Predictors of Left Main Coronary Artery Disease in the ISCHEMIA Trial

Left Main Coronary Artery Disease: A Contemporary Review of Diagnosis and Management

Significant left main coronary artery disease is a very high-risk subgroup of coronary artery disease that is a crucial indicator of heightened morbidity and mortality rates. Despite its clinical significance, uncertainties persist regarding the optimal management strategy for patients, particularly given its phenotypic variations. Existing evidence-based guidelines offer insights into revascularization options, yet questions remain regarding long-term prognoses and clinical outcomes when comparing percutaneous coronary intervention to coronary artery bypass grafting. This comprehensive review aims to provide an in-depth analysis of contemporary strategies for the diagnosis, assessment, and treatment of left main coronary artery disease. By synthesizing current literature and addressing the evolving landscape of revascularization modalities, this review seeks to contribute valuable insights for clinicians and researchers grappling with the complexities of managing left main coronary artery disease.

RBP4-based Multimarker Score: A Prognostic Tool for Adverse Cardiovascular Events in Acute Coronary Syndrome Patients

CONTEXT

Retinol binding protein 4 (RBP4) has been implicated in the progression of cardiovascular diseases. However, its association with major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS) remains obscure.

OBJECTIVE

Here, we examined the prognostic value of baseline RBP4 and its derived multimarker score for MACEs in ACS patients.

METHODS

A total of 826 patients with ACS were consecutively recruited from the department of cardiology and prospectively followed up for a median of 1.95 years (interquartile range, 1.02-3.25 years). Plasma RBP4 was measured using enzyme-linked immunosorbent assay. Adjusted associations between RBP4 and its derived multimarker score (1 point was assigned when RBP4 ≥ 38.18μg/mL, left ventricular ejection fraction [LVEF] ≤ 55%, N-terminal pro-B-type natriuretic peptide [NT-proBNP] ≥ 450 ng/L, estimated glomerular filtration rate [eGFR] ≤ 90 mL/min/1.73 m2, and age ≥60) with MACEs were analyzed.

RESULTS

In total, 269 ACS patients (32.57%) experienced MACEs. When patients were grouped by multimarker score (0-1, n = 315; 2-3, n = 406; 4-5, n = 105), there was a significant graded association between RBP4-based multimarker score and risk of MACEs (intermediate score (2-3): HRadj: 1.80; 95% CI, 1.34-2.41; high score (4-5): HRadj: 3.26; 95% CI, 2.21-4.81) and its components (P < .05 for each). Moreover, the prognostic and discriminative value of the RBP4-derived multimarker score remained robust in ACS patients with various high-risk anatomical or clinical characteristics.

CONCLUSION

The RBP4-derived 5-item score serves as a useful risk stratification and decision support for secondary prevention in patients with ACS.

Rationale and design of the INVICTUS Registry: (Multicenter Registry of Invasive and Non-Invasive imaging modalities to compare Coronary Computed Tomography Angiography, Intravascular Ultrasound and Optical Coherence Tomography for the determination of Severity, Volume and Type of coronary atherosclerosiS)

BACKGROUND

Coronary CT angiography (CCTA) is a first-line noninvasive imaging modality for evaluating coronary artery disease (CAD). Recent advances in CCTA technology enabled semi-automated detection of coronary arteries and atherosclerosis. However, there have been to date no large-scale validation studies of automated assessment of coronary atherosclerosis phenotype and coronary artery dimensions by artificial intelligence (AI) compared to current standard invasive imaging.

METHODS

INVICTUS registry is a multicenter, retrospective, and prospective study designed to evaluate the dimensions of coronary arteries, as well as the characteristic, volume, and phenotype of coronary atherosclerosis by CCTA, compared with the invasive imaging modalities including intravascular ultrasound (IVUS), near-infrared spectroscopy (NIRS)-IVUS and optical coherence tomography (OCT). All patients clinically underwent both CCTA and invasive imaging modalities within three months.

RESULTS

Patients data are sent to the core-laboratories to analyze for stenosis severity, plaque characteristics and volume. The variables for CCTA are measured using an AI-based automated software and assessed independently with the variables measured at the imaging core laboratories for IVUS, NIRS-IVUS, and OCT in a blind fashion.

