American heart journal plus : cardiology research and practice最新文献

{"title":"Pacemaker with automatic activation of a magnetic resonance imaging mode: A single-center experience","authors":"Bridget McIlraith ,&nbsp;Justin A. Mariani ,&nbsp;Ross Downey ,&nbsp;Geoffrey Clare ,&nbsp;Matthew Daly ,&nbsp;Houda El Banna ,&nbsp;Ian Crozier","doi":"10.1016/j.ahjo.2026.100732","DOIUrl":"10.1016/j.ahjo.2026.100732","url":null,"abstract":"<div><h3>Introduction</h3><div>In patients with permanent pacemakers, magnetic resonance imaging (MRI) traditionally requires resource-intensive manual device reprogramming before and after the scan putting demands on clinical resources.</div></div><div><h3>Methods</h3><div>In this single-center case series, we report five MRI procedures in three patients with a pacemaker using an always-on MRI workflow facilitating feature (MRI Guard 24/7) that automatically detects MRI conditions and adjusts the pacing mode without the need for pre- or post-scan checks.</div></div><div><h3>Results</h3><div>All scans were completed successfully, with automatic switching into MRI mode and reverting to the permanent setting. No device reconfigurations were required pre- or post-scan.</div></div><div><h3>Discussion</h3><div>We discuss the potential of this feature to streamline MRI workflows, reduce staffing demands and improve access to timely imaging for patients with cardiac implantable electronic devices.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100732"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146144803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting complications in emergency department patients with acute coronary syndrome – Existing risk scores versus a new logistic regression model","authors":"T. Nilsson ,&nbsp;M. Strömfors ,&nbsp;A. Trägårdh ,&nbsp;A. Mokhtari ,&nbsp;A.M. Khoshnood ,&nbsp;U. Ekelund","doi":"10.1016/j.ahjo.2026.100736","DOIUrl":"10.1016/j.ahjo.2026.100736","url":null,"abstract":"<div><h3>Background</h3><div>Patients with acute coronary syndrome (ACS) are often admitted to monitored wards due to the risk of complications. Several risk prediction scores exist, but their use in the emergency department (ED) is limited. We aimed to compare the ability of existing risk scores with a new logistic regression model in predicting complications in ACS patients.</div></div><div><h3>Methods</h3><div>This was a secondary analysis of data from the ESC TROP trial (<span><span>NCT03421873</span><svg><path></path></svg></span>), including ACS patients from five EDs in Region Skåne, Sweden (2017–2018). Complications were identified via diagnosis and/or intervention codes and manual chart review. GRACE, GRACE FFE, TIMI, HEART, ACTION ICU, and CHA₂DS₂-VASc scores were calculated. A new logistic regression model was developed, and its predictive performance was assessed using the area under the ROC curve (AUROC) and a net reclassification improvement analysis (NRI).</div></div><div><h3>Results</h3><div>Among 2223 ACS patients, 164 (7.4%) experienced complications. Independent predictors for complications included age, STEMI, troponin and lactate at arrival, shock index, Killip class, and new ECG changes. The logistic regression model's AUROC 0.84 (95% CI 0.80–0.88) outperformed all known risk scores: GRACE FFE 0.79 (0.75–0.84), ACTION ICU 0.77 (0.72–0.82), GRACE 0.76 (0.70–0.81), TIMI 0.74 (0.68–0.79), HEART 0.69 (0.64–0.74), and CHA₂DS₂-VASc 0.64 (0.59–0.69). Logistic regression improved reclassification of non-events, with a positive non-event NRI compared with all other scores.</div></div><div><h3>Conclusions</h3><div>Serious complications occurred in 7% of ACS patients. A logistic regression model based on simple ED variables showed excellent predictive performance, surpassing existing risk scores. Improved risk stratification may optimize resource allocation while maintaining patient safety.