BACKGROUND: Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. We aimed to investigate whether neural network-derived ECG features could be used to predict future cardiovascular disease and mortality and have phenotypic and genotypic associations. METHODS: We extracted 5120 neural network-derived ECG features from an artificial intelligence-enabled ECG model trained for 6 simple diagnoses and applied unsupervised machine learning to identify 3 phenogroups. Using the identified phenogroups, we externally validated our findings in 5 diverse cohorts from the United States, Brazil, and the United Kingdom. Data were collected between 2000 and 2023. RESULTS: In total, 1 808 584 patients were included in this study. In the derivation cohort, the 3 phenogroups had significantly different mortality profiles. After adjusting for known covariates, phenogroup B had a 20% increase in long-term mortality compared with phenogroup A (hazard ratio, 1.20 [95% CI, 1.17-1.23]; P<0.0001; phenogroup A mortality, 2.2%; phenogroup B mortality, 6.1%). In univariate analyses, we found phenogroup B had a significantly greater risk of mortality in all cohorts (log-rank P<0.01 in all 5 cohorts). Phenome-wide association study showed phenogroup B had a higher rate of future atrial fibrillation (odds ratio, 2.89; P<0.00001), ventricular tachycardia (odds ratio, 2.00; P<0.00001), ischemic heart disease (odds ratio, 1.44; P<0.00001), and cardiomyopathy (odds ratio, 2.04; P<0.00001). A single-trait genome-wide association study yielded 4 loci. SCN10A, SCN5A, and CAV1 have roles in cardiac conduction and arrhythmia. ARHGAP24 does not have a clear cardiac role and may be a novel target. CONCLUSIONS: Neural network-derived ECG features can be used to predict all-cause mortality and future cardiovascular diseases. We have identified biologically plausible and novel phenotypic and genotypic associations that describe mechanisms for the increased risk identified.

• Klíčová slova
• cardiovascular diseases, electrocardiography, neural networks, computer, supervised machine learning, unsupervised machine learning,
• MeSH
• časové faktory MeSH
• elektrokardiografie * MeSH
• fenotyp * MeSH
• hodnocení rizik MeSH
• kardiovaskulární nemoci diagnóza   mortalita   genetika   patofyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• neuronové sítě (počítačové) * MeSH
• prediktivní hodnota testů * MeSH
• prognóza MeSH
• reprodukovatelnost výsledků MeSH
• rizikové faktory MeSH
• senioři MeSH
• srdeční frekvence MeSH
• strojové učení bez učitele MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• Geografické názvy
• Spojené státy americké epidemiologie   MeSH

To identify patterns in big medical datasets and use Deep Learning and Machine Learning (ML) to reliably diagnose Cardio Vascular Disease (CVD), researchers are currently delving deeply into these fields. Training on large datasets and producing highly accurate validation results is exceedingly difficult. Furthermore, early and precise diagnosis is necessary due to the increased global prevalence of cardiovascular disease (CVD). However, the increasing complexity of healthcare datasets makes it challenging to detect feature connections and produce precise predictions. To address these issues, the Intelligent Cardiovascular Disease Diagnosis based on Ant Colony Optimisation with Enhanced Deep Learning (ICVD-ACOEDL) model was developed. This model employs feature selection (FS) and hyperparameter optimization to diagnose CVD. Applying a min-max scaler, medical data is first consistently prepared. The key feature that sets ICVD-ACOEDL apart is the use of Ant Colony Optimisation (ACO) to select an optimal feature subset, which in turn helps to upgrade the performance of the ensuring deep learning enhanced neural network (DLENN) classifier. The model reforms the hyperparameters of DLENN for CVD classification using Bayesian optimization. Comprehensive evaluations on benchmark medical datasets show that ICVD-ACOEDL exceeds existing techniques, indicating that it could have a significant impact on CVD diagnosis. The model furnishes a workable way to increase CVD classification efficiency and accuracy in real-world medical situations by incorporating ACO for feature selection, min-max scaling for data pre-processing, and Bayesian optimization for hyperparameter tweaking.

