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.

Effects of Age and Sex on Systemic Inflammation and Cardiometabolic Function in Individuals with Type 2 Diabetes.

Objective: Systemic inflammation, aging, and type 2 diabetes (T2DM) all contribute to the development of cardiovascular dysfunction and impaired aerobic exercise capacity but their interplay remains unclear. This study evaluates the impact of age, sex, and inflammation on coronary and peripheral vascular function and exercise capacity in elderly individuals with and without type 2 diabetes (T2DM). Research Design and Methods: Elderly individuals (age ≥65 years) underwent biochemical and tissue inflammatory phenotyping, cardiopulmonary exercise testing (CPET), cardiovascular magnetic resonance (CMR) imaging, and vascular reactivity testing. Correlation and regression analyses determined the effects of systemic inflammation, older age, and sex on cardiovascular health, stratified by T2DM status. Results: For the 133 recruited individuals (44% female; median age 71, IQR=7 years, 41% with T2DM) the presence of T2DM did not have an effect on most blood serum inflammatory markers and skin biopsies. Hyperemic myocardial blood flow (hMBF), flow-mediated, and flow-independent nitroglycerin induced brachial artery dilation were significantly impaired in males, but not females with T2DM. Peak VO2 was lower with T2DM (p=0.022), mostly because of the effect of T2DM in females. Females showed more adverse myocardial remodeling assessed by extracellular volume (p=0.008), independent of T2DM status. Conclusions: Our findings suggest that the pathophysiological manifestations of T2DM on vascular function and aerobic exercise capacity are distinct in elderly males and females and this may reflect underlying differences in vascular and myocardial aging in the presence of T2DM.

Association of Lipoprotein (a) and Standard Modifiable Cardiovascular Risk Factors With Incident Myocardial Infarction: The Mass General Brigham Lp(a) Registry.

BACKGROUND: Lipoprotein (a) [Lp(a)] is a robust predictor of coronary heart disease outcomes, with targeted therapies currently under investigation. We aimed to evaluate the association of high Lp(a) with standard modifiable risk factors (SMuRFs) for incident first acute myocardial infarction (AMI). METHODS AND RESULTS: This retrospective study used the Mass General Brigham Lp(a) Registry, which included patients aged ≥18 years with an Lp(a) measurement between 2000 and 2019. Exclusion criteria were severe kidney dysfunction, malignant neoplasm, and prior known atherosclerotic cardiovascular disease. Diabetes, dyslipidemia, hypertension, and smoking were considered SMuRFs. High Lp(a) was defined as >90th percentile, and low Lp(a) was defined as <50th percentile. The primary outcome was fatal or nonfatal AMI. A combination of natural language processing algorithms, International Classification of Diseases (ICD) codes, and laboratory data was used to identify the outcome and covariates. A total of 6238 patients met the eligibility criteria. The median age was 54 (interquartile range, 43-65) years, and 45% were women. Overall, 23.7% had no SMuRFs, and 17.8% had ≥3 SMuRFs. Over a median follow-up of 8.8 (interquartile range, 4.2-12.8) years, the incidence of AMI increased gradually, with higher number of SMuRFs among patients with high (log-rank P=0.031) and low Lp(a) (log-rank P<0.001). Across all SMuRF subgroups, the incidence of AMI was significantly higher for patients with high Lp(a) versus low Lp(a). The risk of high Lp(a) was similar to having 2 SMuRFs. Following adjustment for confounders and number of SMuRFs, high Lp(a) remained significantly associated with the primary outcome (hazard ratio, 2.9 [95% CI, 2.0-4.3]; P<0.001). CONCLUSIONS: Among patients with no prior atherosclerotic cardiovascular disease, high Lp(a) is associated with significantly higher risk for first AMI regardless of the number of SMuRFs.

Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as % stenosis, plaque volume, and plaque composition. AI-QCT plaque volume was then staged by recently validated prognostic thresholds, and compared with CAD-RADS 2.0 clinical methods of plaque evaluation (segment involvement score (SIS), coronary artery calcium score (CACS), visual assessment, and CAD-RADS percent (%) stenosis) by expert consensus blinded to the AI-QCT core lab reads. Average age of subjects were 59 ± 11 years; 44% women, with 50% of patients at CAD-RADS 1-2 and 21% at CAD-RADS 3 and above by expert consensus. AI-QCT quantitative plaque burden staging had excellent agreement of 93% (k = 0.87 95% CI: 0.79-0.96) with SIS. There was moderate agreement between AI-QCT quantitative plaque volume and categories of visual assessment (64.4%; k = 0.488 [0.38-0.60]), and CACS (66.3%; k = 0.488 [0.36-0.61]). Agreement between AI-QCT plaque volume stage and CAD-RADS % stenosis category was also moderate. There was discordance at small plaque volumes. With ongoing validation, these results demonstrate a potential for AI-QCT as a rapid, reproducible approach to quantify total plaque burden.

Prognostic value of myocardial flow reserve vs corrected myocardial flow reserve in patients without obstructive coronary artery disease.

BACKGROUND: Myocardial flow reserve (MFR) by positron emission tomography (PET) is a validated measure of cardiovascular risk. Elevated resting rate pressure product (RPP = heart rate x systolic blood pressure) can cause high resting myocardial blood flow (MBF), resulting in reduced MFR despite normal/near-normal peak stress MBF. When resting MBF is high, it is not known if RPP-corrected MFR (MFRcorrected) helps reclassify CV risk. We aimed to study this question in patients without obstructive coronary artery disease (CAD). METHODS: We retrospectively studied patients referred for rest/stress cardiac PET at our center from 2006 to 2020. Patients with abnormal perfusion (summed stress score >3) or prior coronary artery bypass grafting (CABG) were excluded. MFRcorrected was defined as stress MBF/corrected rest MBF where corrected rest MBF = rest MBF x 10,000/RPP. The primary outcome was major cardiovascular events (MACE): cardiovascular death or myocardial infarction. Associations of MFR and MFRcorrected with MACE were assessed using unadjusted and adjusted Cox regression. RESULTS: 3276 patients were followed for a median of 7 (IQR 3-12) years. 1685 patients (51%) had MFR <2.0, and of those 366 (22%) had an MFR ≥2.0 after RPP correction. MFR <2.0 was associated with an increased absolute risk of MACE (HR 2.24 [1.79-2.81], P < 0.0001). Among patients with MFR <2.0, the risk of MACE was not statistically different between patients with an MFRcorrected ≥2.0 compared with those with MFRcorrected <2.0 (1.9% vs 2.3% MACE/year, HR 0.84 [0.63-1.13], P = 0.26) even after adjustment for confounders (P = 0.66). CONCLUSIONS: In patients without overt obstructive CAD and MFR< 2.0, there was no significant difference in cardiovascular risk between patients with discordant (≥2.0) and concordant (<2) MFR following RPP correction. This suggests that RPP-corrected MFR may not consistently provide accurate risk stratification in patients with normal perfusion and MFR <2.0. Stress MBF and uncorrected MFR should be reported to more reliably convey cardiovascular risk beyond perfusion results.

Lipoprotein(a): Emerging insights and therapeutics.

The strong association between lipoprotein (a) [Lp(a)] and atherosclerotic cardiovascular disease has led to considerations of Lp(a) being a potential target for mitigating residual cardiovascular risk. While approximately 20 % of the population has an Lp(a) level greater than 50 mg/dL, there are no currently available pharmacological lipid-lowering therapies that have demonstrated substantial reduction in Lp(a). Novel therapies to lower Lp(a) include antisense oligonucleotides and small-interfering ribonucleic acid molecules and have shown promising results in phase 2 trials. Phase 3 trials are currently underway and will test the causal relationship between Lp(a) and ASCVD and whether lowering Lp(a) reduces cardiovascular outcomes. In this review, we summarize emerging insights related to Lp(a)'s role as a risk-enhancing factor for ASCVD, association with calcific aortic stenosis, effects of existing therapies on Lp(a) levels, and variations amongst patient populations. The evolving therapeutic landscape of emerging therapeutics is further discussed.

Diagnosis and Management of Cardiac Sarcoidosis: A Scientific Statement From the American Heart Association.

