Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes.

Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered a key pathogenic driver of these diseases, but the underlying immune states and their clinical implications remain poorly understood. Multiomic factor analysis (MOFA) allows unsupervised data exploration across multiple data types, identifying major axes of variation and associating these with underlying molecular processes. We hypothesized that applying MOFA to multiomic data obtained from blood might uncover hidden sources of variance and provide pathophysiological insights linked to clinical needs. Here we compile a longitudinal multiomic dataset of the systemic immune landscape in both ACS and CCS (n = 62 patients in total, n = 15 women and n = 47 men) and validate this in an external cohort (n = 55 patients in total, n = 11 women and n = 44 men). MOFA reveals multicellular immune signatures characterized by distinct monocyte, natural killer and T cell substates and immune-communication pathways that explain a large proportion of inter-patient variance. We also identify specific factors that reflect disease state or associate with treatment outcome in ACS as measured using left ventricular ejection fraction. Hence, this study provides proof-of-concept evidence for the ability of MOFA to uncover multicellular immune programs in cardiovascular disease, opening new directions for mechanistic, biomarker and therapeutic studies.

Determining Hemodynamically Significant Coronary Artery Disease: Patient-Specific Cutoffs in Quantitative Myocardial Blood Flow Using [15O]H2O PET Imaging.

Currently, cutoffs of quantitative [15O]H2O PET to detect fractional flow reserve (FFR)-defined coronary artery disease (CAD) were derived from a single cohort that included patients without prior CAD. However, prior CAD, sex, and age can influence myocardial blood flow (MBF). Therefore, the present study determined the influence of prior CAD, sex, and age on optimal cutoffs of hyperemic MBF (hMBF) and coronary flow reserve (CFR) and evaluated whether cutoff optimization enhanced diagnostic performance of quantitative [15O]H2O PET against an FFR reference standard. Methods: Patients with chronic coronary symptoms underwent [15O]H2O PET and invasive coronary angiography with FFR. Optimal cutoffs for patients with and without prior CAD and subpopulations based on sex and age were determined. Results: This multicenter study included 560 patients. Optimal cutoffs were similar for patients with (n = 186) and without prior CAD (hMBF, 2.3 vs. 2.3 mL·min-1·g-1; CFR, 2.7 vs. 2.6). Females (n = 190) had higher hMBF cutoffs than males (2.8 vs. 2.3 mL·min-1·g-1), whereas CFRs were comparable (2.6 vs. 2.7). However, female sex-specific hMBF cutoff implementation decreased diagnostic accuracy as compared with the cutoff of 2.3 mL·min-1·g-1 (72% vs. 82%, P < 0.001). Patients aged more than 70 y (n = 79) had lower hMBF (1.7 mL·min-1·g-1) and CFR (2.3) cutoffs than did patients aged 50 y or less, 51-60 y, and 61-70 y (hMBF, 2.3-2.4 mL·min-1·g-1; CFR, 2.7). Age-specific cutoffs in patients aged more than 70 y yielded comparable accuracy to the previously established cutoffs (hMBF, 72% vs. 76%, P = 0.664; CFR, 80% vs. 75%, P = 0.289). Conclusion: Patients with and without prior CAD had similar [15O]H2O PET cutoffs for detecting FFR-defined significant CAD. Stratifying patients according to sex and age led to different optimal cutoffs; however, these values did not translate into an increased overall accuracy as compared with previously established thresholds for MBF.

ECPELLA as a bridge-to-decision in refractory cardiogenic shock: a single-centre experience.

