Cardiovascular Research Foundation

Purpose Dual antiplatelet therapy (DAPT) is the cornerstone for patients with coronary atherosclerotic heart disease (CHD) undergoing percutaneous coronary intervention (PCI) while increasing the risk of bleeding, particularly when combined with gastrointestinal disease (GID). Rivaroxaban 10 mg once daily is widely used in Asia. This study compared the effects of low-dose rivaroxaban (10 mg daily) plus clopidogrel vs. DAPT in CHD patients with GID undergoing PCI. Methods In this prospective, single-center, randomized controlled trial, eligible CHD patients with GID undergoing PCI were randomized (1:1) to either the dual pathway inhibition (DPI) group (rivaroxaban 10 mg plus clopidogrel 75 mg daily) or the DAPT group (aspirin 100 mg plus clopidogrel 75 mg daily). The primary outcome was Bleeding Academic Research Consortium (BARC) type 2–5 bleeding. The secondary outcome was major adverse cardiovascular or cerebrovascular events (MACCE), which included cardiac death, nonfatal myocardial infarction, ischemia-driven target vessel revascularization, all-cause death, stent thrombosis, and stroke during the 6-month follow-up. Results A total of 1042 patients were enrolled and analyzed (DPI, 522; DAPT, 520). Low-dose rivaroxaban (10 mg daily) plus clopidogrel was non-inferior to DAPT in BARC type 2–5 bleeding [8 (1.5%) vs. 6 (1.2%), absolute risk difference 0.38%, 95% confidence interval (CI) (− 1.02–1.78), p < 0.0001 for non-inferiority]. Abdominal pain was significantly lower in the DPI group (p = 0.009). Other abdominal discomforts, gastrointestinal bleeding, or MACCE were similar. Conclusions In CHD patients with GID undergoing PCI, low-dose rivaroxaban (10 mg daily) plus clopidogrel was non-inferior to DAPT. Trial registration Chinese Clinical Trial Registry ChiCTR2100044319. Registered on March 16, 2021.

Astrocytes are important glia cell type in the central nervous system. These cells can undergo transformation to a reactive state upon injury such as focal ischemic stroke (FIS). Reactive astrocytes are distinct from normal or homeostatic astrocytes in morphology, protein profiles and metabolic functions. Glial cell-derived neurotrophic factor (GDNF) was discovered as a potent survival neurotrophic factor for multiple subtypes of neurons and can be released from reactive astrocytes. In our previous study, we found that GDNF expression was upregulated in reactive astrocytes following ischemic stroke. Specific knock out of GDNF in reactive astrocytes exacerbated brain damage and motor deficits after ischemic stroke. Here, using in vitro and in vivo ischemia models, we investigated the effects of GDNF overexpression in astrocytes on neuronal survival and brain recovery after ischemia. We observed that astrocyte specific GDNF overexpression by viral transduction could decrease brain infarction and promote motor function recovery after photothrombosis (PT)-induced FIS. In addition, GDNF overexpression in astrocytes could increase the proliferation of reactive astrocytes and reduce oxidative stress after PT. Using the oxygen-glucose deprivation (OGD) model of cultured astrocytes, we confirmed that this ischemic insult could upregulate GDNF expression and increase its release to extracellular space. Transfection of GDNF DNA plasmid could further increase GDNF release after OGD. To further study the effects of reactive astrocytes-derived extracellular GDNF on neuronal survival after ischemia, cultured neurons subjected to OGD were exposed to astrocyte conditioned medium (ACM). The ACM collected from OGD subjected astrocyte culture could significantly reduce neuronal death, while neutralizing antibodies against GDNF and its receptors including GFRα1, RET and p-RET could suppress this beneficial effect. We also found that reactive astrocytes-derived GDNF could trigger the activation of RET receptors in cultured neurons and suppress neuronal mitochondrial fission and caspase-dependent cell apoptosis after OGD. Overall, our results indicate that reactive astrocytes-derived GDNF could play an important role in neuronal survival and functional recovery and underscore the non-cell autonomy underlying astrocyte-neuron interactions in brain repair after ischemic stroke.

