Rebecca Rylance

Aims: Apolipoprotein B (apoB)-containing lipoproteins contribute heterogeneously to atherosclerosis. While apoB particles are major determinants of plaque burden, Lp(a) has been linked to plaque inflammation and instability. We investigated the associations of non-Lp(a) apoB, Lp(a), and their relative balance with coronary plaque burden and vulnerability. Methods and results: Among 854 patients with recent myocardial infarction enrolled in the PROSPECT II near-infrared spectroscopy–intravascular ultrasound (NIRS-IVUS) study, total apoB was converted to nmol/L and non-Lp(a) apoB calculated by subtracting Lp(a) in nmol/L. The non-Lp(a) apoB/Lp(a) ratio was used to characterize the relative predominance of these lipoprotein classes. Higher non-Lp(a) apoB was independently associated with greater plaque burden [plaque percentage volume; β = 0.19, 95% confidence interval (CI) 0.05–0.33; P = 0.009], but not with lipid core burden index. In contrast, lower non-Lp(a) apoB/Lp(a) ratio tertile were associated with higher odds of plaque burden ≥70% [odds ratio (OR) 1.47, 95% CI 1.04–2.07; P = 0.029] and the composite vulnerability endpoint of plaque burden ≥70% and maxLCBI4mm ≥324.7 (OR 1.62, 95% CI 1.12–2.33; P = 0.011). In an exploratory external cohort from the CASABLANCA study, lower ratios identified an Lp(a)- and oxidized phospholipid-enriched phenotype and were associated with higher unadjusted cardiovascular risk. Conclusion: Non-Lp(a) apoB and Lp(a) demonstrate distinct associations with coronary plaque burden and vulnerability. Differentiating Lp(a)-associated from non-Lp(a)-associated apoB particle pools provides complementary information on coronary plaque phenotype, and the non-Lp(a) apoB/Lp(a) ratio summarizes their relative predominance. Clinical Trial Information: PROSPECT II- https://ClinicalTrial.gov Identifier: NCT02171065 CASABLANCA- https://ClinicalTrial.gov Identifier: NCT00842868. One-sentence summary: In patients with recent heart attack, the balance between conventional cholesterol-carrying particles and lipoprotein(a) identifies different types of coronary artery disease phenotypes and may help explain why some plaques are more likely to become dangerous. Key findings: Conventional apoB-containing lipoproteins (primarily LDL-related particles) were associated with greater overall coronary plaque burden, whereas a relative predominance of lipoprotein(a) was associated with plaques that had features linked to a higher risk of future cardiovascular events. A simple ratio comparing non-lipoprotein(a) apoB particles with lipoprotein(a) particles summarized these distinct biological processes and may provide complementary information for future studies evaluating cardiovascular risk and therapies targeting lipoprotein(a).

BACKGROUND: Lipidomics, the comprehensive profiling of circulating lipid species, has emerged as a powerful tool to investigate metabolic alterations underlying coronary atherosclerosis. Understanding the mechanisms driving high-risk vulnerable plaque formation and progression to myocardial infarction remains a key therapeutic priority. This study investigates associations between circulating lipid metabolites and imaging-defined features of vulnerable coronary plaque. METHODS: Following revascularization, patients with myocardial infarction underwent 3-vessel coronary artery imaging with near-infrared spectroscopy and intravascular ultrasound to assess nonflow-limiting plaques for lipid core burden index and plaque burden. Multivariable models evaluated associations between 424 lipid metabolites in plasma, quantified by mass spectrometry, pan-coronary lipid, pan-coronary plaque burden, and high-risk vulnerable plaque measures (maximum lipid core burden index within any 4-mm segment across the entire lesion ≥324.7 and plaque burden ≥70%) in 877 patients. Findings were validated in the SCAPIS study (Swedish Cardiopulmonary Bioimage Study) using coronary computed tomography angiography–based measures of coronary artery calcium score and segment involvement score. RESULTS: We identified 156 significant associations ( P <0.05) between lipid metabolites and coronary plaque characteristics across 39 metabolic pathways. Sphingomyelins were inversely associated with all plaque metrics, and 1-palmitoyl-2-oleoyl-GPE (16:0/18:1), a phosphatidylethanolamine, was positively associated with all plaque metrics. After correcting for multiple testing, 27 lipid species across 7 pathways remained significant (q<0.05). The majority were linked to pan-coronary lipid burden, with the strongest inverse association observed for sphingomyelin d18:1/22:1, d18:2/22:0, and d16:1/24:1. Similar inverse patterns were seen for select dihydrosphingomyelins and fatty acid dicarboxylates. In contrast, 1-palmitoyl-2-oleoyl-GPE (16:0/18:1) remained positively associated with pan-coronary lipid. In the SCAPIS validation cohort, 19 of the 27 significant lipid associations were successfully replicated (q<0.05). CONCLUSIONS: This study is the first to demonstrate that sphingomyelins are negatively and 1-palmitoyl-2-oleoyl-GPE (16:0/18:1) positively associated with vulnerable coronary plaque features based on multimodality intracoronary imaging in patients with myocardial infarction. Moreover, these associations were validated in a large cohort using coronary computed tomography angiography–derived measures of plaque burden. These novel results may enable the development of new diagnostic and therapeutic strategies.

