Angina in 2022: Current Perspectives

Causal Relationship between Angina and Hepatic Failure as Revealed by Mendelian Randomization

BACKGROUND

Patients with angina are often suffering from comorbidities such as varying degrees of hepatic dysfunction. However, the impact of angina on the incidence of hepatic failure (HF) remains unclear.

METHODS

The genetic data were retrieved from genome-wide association studies. Five Mendelian randomization methods were used to investigate the causal relationship between unstable angina (UA), stable angina (SA), and HF. The result of the Inverse variance weighted (IVW) method was deemed the principal result. In addition, we performed a comprehensive sensitivity analysis to verify the robustness of the results.

RESULTS

The IVW results showed that UA (Odds ratio (OR): 2.055, 95% confidence interval (CI): 1.171-3.606, p = 0.012) was causally associated with the incidence of HF. SA (OR: 1.122, 95% CI: 0.738-1.706, p = 0.591) was not causally associated with the incidence of HF. Sensitivity analysis did not identify any bias in the results.

CONCLUSIONS

UA turned out to be a risk factor for HF. SA does not have a significant causal effect on HF. Therefore, it is highly recommended that patients with chronic liver disease seek prompt medical attention and undergo regular monitoring of liver function when experiencing UA. This may help them to reduce the risk of HF.

A proposed tree-based explainable artificial intelligence approach for the prediction of angina pectoris

Cardiovascular diseases (CVDs) are a serious public health issue that affects and is responsible for numerous fatalities and impairments. Ischemic heart disease (IHD) is one of the most prevalent and deadliest types of CVDs and is responsible for 45% of all CVD-related fatalities. IHD occurs when the blood supply to the heart is reduced due to narrowed or blocked arteries, which causes angina pectoris (AP) chest pain. AP is a common symptom of IHD and can indicate a higher risk of heart attack or sudden cardiac death. Therefore, it is important to diagnose and treat AP promptly and effectively. To forecast AP in women, we constructed a novel artificial intelligence (AI) method employing the tree-based algorithm known as an Explainable Boosting Machine (EBM). EBM is a machine learning (ML) technique that combines the interpretability of linear models with the flexibility and accuracy of gradient boosting. We applied EBM to a dataset of 200 female patients, 100 with AP and 100 without AP, and extracted the most relevant features for AP prediction. We then evaluated the performance of EBM against other AI methods, such as Logistic Regression (LR), Categorical Boosting (CatBoost), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Light Gradient Boosting Machine (LightGBM). We found that EBM was the most accurate and well-balanced technique for forecasting AP, with accuracy (0.925) and Youden's index (0.960). We also looked at the global and local explanations provided by EBM to better understand how each feature affected the prediction and how each patient was classified. Our research showed that EBM is a useful AI method for predicting AP in women and identifying the risk factors related to it. This can help clinicians to provide personalized and evidence-based care for female patients with AP.

Characteristics of patients with recurrent acute myocardial infarction after MINOCA

BACKGROUND

Myocardial infarction (MI) with non-obstructed coronary arteries (MINOCA) is an increasingly recognized condition with challenging management. Some MINOCA patients ultimately experience recurrent acute MI (re-AMI) during follow-up; however, clinical and angiographic factors predisposing to re-AMI are still poorly defined.

METHODS

In this retrospective multicenter cohort study we enrolled consecutive patients fulfilling diagnostic criteria of MINOCA according to the IV universal definition of myocardial infarction; characteristics of patients experiencing re-AMI during the follow-up were compared to a group of MINOCA patients without re-AMI.

RESULTS

54 patients (mean age 66 ± 13) experienced a subsequent re-AMI after MINOCA and follow-up was available in 44 (81%). Compared to MINOCA patients without re-AMI (n = 695), on first invasive coronary angiography (ICA) MINOCA patients with re-AMI showed less frequent angiographically normal coronaries (37 versus 53%, p = 0.032) and had a higher prevalence of atherosclerosis involving 3 vessels or left main stem (17% versus 8%, p = 0.049). Twenty-four patients (44%) with re-AMI underwent a new ICA: 25% had normal coronary arteries, 12.5% had mild luminal irregularities (<30%), 20.8% had moderate coronary atherosclerosis (30-49%), and 41.7% showed obstructive coronary atherosclerosis (≥50% stenosis). Among patients undergoing new ICA, atherosclerosis progression was observed in 11 (45.8%), 37.5% received revascularization, only 4.5% had low-density lipoprotein cholesterol (LDL_C) under 55 mg/dL and 33% experienced a new cardiovascular disease (CVD) event (death, AMI, heart failure, stroke) at subsequent follow-up.

CONCLUSIONS

In the present study, only a minority of MINOCA patients with re-AMI underwent a repeated ICA, nearly one out of two showed atherosclerosis progression, often requiring revascularization. Recommended LDL-C levels were achieved only in a minority of the cases, indicating a possible underestimation of CVD risk in this population.