Background The impact of deep vein thrombosis (DVT) location on acute pulmonary embolism (PE) prognosis remains uncertain. Methods Using the Registro Informatizado de Enfermedad TromboEmbólica registry, we assessed 30-day and 90-day outcomes in patients with acute symptomatic PE and concomitant upper-extremity (UEDVT) versus lower-extremity DVT (LEDVT). Cox regression was employed for analysis, and standardised differences (SRD) were used for reporting clinical characteristics to minimise type I error overinflation. The primary outcome was 30-day all-cause mortality, with secondary outcomes including 90-day mortality, fatal PE, venous thromboembolism (VTE) recurrences, and major bleeding. Results Among 21 617 patients with PE (March 2001–April 2023), 508 had UEDVT, and 21 109 had LEDVT. Patients with UEDVT were younger (SRD: 0.231), more often had cancer (SRD: 0.395) or non-central PEs (SRD: 0.445), but less frequently had raised troponin levels (SRD: 0.376) or right ventricle dysfunction (SRD: 0.249). Thirty-day mortality was higher in UEDVT compared with LEDVT (7.3% vs 3.5%; p<0.001), with similar trends at 90 days (14% vs 6.0%) and in subgroup analysis in patients without cancer. Increased rates of PE-related mortality, VTE recurrences and major bleeding were noted in patients with UEDVT at both 30 and 90 days. UEDVT was associated with a higher risk for 30-day (adjusted HR (aHR): 1.49; 95% CI 1.04 to 2.13) and 90-day (aHR: 1.52; 95% CI 1.15 to 2.00) all-cause mortality on multilevel multivariable analysis. Conclusions Patients with concomitant UEDVT experienced worse short-term outcomes, including higher mortality, despite fewer clinical signs of PE severity compared with LEDVT. These findings suggest that unrecognised patient characteristics might influence prognosis, warranting further research.

Background Although there have been significant advancements in reducing the burden of cardiovascular disease (CVD) by modifying traditional CVD risk factors, substantial risks persist, particularly among male subjects who exhibit heightened susceptibility to atherosclerosis. In this context, we aim to study the link between oral microbiome and carotid intima media thickness (cIMT). Methods The Northern Finland Birth Cohort of 1966 (mean age 46 years, n = 869) underwent an extensive health examination, including the measurement of cIMT. The oral microbiome was also investigated using high-throughput 16S rRNA gene sequencing. Results Here we show that oral microbiome diversity links with atherosclerosis risk factors, namely smoking, glycemic balance, low-grade inflammation, and periodontitis. After excluding CVD-influencing factors (n = 339), oral microbiome genera (p = 0.030), Shannon index (p = 0.001), β-diversity Bray–Curtis (p < 0.001), and Jaccard (p < 0.001) are associated with cIMT in males, but not in the female sub-cohort. Furthermore, in the male sub-cohort (n = 131), the genera Prevotella, Megasphaera, and Veillonella associate positively with cIMT, while Absconditabacteria, Capnocytophaga, Gemella, Fusobacterium, Neisseria, Aggregatibacter, Tannerella, Treponema, Cardiobacterium, and Bacteroidales associate inversely with cIMT. We examine the involvement of serum total immunoglobulins and antibodies to phosphorylcholine (PCho) and malondialdehyde-acetaldehyde LDL (MAA-LDL) with cIMT. Subjects with high cIMT have lower levels of serum total IgA (p = 0.009), IgA to PCho (p = 0.017), and IgG to PCho (p = 0.008). The relative abundance of cIMT-associated genera correlates with serum IgA antibodies. Conclusions This middle-aged birth cohort study shows that male oral microbiome diversity links to cIMT, suggesting a potential sex-specific interaction between the oral microbiome and atherosclerosis.