• Klíčová slova
• Ant Colony Optimisation, Bayesian optimisation, Cardiovascular disease, Hyperparameter, Min–max scaler,
• MeSH
• Bayesova věta MeSH
• deep learning * MeSH
• diagnóza počítačová metody   MeSH
• Formicidae MeSH
• kardiovaskulární nemoci * diagnóza   MeSH
• lidé MeSH
• neuronové sítě (počítačové) * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Metabolomics and lipidomics have emerged as tools in understanding the connections of metabolic syndrome (MetS) with cardiovascular diseases (CVD), type 1 and type 2 diabetes (T1D, T2D), and metabolic dysfunction-associated steatotic liver disease (MASLD). This review highlights the applications of these omics approaches in large-scale cohort studies, emphasizing their role in biomarker discovery and disease prediction. Integrating metabolomics and lipidomics has significantly advanced our understanding of MetS pathology by identifying unique metabolic signatures associated with disease progression. However, challenges such as standardizing analytical workflows, data interpretation, and biomarker validation remain critical for translating research findings into clinical practice. Future research should focus on optimizing these methodologies to enhance their clinical utility and address the global burden of MetS-related diseases.

• MeSH
• biologické markery metabolismus   MeSH
• diabetes mellitus 1. typu metabolismus   komplikace   MeSH
• diabetes mellitus 2. typu * metabolismus   MeSH
• kardiovaskulární nemoci * metabolismus   diagnóza   MeSH
• lidé MeSH
• lipidomika * metody   MeSH
• metabolický syndrom * metabolismus   MeSH
• metabolomika * metody   MeSH
• ztučnělá játra metabolismus   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH
• Názvy látek
• biologické markery MeSH

Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of morbidity and mortality worldwide, highlighting the urgent need for advancements in risk assessment and management strategies. Although significant progress has been made recently, identifying and managing apparently healthy individuals at a higher risk of developing atherosclerosis and those with subclinical atherosclerosis still poses significant challenges. Traditional risk assessment tools have limitations in accurately predicting future events and fail to encompass the complexity of the atherosclerosis trajectory. In this review, we describe novel approaches in biomarkers, genetics, advanced imaging techniques, and artificial intelligence that have emerged to address this gap. Moreover, polygenic risk scores and imaging modalities such as coronary artery calcium scoring, and coronary computed tomography angiography offer promising avenues for enhancing primary cardiovascular risk stratification and personalised intervention strategies. On the other hand, interventions aiming against atherosclerosis development or promoting plaque regression have gained attention in primary ASCVD prevention. Therefore, the potential role of drugs like statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, omega-3 fatty acids, antihypertensive agents, as well as glucose-lowering and anti-inflammatory drugs are also discussed. Since findings regarding the efficacy of these interventions vary, further research is still required to elucidate their mechanisms of action, optimize treatment regimens, and determine their long-term effects on ASCVD outcomes. In conclusion, advancements in strategies addressing atherosclerosis prevention and plaque regression present promising avenues for enhancing primary ASCVD prevention through personalised approaches tailored to individual risk profiles. Nevertheless, ongoing research efforts are imperative to refine these strategies further and maximise their effectiveness in safeguarding cardiovascular health.

• Klíčová slova
• Atherosclerosis, Cardiovascular disease, Plaque regression, Primary prevention, Risk stratification,
• MeSH
• ateroskleróza prevence a kontrola   diagnóza   MeSH
• biologické markery krev   MeSH
• hodnocení rizik MeSH
• kardiovaskulární nemoci prevence a kontrola   diagnóza   MeSH
• lidé MeSH
• prediktivní hodnota testů MeSH
• primární prevence * metody   MeSH
• rizikové faktory kardiovaskulárních chorob MeSH
• rizikové faktory MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Názvy látek
• biologické markery MeSH