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100736"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the editor: data accuracy","authors":"Magdalini Manti ,&nbsp;Panagiotis-Anastasios Tsioufis","doi":"10.1016/j.ahjo.2026.100727","DOIUrl":"10.1016/j.ahjo.2026.100727","url":null,"abstract":"","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100727"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obesity paradox in patients with non‐ST‐elevation myocardial infarction undergoing percutaneous coronary intervention: A nationwide retrospective observational study","authors":"Sean Moore ,&nbsp;Aditya Thakkar ,&nbsp;Shahnawaz Notta ,&nbsp;Jacob Snipp ,&nbsp;Colin McGuire ,&nbsp;Venkata Vedantam ,&nbsp;Manar H. Jbara","doi":"10.1016/j.ahjo.2026.100733","DOIUrl":"10.1016/j.ahjo.2026.100733","url":null,"abstract":"<div><h3>Introduction</h3><div>The prevalence of obesity in the United States is high, with over 35% of the population classified as obese. Obesity, along with the lifestyle factors contributing to it, is considered a major risk factor for heart disease. However, research studies have reported controversial findings regarding its impact on morbidity and mortality.</div></div><div><h3>Methods</h3><div>Data was obtained from the Nationwide Inpatient Sample database from January 2016 to December 2020. The study included adult patients with a principal discharge diagnosis of NSTEMI who underwent PCI during hospitalization. They were divided into obese (BMI &gt; 30) and not obese (BMI &lt; 30). The primary outcome was inpatient mortality. Secondary outcomes were cardiogenic shock, cardiac arrest, arrhythmias, and acute renal failure, as well as the need for transfusions, pressors, ventilators, and ECMO.</div></div><div><h3>Results</h3><div>We analyzed 448,424 hospitalizations for NSTEMI, of which 172,665 patients underwent PCI. Among these, 39,548 (22.9%) were obese (BMI &gt;30). Obesity was associated with lower in-hospital mortality compared to non-obese patients (1.2% vs. 1.8%; adjusted odds ratio [aOR]: 0.82; 95% CI: 0.74–0.90; <em>p</em> &lt; 0.001), after adjustment for age, sex, race, and Charlson Comorbidity Index. Obese patients also had lower rates of cardiogenic shock (2.7% vs. 3.3%; aOR: 0.84; 95% CI: 0.78–0.90; <em>p</em> &lt; 0.001), cardiac arrest (1.3% vs. 1.6%; aOR: 0.86; 95% CI: 0.78–0.95; <em>p</em> &lt; 0.005), and ventricular arrhythmias (5.2% vs. 5.7%; aOR: 0.93; 95% CI: 0.88–0.98; p &lt; 0.005). They also required fewer blood transfusions (1.9% vs. 2.3%; aOR: 0.90; 95% CI: 0.83–0.98; <em>p</em> &lt; 0.05) and mechanical ventilation (2.9% vs. 3.2%; aOR: 0.91; 95% CI: 0.85–0.98; p &lt; 0.05). No significant differences were observed in dialysis, vasopressor use, or ECMO. However, obese patients had higher rates of acute kidney injury (15.0% vs. 13.5%; aOR: 1.25; 95% CI: 1.21–1.29; <em>p</em> &lt; 0.001) and acute respiratory failure (9.1% vs. 8.2%; aOR: 1.17; 95% CI: 1.13–1.23; p &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>The “obesity paradox” suggests that despite obesity's role in cardiovascular disease risk, individuals with obesity may have a survival advantage during acute cardiovascular events and certain surgeries. Our study aligns with these findings, underscoring the need for further research to comprehend the underlying pathophysiological mechanisms.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100733"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social determinants of health and hospitalization risk in heart failure: A Retrospective analysis","authors":"Alisha A. Crump ,&nbsp;Milan Bimali ,&nbsp;Sanchia McCall ,&nbsp;Pearman Parker ,&nbsp;Taren Massey-Swindle ,&nbsp;Kevin Wayne Sexton ,&nbsp;Emel Seker ,&nbsp;Maryam Y. Garza ,&nbsp;Tremaine B. Williams","doi":"10.1016/j.ahjo.2026.100731","DOIUrl":"10.1016/j.ahjo.2026.100731","url":null,"abstract":"<div><h3>Background</h3><div>Heart failure affects over 6.5 million Americans and accounts for substantial healthcare utilization, with social determinants of health (SDOH) increasingly recognized as critical factors influencing patient outcomes. The present study aims to examine the relationships among specific SDOH (food insecurity risk, financial resource strain, and medical transportation needs) with subsequent hospitalization risk among patients with heart failure.</div></div><div><h3>Methods</h3><div>This retrospective cross-sectional study analyzed electronic health record data from the Arkansas Clinical Data Repository for 2494 patients with heart failure hospitalized between January 2014 and December 2023 at the University of Arkansas for Medical Sciences. Quantile regression on the median was used to analyze the data.