doi":"10.31083/RCM25336","DOIUrl":"https://doi.org/10.31083/RCM25336","url":null,"abstract":"<p><strong>Background: </strong>Limited data are available for evaluating the effect of blood glucose on transcatheter aortic valve replacement (TAVR) outcomes in patients with diabetes. We aimed to assess the impact of glucose levels on short-term and long-term adverse outcomes in patients undergoing TAVR.</p><p><strong>Methods and results: </strong>Data from severe aortic stenosis (AS) patients who underwent TAVR from 2010 to 2022 were collected retrospectively. In total, 615 patients were enrolled in the study: Among the total patient population, 43% had diabetes mellitus (DM), with a mean hemoglobin A1c (HbA1c) level of 7.4 ± 2.5. Within this cohort, 33% were classified as having uncontrolled diabetes, while 17% were considered well-controlled. Diabetic patients were younger (80.7 ± 6.8 vs. 82.0 ± 6.8 years, <i>p</i> = 0.001) and had more cardiovascular risk factors. No significant differences were found in outcomes between the two groups during the twelve-year follow-up. A multivariable logistic regression analysis was conducted on 270 DM patients to examine the impact of blood glucose levels and HbA1c on outcomes such as arrhythmia, stroke, and acute kidney injury (AKI). For arrhythmia, the odds ratio for HbA1c and blood glucose were 1.1039 (<i>p</i> = 0.23), and 0.998 (<i>p</i> = 0.76), indicating no significant associations. In stroke cases, HbA1c had an odds ratio of 1.194 (<i>p</i> = 0.36), while an odds ratio of 1.020 (<i>p</i> = 0.013) for blood glucose indicated a significant association. Notably, for AKI, the odds ratio for HbA1c was 2.304 (<i>p</i> = 0.02), indicating a significant link between higher HbA1c levels and increased AKI risk, with blood glucose levels trending toward significance (odds ratio = 1.0137, <i>p</i> = 0.061).</p><p><strong>Conclusions: </strong>Diabetic status is a predictor of short-term outcomes following TAVR. Thus, these screening parameters should be included in risk assessment tools for TAVR candidates.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 2","pages":"25336"},"PeriodicalIF":1.9,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}