Background: Win statistics offer an alternative approach to clinical trials that use survival analysis to analyze composite endpoints. Our objective was to re-analyze data from previously published registry-based randomized controlled trials that produced hazard ratios using win statistics to evaluate the correspondence between them. Good correspondence was defined as both results being positive, negative, or neutral. Win statistics were calculated for these trials to encourage transparency, scientific rigor, and possibly validate results. Methods: The win ratio ordered events hierarchically by clinical importance for each trial, with all-cause death regarded as most severe, followed by acute myocardial infarction. Further components, i.e., other endpoints, were added subsequently to the hierarchy. Each patient in the treatment group was compared with each patient in the control arm in hierarchical order. The total number of wins for each category in the treatment group was added and divided by the total number of wins in the control group. Win odds were calculated as an extension, which incorporate ties into the calculation. Results: The results using win statistics showed good correspondence to the previously reported hazard ratios with their composite endpoints: for the TASTE trial, the results were neutral for both the hazard ratio and win odds. The hazard ratio was 0.86 (0.67–1.10), and the win odds were 1.02 (0.99–1.04). Similar results were found for the iFR-SWEDEHEART, DETO2X-AMI, and VALIDATE trials. The IAMI trial showed better results for the vaccinated group compared to the placebo for both the hazard ratio and win odds. Conclusions: Win statistics offer an alternative approach to traditional survival analysis by harnessing multiple events hierarchically by clinical importance. Win statistics also offer the potential to evaluate a broader range of clinical endpoints, providing a more rounded perspective of treatment efficacy, an important consideration when designing future randomized controlled trials. This is the first multi-registry-based controlled trial reanalysis using win statistics.

Background: Electrocardiographic abnormalities are common in arrhythmogenic right ventricular cardiomyopathy and are included in the 2010 Task Force Criteria. Their time course, however, remains uncertain. In this retrospective observational study, we aimed to assess the long‐term evolution of electrocardiographic characteristics and their relation to ventricular arrhythmias. Methods and Results: Three hundred fifty‐three patients with arrhythmogenic right ventricular cardiomyopathy as per the 2010 Task Force Criteria with 6871 automatically processed 12‐lead digital ECGs were included. The relationship between the electrocardiographic parameters and the risk of ventricular arrhythmias was assessed at 10 years from the first ECG. Electrocardiographic parameters were compared between the first contact ECG, the ECG at diagnosis, and the most recent ECG. Median time between the first and the latest ECG was 6 [interquartile range, 1–14] years. Reductions of QRS voltage, R‐ and T‐wave amplitudes between the first, diagnostic, and the latest ECGs were observed across precordial and extremity leads. Mean QRS duration increased from 96 to 102 ms ( P 1 ) from 47 to 52 ms ( P P 3 to V ₆ and aVF at first ECG were associated with ventricular arrhythmias (adjusted hazard ratio [HR _adj ][V ₃ ], 2.03 [95% CI, 1.23–3.34] and HR _adj [aVF], 1.87 [95% CI, 1.13–3.08]). Conclusions: Depolarization and repolarization parameters evolved over time in patients with arrhythmogenic right ventricular cardiomyopathy, supporting the progressive nature of arrhythmogenic right ventricular cardiomyopathy. Electrocardiographic abnormalities may be detected before diagnosis and might, although not fulfilling the 2010 Task Force Criteria, be markers of early disease. T‐wave inversion in leads V ₃ or aVF before diagnosis was associated with ventricular arrhythmias during follow‐up.