Objective We developed a risk stratification model to predict serious adverse hospitalization events (mortality, cardiac shock, cardiac arrest) (SAHE) after acute coronary syndrome (ACS) based on machine-learning models and logistic regression model. Methods This cohort study is based on the CCC-ACS project. The primary efficacy outcomes were SAHE. Clinical prediction models were established based on five machine-learning (XGBoost, RF, MLP, KNN, and stacking model) and logistic regression models. Results Among the 112 363 patients in the study, age (55–65 years: OR: 1.392; 95%CI: 1.212–1.600; 65–75 years: OR: 1.878; 95%CI: 1.647–2.144; ≥75 year: OR: 2.976; 95%CI: 2.615–3.393), history of diabetes mellitus (OR: 1.188; 95%CI: 1.083–1.302), history of renal failure (OR: 1.645; 95%CI: 1.311–2.044), heart rate (60–100 beats/min: OR: 0.468; 95%CI: 0.409–0.536; ≥100 beats/min: OR: 0.540; 95%CI: 0.454–0.643), shock index (0.4–0.8: OR: 1.796; 95%CI: 1.440–2.264; ≥0.8: OR: 5.883; 95%CI: 4.619–7.561), KILLIP (II: OR: 1.171; 95%CI: 1.048–1.306; III: OR: 1.696; 95%CI: 1.469–1.952; IV: OR: 7.811; 95%CI: 7.023–8.684), and cardiac arrest at admission (OR: 12.507; 95%CI: 10.757–14.530) were independent predictors of severe adverse hospitalization events for ACS patients. In several machine-learning models, RF (AUC: 0.817; 95%CI: 0.808–0.826) and XGBoost (AUC: 0.816; 95%CI: 0.807–0.825) also showed good discrimination in the training set, which ranked the first two positions. They also presented good accuracy and the best clinical benefits in the decision curve analysis. In addition, logistic regression was able to discriminate the SAHE (AUC: 0.816; 95%CI: 0.807–0.825) and performed the best prediction accuracy (0.822; 95%CI: 0.822–0.822) compared to several machine-learning models. Model calibration and decision curve analysis showed these prediction models have similar predictive performance. Based on these findings, we developed two CCC-ACS In-hospital Major Adverse Events Risk Scores and its online calculator. One is based on machine-learning model (https://ccc-acs-sae-3-xcnjsvoccusjwkfhfthh44.streamlit.app/), and another is based on logistic regression model (https://ccc-acs-sae-logistic-9te57ylnq3kazkeuyc7dub.streamlit.app/), offering a validated tool to predict survival for patients with ACS during hospitalization. Conclusions Machine-learning-based approaches for identifying predictors of SAHE after an ACS were feasible and practical. Based on this, we developed two online risk prediction websites for clinicians’ decision-making. The CCC-ACS-MSAE score showed accurate discriminative capabilities for predicting severe adverse hospitalization events and might help guide clinical decision-making. Key messages: Three research questions and three bullet points What is already known on this topic? Observational studies have identified risk factors for in-hospital death in patients with acute coronary syndromes (ACS). However, the real-world results of a large sample in China still need to be further explored. What does this study add? Machine-learning-based approaches for identifying predictors of SAHE after an ACS were feasible and practical. Based on these findings, we developed two CCC-ACS In-hospital Major Adverse Events Risk Scores and its online calculator. One is based on machine-learning model (https://ccc-acs-sae-3-xcnjsvoccusjwkfhfthh44.streamlit.app/), and another is based on logistic regression model (https://ccc-acs-sae-logistic-9te57ylnq3kazkeuyc7dub.streamlit.app/), offering a validated tool to predict survival for patients with ACS during hospitalization. How this study might affect research, practice, or policy? Early identification of high-risk ACS patients will help reduce in-hospital deaths and improve the prognosis of ACS patients.

Background Calcific aortic valve disease (CAVD), and ensuing severe aortic stenosis (AS), is the foremost valvular disorder of aging, yet preventive therapies are lacking. A better understanding of the molecular underpinnings of aortic valve calcification (AVC) is necessary to develop pharmacologic interventions. Methods and Results We undertook large‐scale plasma proteomics in a cohort study of adults ≥65 years old, the CHS (Cardiovascular Health Study), to identify individual proteins associated with echocardiographic AVC and incident moderate/severe AS. Proteomics measurements were performed with the aptamer‐based SomaLogic platform of ~5000 proteins. Significant proteins were validated in a second cohort, the AGES‐RS (Age, Gene/Environment Susceptibility‐Reykjavik Study), which assessed AVC and AS by computed tomography. The potential causal associations of replicated proteins were tested in 2‐sample Mendelian randomization using identified cis protein quantitative trait loci in consortia having computed tomography‐quantified AVC or AS as outcomes. Six proteins showed Bonferroni‐corrected significant relationships with AVC in CHS. Three of these, CXCL‐12 (C‐X‐C chemokine ligand 12), KLKB1 (kallikrein), and leptin, replicated in AGES‐RS, of which the former 2 are novel. Only 1 protein, CXCL6, which showed a near‐significant association with AS in the replication cohort, was significantly (positively) associated with incident AS. Mendelian randomization analysis was conducted for KLKB1, CXCL12, and CXCL6, which supported a causal relationship for higher KLKB1 with lower AVC (beta=−0.25, P =0.009). Conclusions This study of older adults newly identified and largely replicated associations of 3 circulating proteins with calcific aortic valve disease, of which the relationship of plasma KLKB1 may have a causal basis. Additional investigation is necessary to determine if KLKB1 could be harnessed for calcific aortic valve disease therapeutics.