BACKGROUND: In refractory cardiogenic shock, temporary mechanical support (tMCS) may be crucial for maintaining tissue perfusion and oxygen delivery. tMCS can serve as a bridge-to-decision to assess eligibility for left ventricular assist device (LVAD) implantation or heart transplantation, or as a bridge-to-recovery. ECPELLA is a novel tMCS configuration combining venoarterial extracorporeal membrane oxygenation with Impella. The present study presents the clinical parameters, outcomes, and complications of patients supported with ECPELLA. METHODS: All patients supported with ECPELLA at University Medical Centre Utrecht between December 2020 and August 2023 were included. The primary outcome was 30-day mortality, and secondary outcomes were LVAD implantation/heart transplantation and safety outcomes. RESULTS: Twenty patients with an average age of 51 years, and of whom 70% were males, were included. Causes of cardiogenic shock were acute heart failure (due to acute coronary syndrome, myocarditis, or after cardiac surgery) or chronic heart failure, respectively 70 and 30% of cases. The median duration of ECPELLA support was 164 h (interquartile range 98-210). In 50% of cases, a permanent LVAD was implanted. Cardiac recovery within 30 days was seen in 30% of cases and 30-day mortality rate was 20%. ECPELLA support was associated with major bleeding (40%), haemolysis (25%), vascular complications (30%), kidney failure requiring replacement therapy (50%), and Impella failure requiring extraction (15%). CONCLUSION: ECPELLA can be successfully used as a bridge to LVAD implantation or as a bridge-to-recovery in patients with refractory cardiogenic shock. Despite a significant number of complications, 30-day mortality was lower than observed in previous cohorts.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

BACKGROUND: The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. METHODS: For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). RESULTS: Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. CONCLUSIONS: Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Incidence and predictors of heart failure with reduced and preserved ejection fraction after ST-elevation myocardial infarction in the contemporary era of early percutaneous coronary intervention.

AIMS: The development and incidence of de-novo heart failure after ST-elevation myocardial infarction (STEMI) in the contemporary era of rapid reperfusion are largely unknown. We aimed to establish the incidence of post-STEMI heart failure, stratified by left ventricular ejection fraction (LVEF) and to find predictors for its occurrence. Furthermore, we investigated the course of left ventricular systolic and diastolic function after STEMI. METHODS AND RESULTS: A total of 1172 all-comer STEMI patients from the CardioLines Biobank were included. Patients were predominantly male (74.5%) and 64 ± 12 years of age. During a median follow-up of 3.7 years (2.0, 5.5) we found a total incidence of post-STEMI heart failure of 10.9%, of which 52.1% heart failure with reduced ejection fraction (HFrEF), 29.4% heart failure with mildly reduced ejection fraction and 18.5% heart failure with preserved ejection fraction (HFpEF). Independent predictors for the development of HFrEF were male sex (ß = 0.97, p = 0.009), lung crepitations (ß = 1.09, p = 0.001), potassium level (mmol/L, ß = 0.43, p = 0.012), neutrophil count (109/L, ß = 0.09, p = 0.001) and a reduced LVEF (ß = 1.91, p < 0.001) at baseline. Independent predictors for the development of HFpEF were female sex (ß = 0.99, p = 0.029), pre-existing kidney failure (ß = 1.95, p = 0.003) and greater left atrial volume index (ß = 0.04, p = 0.033) at baseline. Follow-up echocardiography (median follow-up 20 months) showed an improvement in LVEF (p < 0.001), whereas changes in diastolic function parameters showed both improvement and deterioration. CONCLUSION: In the current era of early STEMI reperfusion, still one in 10 patients develops heart failure, with approximately half of the patients with a reduced and half with a mildly reduced or normal LVEF. Predictors for the development of HFrEF were different from HFpEF.

Prognostic significance of echocardiographic deformation imaging in adult congenital heart disease.

BACKGROUND: Due to medical and surgical advancements, the population of adult patients with congenital heart disease (ACHD) is growing. Despite successful therapy, ACHD patients face structural sequalae, placing them at increased risk for heart failure and arrhythmias. Left and right ventricular function are important predictors for adverse clinical outcomes. In acquired heart disease it has been shown that echocardiographic deformation imaging is of superior prognostic value as compared to conventional parameters as ejection fraction. However, in adult congenital heart disease, the clinical significance of deformation imaging has not been systematically assessed and remains unclear. METHODS: According to the Preferred Reporting Items for Systematic Reviews checklist, this systematic review included studies that reported on the prognostic value of echocardiographic left and/or right ventricular strain by 2-dimensional speckle tracking for hard clinical end-points (death, heart failure hospitalization, arrhythmias) in the most frequent forms of adult congenital heart disease. RESULTS: In total, 19 contemporary studies were included. Current data shows that left ventricular and right ventricular global longitudinal strain (GLS) predict heart failure, transplantation, ventricular arrhythmias and mortality in patients with Ebstein's disease and tetralogy of Fallot, and that GLS of the systemic right ventricle predicts heart failure and mortality in patients post atrial switch operation or with a congenitally corrected transposition of the great arteries. CONCLUSIONS: Deformation imaging can potentially impact the clinical decision making in ACHD patients. Further studies are needed to establish disease-specific reference strain values and ranges of impaired strain that would indicate the need for medical or structural intervention.