BACKGROUND: The cardio-ankle vascular index (CAVI) measure of arterial stiffness is associated with prevalent cardiovascular risk factors, while its predictive value for cardiovascular events remains to be established. The aim was to determine associations of CAVI with cardiovascular morbimortality (primary outcome) and all-cause mortality (secondary outcome), and to establish the determinants of CAVI progression. METHODS: TRIPLE-A-Stiffness, an international multicentre prospective longitudinal study, enrolled >2000 subjects ≥40 years old at 32 centres from 18 European countries. Of these, 1250 subjects (55% women) were followed for a median of 3.82 (2.81-4.69) years. FINDINGS: Unadjusted cumulative incidence rates of outcomes according to CAVI stratification were higher in highest stratum (CAVI > 9). Cox regression with adjustment for age, sex, and cardiovascular risk factors revealed that CAVI was associated with increased cardiovascular morbimortality (HR 1.25 per 1 increase; 95% confidence interval, CI: 1.03-1.51) and all-cause mortality (HR 1.37 per 1 increase; 95% CI: 1.10-1.70) risk in subjects ≥60 years. In ROC analyses, CAVI optimal threshold was 9.25 (c-index 0.598; 0.542-0.654) and 8.30 (c-index 0.565; 0.512-0.618) in subjects ≥ or <60 years, respectively, to predict increased CV morbimortality. Finally, age, mean arterial blood pressure, anti-diabetic and lipid-lowering treatment were independent predictors of yearly CAVI progression adjusted for baseline CAVI. INTERPRETATION: The present study identified additional value for CAVI to predict outcomes after adjustment for CV risk factors, in particular for subjects ≥60 years. CAVI progression may represent a modifiable risk factor by treatments. FUNDING: International Society of Vascular Health (ISVH) and Fukuda Denshi, Japan.

• Klíčová slova
• Arterial stiffness, Cardio-ankle vascular index, Cardiovascular morbimortality, Risk factor,
• MeSH
• cévní index srdce-kotník * MeSH
• dospělí MeSH
• kardiovaskulární nemoci * mortalita   diagnóza   etiologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• longitudinální studie MeSH
• prognóza MeSH
• progrese nemoci MeSH
• prospektivní studie MeSH
• rizikové faktory kardiovaskulárních chorob MeSH
• rizikové faktory MeSH
• ROC křivka MeSH
• senioři MeSH
• tuhost cévní stěny * MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH

The 9th Cardiovascular Outcome Trial (CVOT) Summit: Congress on Cardiovascular, Kidney, and Metabolic Outcomes was held virtually on November 30-December 1, 2023. This reference congress served as a platform for in-depth discussions and exchange on recently completed outcomes trials including dapagliflozin (DAPA-MI), semaglutide (SELECT and STEP-HFpEF) and bempedoic acid (CLEAR Outcomes), and the advances they represent in reducing the risk of major adverse cardiovascular events (MACE), improving metabolic outcomes, and treating obesity-related heart failure with preserved ejection fraction (HFpEF). A broad audience of endocrinologists, diabetologists, cardiologists, nephrologists and primary care physicians participated in online discussions on guideline updates for the management of cardiovascular disease (CVD) in diabetes, heart failure (HF) and chronic kidney disease (CKD); advances in the management of type 1 diabetes (T1D) and its comorbidities; advances in the management of CKD with SGLT2 inhibitors and non-steroidal mineralocorticoid receptor antagonists (nsMRAs); and advances in the treatment of obesity with GLP-1 and dual GIP/GLP-1 receptor agonists. The association of diabetes and obesity with nonalcoholic steatohepatitis (NASH; metabolic dysfunction-associated steatohepatitis, MASH) and cancer and possible treatments for these complications were also explored. It is generally assumed that treatment of chronic diseases is equally effective for all patients. However, as discussed at the Summit, this assumption may not be true. Therefore, it is important to enroll patients from diverse racial and ethnic groups in clinical trials and to analyze patient-reported outcomes to assess treatment efficacy, and to develop innovative approaches to tailor medications to those who benefit most with minimal side effects. Other keys to a successful management of diabetes and comorbidities, including dementia, entail the use of continuous glucose monitoring (CGM) technology and the implementation of appropriate patient-physician communication strategies. The 10th Cardiovascular Outcome Trial Summit will be held virtually on December 5-6, 2024 ( http://www.cvot.org ).