Background Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses machine learning (ML) for automatic segmentation, promises to simplify lesion assessment. This study evaluated the agreement in stent size selection between ALA, an independent core laboratory (CL), and an expert interventional cardiologist (IC) for complex lesions. Aims The primary endpoint was the agreement in stent size selection, within 0.25 mm, of AVVIGO ALA automatic segmentation of Class I lesions against the gold‐standard measurement by an independent CL analysis and against an expert IC, (H. H.). The secondary endpoint was to assess the relative differences between AVVIGO ALA and CL, AVVIGO ALA and IC, and CL and IC, in vessel and lumen areas. Methods Patients with complex coronary lesions, including left main bifurcation, long, and severely calcified lesions, were retrospectively analyzed using IVUS with ALA. Stent size selection and area measurements by ALA were compared against a CL and IC using established sizing methods. Results In 48 patients, ALA demonstrated high agreement with CL (92%–100%) and IC (91%–98.5%) in stent size selection across lesion subtypes using recommended sizing methods. Lumen‐based sizing achieved higher agreement than vessel‐based sizing, particularly in calcified lesions (100% vs. 87%). The variability in relative difference in measurements between ALA and CL was greater than IC and CL in distal vessel and lesion vessel areas. The relative difference in measurements between ALA and IC was greater in vessel‐based sizing compared to lumen‐based sizing in the distal reference marker. Conclusion AVVIGO ALA demonstrated high agreement in stent size selection compared to a CL and expert IC. ML's ability to automate IVUS analysis may improve operator efficiency, reduce radiation exposure, and enhance the adoption of intravascular imaging in routine practice. It remains to be seen if it will impact of adoption of IVUS to guide complex PCI.

Aims Treatment of patients with cancer presenting with ST-elevation myocardial infarction (STEMI) is complex given the increased risk of both thrombotic and major bleeding complications. Methods and results A nationally linked cohort of STEMI patients between January 2005 and March 2019 was obtained from the UK Myocardial Infarction National Audit Project and the UK National Hospital Episode Statistics Admitted Patient Care registries. The primary outcomes were major bleeding and re-infarction at 1 year following admission with STEMI. Major bleeding was defined as bleeding events that require hospital admission. Re-infarction was defined as acute MI according to the fourth Universal Definition of Myocardial Infarction. A total of 322 776 STEMI-indexed admissions were identified between January 2005 and March 2019. Of those, 7050 (2.2%) patients were diagnosed with active cancer. Cancer patients were older with more cardiovascular comorbidities. Cancer patients received invasive coronary angiography (62.2% vs. 72.7%, P < 0.001) and percutaneous coronary intervention (58.4% vs. 69.5%, P < 0.001) less often compared with patients without cancer and were less likely to be prescribed dual antiplatelet therapy (85% vs. 95.4%, P < 0.001). The incidence of major bleeding (6.5% vs. 3.5%, P < 0.001) and re-infarction (cancer 5.7%, no cancer 5.1%, P = 0.01) was higher in cancer patients at 1 year. After adjustment for differences in baseline covariates, a similar risk of re-infarction (sub-hazard ratios (SHR) 1.10, 95% CI 0.94–1.27) and a 50% increased risk of major bleeding (SHR 1.49, 95% CI 1.30–1.71) were observed in cancer patients. Conclusion Compared with non-cancer patients, cancer patients have a higher risk of major bleeding but not of re-infarction. Mitigating bleeding risk in STEMI patients with cancer is of paramount importance to improve outcomes.

BACKGROUND Cytokinesis is the last step in the eukaryotic cell cycle, which physically separates a mitotic cell into 2 daughter cells. A few days after birth in mouse cardiomyocytes, DNA synthesis occurs without cytokinesis, leading to the majority of cardiomyocytes becoming binucleated instead of generating 2 daughter cells with 1 nucleus each. This results in cell cycle arrest of cardiomyocytes, and the mouse heart is no longer able to regenerate. A longstanding unanswered question is whether binucleation of cardiomyocytes is a result of cytokinesis failure. METHODS To address this, we generated several transgenic mouse models to determine whether forced induction of cardiomyocyte cytokinesis generates mononucleated cardiomyocytes and restores the endogenous regenerative properties of the myocardium. We focused on 2 complementary regulators of cytokinesis: Plk1 (polo-like kinase 1) and Ect2 (epithelial cell-transformation sequence 2). RESULTS We found that cardiomyocyte-specific transgenic overexpression of constitutively active Plk1(T210D) promotes mitosis and cytokinesis in adult hearts, whereas overexpression of Ect2 alone promotes only cytokinesis. Cardiomyocyte-specific overexpression of both Plk1(T210D) and Ect2 concomitantly (double transgenic) prevents binucleation of cardiomyocytes postnatally and results in widespread cardiomyocyte mitosis, cardiac enlargement, contractile failure, and death before 2 weeks of age. Similarly, doxycycline-inducible cardiomyocyte-specific overexpression of both proteins (inducible double transgenic) in the adult heart results in reversible widespread cardiomyocyte mitosis and contractile failure. Transient induction of both genes in adult mice improves left ventricular systolic function after myocardial infarction. CONCLUSIONS These results collectively demonstrate that cytokinesis failure mediates cardiomyocyte multinucleation and cell cycle exit of postnatal cardiomyocytes, but may be a protective mechanism to preserve the contractile function of the myocardium.

