Management and outcomes of spontaneous coronary artery dissection: a systematic review of the literature.

Background: Contemporary management of spontaneous coronary artery dissection (SCAD) is still controversial. This systematic review of the literature aims to explore outcomes in the patients treated with conservative management vs. invasive strategy. Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed when we extensively searched three electronic databases: PubMed, ScienceDirect, and Web of Science, for studies that compared conservative vs. invasive revascularization treatment outcomes for patients with SCAD from 2003 to 2023. The outcomes of interest were all-cause death and major adverse cardiovascular events (MACE), including acute coronary syndrome (ACS), heart failure (HF), need for additional revascularization, target vessel revascularization (TVR), SCAD recurrence, and stroke. Results: The systematic review included 13 observational studies evaluating 1,801 patients with SCAD. The overall mean age was 49.12 +/- 3.41, and 88% were females. The overall prevalence of arterial hypertension was 33.2%, hyperlipidemia, 26.9%, smoking, 17.8%, and diabetes, 3.9%. Approximately 48.5% of the patients were diagnosed with non-ST elevated myocardial infarction (NSTEMI), 36.8% with ST elevated myocardial infarction (STEMI), 3.41% with unstable angina, 0.56% with stable angina, and 0.11% were diagnosed with various types of arrhythmias. The left anterior descending artery (LAD) was the most common culprit lesion in 51% of the patients. There were initially 65.2% of conservatively treated patients vs. 33.4% that underwent percutaneous coronary intervention (PCI) or 1.28% that underwent coronary artery bypass graft (CABG). SCAD-PCI revascularization was associated with a variable range of PCI failure. The most common complications were hematoma extension and iatrogenic dissection. SCAD-PCI revascularization frequently required three or more stents and had residual areas of dissection. The overall reported in-hospital and follow-up mortality rates were 1.2% and 1.3%, respectively. The follow-up range across studies was 7.3-75.6 months. The authors reported variable prevalence of MACE, recurrent SCAD up to 31%, ACS up to 27.4%, TVR up to 30%, repeat revascularization up to 14.7%, UA up to 13.3%, HF up to 17.4%, and stroke up to 3%. Conclusion: Our results highlight that conservative treatment should be the preferred method of treatment in patients with SCAD. PCI revascularization is associated with a high prevalence of periprocedural complications. SCAD poses a considerable risk of MACE, mainly associated with TVR, ACS, and recurrent SCAD.

Data processing pipeline for cardiogenic shock prediction using machine learning.

Introduction: Recent advances in machine learning provide new possibilities to process and analyse observational patient data to predict patient outcomes. In this paper, we introduce a data processing pipeline for cardiogenic shock (CS) prediction from the MIMIC III database of intensive cardiac care unit patients with acute coronary syndrome. The ability to identify high-risk patients could possibly allow taking pre-emptive measures and thus prevent the development of CS. Methods: We mainly focus on techniques for the imputation of missing data by generating a pipeline for imputation and comparing the performance of various multivariate imputation algorithms, including k-nearest neighbours, two singular value decomposition (SVD)-based methods, and Multiple Imputation by Chained Equations. After imputation, we select the final subjects and variables from the imputed dataset and showcase the performance of the gradient-boosted framework that uses a tree-based classifier for cardiogenic shock prediction. Results: We achieved good classification performance thanks to data cleaning and imputation (cross-validated mean area under the curve 0.805) without hyperparameter optimization. Conclusion: We believe our pre-processing pipeline would prove helpful also for other classification and regression experiments.

Regional differences in presentation characteristics, use of treatments and outcome of patients with cardiogenic shock: Results from multicenter, international registry.

BACKGROUND: Concurrent evidence about cardiogenic shock (CS) characteristics, treatment and outcome does not represent a global spectrum of patients and is therefore limited. The aim of this study was to investigate these regional differences. METHODS: To investigate regional differences in presentation characteristics, treatments and outcomes of patients treated with all types of cardiogenic shock (CS) in a single calendar year on a multi-national level. Consecutive patients from 19 tertiary care hospitals in 13 countries with CS who were treated between January 1, 2018 and December 31, 2018 were enrolled in this study. RESULTS: In total, 699 cardiogenic shock patients were included in this study. Of these patients, 440 patients (63%) were treated in European hospitals and 259 (37%) were treated in Non-European hospitals. Female patients (P<0.01) and patients with a previous myocardial infarction (P=0.02) were more likely to present at Non-European hospitals; whereas older patients (P=0.01) and patients with cardiogenic shock due to acute heart failure (P<0.01) were more likely to present at European hospitals. Vasopressor use was more likely in Non-European hospitals (P=0.04), whereas use of mechanical circulatory support (MCS) was more likely in European hospitals (P<0.01). Despite adjustment for relevant confounders, 30-day in-hospital mortality risk was comparably high in CS patients treated in European vs. Non-European hospitals (hazard ratio 1.08, 95% CI 0.84-1.39, P=0.56). CONCLUSION: Despite marked heterogeneity in characteristics and treatment of CS patients, including fewer use of MCS but more frequent use of vasopressors in Non-European hospitals, 30-day in-hospital mortality did not differ between regions.