• Klíčová slova
• CGM, Cardiovascular disease, Chronic kidney disease, Diabetes, Finerenone, GLP-1 RA, Guidelines, Heart failure, MASLD, NAFLD, Obesity, SGLT2 inhibitor, Teplizumab,
• MeSH
• chronická renální insuficience * diagnóza   epidemiologie   terapie   MeSH
• diabetes mellitus 2. typu * farmakoterapie   MeSH
• diabetes mellitus * farmakoterapie   MeSH
• kardiovaskulární nemoci * diagnóza   epidemiologie   prevence a kontrola   MeSH
• krevní glukóza MeSH
• ledviny MeSH
• lidé MeSH
• obezita komplikace   MeSH
• selfmonitoring glykemie MeSH
• srdeční selhání * komplikace   MeSH
• tepový objem MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• dopisy MeSH
• Názvy látek
• krevní glukóza MeSH

AIMS: The Southern European Atlantic diet (SEAD) is the traditional dietary pattern of northwestern Spain and northern Portugal, but it may resemble that of central, eastern, and western European countries. The SEAD has been found associated with lower risk of myocardial infarction and mortality in older adults, but it is uncertain whether this association also exists in other European populations and if it is similar as that found in its countries of origin. METHODS AND RESULTS: We conducted a prospective analysis of four cohorts with 35 917 subjects aged 18-96 years: ENRICA (Spain), HAPIEE (Czechia and Poland), and Whitehall II (United Kingdom). The SEAD comprised fresh fish, cod, red meat and pork products, dairy, legumes and vegetables, vegetable soup, potatoes, whole-grain bread, and moderate wine consumption. Associations were adjusted for sociodemographic variables, energy intake, lifestyle, and morbidity. After a median follow-up of 13.6 years (range = 0-15), we recorded 4 973 all-cause, 1 581 cardiovascular, and 1 814 cancer deaths. Higher adherence to the SEAD was associated with lower mortality in the pooled sample. Fully adjusted hazard ratios and 95% confidence interval per 1-standard deviation increment in the SEAD were 0.92 (0.89, 0.95), 0.91 (0.86, 0.96), and 0.94 (0.89, 0.99) for all-cause, cardiovascular, and cancer mortality, respectively. The association of the SEAD with all-cause mortality was not significantly different between countries [Spain = 0.93 (0.88, 0.99), Czechia = 0.94 (0.89,0.99), Poland = 0.89 (0.85, 0.93), United Kingdom = 0.98 (0.89, 1.07); P for interaction = 0.16]. CONCLUSION: The SEAD was associated with lower all-cause, cardiovascular, and cancer mortality in southern, central, eastern, and western European populations. Associations were of similar magnitude as those found for existing healthy dietary patterns.

In this study of 35 917 subjects from southern, central, eastern, and western European countries, the Southern European Atlantic diet (traditional dietary pattern of northwestern Spain and northern Portugal) was associated with lower 13.6-year mortality from any cause, cardiovascular disease, and cancer. The associations of the Southern European Atlantic diet with lower mortality were not significantly different between countries (Spain, Czechia, Poland, and the United Kingdom). Study associations were similar as those found for existing healthy dietary patterns, suggesting that rather different diets could confer comparable benefits on health.

• Klíčová slova
• Alcohol, Coronary heart disease, Cox model, Death, Longitudinal, Mediterranean diet, Processed meat, Public health, Seafood, Stroke,
• MeSH
• dieta škodlivé účinky   MeSH
• infarkt myokardu * MeSH
• kardiovaskulární nemoci * diagnóza   MeSH
• lidé MeSH
• nádory * diagnóza   MeSH
• příčina smrti MeSH
• senioři MeSH
• zelenina MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• senioři MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

Sports activity is generally considered to be beneficial to health. The World Health Organization (WHO) recommends physical activity as part of a healthy lifestyle. Sports activities significantly affect the cardiovascular system. A number of studies show that they significantly reduce the risk of cardiovascular disease as well as decrease cardiovascular mortality. This review discusses changes in various cardiovascular parameters in athletes - vagotonia/bradycardia, hypertrophy of heart, ECG changes, blood pressure, and variability of cardiovascular parameters. Because of its relationship to the cardiovascular system, VO2max, which is widely used as an indicator of cardiorespiratory fitness, is also discussed. The review concludes with a discussion of reactive oxygen species (ROS) and oxidative stress, particularly in relation to changes in the cardiovascular system in athletes. The review appropriately summarizes the above issues and points out some new implications.

