Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Artificial intelligence-enhanced patient evaluation: bridging art and science.

The advent of digital health and artificial intelligence (AI) has promised to revolutionize clinical care, but real-world patient evaluation has yet to witness transformative changes. As history taking and physical examination continue to rely on long-established practices, a growing pipeline of AI-enhanced digital tools may soon augment the traditional clinical encounter into a data-driven process. This article presents an evidence-backed vision of how promising AI applications may enhance traditional practices, streamlining tedious tasks while elevating diverse data sources, including AI-enabled stethoscopes, cameras, and wearable sensors, to platforms for personalized medicine and efficient care delivery. Through the lens of traditional patient evaluation, we illustrate how digital technologies may soon be interwoven into routine clinical workflows, introducing a novel paradigm of longitudinal monitoring. Finally, we provide a skeptic's view on the practical, ethical, and regulatory challenges that limit the uptake of such technologies.

Targeting the Gut Microbiome to Treat Cardiometabolic Disease.

PURPOSE OF REVIEW: Cardiometabolic diseases, which include obesity, type 2 diabetes, and cardiovascular diseases, constitute a worldwide health crisis of unparalleled proportions. The human gut microbiota has emerged as a prominent topic of inquiry in the search for novel treatment techniques. This review summarizes current research on the potential of addressing the gut microbiota to treat cardiometabolic disease. RECENT FINDINGS: Recent studies have highlighted a complex link between the gut microbiota and host physiology, shedding light on the several processes through which gut microorganisms impact metabolic health, inflammation, and cardiovascular function. Furthermore, a growing corpus of research is available on microbiome-based therapies such as dietary interventions, probiotics, prebiotics, synbiotics, and fecal microbiota transplantation. These therapies show promise as methods for reshaping the gut microbiota and, as a result, improving cardiometabolic outcomes. However, hurdles remain, ranging from the intricacies of microbiome research to the necessity for tailored treatments that take individual microbial variations into consideration, emphasizing the significance of furthering research to bridge the gap between microbiome science and clinical practice. The gut microbiome is a beacon of hope for improving the management of cardiometabolic disease in the age of precision medicine, since its association with their pathophysiology is constantly being unraveled and strengthened. Available studies point to the potential of gut microbiome-based therapeutics, which remains to be tested in appropriately designed clinical trials. Further preclinical research is, however, essential to provide answers to the existing obstacles, with the ultimate goal of enhancing patient care.

Burden of cardiovascular disease attributed to air pollution: a systematic review.

BACKGROUND: Cardiovascular diseases (CVDs) are estimated to be the leading cause of global death. Air pollution is the biggest environmental threat to public health worldwide. It is considered a potentially modifiable environmental risk factor for CVDs because it can be prevented by adopting the right national and international policies. The present study was conducted to synthesize the results of existing studies on the burden of CVDs attributed to air pollution, namely prevalence, hospitalization, disability, mortality, and cost characteristics. METHODS: A systematic search was performed in the Scopus, PubMed, and Web of Science databases to identify studies, without time limitations, up to June 13, 2023. Exclusion criteria included prenatal exposure, exposure to indoor air pollution, review studies, conferences, books, letters to editors, and animal and laboratory studies. The quality of the articles was evaluated based on the Agency for Healthcare Research and Quality Assessment Form, the Newcastle-Ottawa Scale, and Drummond Criteria using a self-established scale. The articles that achieved categories A and B were included in the study. RESULTS: Of the 566 studies obtained, based on the inclusion/exclusion criteria, 92 studies were defined as eligible in the present systematic review. The results of these investigations supported that chronic exposure to various concentrations of air pollutants, increased the prevalence, hospitalization, disability, mortality, and costs of CVDs attributed to air pollution, even at relatively low levels. According to the results, the main pollutant investigated closely associated with hypertension was PM2.5. Furthermore, the global DALY related to stroke during 2016-2019 has increased by 1.8 times and hospitalization related to CVDs in 2023 has increased by 8.5 times compared to 2014. CONCLUSION: Ambient air pollution is an underestimated but significant and modifiable contributor to CVDs burden and public health costs. This should not only be considered an environmental problem but also as an important risk factor for a significant increase in CVD cases and mortality. The findings of the systematic review highlighted the opportunity to apply more preventive measures in the public health sector to reduce the footprint of CVDs in human society.

Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers.

Obesity is a modifiable cardiovascular risk factor, but adipose tissue (AT) depots in humans are anatomically, histologically, and functionally heterogeneous. For example, visceral AT is a pro-atherogenic secretory AT depot, while subcutaneous AT represents a more classical energy storage depot. Perivascular adipose tissue (PVAT) regulates vascular biology via paracrine cross-talk signals. In this position paper, the state-of-the-art knowledge of various AT depots is reviewed providing a consensus definition of PVAT around the coronary arteries, as the AT surrounding the artery up to a distance from its outer wall equal to the luminal diameter of the artery. Special focus is given to the interactions between PVAT and the vascular wall that render PVAT a potential therapeutic target in cardiovascular diseases. This Clinical Consensus Statement also discusses the role of PVAT as a clinically relevant source of diagnostic and prognostic biomarkers of vascular function, which may guide precision medicine in atherosclerosis, hypertension, heart failure, and other cardiovascular diseases. In this article, its role as a 'biosensor' of vascular inflammation is highlighted with description of recent imaging technologies that visualize PVAT in clinical practice, allowing non-invasive quantification of coronary inflammation and the related residual cardiovascular inflammatory risk, guiding deployment of therapeutic interventions. Finally, the current and future clinical applicability of artificial intelligence and machine learning technologies is reviewed that integrate PVAT information into prognostic models to provide clinically meaningful information in primary and secondary prevention.

Severe aortic stenosis detection by deep learning applied to echocardiography.

BACKGROUND AND AIMS: Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on two-dimensional (2D) parasternal long axis videos from transthoracic echocardiography without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography. METHODS AND RESULTS: In a training set of 5257 studies (17 570 videos) from 2016 to 2020 [Yale-New Haven Hospital (YNHH), Connecticut], an ensemble of three-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 4226 and 3072 studies, from California and other hospitals in New England, respectively. The deep learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS in the temporally distinct test set, maintaining its diagnostic performance in geographically distinct cohorts [0.952 AUROC (95% CI: 0.941, 0.963) in California and 0.942 AUROC (95% CI: 0.909, 0.966) in New England]. The model was interpretable with saliency maps identifying the aortic valve, mitral annulus, and left atrium as the predictive regions. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting an association with various stages of AS severity. CONCLUSION: This study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with potential utility for point-of-care screening.

Coronary Plaque Erosion: Epidemiology, Diagnosis, and Treatment.

Plaque erosion (PE), a distinct etiology of acute coronary syndromes (ACSs), is often overshadowed by plaque ruptures (PRs). Concerning its epidemiology, PE has garnered increasing recognition, with recent studies revealing its prevalence to be approximately 40% among ACS patients, challenging earlier assumptions based on autopsy data. Notably, PE exhibits distinct epidemiological features, preferentially affecting younger demographics, particularly women, and often manifesting as a non-ST-segment elevation myocardial infarction. There are seasonal variations, with PE events being less common in winter, potentially linked to physiological changes and cholesterol solidification, while peaking in summer, warranting further investigation. Moving to molecular mechanisms, PE presents a unique profile characterized by a lesser degree of inflammation compared to PR, with endothelial shear stress emerging as a plausible molecular mechanism. Neutrophil activation, toll-like receptor-2 pathways, and hyaluronidase 2 expression are among the factors implicated in PE pathophysiology, underscoring its multifactorial nature. Advancements in intravascular imaging diagnostics, particularly optical coherence tomography and near-infrared spectroscopy coupled with intravascular ultrasound, offer unprecedented insights into plaque composition and morphology. Artificial intelligence algorithms show promise in enhancing diagnostic accuracy and streamlining image interpretation, augmenting clinician decision-making. Therapeutically, the management of PE evolves, with studies exploring less invasive approaches such as antithrombotic therapy without stenting, particularly in cases identified early through intravascular imaging. Additionally, the potential role of drug-coated balloons in reducing thrombus burden and minimizing future major adverse cardiovascular events warrants further investigation. Looking ahead, the integration of advanced imaging modalities, biomarkers, and artificial intelligence promises to revolutionize the diagnosis and treatment of coronary PE, ushering in a new era of personalized and precise cardiovascular care.