</div></div><div><h3>Results</h3><div>Study population descriptive results demonstrated moderate hospitalization risk (average score 40.3). The population was predominantly older adults (mean age ∼ 65), female (55.8%), non-Hispanic (98.3%) and White (54.3%). In fully adjusted models, all three social determinants remained significant predictors of increased subsequent hospitalization risk: food insecurity was associated with a 9.37-point increase (95% CI: 4.83–13.90, <em>p</em> &lt; 0.01), high financial resource strain with a 13.13-point increase (95% CI: 8.50–17.76, p &lt; 0.01), and medical transportation needs with a 13.23-point increase (95% CI: 7.55–18.89, p &lt; 0.01).</div></div><div><h3>Conclusions</h3><div>Food insecurity risk, financial resource strain, and medical transportation needs are associated with increased future hospitalization risk among patients with heart failure. These findings support the integration of social determinant screening into clinical risk stratification and the development of targeted interventions addressing these modifiable social factors to potentially reduce healthcare utilization and improve outcomes for vulnerable populations with heart failure.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100731"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chronic kidney disease is associated with worse survival after revascularization in subjects with genetically diagnosed familial hypercholesterolemia and significant coronary artery disease","authors":"Kae-Woei Liang ,&nbsp;Han-Ni Chuang ,&nbsp;Li-Chin Liao ,&nbsp;Tzu-Hung Hsiao ,&nbsp;Wayne H.-H. Sheu ,&nbsp;Hsin Tung","doi":"10.1016/j.ahjo.2026.100730","DOIUrl":"10.1016/j.ahjo.2026.100730","url":null,"abstract":"<div><h3>Background</h3><div>Familial hypercholesterolemia (FH) is a genetic disorder associated with elevated low-density lipoprotein cholesterol (LDL-C) and coronary artery disease (CAD). Few studies have reported survival data and the associated factors in FH patients with significant CAD after revascularization.</div></div><div><h3>Methods</h3><div>We retrospectively analyzed 79 genetically confirmed FH who underwent percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) in a single medical center. Genetic variants for FH were identified by next-generation sequencing. A logistic regression was performed to find the associated factors for choosing CABG revascularization. The Kaplan-Meier equation and the stratified survival curve with log-rank testing were depicted for significant associated factors for survival.</div></div><div><h3>Results</h3><div>There were 62 men (78.5%) and 17 women (21.5%) in this study. Twenty-three (29.1%) underwent CABG and 56 (70.9%) received only PCI. Logistic regression revealed that a higher LDL-C record and a higher coronary Jeopardy score were associated with CABG revascularization. The median duration of follow-up was 61 months after revascularization and 11 patients (13.9%) died. The cumulative survival at 5 years was 88.5%. The deceased patients had significantly lower estimated glomerular filtration rate (eGFR) (62.3 ± 18.6 vs. 81.2 ± 21.2 ml/min/1.73 m², <em>p</em> = 0.007) and a higher proportion with CKD (54.5% vs. 14.7%, p = 0.007). The Kaplan-Meier equation with log-rank testing (<em>p</em> = 0.018) showed that subjects with chronic kidney disease (CKD) had worse survival.</div></div><div><h3>Conclusions</h3><div>A higher LDL-C and coronary severity score were associated with CABG revascularization. Chronic kidney disease and lower eGFR were associated with worse survival in subjects with FH and CAD after revascularization.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100730"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiovascular sex differences and associated factors among adult population in Somaliland using insights from Somaliland demography and health survey","authors":"Idiris F. Mohamed ,&nbsp;Hodo Abdikarim ,&nbsp;Shabcan Mohamed Ali ,&nbsp;Hafsa Mohamed ,&nbsp;Asma Mahamoud Abdillahi ,&nbsp;Saeed Hassan Mohamed ,&nbsp;Abdisalam Hassan Muse","doi":"10.1016/j.ahjo.2026.100739","DOIUrl":"10.1016/j.ahjo.2026.100739","url":null,"abstract":"<div><h3>Study objective</h3><div>To examine sex differences and identify associated risk factors for cardiovascular disease (CVD) among adults in Somaliland, in order to inform targeted public health interventions.</div></div><div><h3>Design</h3><div>A cross-sectional analysis of nationally representative survey data.</div></div><div><h3>Setting</h3><div>Community-based, covering all regions of Somaliland.</div></div><div><h3>Participants</h3><div>A sample of 20,669 adults from the 2020 Somaliland Demographic and Health Survey (SLDHS).