Objectives Our aim was to derive, based on the SWEDEHEART registry, and validate, using the Western Denmark Heart registry, a patient-oriented risk score, the SweDen score, which could calculate the risk of 1-year mortality following a myocardial infarction (MI). Methods The factors included in the SweDen score were age, sex, smoking, diabetes, heart failure and statin use. These were chosen a priori by the SWEDEHEART steering group based on the premise that the factors were information known by the patients themselves. The score was evaluated using various statistical methods such as time-dependent receiver operating characteristics curves of the linear predictor, area under the curve metrics, Kaplan-Meier survivor curves and the calibration slope. Results The area under the curve values were 0.81 in the derivation data and 0.76 in the validation data. The Kaplan-Meier curves showed similar patient profiles across datasets. The calibration slope was 1.03 (95% CI 0.99 to 1.08) in the validation data using the linear predictor from the derivation data. Conclusions The SweDen risk score is a novel tool created for patient use. The risk score calculator will be available online and presents mortality risk on a colour scale to simplify interpretation and to avoid exact life span expectancies. It provides a validated patient-oriented risk score predicting the risk of death within 1 year after suffering an MI, which visualises the benefit of statin use and smoking cessation in a simple way.

Objectives: Our aim was to derive, based on the SWEDEHEART registry, and validate, using the Western Denmark Heart registry, a patient-oriented risk score, the SweDen score, which could calculate the risk of 1-year mortality following a myocardial infarction (MI). Methods: The factors included in the SweDen score were age, sex, smoking, diabetes, heart failure, and statin use. These were chosen a priori by the SWEDEHEART steering group based on the premise that the factors were information known by the patients themselves. The score was evaluated using various statistical methods such as time-dependent receiver operating characteristics curves of the linear predictor, area under the curve metrics, Kaplan-Meier survivor curves, and the calibration slope. Results: The area under the curve values were 0.81 in the derivation data and 0.76 in the validation data. The Kaplan-Meier curves showed similar patient profiles across datasets. The calibration slope was 1.03 (95% CI 0.99-1.08) in the validation data using the linear predictor from the derivation data. Conclusions: The SweDen risk score is a novel tool created for patient use. The risk score calculator will be available online and presents mortality risk on a colour scale to simplify interpretation and to avoid exact life span expectancies. It provides a validated patient-oriented risk score predicting the risk of death at 1 year after suffering a MI, which visualizes the benefit of statin use and smoking cessation in a simple way.

Background: The assessment of prognostic impact of ventricular arrhythmias in ST-elevation myocardial infarction (STEMI) is currently based mainly on their timing with regard to the symptom onset and does not distinguish between monomorphic ventricular tachycardia (VT) and polymorphic VT/ventricular fibrillation (VF). However, recent data indicate long-term hazard of monomorphic VT occurring early in the course of STEMI. Purpose: To evaluate the incidence, time distribution and prognostic value of early monomorphic VT compared to polymorphic VT/VF in STEMI patients treated by primary percutaneous coronary interventions (PCI). Methods: A prespecified analysis of the multicentre prospective registry-based randomised VALIDATE-SWEDEHEART trial included STEMI patients enrolled at 16 sites in Sweden between June 2014 and September 2016. Source data verification regarding the type and timing of arrhythmia from all patients with VT/VF during STEMI was performed. Survival status was obtained from the Swedish national population registry. Endpoint was total mortality at 180 days. Results: In total, 2886 patients were identified. Among them, 97 (3.4%) had VF or polymorphic VT, 16 (0.5%) monomorphic VT, 6 (0.2%) had other undefined shockable rhythm. Total mortality (10.9% vs 2.8%, p≤0.001) was higher among patients with VT/VF. VT/VF was associated with total mortality (HR 3.18 95% CI 1.74–5.8; p≤0.001) after adjustment on age, gender and myocardial infarction localisation. In patients discharged from hospital, VT/VF did not influence the long-term prognosis. Patients with monomorphic VT had similar clinical characteristics as compared to those with polymorphic VT/VF. The time distribution of VT/VF differed with regard to the type of arrhythmia: 63% of monomorphic VT/VF episodes occurred after PCI (n=10) compared to 24% (n=23) of all documented polymorphic VT/VF, p=0.003. Total mortality (12.5% vs 10.3%, p=0.678) did not differ between patients with monomorphic VT and polymorphic VT/VF. In Cox model, total mortality was not associated with the type of arrhythmia (Figure). Conclusion: Early VT/VF is a marker of poor short-term outcome in patients with STEMI, which does not affect long-term prognosis in those who are successfully resuscitated and discharged from hospital. The incidence of monomorphic VT in STEMI treated by primary PCI is low, and it occurs mainly after PCI. Though no significant difference in mortality was found between patients with monomorphic VT and polymorphic VT/VF, the observed low incidence hampers drawing conclusions with regard to the prognostic hazard impact of monomorphic VT. Funding Acknowledgement: Type of funding sources: Foundation. Main funding source(s): The Swedish Heart Lung Foundation