CONCLUSION

The INVICTUS registry will provide new insights into the diagnostic value of CCTA for determining coronary atherosclerosis phenotype and coronary artery dimensions compared to IVUS, NIRS-IVUS, and OCT. Our findings will potentially shed new light on precision medicine informed by an AI-based coronary CTA assessment of coronary atherosclerosis burden, composition, and severity. (ClinicalTrials.gov: NCT04066062).

Determination of Left Main Coronary Artery Stenosis Through Noninvasive Testing to Guide Revascularization in Ischemic Heart Disease

Anatomically severe left main coronary artery (LMCA) stenosis (>50%) remains one of the few groups to benefit from early revascularization in stable ischemic heart disease (SIHD). Identification of these patients through widely available noninvasive testing would decrease the need for additional upfront anatomic testing, lowering the overall cost of healthcare. Patients with SIHD who underwent either percutaneous or surgical revascularization over a 7-year period at our institution were retrospectively analyzed and categorized as having LMCA stenosis versus non-LM stenosis. All preceding noninvasive testing, including resting electrocardiogram, echocardiogram, and functional testing was evaluated and compared between groups using chi-square and t test. In total, 806 patients were evaluated. Of those, 121 were identified as having significant LMCA stenosis with 685 patients in the non-LM cohort. Between LMCA versus non-LM cohorts, there were similar rates of electrocardiogram abnormalities (68.9% vs 70.8%, p >0.05), abnormal echocardiograms (72.7% vs 69.7%, p >0.05), abnormal functional testing (83.3% vs 77.4%, p >0.05), and high-risk imaging findings (5.6% vs 4.8%, p >0.05). More importantly, of those with a complete workup, there were similar rates of normal results between the LMCA (3 of 18, 16.7%) and non-LM stenosis (9 of 189, 4.8%) groups. A comprehensive noninvasive profile of patients with IHD failed to identify or exclude patients with anatomically severe LMCA stenosis, necessitating anatomic assessment.

Machine learning approaches that use clinical, laboratory, and electrocardiogram data enhance the prediction of obstructive coronary artery disease

Pretest probability (PTP) for assessing obstructive coronary artery disease (ObCAD) was updated to reduce overestimation. However, standard laboratory findings and electrocardiogram (ECG) raw data as first-line tests have not been evaluated for integration into the PTP estimation. Therefore, this study developed an ensemble model by adopting machine learning (ML) and deep learning (DL) algorithms with clinical, laboratory, and ECG data for the assessment of ObCAD. Data were extracted from the electronic medical records of patients with suspected ObCAD who underwent coronary angiography. With the ML algorithm, 27 clinical and laboratory data were included to identify ObCAD, whereas ECG waveform data were utilized with the DL algorithm. The ensemble method combined the clinical-laboratory and ECG models. We included 7907 patients between 2008 and 2020. The clinical and laboratory model showed an area under the curve (AUC) of 0.747; the ECG model had an AUC of 0.685. The ensemble model demonstrated the highest AUC of 0.767. The sensitivity, specificity, and F1 score of the ensemble model ObCAD were 0.761, 0.625, and 0.696, respectively. It demonstrated good performance and superior prediction over traditional PTP models. This may facilitate personalized decisions for ObCAD assessment and reduce PTP overestimation.

Cardiac Surgery 2022 Reviewed

PubMed displayed almost 37,000 hits for the search term "cardiac surgery AND 2022." As before, we used the PRISMA approach and selected relevant publications for a results-oriented summary. We focused on coronary and conventional valve surgery, their overlap with interventional alternatives, and briefly assessed surgery for aorta or terminal heart failure. In the field of coronary artery disease (CAD), key manuscripts addressed prognostic implications of invasive treatment options, classically compared modern interventions (percutaneous coronary intervention [PCI]) with surgery (coronary artery bypass grafting [CABG]), and addressed technical aspects of CABG. The general direction in 2022 confirms the superiority of CABG over PCI in patients with anatomically complex chronic CAD and supports an infarct-preventative effect as underlying mechanism. In addition, the relevance of proper surgical technique to achieve durable graft patency and the need for optimal medical treatment in CABG patients was impressively illustrated. In structural heart disease, the comparisons of interventional and surgical techniques have been characterized by prognostic and mechanistic investigations underscoring the need for durable treatment effects and reductions of valve-related complications. Early surgery for most valve pathologies appears to provide significant survival advantages, and two publications on the Ross operation prototypically illustrate an inverse association between long-term survival and valve-related complications. For surgical treatment of heart failure, the first xenotransplantation was certainly dominant, and in the aortic surgery field, innovations in arch surgery prevailed. This article summarizes publications perceived as important by us. It cannot be complete nor free of individual interpretation, but provides up-to-date information for decision-making and patient information.