Unveiling the Role of Endothelial Dysfunction: A Possible Key to Enhancing Catheter Ablation Success in Atrial Fibrillation.

Atrial fibrillation, a prevalent type of arrhythmia, is increasingly contributing to the economic burden on healthcare systems. The development of innovative treatments, notably catheter ablation, has demonstrated both impressive and promising outcomes. However, these treatments have not yet fully replaced pharmaceutical approaches, primarily due to the relatively high incidence of atrial fibrillation recurrence post-procedure. Recent insights into endothelial dysfunction have shed light on its role in both the onset and progression of atrial fibrillation. This emerging understanding suggests that endothelial function might significantly influence the effectiveness of catheter ablation. Consequently, a deeper exploration into endothelial dynamics could potentially elevate the status of catheter ablation, positioning it as a primary treatment option for atrial fibrillation.

The Association of Depression With QT Duration: A Comparison Between Individuals Younger or Older Than 65 Years.

OBJECTIVE: The electrocardiogram-derived corrected QT (QTc) interval is an indicator of cardiac autonomic activity that has been proposed as a biological measure to investigate the interplay between depression and cardiovascular diseases. This study assesses whether depression is associated with a longer QTc interval across age groups. METHODS: Assessment of depressive symptoms was performed in 1637 participants of the cross-sectional Corinthia study with the Zung Self-Rating Depression Scale in those younger than 65 years (group 1) and with the Geriatric Depression Scale in elderly individuals (≥65 years, group 2). The QT interval was obtained from electrocardiogram recordings and corrected for heart rate (QTc). RESULTS: Individuals in group 1 with depression were predominantly women and had a higher prevalence of coronary artery disease and diabetes mellitus. Group 1 individuals with depression had longer QTc duration (no depression versus depression, 389.3 [27.0] versus 401.1 [32.9] milliseconds; p < .001) and percentage of abnormal QTc (no depression versus depression, 2.0% versus 10.8%; p = .001) compared with those without depression. Elderly individuals (group 2) had similar values of QTc and percentage of abnormal QTc irrespective of depression status. Even after adjustment for known QT-prolonging factors, the presence of depression in younger individuals was associated with an increased QTc by 11.1 milliseconds and with an approximately 10.6-fold higher prevalence of abnormal QTc duration. CONCLUSIONS: Depression was associated with a longer QTc interval especially in individuals younger than 65 years. These findings may indicate an interrelationship between depression and autonomic dysregulation as potential risk factors for cardiovascular disease and sudden cardiac death.

Machine learning in precision diabetes care and cardiovascular risk prediction.

Artificial intelligence and machine learning are driving a paradigm shift in medicine, promising data-driven, personalized solutions for managing diabetes and the excess cardiovascular risk it poses. In this comprehensive review of machine learning applications in the care of patients with diabetes at increased cardiovascular risk, we offer a broad overview of various data-driven methods and how they may be leveraged in developing predictive models for personalized care. We review existing as well as expected artificial intelligence solutions in the context of diagnosis, prognostication, phenotyping, and treatment of diabetes and its cardiovascular complications. In addition to discussing the key properties of such models that enable their successful application in complex risk prediction, we define challenges that arise from their misuse and the role of methodological standards in overcoming these limitations. We also identify key issues in equity and bias mitigation in healthcare and discuss how the current regulatory framework should ensure the efficacy and safety of medical artificial intelligence products in transforming cardiovascular care and outcomes in diabetes.

Association of food allergy in children with vitamin D insufficiency: a systematic review and meta-analysis.