Proteomics couples electrical remodelling to inflammation in a murine model of heart failure with sinus node dysfunction.

AIMS: In patients with heart failure (HF), concomitant sinus node dysfunction (SND) is an important predictor of mortality, yet its molecular underpinnings are poorly understood. Using proteomics, this study aimed to dissect the protein and phosphorylation remodelling within the sinus node in an animal model of HF with concurrent SND. METHODS AND RESULTS: We acquired deep sinus node proteomes and phosphoproteomes in mice with heart failure and SND and report extensive remodelling. Intersecting the measured (phospho)proteome changes with human genomics pharmacovigilance data, highlighted downregulated proteins involved in electrical activity such as the pacemaker ion channel, Hcn4. We confirmed the importance of ion channel downregulation for sinus node physiology using computer modelling. Guided by the proteomics data, we hypothesized that an inflammatory response may drive the electrophysiological remodeling underlying SND in heart failure. In support of this, experimentally induced inflammation downregulated Hcn4 and slowed pacemaking in the isolated sinus node. From the proteomics data we identified proinflammatory cytokine-like protein galectin-3 as a potential target to mitigate the effect. Indeed, in vivo suppression of galectin-3 in the animal model of heart failure prevented SND. CONCLUSION: Collectively, we outline the protein and phosphorylation remodeling of SND in heart failure, we highlight a role for inflammation in electrophysiological remodelling of the sinus node, and we present galectin-3 signalling as a target to ameliorate SND in heart failure.

DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.

BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging. METHODS: 730 consecutive patients [mean age: 63 ± 10 years; 616 men] who underwent stress CMR for known or suspected coronary artery disease were randomly divided into derivation (n = 365) and validation (n = 365) cohorts. MACE was defined as non-fatal myocardial infarction and cardiac deaths. A deep learning algorithm was developed and trained to quantify EAT volume from CMR. EAT volume was adjusted for height (EAT volume index). A composite CMR-based risk score by Cox analysis of the risk of MACE was created. RESULTS: In the derivation cohort, 32 patients (8.7 %) developed MACE during a follow-up of 2103 days. Left ventricular ejection fraction (LVEF) < 35 % (HR 4.407 [95 % CI 1.903-10.202]; p<0.001), stress perfusion defect (HR 3.550 [95 % CI 1.765-7.138]; p<0.001), late gadolinium enhancement (LGE) (HR 4.428 [95%CI 1.822-10.759]; p = 0.001) and EAT volume index (HR 1.082 [95 % CI 1.045-1.120]; p<0.001) were independent predictors of MACE. In a multivariate Cox regression analysis, adding EAT volume index to a composite risk score including LVEF, stress perfusion defect and LGE provided additional value in MACE prediction, with a net reclassification improvement of 0.683 (95%CI, 0.336-1.03; p<0.001). The combined evaluation of risk score and EAT volume index showed a higher Harrel C statistic as compared to risk score (0.85 vs. 0.76; p<0.001) and EAT volume index alone (0.85 vs.0.74; p<0.001). These findings were confirmed in the validation cohort. CONCLUSIONS: In patients with clinically indicated stress CMR, fully automated EAT volume measured by deep learning can provide additional prognostic information on top of standard clinical and imaging parameters.

ANOCA patients with and without coronary vasomotor dysfunction present with limited electrocardiographic remodeling.