Coronary revascularization for heart failure with coronary artery disease: A systematic review and meta-analysis of randomized trials

AIMS

Coronary artery disease (CAD) is a common cause of heart failure (HF). Whether coronary revascularization improves outcomes in patients with HF receiving guideline-recommended pharmacological therapy (GRPT) remains uncertain; therefore, we conducted a systematic review and meta-analysis of relevant randomized controlled trials (RCTs).

METHODS AND RESULTS

We searched in public databases for RCTs published between 1 January 2001 and 22 November 2022, investigating the effects of coronary revascularization on morbidity and mortality in patients with chronic HF due to CAD. All-cause mortality was the primary outcome. We included five RCTs that enrolled, altogether, 2842 patients (most aged <65 years; 85% men; 67% with left ventricular ejection fraction ≤35%). Overall, compared to medical therapy alone, coronary revascularization was associated with a lower risk of all-cause mortality (hazard ratio [HR] 0.88, 95% confidence interval [CI] 0.79-0.99; p = 0.0278) and cardiovascular mortality (HR 0.80, 95% CI 0.70-0.93; p = 0.0024) but not the composite of hospitalization for HF or all-cause mortality (HR 0.87, 95% CI 0.74-1.01; p = 0.0728). There were insufficient data to show whether the effects of coronary artery bypass graft surgery or percutaneous coronary intervention were similar or differed.

CONCLUSIONS

For patients with chronic HF and CAD enrolled in RCTs, the effect of coronary revascularization on all-cause mortality was statistically significant but neither substantial (HR 0.88) nor robust (upper 95% CI close to 1.0). RCTs were not blinded, which may bias reporting of the cause-specific reasons for hospitalization and mortality. Further trials are required to determine which patients with HF and CAD obtain a substantial benefit from coronary revascularization by either coronary artery bypass graft surgery or percutaneous coronary intervention.

Percutaneous Coronary Intervention Versus Coronary Artery Bypass Grafting for Revascularization of Left Main Coronary Artery Disease

Owing to a large-jeopardized myocardium, left main coronary artery disease (LMCAD) represents the substantial high-risk anatomical subset of obstructive coronary artery disease. For several decades, coronary artery bypass grafting (CABG) has been the "gold standard" treatment for LMCAD. Along with advances in CABG, percutaneous coronary intervention (PCI) has also dramatically evolved over time in conjunction with advances in the stent or device technology, adjunct pharmacotherapy, accumulated experiences, and practice changes, establishing its position as a safe, reasonable treatment option for such a complex disease. Until recently, several randomized clinical trials, meta-analyses, and observational registries comparing PCI and CABG for LMCAD have shown comparable long-term survival with tradeoffs between early and late risk-benefit of each treatment. Despite this, there are still several unmet issues for revascularization strategy and management for LMCAD. This review article summarized updated knowledge on evolution and clinical evidence on the treatment of LMCAD, with a focus on the comparison of state-of-the-art PCI with CABG.

Development and assessment of scoring model for ICU stay and mortality prediction after emergency admissions in ischemic heart disease: a retrospective study of MIMIC-IV databases

