Journal of Cardiovascular Medicine最新文献

Artificial intelligence has increasingly become an integral part of our daily activities. ChatGPT, a natural language processing technology developed by OpenAI, is widely used in various industries, including healthcare. The application of ChatGPT in healthcare is still evolving, with studies exploring its potential in clinical decision-making, patient education, workflow optimization, and scientific literature. ChatGPT could be exploited in the medical field to improve patient education and information, thus increasing compliance. ChatGPT could facilitate information exchange on major cardiovascular diseases, provide clinical decision support, and improve patient communication and education. It could assist the clinician in differential diagnosis, suggest appropriate imaging modalities, and optimize treatment plans based on evidence-based guidelines. However, it is unclear whether it will be possible to use ChatGPT for the management of patients who require rapid decisions. Indeed, many drawbacks are associated with the daily use of these technologies in the medical field, such as insufficient expertise in specialized fields and a lack of comprehension of the context in which it works. The pros and cons of its use have been explored in this review, which was not written with the help of ChatGPT.

Aims: Secondary mitral regurgitation (MR) negatively affects prognosis in acutely decompensated heart failure (ADHF), but can be rapidly sensitive to changes in volume status and medical interventions. We sought to assess the evolution of secondary MR in patients hospitalized for ADHF and its prognostic implications.

Methods: We retrospectively enrolled 782 patients admitted for ADHF with at least two in-hospital echocardiographic evaluations of MR. We classified MR severity as none-mild or moderate-severe. Based on MR evolution, patients were divided into 'persistent moderate-severe MR', 'improved MR' (from moderate-severe to none-mild) and 'persistent none-mild MR'.

Results: Four hundred and forty patients (56%) had moderate-severe MR at first evaluation, of whom 144 (33% of patients with baseline moderate-severe MR) had 'improved MR', while 296 (67%) had 'persistent moderate-severe MR'. Patients with improved MR had better clinical, laboratory and echocardiographic parameters of decongestion at discharge compared with those with persistent moderate-severe MR and showed a higher up-titration of recommended therapies. Left ventricular volume, ejection fraction and serum urea were the predictors of improved MR at multivariable analysis. After adjustment, no differences in 5-years survival (primary outcome) were observed according to baseline MR severity. When patients were stratified according to the in-hospital changes in MR severity, improved MR was associated with lower risk of 5-years mortality, compared with both persistent none-mild MR [hazard ratio (HR) = 0.505, P = 0.032] and persistent moderate-severe MR (HR = 0.556, P = 0.040).

Conclusions: The severity of MR frequently improved during hospitalization for ADHF; the extent and the changes in MR severity during the in-hospital stay identified distinct patient phenotypes, and seemed to portend different long-term outcomes, with higher 5-years survival associated with improvement in MR.

Background: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI) model that estimates biological age and mortality risk.

Methods: Using a dataset of 978 319 ECGs from 250 145 patients at Seoul National University Bundang Hospital, we developed a deep-learning model utilizing printed 12-lead ECG images to estimate patients' age (ECG-Age) and 1- and 5-year mortality risks. The model was validated externally using the CODE-15% dataset from Brazil.

Results: The ECG-Age showed a high correlation with chronological age in both the internal and external validation datasets (Pearson's R = 0.888 and 0.852, respectively). In the internal validation, the direct mortality risk prediction models showed area under the curves (AUCs) of 0.843 and 0.867 for 5- and 1-year all-cause mortality, respectively. For 5- and 1-year cardiovascular mortality, the AUCs were 0.920 and 0.916, respectively. In the CODE-15%, the mortality risk predictions showed AUCs of 0.818 and 0.836 for the prediction of 5- and 1-year all-cause mortality, respectively. Compared to the neutral Delta-Age (ECG-Age - chronological age) group, hazard ratios for deaths were 1.88 [95% confidence interval (CI): 1.14-3.92], 2.12 (95% CI: 1.15-3.92), 4.46 (95% CI: 2.22-8.96) and 7.68 (95% CI: 3.32-17.76) for positive Delta-Age groups (5-10, 10-15, 15-20, >20), respectively.

Conclusion: An image-based AI-ECG model is a feasible tool for estimating biological age and assessing all-cause and cardiovascular mortality risks, providing a practical approach for utilizing standardized ECG images in predicting long-term health outcomes.

Aims: Presence of family cases and multiple recurrences of pericarditis suggest the existence of a possible genetic background in at least 10% of cases. The aim of the present study is to describe the genetic landscape of a cohort of patients with multiple recurrences (at least two recurrences).