Current literature regarding the association of vitamin D insufficiency and food allergy is contradicting. The purpose of our study was to investigate this association. This is a systematic review and meta-analysis according to the PRISMA statement. PubMeD and Scopus databases were systematically searched for case-control studies investigating the association between pediatric food allergy and vitamin D insufficiency. Our search yielded 806 studies. Ten final studies were considered eligible for qualitative and quantitative analysis. Children with vitamin D insufficiency were found to have 68% more probability to present a food allergy episode (adjusted pooled OR: 1.68, 95% CI [1.25-2.27], p-value: 0.001). In their second year of life they were 4 times more likely to present a food allergy episode (adjusted pooled OR: 4.06, 95% CI [1.93-8.56], p-value: < 0.001), and 56% more probable to develop food sensitization (OR: 1.56, 95% CI [1.15-2.11], p-value: < 0.004). Children in Australia with vitamin D insufficiency were almost 4 times more likely to develop egg sensitization (adjusted OR: 3.79, 95% CI [1.19-12.08], p-value: 0.024). Children with vitamin D insufficiency were almost twice as likely to have peanut sensitization (OR: 1.96, 95% CI [1.08-3.57], p-value: 0.028).  Conclusion: Decreased maternal vitamin D levels and infant vitamin D insufficiency appear to increase the incidence of food allergies, particularly in the second year of life. To confirm this association, multicenter longitudinal studies are required. What is Known: • In newborns and young children, vitamin D deficiency and insufficiency are prevalent. • The exact role of vitamin D in atopic diseases remains controversial. What is New: • Decreased maternal vitamin D levels and infant vitamin D insufficiency appear to increase the incidence of food allergies. This association is more evident in the second year of life.

Impaired left ventricular deformation and ventricular-arterial coupling in post-COVID-19: association with autonomic dysregulation.

Coronavirus disease-19 (COVID-19) has extended implications namely the long COVID-19 syndrome. We assessed over-time changes in left ventricular (LV) function, aortic stiffness, autonomic function, and ventricular-arterial coupling (VAC) in post-COVID-19 patients. We followed 34 post-COVID-19 subjects, up to 6 months post-hospital discharge. Subjects without COVID-19 served as control. We evaluated LV global longitudinal strain (LV-GLS), arterial stiffness [carotid-femoral pulse wave velocity (cf-PWV)], and heart rate variability -standard deviation of normal RR intervals (SDNN). VAC was estimated as the ratio of cf-PWV to LV-GLS. Post-COVID-19 individuals (1-month post-hospital discharge) presented with impaired LV-GLS [-18.4%(3.1) vs. -22.0%(2.7), P < 0.001], cf-PWV [12.1 m/s (3.2) vs. 9.6 m/s (1.9), P < 0.001], SDNN [111.3 ms (22.6) vs. 147.2 ms (14.0), P < 0.001], and VAC [-0.68 (0.22) vs. -0.44 (0.10), P < 0.001] compared to control. LV-GLS, SDNN, and VAC improved at the 6-month follow-up however they did not reach control levels. In post-COVID-19 subjects, SDNN and VAC were correlated at the 1-month (R = 0.499, P = 0.003) and 6-month (R = 0.372, P = 0.04) follow-up. Long COVID-19 syndrome was associated with impaired LV-GLS, SDNN, and VAC. Post-COVID-19 subjects presented with autonomic dysregulation associated with aortic stiffness, ventricular-arterial impairment, and LV dysfunction, even 6-months post-hospital discharge. These abnormalities may be related to the presence of long COVID-19 syndrome.

The Role of Macrophages in Atherosclerosis: Pathophysiologic Mechanisms and Treatment Considerations.

Atherosclerotic diseases are a leading cause of morbidity and mortality worldwide, despite the recent diagnostic and therapeutic advances. A thorough understanding of the pathophysiologic mechanisms is thus essential to improve the care of affected individuals. Macrophages are crucial mediators of the atherosclerotic cascade, but their role has not been fully elucidated. The two main subtypes, tissue-resident and monocyte-derived macrophages, have distinct functions that contribute to atherosclerosis development or regression. Since polarization of macrophages to an M2 phenotype and induction of macrophage autophagy have been demonstrated to be atheroprotective, targeting these pathways could represent an appealing approach. Interestingly, macrophage receptors could act as drug targets, as seen in recent experimental studies. Last but not least, macrophage-membrane-coated carriers have been investigated with encouraging results.