Background: Coronary vasomotor dysfunction (CVDys) comprises coronary vasospasm (CVS) and/or coronary microvascular dysfunction (CMD) and is highly prevalent in patients with angina and non-obstructive coronary artery disease (ANOCA). Invasive coronary function testing (CFT) to diagnose CVDys is becoming more common, enabling pathophysiologic research of CVDys. This study aims to explore the electrophysiological characteristics of ANOCA patients with CVDys. Methods: We collected pre-procedural 12-lead electrocardiograms of ANOCA patients with CVS (n = 35), CMD (n = 24), CVS/CMD (n = 26) and patients without CVDys (CFT-, n = 23) who participated in the NL-CFT registry and underwent CFT. Heart axis and conduction times were compared between patients with CVS, CMD or CVS/CMD and patients without CVDys. Results: Heart axis, heart rate, PQ interval and QRS duration were comparable between the groups. A small prolongation of the QT-interval corrected with Bazett (QTcB) and Fridericia (QTcF) was observed in patients with CVDys compared to patients without CVDys (CVS vs CFT-: QTcB = 422 ± 18 vs 414 ± 18 ms (p = 0.14), QTcF = 410 ± 14 vs 406 ± 12 ms (p = 0.21); CMD vs CFT-: QTcB = 426 ± 17 vs 414 ± 18 ms (p = 0.03), QTcF = 413 ± 11 vs 406 ± 12 ms (p = 0.04); CVS/CMD vs CFT-: QTcB = 424 ± 17 vs 414 ± 18 ms (p = 0.05), QTcF = 414 ± 14 vs 406 ± 12 ms (p = 0.04)). Conclusions: Pre-procedural 12-lead electrocardiograms were comparable between patients with and without CVDys undergoing CFT except for a slightly longer QTc interval in patients with CVDys compared to patients without CVDys, suggesting limited cardiac remodeling in patients with CVDys.

Automatic triage of twelve-lead electrocardiograms using deep convolutional neural networks: a first implementation study.

Aims: Expert knowledge to correctly interpret electrocardiograms (ECGs) is not always readily available. An artificial intelligence (AI)-based triage algorithm (DELTAnet), able to support physicians in ECG prioritization, could help reduce current logistic burden of overreading ECGs and improve time to treatment for acute and life-threatening disorders. However, the effect of clinical implementation of such AI algorithms is rarely investigated. Methods and results: Adult patients at non-cardiology departments who underwent ECG testing as a part of routine clinical care were included in this prospective cohort study. DELTAnet was used to classify 12-lead ECGs into one of the following triage classes: normal, abnormal not acute, subacute, and acute. Performance was compared with triage classes based on the final clinical diagnosis. Moreover, the associations between predicted classes and clinical outcomes were investigated. A total of 1061 patients and ECGs were included. Performance was good with a mean concordance statistic of 0.96 (95% confidence interval 0.95-0.97) when comparing DELTAnet with the clinical triage classes. Moreover, zero ECGs that required a change in policy or referral to the cardiologist were missed and there was a limited number of cases predicted as acute that did not require follow-up (2.6%). Conclusion: This study is the first to prospectively investigate the impact of clinical implementation of an ECG-based AI triage algorithm. It shows that DELTAnet is efficacious and safe to be used in clinical practice for triage of 12-lead ECGs in non-cardiology hospital departments.

Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long-Term Mortality Risk.

BACKGROUND: We aimed to identify patients with subphenotypes of postacute coronary syndrome (ACS) using repeated measurements of high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, and growth differentiation factor 15 in the year after the index admission, and to investigate their association with long-term mortality risk. METHODS AND RESULTS: BIOMArCS (BIOMarker Study to Identify the Acute Risk of a Coronary Syndrome) was an observational study of patients with ACS, who underwent high-frequency blood sampling for 1 year. Biomarkers were measured in a median of 16 repeated samples per individual. Cluster analysis was performed to identify biomarker-based subphenotypes in 723 patients without a repeat ACS in the first year. Patients with a repeat ACS (N=36) were considered a separate cluster. Differences in all-cause death were evaluated using accelerated failure time models (median follow-up, 9.1 years; 141 deaths). Three biomarker-based clusters were identified: cluster 1 showed low and stable biomarker concentrations, cluster 2 had elevated concentrations that subsequently decreased, and cluster 3 showed persistently elevated concentrations. The temporal biomarker patterns of patients in cluster 3 were similar to those with a repeat ACS during the first year. Clusters 1 and 2 had a similar and favorable long-term mortality risk. Cluster 3 had the highest mortality risk. The adjusted survival time ratio was 0.64 (95% CI, 0.44-0.93; P=0.018) compared with cluster 1, and 0.71 (95% CI, 0.39-1.32; P=0.281) compared with patients with a repeat ACS. CONCLUSIONS: Patients with subphenotypes of post-ACS with different all-cause mortality risks during long-term follow-up can be identified on the basis of repeatedly measured cardiovascular biomarkers. Patients with persistently elevated biomarkers have the worst outcomes, regardless of whether they experienced a repeat ACS in the first year.