Aims: The VALIDATE-SWEDEHEART trial was a registry-based randomized trial comparing bivalirudin and heparin in patients with acute myocardial infarction undergoing percutaneous coronary intervention. It showed no differences in mortality at 30 or 180 days. This study examines how well the trial population results may generalize to the population of all screened patients with fulfilled inclusion criteria in regard to mortality at 30 and 180 days. Methods: The standardized difference in the mean propensity score for trial inclusion between trial population and the screened not-enrolled with fulfilled inclusion criteria was calculated as a metric of similarity. Propensity scores were then used in an inverse-probability weighted Cox regression analysis using the trial population only to estimate the difference in mortality as it would have been had the trial included all screened patients with fulfilled inclusion criteria. Patients who were very likely to be included were weighted down and those who had a very low probability of being in the trial were weighted up. Results: The propensity score difference was 0.61. There were no significant differences in mortality between bivalirudin and heparin in the inverse-probability weighted analysis (hazard ratio 1.11, 95% confidence interval (0.73, 1.68)) at 30 days or 180 days (hazard ratio 0.98, 95% confidence interval (0.70, 1.36)). Conclusion: The propensity score difference demonstrated that the screened not-enrolled with fulfilled inclusion criteria and trial population were not similar. The inverse-probability weighted analysis showed no significant differences in mortality. From this, we conclude that the VALIDATE results may be generalized to the screened not-enrolled with fulfilled inclusion criteria.

Background The VALIDATE-SWEDEHEART trial was a registry-based randomized trial comparing bivalirudin and heparin in patients with acute myocardial infarction undergoing percutaneous coronary intervention. It showed no differences in mortality at 30 or 180 days. This study examines how well the trial population results may generalize to all of the screened patients with fulfilled inclusion criteria for mortality at 30 and 180 days.Methods The standardized difference in the mean propensity score for trial inclusion between the trial population and the screened not-enrolled with fulfilled inclusion criteria population was calculated as a metric of similarity. A predefined criterion of ≤ 0.25 was used. Predictions were futher used to standardize the observed trial results to all the screened patients with fulfilled inclusion criteria through an inverse-probability weighted Cox regression analysis, thereby evaluating the generalizability of the trial results to this population. An adjusted Cox regression analysis was applied to analyze differences in mortality with respect to anticoagulant treatment between the trial population and the screened not enrolled with fulfilled inclusion criteria.Results The propensity-score difference was 0.61, above the limit defining similar populations. There were no significant differences in mortality between bivalirudin and heparin in the inverse-probability weighted analysis [HR 1.11, 95% CI (0.73 1.68)]. In the interaction analysis, the neutral effect of bivalirudin vs. heparin remained in the screened not-enrolled with fulfilled inclusion criteria population [HR 1.01, 95% CI (0.63 1.61)].Conclusion The propensity-score difference demonstrated that the screened not enrolled with fulfilled inclusion criteria and the trial population were not similar. The inverse-probability weighted analysis showed no significant differences in mortality associated with treatment in either of the populations as was reiterated by the Cox analysis. From these analyses, we conclude that the VALIDATE trial results may be generalized.