Molecular Mechanisms and Therapeutic Implications of Endothelial Dysfunction in Patients with Heart Failure.

Heart failure is a complex medical syndrome that is attributed to a number of risk factors; nevertheless, its clinical presentation is quite similar among the different etiologies. Heart failure displays a rapidly increasing prevalence due to the aging of the population and the success of medical treatment and devices. The pathophysiology of heart failure comprises several mechanisms, such as activation of neurohormonal systems, oxidative stress, dysfunctional calcium handling, impaired energy utilization, mitochondrial dysfunction, and inflammation, which are also implicated in the development of endothelial dysfunction. Heart failure with reduced ejection fraction is usually the result of myocardial loss, which progressively ends in myocardial remodeling. On the other hand, heart failure with preserved ejection fraction is common in patients with comorbidities such as diabetes mellitus, obesity, and hypertension, which trigger the creation of a micro-environment of chronic, ongoing inflammation. Interestingly, endothelial dysfunction of both peripheral vessels and coronary epicardial vessels and microcirculation is a common characteristic of both categories of heart failure and has been associated with worse cardiovascular outcomes. Indeed, exercise training and several heart failure drug categories display favorable effects against endothelial dysfunction apart from their established direct myocardial benefit.

Non-Alcoholic Fatty Liver Disease and Echocardiographic Parameters of Left Ventricular Diastolic Function: A Systematic Review and Meta-Analysis.

The cardiovascular implications of non-alcoholic fatty liver disease (NAFLD) have been associated with heart failure with preserved ejection fraction (HFpEF). The purpose of this review was to conduct a bibliographic search regarding the correlation between NAFLD and the echocardiographic parameters of left ventricular diastolic function. A systematic literature search was conducted in PubMed and Embase for original research data reporting on the association of NAFLD with diastolic function markers [E/e', left atrial volume index (LAVi), left ventricular mass index (LVMi)]. Meta-analysis was performed using the meta and dmetar packages in R studio v.1.4.1106, with p < 0.05 values being considered significant. Results are expressed as the standardized mean difference (SMD) for continuous variables and as the odds ratio (OR) for categorical variables, with respective 95% confidence intervals (CI). Heterogeneity between studies was expressed with index Ι2. From the preliminary search, 2619 articles were found from which 31 studies were included in the final statistical analysis. The meta-analysis of 8 studies which reported on the prevalence of diastolic dysfunction showed that it was increased in patients with NAFLD (OR: 2.07, 95% CI 1.24-3.44 with p = 0.01, I2: 80% with p < 0.01). The meta-analysis of 21 studies showed significantly higher E/e' in NAFLD patients (SMD 1.02, 95% CI 0.43-1.61 with p < 0.001, I2: 97% with p < 0.001). Individuals with NAFLD had increased LAVi (SMD: 0.87, 95% CI 0.38-1.37 with p < 0.001, I2: 96% with p < 0.001) and LVMi (SMD: 0.89, 95% CI 0.31-1.48 with p = 0.003, I2: 100% with p < 0.001). To conclude, in the meta-analysis of 31 observational studies, NAFLD patients were found to have affected left ventricular diastolic function, supporting the hypothesis of NAFLD being associated with HFpEF.

Lipoprotein(a) in Atherosclerotic Diseases: From Pathophysiology to Diagnosis and Treatment.

Lipoprotein(a) (Lp(a)) is a low-density lipoprotein (LDL) cholesterol-like particle bound to apolipoprotein(a). Increased Lp(a) levels are an independent, heritable causal risk factor for atherosclerotic cardiovascular disease (ASCVD) as they are largely determined by variations in the Lp(a) gene (LPA) locus encoding apo(a). Lp(a) is the preferential lipoprotein carrier for oxidized phospholipids (OxPL), and its role adversely affects vascular inflammation, atherosclerotic lesions, endothelial function and thrombogenicity, which pathophysiologically leads to cardiovascular (CV) events. Despite this crucial role of Lp(a), its measurement lacks a globally unified method, and, between different laboratories, results need standardization. Standard antilipidemic therapies, such as statins, fibrates and ezetimibe, have a mediocre effect on Lp(a) levels, although it is not yet clear whether such treatments can affect CV events and prognosis. This narrative review aims to summarize knowledge regarding the mechanisms mediating the effect of Lp(a) on inflammation, atherosclerosis and thrombosis and discuss current diagnostic and therapeutic potentials.