BACKGROUND Validly measuring disease-specific health status is critical in patients with severe tricuspid regurgitation (TR) to quantify the benefit of different interventions. The Kansas City Cardiomyopathy Questionnaire (KCCQ) has been used to assess health status in patients with severe TR, but its content validity in this patient population is unknown, including whether additional questions are needed to supplement the KCCQ. METHODS Twenty participants with symptomatic severe TR from 2 midwestern clinical sites were interviewed in 2023 using a semistructured guide. The interview guide addressed symptoms, physical and social functioning, and quality of life concepts of the KCCQ, as well as other potential TR symptoms not represented in the KCCQ. Interview transcripts were analyzed using inductive and deductive coding and content analysis, with additional participants recruited until thematic saturation occurred. RESULTS Mean age of the participants was 80 (41–89), and 75% were female. Shortness of breath and fatigue were reported by virtually all participants (n=20 and n=19, respectively) and had a marked negative impact on their physical and social functioning and quality of life. Lower limb edema was also reported by 10 participants. Although these concepts are captured by the KCCQ, other symptoms were also reported, including appetite loss (n=8) and upper body edema (n=4), but did not seem to markedly affect participants’ function or quality of life. In addition, all participants who experienced these other symptoms reported symptoms that were already captured by the KCCQ. CONCLUSIONS All participants experienced symptoms captured by the KCCQ, and these symptoms had a substantial impact on their physical and social functioning and quality of life. Although some participants reported additional symptoms not assessed by the KCCQ, their incorporation would only marginally improve content validity. Thus, the current KCCQ appears to be appropriate for capturing the disease-specific health status of patients with severe TR.

Background: Previous studies have reported the value of quantitative flow ratio (QFR) to assess the physiological significance of non-culprit lesions (NCLs) in acute myocardial infarction (AMI) patients and of optical coherence tomography (OCT)-defined thin-cap fibroatheroma (TCFA) to identify non-culprit vulnerable plaques. Aims: We sought to systematically compare long-term NCL-related clinical prognosis in an AMI population utilising acute Murray fractal law-based QFR (μQFR) values and OCT-defined TCFA. Methods: Three-vessel OCT imaging and μQFR assessment were conducted in 645 AMI patients, identifying 1,320 intermediate NCLs in non-infarct-related arteries. The primary endpoint was a composite of cardiac death, NCL-related non-fatal myocardial infarction (MI), and NCL-related unplanned coronary revascularisation, with follow-up lasting up to 5 years. Results: The primary endpoint occurred in 59 patients (11.1%). OCT-defined TCFA independently predicted patient-level (adjusted hazard ratio [HR] 3.05, 95% confidence interval [CI]: 1.80-5.19) and NCL-specific primary endpoints (adjusted HR 4.46, 95% CI: 2.33-8.56). The highest event rate of 29.6% was observed in patients with NCLs that were TCFA (+) with μQFR ≤0.80, compared to 16.3% in those that were also TCFA (+) but with μQFR>0.80, 6.0% in those that were TCFA (-) with μQFR ≤0.80, and 6.6% in those that were TCFA (-) with μQFR>0.80 (log-rank p<0.001). TCFA was an independent predictor for the primary endpoint in ST-segment elevation MI (STEMI; adjusted HR 3.27, 95% CI: 1.67-6.41) and non-STEMI (adjusted HR 3.26, 95% CI: 1.24-8.54) patients, whereas μQFR ≤0.80 was not. Conclusions: When assessing NCLs during the index procedure in AMI patients, OCT-defined TCFA serves as the dominant prognostic predictor for long-term clinical outcomes, rather than μQFR-determined physiological significance.