• MeSH
• cvičení fyziologie   MeSH
• kardiovaskulární nemoci * diagnóza   epidemiologie   MeSH
• kardiovaskulární systém * MeSH
• krevní tlak fyziologie   MeSH
• lidé MeSH
• sporty * fyziologie   MeSH
• srdce MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Cardiovascular diseases are characterized by many clinical, morphological, functional, and biochemical markers, including age, sex, genetic factors, plasma lipids, glycemia, and many other laboratory parameters [...].

• MeSH
• biologické markery MeSH
• diferenciální diagnóza MeSH
• kardiovaskulární nemoci * diagnóza   etiologie   prevence a kontrola   MeSH
• lidé MeSH
• myokard MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• úvodníky MeSH
• Názvy látek
• biologické markery MeSH

PURPOSE: Low-density lipoprotein cholesterol (LDL-C) recommendations differ between the 2018 American College of Cardiology/American Heart Association (ACC/AHA) and 2019 European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) guidelines for patients with atherosclerotic cardiovascular disease (ASCVD) (< 70 vs. < 55 mg/dl, respectively). In the DA VINCI study, residual cardiovascular risk was predicted in ASCVD patients. The extent to which relative and absolute risk might be lowered by achieving ACC/AHA versus ESC/EAS LDL-C recommended approaches was simulated. METHODS: DA VINCI was a cross-sectional observational study of patients prescribed lipid-lowering therapy (LLT) across 18 European countries. Ten-year cardiovascular risk (CVR) was predicted among ASCVD patients receiving stabilized LLT. For patients with LDL-C ≥ 70 mg/dl, the absolute LDL-C reduction required to achieve an LDL-C of < 70 or < 55 mg/dl (LDL-C of 69 or 54 mg/dl, respectively) was calculated. Relative and absolute risk reductions (RRRs and ARRs) were simulated. RESULTS: Of the 2039 patients, 61% did not achieve LDL-C < 70 mg/dl. For patients with LDL-C ≥ 70 mg/dl, median (interquartile range) baseline LDL-C and 10-year CVR were 93 (81-115) mg/dl and 32% (25-43%), respectively. Median LDL-C reductions of 24 (12-46) and 39 (27-91) mg/dl were needed to achieve an LDL-C of 69 and 54 mg/dl, respectively. Attaining ACC/AHA or ESC/EAS goals resulted in simulated RRRs of 14% (7-25%) and 22% (15-32%), respectively, and ARRs of 4% (2-7%) and 6% (4-9%), respectively. CONCLUSION: In ASCVD patients, achieving ESC/EAS LDL-C goals could result in a 2% additional ARR over 10 years versus the ACC/AHA approach.

• Klíčová slova
• Atherosclerotic cardiovascular disease, Cardiovascular disease prevention, Cardiovascular risk, LDL-C, Lipid-lowering, Statins,
• MeSH
• ateroskleróza * diagnóza   farmakoterapie   epidemiologie   MeSH
• chování snižující riziko MeSH
• kardiovaskulární nemoci * diagnóza   epidemiologie   prevence a kontrola   MeSH
• LDL-cholesterol MeSH
• lidé MeSH
• průřezové studie MeSH
• rizikové faktory MeSH
• statiny * terapeutické užití   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• pozorovací studie MeSH
• Geografické názvy
• Spojené státy americké epidemiologie   MeSH
• Názvy látek
• LDL-cholesterol MeSH
• statiny * MeSH