The impact of SGLT2 inhibition on imaging markers of cardiac function: A systematic review and meta-analysis.

OBJECTIVES: The use of sodium-glucose cotransporter-2 inhibitors (SGLT2-Is) has resulted in significant benefits in patients with heart failure irrespective of left ventricular ejection fraction (LVEF) and the presence of diabetes mellitus. The aim of this systematic review and meta-analysis was to assess the impact of SGLT2-Is on cardiac function indices. METHODS: We conducted a systematic literature search for studies assessing the changes in LVEF, global longitudinal strain (GLS), left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), left ventricular mass index (LVMi), left atrial volume index (LAVi), and E/e' following the initiation of an SGLT2-I. RESULTS: A total of 32 studies with 2351 patients were included. SGLT2 inhibition resulted in a significant improvement of LVEF [MD 1.97 (95%CI 0.92, 3.02), p < .01, I2:84%] in patients with heart failure, an increase in GLS [MD 1.17 (95% CI 0.25, 2.10), p < .01], a decrease in LVESV [MD: -3.60 (95% CI -7.02, -0.18), p = .04, I2:9%] while the effect was neutral concerning LVEDV [MD: -3.10 (95% CI -6.76, 0.56), p = .40, I2:4%]. LVMi [MD: -3.99 (95% CI -7.16 to -0.82), p = .01, I2:65%], LAVi [MD: -1.77 (95% CI -2.97, -0.57), p < .01, I2:0%], and E/e' [MD: -1.39 (95% CI -2.04, -0.73), p < .01, I2:55%] were significantly reduced. CONCLUSIONS: In this systematic review and meta-analysis, the use of SGLT2 inhibitors was associated with an improvement in markers of cardiac function, confirming the importance of SGLT2 inhibition towards the reversal of cardiac remodeling.

The association of diabetes mellitus with carotid atherosclerosis and arterial stiffness in the Corinthia study.

BACKGROUND AND AIMS: Evaluation of arterial stiffness and carotid atherosclerotic burden can provide important prognostic information regarding the risk of future cardiovascular events. The aim of this study was to assess these vascular properties in patients with diabetes mellitus (DM). METHODS AND RESULTS: In the context of the observational "Corinthia" study, we analyzed 1757 participants with determined DM status. Carotid ultrasonography was performed to evaluate intima-media thickness (cIMT) and carotid plaque burden. Arterial stiffness was estimated via assessment of carotid-to-femoral pulse wave velocity (cfPWV). Individuals with DM had increased mean cIMT, maximum cIMT, carotid plaque burden, and cfPWV compared to those without DM. After multivariable regression analysis, the presence of DM was still associated with significantly increased mean cIMT (by 0.074 mm, p = .004), maximum cIMT (by 0.134 mm, p = .007), cfPWV (by 0.929 m/s, p < .001), and a higher prevalence of carotid plaques (odds ratio 1.52, 95% confidence intervals 1.11, 2.10, p = .01). In a propensity score-matched cohort, mean cIMT, maximum cIMT, and carotid plaque burden were significantly higher in individuals with DM. Analysis according to territory of cIMT measurement displayed substantial differences in left (DM: 1.32 ± 0.78 mm vs. no DM: 1.20 ± 0.66 mm, p = .04) and right carotid bulbs (DM: 1.33 ± 0.82 mm vs. no DM: 1.18 ± 0.69 mm, p = .02) with respect to DM status while non-significant variations were observed in left (DM: 0.98 ± 0.49 mm vs. no DM: 0.91 ± 0.35 mm, p = .06) and right common carotid artery (DM: 0.95 ± 0.50 mm vs. no DM: 0.92 ± 0.40 mm, p = .36). CONCLUSIONS: Diabetes mellitus is associated with increased cfPWV and cIMT, with more pronounced lesions in the carotid bulb.

