Atherosclerosis on CT coronary angiography and the risk of long-term cardiovascular events after liver transplantation

Coronary Computed Angiography and Coronary Artery Calcium Score for Preoperative Cardiovascular Risk Stratification in Patients Undergoing Noncardiac Surgery

Perioperative and long-term postoperative major adverse cardiovascular events (MACE) are a leading cause of morbidity and mortality in patients undergoing noncardiac surgery. In selected high-risk patients, when information about cardiovascular status may influence surgical decisions, preoperative risk stratification is reasonable, with stress imaging being the preferred method. Coronary computed angiography (CCTA) and coronary artery calcium score (CACS) offer direct anatomical assessment of atherosclerotic coronary arteries and help gauge the extent and severity of coronary artery disease. Strong evidence supports that CCTA and CACS, either alone or in combination, are reliable methods for assessing the risk of both perioperative and long-term postoperative MACE, often demonstrating equal or superior prognostic performance compared to traditional imaging tools. Moreover, integrating CCTA or CACS into standard preoperative imaging protocols further enhances perioperative risk prediction and improves the ability to accurately stratify patients. Future research is needed to better define the role of CCTA and CACS in preoperative cardiovascular risk evaluation of patients undergoing noncardiac surgery.

Automatic Detection of Occluded Main Coronary Arteries of NSTEMI Patients with MI-MS ConvMixer + WSSE Without CAG

Background/Objectives: Heart attacks are the leading cause of death in the world. There are two important classes of heart attack: ST-segment Elevation Myocardial Infarction (STEMI) and Non-ST-segment Elevation Myocardial Infarction (NSTEMI) patient groups. While the STEMI group has a higher mortality rate in the short term, the NSTEMI group is considered more dangerous and insidious in the long term. Blocked coronary arteries can be predicted from ECG signals in STEMI patients but not in NSTEMI patients. Therefore, coronary angiography (CAG) is inevitable for these patients. However, in the elderly and some patients with chronic diseases, if there is a single blockage, the CAG procedure poses a risk, so medication may be preferred. In this study, a novel deep learning-based approach is used to automatically detect the occluded main coronary artery or arteries in NSTEMI patients. For this purpose, a new seven-class dataset was created with expert cardiologists. Methods: A new Multi Input-Multi Scale (MI-MS) ConvMixer model was developed for automatic detection. The MI-MS ConvMixer model allows simultaneous training of 12-channel ECG data and highlights different regions of the data at different scales. In addition, the ConMixer structure provides high classification performance without increasing the complexity of the model. Moreover, to maximise the classifier performance, the WSSE algorithm was developed to adjust the classification prediction value according to the feature importance weights. Results: This algorithm improves the SVM classifier performance. The features extracted from this model were classified with the WSSE algorithm, and an accuracy of 88.72% was achieved. Conclusions: This study demonstrates the potential of the MI-MS ConvMixer model in advancing ECG signal classification for diagnosing coronary artery diseases, offering a promising tool for real-time, automated analysis in clinical settings. The findings highlight the model's ability to achieve high sensitivity, specificity, and precision, which could significantly improve.

[May Coronary CT-Scan be used as a systematic screening tool for the global population to prevent acute coronary syndrome and ischemic heart failure?]

Coronary CT-Scan permits non-invasive visualization of all stages of coronary artery atherosclerosis allowing early therapeutic interventions, lifestyle changes and accurate follow-up all of which result in an improved prognosis. We discuss the possibility of a systematic coronary CT-scan in the global population at certain ages such as fifty or sixty years-old (or both). May this strategy decrease the onset of myocardial infarction or ischemic chronic heart failure thus improving quality (and quantity) of life? May it also reduce the medical costs for the individual and the society? Is it technically possible to deploy such a strategy? What would be the obstacles for its set up and what solutions might be proposed?

CACS, CCTA and mCAD-LT score in the pre-transplant assessment of coronary artery disease and the prediction of post-transplant cardiovascular events

BACKGROUND

The optimal cardiovascular assessment of liver transplant (LT) candidates is unclear. We aimed to evaluate the performance of CT-based coronary tests (coronary artery calcium score [CACS] and coronary CT angiography [CCTA]) and a modification of the CAD-LT score (mCAD-LT, excluding family history of CAD) to diagnose significant coronary artery disease (CAD) before LT and predict the incidence of post-LT cardiovascular events (CVE).

METHODS

We retrospectively analysed a single-centre cohort of LT candidates who underwent non-invasive tests; invasive coronary angiography (ICA) was performed depending on the results of non-invasive tests. mCAD-LT was calculated in all patients.

RESULTS

Six-hundred-and-thirty-four LT candidates were assessed and 351 of them underwent LT. CACS, CCTA and ICA were performed in 245, 123 and 120 LT candidates, respectively. Significant CAD was found in 30% of patients undergoing ICA. The AUROCs of mCAD-LT (.722) and CCTA (.654) were significantly higher than that of CACS (.502) to predict the presence of significant CAD. Specificity of the tests ranged between 31% for CCTA and 53% for CACS. Among patients who underwent LT, CACS ≥ 400 and mCAD-LT were independently associated with the incidence of CVE; in patients who underwent CCTA before LT, significant CAD at CCTA also predicted post-LT CVE.

CONCLUSION

In this cohort, mCAD-LT score and CT-based tests detect the presence of significant CAD in LT candidates, although they tend to overestimate it. Both mCAD-LT score and CT-based tests classify LT recipients according to their risk of post-LT CVE and can be used to improve post-LT risk mitigation.