Ischemic heart disease (IHD) is the leading cause of death and emergency department (ED) admission. We aimed to develop more accurate and straightforward scoring models to optimize the triaging of IHD patients in ED. This was a retrospective study based on the MIMIC-IV database. Scoring models were established by AutoScore formwork based on machine learning algorithm. The predictive power was measured by the area under the curve in the receiver operating characteristic analysis, with the prediction of intensive care unit (ICU) stay, 3d-death, 7d-death, and 30d-death after emergency admission. A total of 8381 IHD patients were included (median patient age, 71 years, 95% CI 62-81; 3035 [36%] female), in which 5867 episodes were randomly assigned to the training set, 838 to validation set, and 1676 to testing set. In total cohort, there were 2551 (30%) patients transferred into ICU; the mortality rates were 1% at 3 days, 3% at 7 days, and 7% at 30 days. In the testing cohort, the areas under the curve of scoring models for shorter and longer term outcomes prediction were 0.7551 (95% CI 0.7297-0.7805) for ICU stay, 0.7856 (95% CI 0.7166-0.8545) for 3d-death, 0.7371 (95% CI 0.6665-0.8077) for 7d-death, and 0.7407 (95% CI 0.6972-0.7842) for 30d-death. This newly accurate and parsimonious scoring models present good discriminative performance for predicting the possibility of transferring to ICU, 3d-death, 7d-death, and 30d-death in IHD patients visiting ED.

Predicting left main stenosis in stable ischemic heart disease using logistic regression and boosted trees

BACKGROUND

The ISCHEMIA trial showed similar cardiovascular outcomes of an initial conservative strategy as compared with invasive management in patients with stable ischemic heart disease without left main stenosis. We aim to assess the feasibility of predicting significant left main stenosis using extensive clinical, laboratory and non-invasive tests data.

METHODS

All adult patients who had stress testing prior to undergoing an elective coronary angiography for stable ischemic heart disease in Ontario, Canada, between April 2010 and March 2019, were included. Candidate predictors included comprehensive demographics, comorbidities, laboratory tests, and cardiac stress test data. The outcome was stenosis of 50% or greater in the left main coronary artery. A traditional model (logistic regression) and a machine learning algorithm (boosted trees) were used to build prediction models.

RESULTS

Among 150,423 patients included (mean age: 64.2 ± 10.6 years; 64.1% males), there were 9,225 (6.1%) with left main stenosis. The final logistic regression model included 24 predictors and 3 interactions, had an optimism-adjusted c-statistic of 0.72 and adequate calibration (optimism-adjusted Integrated Calibration Index 0.0044). These results were consistent in subgroups of males and females, diabetes and non-diabetes, and extent of ischemia. The boosted tree algorithm had similar accuracy, also resulting in a c-statistic of 0.72 and adequate calibration (Integrated Calibration Index 0.0054).

CONCLUSIONS

In this large population-based study of patients with stable ischemic heart disease using extensive clinical data, only modest prediction of left main coronary artery disease was possible with traditional and machine learning modelling techniques.

Left main coronary disease: evolving management concepts

Remarkable advances in the management of coronary artery disease have enhanced our approach to left main coronary artery (LMCA) disease. The traditional role of coronary artery bypass graft surgery has been challenged by the less invasive percutaneous coronary interventional approach. Additionally, major strides in optimal medical therapy now provide a rich menu of treatment choices in selected circumstances. Although a LMCA stenosis >70% is an acceptable threshold for revascularization, those patients with a LMCA narrowing between 40 and 69% present a more complex scenario. This review examines the relative merits of the different treatment options, addresses key diagnostic and therapeutic unknowns, and identifies future work likely to advance progress.

The role of cardiac computed tomography in predicting adverse coronary events

Cardiac computed tomography (CCT) is now considered a first-line diagnostic test for suspected coronary artery disease (CAD) providing a non-invasive, qualitative, and quantitative assessment of the coronary arteries and pericoronary regions. CCT assesses vascular calcification and coronary lumen narrowing, measures total plaque burden, identifies plaque composition and high-risk plaque features and can even assist with hemodynamic evaluation of coronary lesions. Recent research focuses on computing coronary endothelial shear stress, a potent modulator in the development and progression of atherosclerosis, as well as differentiating an inflammatory from a non-inflammatory pericoronary artery environment using the simple measurement of pericoronary fat attenuation index. In the present review, we discuss the role of the above in the diagnosis of coronary atherosclerosis and the prediction of adverse cardiovascular events. Additionally, we review the current limitations of cardiac computed tomography as an imaging modality and highlight how rapid technological advancements can boost its capacity in predicting cardiovascular risk and guiding clinical decision-making.