Cardiac sarcoidosis is an infiltrative cardiomyopathy that results from granulomatous inflammation of the myocardium and may present with high-grade conduction disease, ventricular arrhythmias, and right or left ventricular dysfunction. Over the past several decades, the prevalence of cardiac sarcoidosis has increased. Definitive histological confirmation is often not possible, so clinicians frequently face uncertainty about the accuracy of diagnosis. Hence, the likelihood of cardiac sarcoidosis should be thought of as a continuum (definite, highly probable, probable, possible, low probability, unlikely) rather than in a binary fashion. Treatment should be initiated in individuals with clinical manifestations and active inflammation in a tiered approach, with corticosteroids as first-line treatment. The lack of randomized clinical trials in cardiac sarcoidosis has led to treatment decisions based on cohort studies and consensus opinions, with substantial variation observed across centers. This scientific statement is intended to guide clinical practice and to facilitate management conformity by providing a framework for the diagnosis and management of cardiac sarcoidosis.

Interaction Between Risk Factors, Coronary Calcium, and CCTA Plaque Characteristics in Patients Age 18-45.

AIMS: The atherosclerotic profile and advanced plaque subtype burden in symptomatic patients ≤45 years old have not been established. This study aimed to assess the prevalence and predictors of coronary artery calcium (CAC), plaque subtypes, and plaque burden by coronary computed tomography angiography (CCTA) in symptomatic young patients. METHODS AND RESULTS: We included 907 symptomatic young patients (18-45 years) from Montefiore undergoing CCTA for chest pain evaluation. Prevalence and predictors of CAC, plaque subtypes, and burden were evaluated using semi-automated software. In the overall population (55% female and 44% Hispanic), 89% had CAC = 0. The likelihood of CAC or any plaque by CCTA increased with >3 risk factors (RF, OR 7.13 [2.14-23.7] and OR 10.26 [3.36-31.2], respectively). Any plaque by CCTA was present in 137 (15%); the strongest independent predictors were age ≥35 years (OR 3.62 [2.05-6.41]) and family history of premature CAD (FHx) (OR 2.76 [1.67-4.58]). Stenosis ≥50% was rare (1.8%), with 31% of those having CAC = 0. Significant non-calcified (NCP, 37.2%) and low-attenuation (LAP, 4.24%) plaque burdens were seen, even in those with non-obstructive stenosis. Among patients with CAC = 0, 5% had plaque, and the only predictor of exclusively non-calcified plaque was FHx (OR 2.29 [1.08-4.86]). CONCLUSIONS: In symptomatic young patients undergoing CCTA, the prevalence of CAC or any coronary atherosclerosis was not negligible, and the likelihood increased with RF burden. The presence of coronary stenosis ≥50% was rare and most often accompanied by CAC > 0 but there was a significant burden of NCP and LAP even within the non-obstructive group.

Multimodality Cardiac Imaging and the Imaging Workforce in the United States: Diversity, Disparities, and Future Directions.

Innovations in cardiac imaging have fundamentally advanced the understanding and treatment of cardiovascular disease. These advances in noninvasive cardiac imaging have also expanded the role of the cardiac imager and dramatically increased the demand for imagers who are cross-trained in multiple modalities. However, we hypothesize that there is significant variation in the availability of cardiac imaging expertise and a disparity in the adoption of advanced imaging technologies across the United States. To evaluate this, we have brought together the leaders of cardiovascular imaging societies, imaging trainees, as well as collaborated with national imaging accreditation commissions and imaging certification boards to assess the state of cardiac imaging and the diversity of the imaging workforce in the United States. Aggregate data confirm the presence of critical gaps, such as limited access to imaging and imaging expertise in rural communities, as well as disparities in the imaging workforce, notably among women and underrepresented minorities. Based on these results, we have proposed solutions to promote and maintain a robust and diverse community of cardiac imagers and improve equity and accessibility for cardiac imaging technologies.

Lipoprotein(a) and Major Adverse Cardiovascular Events in Patients With or Without Baseline Atherosclerotic Cardiovascular Disease.