</div></div><div><h3>Interventions</h3><div>Not applicable (observational study).</div></div><div><h3>Main outcome measure(s)</h3><div>The primary outcome was the prevalence of self-reported, doctor-diagnosed CVD (including coronary heart disease, hypertensive heart disease, and stroke). Key determinants were assessed via adjusted odds ratios (AOR) from multivariable logistic regression.</div></div><div><h3>Results</h3><div>The overall CVD prevalence was 0.94%, with significant sex and geographic disparities. Hypertension was the strongest predictor overall (AOR = 4.68, 95% CI: 3.26–6.71), with a greater effect in females (AOR = 5.10, 95% CI: 3.23–8.04). Diabetes was a significant risk factor for males only (AOR = 2.59, 95% CI: 1.11–6.07). Widowhood and rural residence increased CVD risk for females, while nomadic residence was protective for males.</div></div><div><h3>Conclusions</h3><div>This study reveals significant, sex-specific disparities in CVD determinants in Somaliland. Public health strategies must prioritize hypertension and diabetes control, improve healthcare access for women—particularly widowed and rural residents—and develop regionally tailored interventions to mitigate the growing CVD burden.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100739"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147313119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer therapy-associated Takotsubo cardiomyopathy: A narrative review of mechanisms, drug associations, and clinical implications","authors":"Michael Simeon ,&nbsp;Elizabeth Evans ,&nbsp;Sally Arif ,&nbsp;Thomas Granado ,&nbsp;Tochukwu M. Okwuosa ,&nbsp;Annabelle Santos Volgman ,&nbsp;Salaheldin Abusin","doi":"10.1016/j.ahjo.2026.100723","DOIUrl":"10.1016/j.ahjo.2026.100723","url":null,"abstract":"<div><div>Anticancer therapies have been increasingly associated with Takotsubo cardiomyopathy (TTC). As prior reports remain fragmented across case studies and drug-specific reviews, this paper offers one of the most comprehensive reviews to date of cancer therapy-associated TTC. While classically triggered by emotional or physical stress, TTC has been increasingly associated with chemotherapy and other cancer-directed therapies. This literature review explores the pathophysiology, clinical features, and evolving evidence linking anticancer agents to TTC, with a focus on cytotoxic cancer therapy, hormonal therapy, targeted treatments, and immune checkpoint inhibitors.</div><div>We describe the proposed mechanisms of cancer therapy-associated TTC, the diagnostic challenges, particularly in patients with cancer, and the complex management strategies, especially regarding the decision to resume oncologic treatment after TTC recovery.</div><div>Given the increasing use of cardiotoxic agents, a multidisciplinary approach to cardio-oncology care among patients with suspected TTC is crucial. More research is needed to understand the role of TTC in cardiac dysfunction among patients with cancer, clarify risk stratification methods, and improve outcomes for patients at risk of TTC during cancer treatment.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100723"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting cardiovascular diseases using imbalanced data: An XGBoost-based analysis of the 2022 BRFSS dataset","authors":"Masoud Imani ,&nbsp;Ali Maroosi ,&nbsp;Seyedshayan Shojaei ,&nbsp;Kimia Heidari ,&nbsp;Seyed Mahdi Hoseinzadeh ,&nbsp;Nima Daneshi ,&nbsp;Zahra Saber ,&nbsp;Negar Sajadi ,&nbsp;Morteza Mohammadzadeh","doi":"10.1016/j.ahjo.2026.100719","DOIUrl":"10.1016/j.ahjo.2026.100719","url":null,"abstract":"<div><h3>Background</h3><div>Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clinical, behavioral, and social determinants. Leveraging large, nationally representative datasets such as the 2022 Behavioral Risk Factor Surveillance System (BRFSS) offers a unique opportunity to identify emerging risk patterns, monitor population-level disparities, and inform more targeted prevention strategies.