Methods: Retrospective cohort study of consecutive adult patients referred for at least two episodes of recurrences in a tertiary referral centre. Genetic testing was performed by whole exome sequencing (WES).

Results: Our cohort included 108 consecutive patients with recurrent pericarditis [median age 32 years, interquartile range (IQR) 18.5; 67.6% females, all Caucasian, idiopathic aetiology in 71.1%] with a median number of recurrences of 5 (IQR 2). Overall, 16 patients (14.8%) had variants in genes related to the inflammatory response. Eleven variants were located in genes already associated with recurrent pericarditis (NLRP3, TNFRSF1A and MEFV) and five in inflammation/immunodeficiency-related genes (IFIH1, NFKBIA, JAK1, NOD2 and ALPK1). Furthermore, we identified 10 patients with variants located in genes associated with conduction system-related diseases, and 22 variants in 21 patients with genes associated with heart structural-related diseases.

Conclusion: In this first observational study using WES to assess genetic variants in patients with multiple recurrences of pericarditis, about 15% of patients bore at least one variant that may be related to the disease. These findings highlight the importance of addressing the role of genetic predisposition in recurrent pericarditis. Moreover, 28.7% of patients carry variants in different cardiac genes, worthy of a deeper investigation.

Aims: The impact of sex-related factors on current clinical management and outcomes of chronic coronary syndromes (CCS) are unclear.

Methods: All patients belonging to the prospective, nationwide START registry were included. Their baseline characteristics, diagnostic workup, revascularization strategy, pharmacological treatment and 1-year clinical outcomes were compared with respect to sex overall and in age tertiles.

Results: A total of 5070 consecutive patients were included. Most patients were males (80.1%). As expected, the prevalence of females increased with age. Distribution of risk factors and history of cardiovascular disease were different depending on sex, as well as diagnostic workup, with lower use of exercise stress testing in women (25.1% vs. 36.7%, P < 0.0001). The use of coronary angiography was similar in the two groups. Women had lower rates of multivessel coronary artery disease (CAD) (33.0% vs. 40.6% P < 0.0001) and higher rates of nonobstructive CAD (18.3% vs. 11.3%, P < 0.0001). Rates of myocardial revascularization were similar, but women were more likely to receive percutaneous coronary intervention than men (84.3% vs. 77.8%, P < 0.0001) and less likely to receive surgical/hybrid revascularization (10.0% vs. 15.1%, P < 0.0001). At 12-month follow-up, no differences were observed for the combined endpoint of all-cause mortality, re-hospitalization for myocardial infarction, heart failure, stroke or myocardial revascularization between males and females; however, a significantly worse perceived quality of life was observed in women.

Conclusions: In a large nationwide cohort of patients with CCS, clinical outcomes were not different depending on sex. However, several differences in the diagnostic work-up, treatment strategies and quality of life were found between sexes.

Background: Lower extremity arterial disease (LEAD) and increased aortic stiffness are associated with higher mortality in patients with chronic coronary syndrome, while their prognostic significance after an acute coronary syndrome (ACS) is less known.

Methods: We analyzed prevalence, clinical phenotypes and association of LEAD - assessed by the ankle-brachial index (ABI) - and increased aortic stiffness - assessed by the aortic pulse wave velocity (PWV) - with all-cause mortality and major adverse cardiovascular events (MACE) in patients admitted with an ACS.

Results: Among 270 patients admitted for ACS (mean age 67 years, 80% males), 41 (15%) had an ABI ≤0.9, with 14 of them (34%) presenting with intermittent claudication (symptomatic LEAD). Patients with symptomatic LEAD, compared with those with asymptomatic LEAD or without LEAD, had higher prevalence of cardiovascular risk factors, lower estimated glomerular filtration rate and higher high-sensitivity C-reactive protein. Patients with LEAD, either symptomatic or asymptomatic, more frequently presented with non-ST-elevation myocardial infarction and more frequently had multivessel coronary artery disease. Both symptomatic and asymptomatic LEAD were significantly associated with all-cause mortality after adjustment for confounders, including multivessel disease or carotid artery disease (hazard ratio 4.03, 95% confidence interval 1.61-10.08, P  < 0.01), whereas PWV was not associated with the outcome in the univariable model. LEAD and PWV were not associated with a higher risk of MACE (myocardial infarction or unstable angina, stroke, or transient ischemic attack).

Conclusions: LEAD, either clinical or subclinical, but not increased aortic stiffness, is an independent predictor of all-cause mortality in patients admitted for ACS.