BACKGROUND: Lipoprotein(a) [Lp(a)] is associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). However, whether the optimal Lp(a) threshold for risk assessment should differ based on baseline ASCVD status is unknown. OBJECTIVES: The purpose of this study was to assess the association between Lp(a) and major adverse cardiovascular events (MACE) among patients with and without baseline ASCVD. METHODS: We studied a retrospective cohort of patients with Lp(a) measured at 2 medical centers in Boston, Massachusetts, from 2000 to 2019. To assess the association of Lp(a) with incident MACE (nonfatal myocardial infarction [MI], nonfatal stroke, coronary revascularization, or cardiovascular mortality), Lp(a) percentile groups were generated with the reference group set at the first to 50th Lp(a) percentiles. Cox proportional hazards modeling was used to assess the association of Lp(a) percentile group with MACE. RESULTS: Overall, 16,419 individuals were analyzed with a median follow-up of 11.9 years. Among the 10,181 (62%) patients with baseline ASCVD, individuals in the 71st to 90th percentile group had a 21% increased hazard of MACE (adjusted HR: 1.21; P < 0.001), which was similar to that of individuals in the 91st to 100th group (adjusted HR: 1.26; P < 0.001). Among the 6,238 individuals without established ASCVD, there was a continuously higher hazard of MACE with increasing Lp(a), and individuals in the 91st to 100th Lp(a) percentile group had the highest relative risk with an adjusted HR of 1.93 (P < 0.001). CONCLUSIONS: In a large, contemporary U.S. cohort, elevated Lp(a) is independently associated with long-term MACE among individuals with and without baseline ASCVD. Our results suggest that the threshold for risk assessment may be different in primary vs secondary prevention cohorts.

Comparative Effectiveness of PET and SPECT MPI for Predicting Cardiovascular Events After Kidney Transplant.

BACKGROUND: Advanced chronic kidney disease is associated with high cardiovascular risk, even after kidney transplant. Pretransplant cardiac testing may identify patients who require additional assessment before transplant or would benefit from risk optimization. The objective of the current study was to determine the relative prognostic utility of pretransplant positron emission tomography (PET) and single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) for posttransplant major adverse cardiovascular events (MACEs). METHODS: We retrospectively followed patients who underwent MPI before kidney transplant for the occurrence of MACE after transplant including myocardial infarction, stroke, heart failure, and cardiac death. An abnormal MPI result was defined as a total perfusion deficit >5% of the myocardium. To determine associations of MPI results with MACE, we utilized Cox hazard regression with propensity weighting for PET versus SPECT with model factors, including demographics and cardiovascular risk factors. RESULTS: A total of 393 patients underwent MPI (208 PET and 185 SPECT) and were followed for a median of 5.9 years post-transplant. Most were male (58%), median age was 58 years, and there was a high burden of hypertension (88%) and diabetes (33%). A minority had abnormal MPI (n=58, 15%). In propensity-weighted hazard regression, abnormal PET result was associated with posttransplant MACE (hazard ratio, 3.02 [95% CI, 1.78-5.11]; P<0.001), while there was insufficient evidence of an association of abnormal SPECT result with MACE (1.39 [95% CI, 0.72-2.66]; P=0.33). The explained relative risk of the PET result was higher than the SPECT result (R2 0.086 versus 0.007). Normal PET was associated with the lowest risk of MACE (2.2%/year versus 3.6%/year for normal SPECT; P<0.001). CONCLUSIONS: Kidney transplant recipients are at high cardiovascular risk, despite a minority having obstructive coronary artery disease on MPI. PET MPI findings predict posttransplant MACE. Normal PET may better discriminate lower risk patients compared with normal SPECT, which should be confirmed in a larger prospective study.

Changes in use of preventive medications after assessment of chest pain by coronary computed tomography angiography: A meta-analysis.

BACKGROUND: Coronary computed tomography angiogram (CCTA) is a crucial tool for diagnosing CAD, but its impact on altering preventive medications is not well-documented. This systematic review aimed to compare changes in aspirin and statin therapy following CCTA and functional stress testing in patients with suspected CAD, and in those underwent CCTA when stratified by the presence/absence of plaque. RESULTS: Eight studies involving 42,812 CCTA patients and 64,118 cardiac stress testing patients were analyzed. Compared to functional testing, CCTA led to 66 â€‹% more changes in statin therapy (pooled RR, 95 â€‹% CI [1.28-2.15]) and a 74 â€‹% increase in aspirin prescriptions (pooled RR, 95 â€‹% CI [1.34-2.26]). For medication modifications based on CCTA results, 13 studies (47,112 patients with statin data) and 11 studies (12,089 patients with aspirin data) were included. Patients with any plaque on CCTA were five times more likely to use or intensify statins compared to those without CAD (pooled RR, 5.40, 95 â€‹% CI [4.16-7.00]). Significant heterogeneity remained, which decreased when stratified by diabetes rates. Aspirin use increased eightfold after plaque detection (pooled RR, 8.94 [95 â€‹% CI, 4.21-19.01]), especially with obstructive plaque findings (pooled RR, 9.41, 95 â€‹% CI [2.80-39.02]). CONCLUSION: In conclusion, CCTA resulted in higher changes in statin and aspirin therapy compared to cardiac stress testing. Detection of plaque by CCTA significantly increased statin and aspirin therapy.

Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification.

Coronary artery calcium (CAC) is a marker of coronary atherosclerosis, and the presence and severity of CAC have been shown to be powerful predictors of future cardiovascular events. Due to its value in risk discrimination and reclassification beyond traditional risk factors, CAC has been supported by recent guidelines, particularly for the purposes of informing shared decision-making regarding the use of preventive therapies. In addition to dedicated ECG-gated CAC scans, the presence and severity of CAC can also be accurately estimated on non-contrast chest computed tomography scans performed for other clinical indications. However, the presence of such "incidental" CAC is rarely reported. Advances in artificial intelligence have now enabled automatic CAC scoring for both cardiac and non-cardiac CT scans. Various AI approaches, from rule-based models to machine learning algorithms and deep learning, have been applied to automate CAC scoring. Convolutional neural networks, a deep learning technique, have had the most successful approach, with high agreement with manual scoring demonstrated in multiple studies. Such automated CAC measurements may enable wider and more accurate detection of CAC from non-gated CT studies, thus improving the efficiency of healthcare systems to identify and treat previously undiagnosed coronary artery disease.

AI-Guided Quantitative Plaque Staging Predicts Long-Term Cardiovascular Outcomes in Patients at Risk for Atherosclerotic CVD.

BACKGROUND: The recent development of artificial intelligence-guided quantitative coronary computed tomography angiography analysis (AI-QCT) has enabled rapid analysis of atherosclerotic plaque burden and characteristics. OBJECTIVES: This study set out to investigate the 10-year prognostic value of atherosclerotic burden derived from AI-QCT and to compare the spectrum of plaque to manually assessed coronary computed tomography angiography (CCTA), coronary artery calcium scoring (CACS), and clinical risk characteristics. METHODS: This was a long-term follow-up study of 536 patients referred for suspected coronary artery disease. CCTA scans were analyzed with AI-QCT and plaque burden was classified with a plaque staging system (stage 0: 0% percentage atheroma volume [PAV]; stage 1: >0%-5% PAV; stage 2: >5%-15% PAV; stage 3: >15% PAV). The primary major adverse cardiac event (MACE) outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, and all-cause mortality. RESULTS: The mean age at baseline was 58.6 years and 297 patients (55%) were male. During a median follow-up of 10.3 years (IQR: 8.6-11.5 years), 114 patients (21%) experienced the primary outcome. Compared to stages 0 and 1, patients with stage 3 PAV and percentage of noncalcified plaque volume of >7.5% had a more than 3-fold (adjusted HR: 3.57; 95% CI 2.12-6.00; P < 0.001) and 4-fold (adjusted HR: 4.37; 95% CI: 2.51-7.62; P < 0.001) increased risk of MACE, respectively. Addition of AI-QCT improved a model with clinical risk factors and CACS at different time points during follow-up (10-year AUC: 0.82 [95% CI: 0.78-0.87] vs 0.73 [95% CI: 0.68-0.79]; P < 0.001; net reclassification improvement: 0.21 [95% CI: 0.09-0.38]). Furthermore, AI-QCT achieved an improved area under the curve compared to Coronary Artery Disease Reporting and Data System 2.0 (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.023) and manual QCT (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.040), although net reclassification improvement was modest (0.09 [95% CI: -0.02 to 0.29] and 0.04 [95% CI: -0.05 to 0.27], respectively). CONCLUSIONS: Through 10-year follow-up, AI-QCT plaque staging showed important prognostic value for MACE and showed additional discriminatory value over clinical risk factors, CACS, and manual guideline-recommended CCTA assessment.