</div></div><div><h3>Methods</h3><div>A total of 221,643 participants from the BRFSS 2022 survey were included after excluding records with missing data. Thirteen key predictors spanning demographics, chronic conditions, and social factors were selected. Data were split into training (80%) and testing (20%) sets. Four machine learning models, XGBoost, Random Forest, Logistic Regression, and Naive Bayes, were developed and evaluated using stratified 10-fold cross-validation. Model performance was assessed via accuracy, F1 score, precision, sensitivity, and ROC AUC. Synthetic Minority Over-sampling Technique (SMOTE) addressed class imbalance. SHAP values provided insights into feature importance and model interpretability.</div></div><div><h3>Results</h3><div>XGBoost demonstrated the best predictive performance (accuracy 94.2%, F1 score 85.3%, ROC AUC 0.94). SHAP analysis highlighted age ≥ 65, male gender, and diabetes as the strongest predictors, with additional contributions from kidney disease, employment status, and social isolation. Protective effects were observed for never smoking and higher education. Stratified analyses revealed that while overweight/obesity (BMI ≥25) was generally associated with higher CVD prevalence, the association was attenuated in older adults, smokers, and those with diabetes or kidney disease, suggesting illness-related weight loss, frailty, and behavioral confounding. These subgroup insights contextualize the apparent “BMI paradox” observed in the aggregate data.</div></div><div><h3>Conclusions</h3><div>Findings from the BRFSS 2022 highlight both established and emerging determinants of CVD risk, including the modifying effects of comorbidities, social isolation, and BMI-related heterogeneity. Beyond algorithmic performance, these results underscore the value of national surveillance data for informing applied, actionable strategies in CVD prevention and risk stratification.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100719"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of patients at risk for adverse events and poor symptom improvement after transcatheter aortic valve implantation","authors":"Kees van Bergeijk ,&nbsp;Constantijn (Stijn) Venema ,&nbsp;Bob Ophuis ,&nbsp;Luca Plekkenpol ,&nbsp;Mara Tomei ,&nbsp;Hayman Al-Barwary ,&nbsp;Jasper Tromp ,&nbsp;Yoran Hummel ,&nbsp;Wouter Ouwerkerk ,&nbsp;Ad van den Heuvel ,&nbsp;Hindrik van der Werf ,&nbsp;Yvonne Douglas ,&nbsp;Dajiro Tomii ,&nbsp;Thomas Pilgrim ,&nbsp;Stephan Windecker ,&nbsp;Adriaan Voors ,&nbsp;Joanna Wykrzykowska","doi":"10.1016/j.ahjo.2026.100735","DOIUrl":"10.1016/j.ahjo.2026.100735","url":null,"abstract":"<div><h3>Background</h3><div>Transcatheter aortic valve implantation (TAVI) aims to improve symptoms and prognosis, while minimising adverse outcomes. Available prediction models focus on individual outcomes, but those combining adverse events and symptom improvement in a single prediction model are scarce, and include only few variables and lack external validation. Using machine learning, we developed a clinically relevant model to identify patients at high risk of both adverse events and poor symptom improvement after TAVI.</div></div><div><h3>Methods</h3><div>In total, 72 candidate variables including clinical, medication use, biomarkers and (AI-derived) echocardiographic parameters were collected in patients with severe symptomatic AS undergoing TAVI. The primary outcome was a combination of poor symptom improvement (NYHA compared with baseline) and a composite of cardiovascular mortality, stroke or heart failure hospitalisation) at one year follow-up. LASSO Logistic regression was used for variable selection. External validation was performed in the Bern TAVI-registry.</div></div><div><h3>Results</h3><div>From a total of 827 patients (age 79.2 (± 7.29), 53% female), 101 patients (12%) had both adverse events and poor symptom improvement during one-year follow-up after TAVI, while 529 (64%) improved without any adverse events. Predictors for the combined primary outcome were history of COPD, use of vitamin-K antagonist, concomitant heart failure, reflected by mineralocorticoid receptor antagonists use, lower sodium and higher urea and (log-)NT-proBNP levels, lower AV mean gradient and larger LVOT diameter (area under the curve (AUC): 0.74 (internal validation: 0.72 and external validation: 0.66)).</div></div><div><h3>Conclusion</h3><div>Our externally validated model can reasonably identify patients with both poor symptom improvement and adverse events after TAVI.</div></div>","PeriodicalId":72158,"journal":{"name":"American heart journal plus : cardiology research and practice","volume":"63 ","pages":"Article 100735"},"PeriodicalIF":1.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}