Prehospital risk assessment and direct transfer to a percutaneous coronary intervention centre in suspected acute coronary syndrome.

OBJECTIVE: Prehospital risk stratification and triage are currently not performed in patients suspected of non-ST-segment elevation acute coronary syndrome (NSTE-ACS). This may lead to prolonged time to revascularisation, increased duration of hospital admission and higher healthcare costs. The preHEART score (prehospital history, ECG, age, risk factors and point-of-care troponin score) can be used by emergency medical services (EMS) personnel for prehospital risk stratification and triage decisions in patients with NSTE-ACS. The aim of the current study was to evaluate the effect of prehospital risk stratification and direct transfer to a percutaneous coronary intervention (PCI) centre, based on the preHEART score, on time to final invasive diagnostics or culprit revascularisation. METHODS: Prospective, multicentre, two-cohort study in patients with suspected NSTE-ACS. The first cohort is observational (standard care), while the second (interventional) cohort includes patients who are stratified for direct transfer to either a PCI or a non-PCI centre based on their preHEART score. Risk stratification and triage are performed by EMS personnel. The primary endpoint of the study is time from first medical contact until final invasive diagnostics or revascularisation. Secondary endpoints are time from first medical contact until intracoronary angiography (ICA), duration of hospital admission, number of invasive diagnostics, number of inter-hospital transfers and major adverse cardiac events at 7 and 30 days. RESULTS: A total of 1069 patients were included. In the interventional cohort (n=577), time between final invasive diagnostics or revascularisation (42 (17-101) hours vs 20 (5-44) hours, p<0.001) and length of hospital admission (3 (2-5) days vs 2 (1-4) days, p=0.007) were shorter than in the observational cohort (n=492). In patients with NSTE-ACS in need for ICA or revascularisation, healthcare costs were reduced in the interventional cohort (€5599 (2978-9625) vs €4899 (2278-5947), p=0.02). CONCLUSION: Prehospital risk stratification and direct transfer to a PCI centre, based on the preHEART score, reduces time from first medical contact to final invasive diagnostics and revascularisation, reduces duration of hospital admission and decreases healthcare costs in patients with NSTE-ACS in need for ICA or revascularisation. TRIAL REGISTRATION: NCT05243485.

Cardiac magnetic resonance for early atrial lesion visualization post atrial fibrillation radiofrequency catheter ablation.

BACKGROUND: Incomplete atrial lesions resulting in pulmonary vein-left atrium reconnection after pulmonary vein antrum isolation (PVAI), are related to atrial fibrillation (AF) recurrence. Unfortunately, during the PVAI procedure, fluoroscopy and electroanatomic mapping cannot accurately determine the location and size of the ablation lesions in the atrial wall and this can result in incomplete PVAI lesions (PVAI-L) after radiofrequency catheter ablation (RFCA). AIM: We seek to evaluate whether cardiac magnetic resonance (CMR), immediately after RFCA of AF, can identify PVAI-L by characterizing the left atrial tissue. METHODS: Ten patients (63.1 ± 5.7 years old, 80% male) receiving a RFCA for paroxysmal AF underwent a CMR before (<1 week) and after (<1 h) the PVAI. Two-dimensional dark-blood T2-weighted short tau inversion recovery (DB-STIR), Three-dimensional inversion-recovery prepared long inversion time (3D-TWILITE) and three-dimensional late gadolinium enhancement (3D-LGE) images were performed to visualize PVAI-L. RESULTS: The PVAI-L was visible in 10 patients (100%) using 3D-TWILITE and 3D-LGE. Conversely, On DB-STIR, the ablation core of the PAVI-L could not be identified because of a diffuse high signal of the atrial wall post-PVAI. Microvascular obstruction was identified in 7 (70%) patients using 3D-LGE. CONCLUSION: CMR can visualize PVAI-L immediately after the RFCA of AF even without the use of contrast agents. Future studies are needed to understand if the use of CMR for PVAI-L detection after RFCA can improve the results of ablation procedures.