A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST).

AIMS: Coronary artery disease is frequently diagnosed following evaluation of stable chest pain with anatomical or functional testing. A more granular understanding of patient phenotypes that benefit from either strategy may enable personalized testing. METHODS AND RESULTS: Using participant-level data from 9572 patients undergoing anatomical (n = 4734) vs. functional (n = 4838) testing in the PROMISE (PROspective Multicenter Imaging Study for Evaluation of Chest Pain) trial, we created a topological representation of the study population based on 57 pre-randomization variables. Within each patient's 5% topological neighbourhood, Cox regression models provided individual patient-centred hazard ratios for major adverse cardiovascular events and revealed marked heterogeneity across the phenomap [median 1.11 (10th to 90th percentile: 0.52-2.61]), suggestive of distinct phenotypic neighbourhoods favouring anatomical or functional testing. Based on this risk phenomap, we employed an extreme gradient boosting algorithm in 80% of the PROMISE population to predict the personalized benefit of anatomical vs. functional testing using 12 model-derived, routinely collected variables and created a decision support tool named ASSIST (Anatomical vs. Stress teSting decIsion Support Tool). In both the remaining 20% of PROMISE and an external validation set consisting of patients from SCOT-HEART (Scottish COmputed Tomography of the HEART Trial) undergoing anatomical-first vs. functional-first assessment, the testing strategy recommended by ASSIST was associated with a significantly lower incidence of each study's primary endpoint (P = 0.0024 and P = 0.0321 for interaction, respectively), as well as a harmonized endpoint of all-cause mortality or non-fatal myocardial infarction (P = 0.0309 and P < 0.0001 for interaction, respectively). CONCLUSION: We propose a novel phenomapping-derived decision support tool to standardize the selection of anatomical vs. functional testing in the evaluation of stable chest pain, validated in two large and geographically diverse clinical trial populations.

Effects of canagliflozin on human myocardial redox signalling: clinical implications.

AIMS: Recent clinical trials indicate that sodium-glucose cotransporter 2 (SGLT2) inhibitors improve cardiovascular outcomes in heart failure patients, but the underlying mechanisms remain unknown. We explored the direct effects of canagliflozin, an SGLT2 inhibitor with mild SGLT1 inhibitory effects, on myocardial redox signalling in humans. METHODS AND RESULTS: Study 1 included 364 patients undergoing cardiac surgery. Right atrial appendage biopsies were harvested to quantify superoxide (O2.-) sources and the expression of inflammation, fibrosis, and myocardial stretch genes. In Study 2, atrial tissue from 51 patients was used ex vivo to study the direct effects of canagliflozin on NADPH oxidase activity and nitric oxide synthase (NOS) uncoupling. Differentiated H9C2 and primary human cardiomyocytes (hCM) were used to further characterize the underlying mechanisms (Study 3). SGLT1 was abundantly expressed in human atrial tissue and hCM, contrary to SGLT2. Myocardial SGLT1 expression was positively associated with O2.- production and pro-fibrotic, pro-inflammatory, and wall stretch gene expression. Canagliflozin reduced NADPH oxidase activity via AMP kinase (AMPK)/Rac1signalling and improved NOS coupling via increased tetrahydrobiopterin bioavailability ex vivo and in vitro. These were attenuated by knocking down SGLT1 in hCM. Canagliflozin had striking ex vivo transcriptomic effects on myocardial redox signalling, suppressing apoptotic and inflammatory pathways in hCM. CONCLUSIONS: We demonstrate for the first time that canagliflozin suppresses myocardial NADPH oxidase activity and improves NOS coupling via SGLT1/AMPK/Rac1 signalling, leading to global anti-inflammatory and anti-apoptotic effects in the human myocardium. These findings reveal a novel mechanism contributing to the beneficial cardiac effects of canagliflozin.