DATA MINING APPROACH FOR IN-HOSPITAL TREATMENT OUTCOME IN PATIENTS WITH ACUTE CORONARY SYNDROME.

INTRODUCTION: Risk stratification is nowadays crucial when estimating the patient's prognosis in terms of treatment outcome and it also helps in clinical decision making. Several risk assessment models have been developed to predict short-term outcomes in patients with acute coronary syndrome. This study was aimed at developing an outcome prediction model for patients with acute coronary syndrome submitted to percutaneus coronary intervention using data mining approach. MATERIAL AND METHODS: A total of 2030 patients hospitalized for acute coronary syndrome and treated with percutaneous coronary intervention from December 2008 to December 2011 were assigned to a derivation cohort. Demographic and anamnestic data, clinical characteristics on admission, biochemical analysis of blood parameters on admission, and left ventricular ejection fraction formed the basis ofthe study. A number of machine learning algorithms available within Waikato Environment for Knowledge Discovery had been evaluated and the most successful was chosen. The predictive model was subsequently validated in a different population of 931 patients (validation cohort), hospitalized during 2012. RESULTS: The best prediction results were achieved using Alternating Decision Tree classifier, which was able to predict in-hospital mortality with 89% accuracy, and preserved good performance on validation cohort with 87% accuracy. Alternating Decision Tree classifier identified a subset of 6 attributes most relevant to mortality prediction: systolic and diastolic blood pressure, heart rate, left ventricular ejection fraction, age, and troponin value. CONCLUSION: Data mining approach enabled the authors to develop a model capable of predicting the in-hospital outcome following percutaneous coronary intervention. The model showed excellent sensitivity and specificity during internal validation.

THE LEVEL OF GRAMMAR SCHOOL STUDENTS' KNOWLEDGE ON CARDIOVASCULAR DISEASE RISK FACTORS.

INTRODUCTION: Cardiovascular diseases are one of the leading causes of mortality and morbidity worldwide. The atherosclerotic process in the aorta starts in childhood, while atheroclerotic changes of coronary heart vessels start in adolescence. The aim of the study was to evaluate the knowledge of the students attending all four grades of grammar school about the risk factors for cardiovascular disease, with special attention to the risk factors that can be influenced by modification of life-style. MATERIAL AND METHODS: Data from the entrance and exit tests were collected from 197 students attending a grammar school in Novi Sad. Chi-square test and Student T-test or Mann-Whitney U test were used to examine the statistical difference between categorized variables and the continuous variables, respectively. RESULTS: The difference between the number of correct answers for all the students on the entrance test and exit test was statistically significant (p<0.0005) and the overall knowledge level after lectures was increased by 29.4%. The lowest level of knowledge on the entrance tests was noted among the students of the third grade of grammar school and after the lectures, the student's knowledge level was increased by 82.3% (p<0.0005). CONCLUSION: Children and adolescents from Vojvodina and Serbia should be well informed about the cardiovascular disease risk factors and their prevention with special attention paid to the risk factors that can be influenced by changing lifestyle habits.

Locally derived system for cardiac operative risk evaluation.

INTRODUCTION: During the last two decades, many authors have found that European Systems for Cardiac Operative Risk Evaluation (additive and logistic models) overestimate the risk in cardiac surgery. The new European model has recently been introduced as an update to previous versions. The aim of the study was to investigate the significance of locally derived system for cardiac operative risk evaluation and to compare its predictive power with the existing European systems. MATERIAL AND METHODS: For developing a local risk prediction model, data from 2681 patients submitted to cardiac surgery at the Institute of Cardiovascular Diseases Vojvodina have thoroughly been collected. Logistic regression analysis was used to construct a local model for prediction of outcome. The evaluation of the local model and three European systems was performed by comparing the observed and expected hospital mortality. RESULTS: The difference between the predicted and observed mortality regardless of the type of surgery was statistically insignificant for the additive European system (p=0.073) and the local model (p=0.134). The logistic European system overestimated the operative risk, while the new European model underestimated mortality. In coronary surgery, all models, except the logistic European system, performed well. In valvular surgery, the new European model and the local model underestimated mortality significantly, while the additive and logistic European models performed well. In combined surgery, the new European system significantly underestimated mortality (p=0.029), while the local model performed well (p=0.252). CONCLUSION: The locally derived model shows satisfactory results, with good calibration and discriminative power. The local model specifically outperforms all other European systems in terms of discriminatory power in combined surgery subset.