Predictor Of Major Adverse Cardiovascular Events Research Articles

Evaluating the Association between Anomalous Aortic Origin of the Right Coronary Artery from the Left Sinus with Interarterial Course at Coronary CT Angiography and Sudden Cardiac Death.

Purpose To investigate the association between the anomalous aortic origin of the right coronary artery (R-AAOCA) from the left coronary sinus with interarterial course (IAC) found at coronary CT angiography and sudden cardiac death using a large data set from five university hospitals. Materials and Methods From a total of 89 314 CCTA scans (January 2009 to December 2016) that were retrospectively collected, 316 patients with R-AAOCA from the left sinus with IAC were retrospectively collected. After excluding patients with less than 2 years of follow-up, patients who had already undergone cardiovascular surgery or intervention, and patients with arrhythmia or heart failure before undergoing coronary CT angiography, 224 patients were analyzed. Follow-up was terminated upon the occurrence of major adverse cardiovascular events (MACE). Logistic regression was used to identify clinical and radiologic information as independent predictors of MACE. Results The period prevalence of R-AAOCA from the left sinus with IAC was 0.354%. The mean age was 62.03 years, with a male-to-female ratio of 182:134. During follow-up, 19 of 224 patients (8.5%) experienced MACE, but none had sudden cardiac death. Of these cases, only seven (3.13%) were suspected of being due to R-AAOCA from the left sinus with IAC and all of them had unstable angina. Coronary artery disease was significantly associated with MACE (P < .001), while no significant correlation was observed with radiologic features. Conclusion Sudden cardiac death was not associated with R-AAOCA from the left sinus with IAC found at coronary CT angiography. The occurrence of MACE was low, with coronary artery disease being the sole significant predictor of a patient's prognosis. Keywords: Anomalous Aortic Origin of the Right Coronary Artery, Left Coronary Sinus with Interarterial Course, Coronary CT Angiography, Sudden Cardiac Death Supplemental material is available for this article. © RSNA, 2024.

Proposal of a novel cardiovascular risk prediction score in lupus nephritis.

Patients with systemic lupus erythematosus are prone to develop cardiovascular disease (CVD), and have increased morbidity and mortality. We conducted a retrospective analysis on lupus nephritis patients to assess the occurrence and predictors of major adverse cardiovascular events (MACE). Data were collected from patients who underwent kidney biopsy between 2005 and 2020. Statistical analysis was performed to unveil correlations. 91 patients were analyzed in this period, with a mean age of 37.3 ± 12.3 years and 86% being female. The mean follow-up time was 62 ± 48 months. 15.38% of the patients underwent at least one MACE. Two patients deceased of CVD. Increased age (35.81 ± 11.14 vs 45.5 ± 15.11 years, p=0.012) entailed a higher occurrence of MACEs. Neutrophil count (5.15 ± 2.83 vs 7.3 ± 2.99 Giga/L, p=0.001) was higher, whereas diastolic blood pressure (DBP) was lower (89.51 ± 10.96 vs 78.43 ± 6.9 mmHg, p<0.001) at the time of the biopsy in patients with MACE. Age, neutrophil count, and DBP proved to be independent predictors of MACEs. We propose a new model (CANDE - Cardiovascular risk based on Age, Neutrophil count, and Diastolic blood pressure Estimation score) calculated from these variables, which predicts the probability of MACE occurrence. This study underscores the importance of actively screening for cardiovascular risks in this vulnerable patient population. Age, neutrophil count, and diastolic blood pressure have been established as independent risk factors for MACE in lupus nephritis. The CANDE score derived from these parameters may serve as a prompt, cost-effective, and easily accessible estimation tool for assessing the likelihood of major adverse cardiovascular risk. These findings emphasize the necessity for comprehensive management strategies addressing both immune dysregulation and cardiovascular risk factors in systemic lupus erythematosus to mitigate adverse outcomes.

The application value of 24 h Holter monitoring indices in predicting MACEs outside the hospital within three years after PCI in patients with STEMI.

Evaluating cardiovascular risk in patients experiencing acute ST-elevation myocardial infarction (STEMI) and undergoing percutaneous coronary intervention (PCI) is crucial for early intervention and improving long-term outcomes. 24 h Holter monitoring provides continuous cardiac electrophysiological data, enabling the detection of arrhythmias and autonomic dysfunction that are not captured during routine examinations. This study aimed to examine the relationship between Holter monitoring metrics and the occurrence of out-of-hospital major adverse cardiovascular events (MACEs) following PCI in patients with STEMI, offering insights into cardiovascular risk evaluation. This prospective cohort study included STEMI patients undergoing PCI. 24 h Holter monitoring data were recorded, including heart rate, heart rate variability (HRV) metrics such as SDNN and SDANN index, heart rate deceleration capacity (DC) at different time scales (DC2, DC4, DC8), and the frequency of premature ventricular contractions (PVCs). Independent correlations between these indices and MACEs, as well as cardiovascular deaths, were investigated using multifactorial logistic regression. Predictive capacities were assessed through receiver operating characteristic (ROC) curves. A total of 172 participants were enrolled in this study. Over the 3-year follow-up period, MACEs were observed in 57 patients, including 20 cases of cardiac death. In logistic regression models adjusted for confounding variables, SDNN [OR: 0.980; 95% CI: (0.967, 0.994); p = 0.005] and SDANN index [OR: 0.982; 95% CI: (0.969, 0.996); p = 0.009] were negatively associated with the incidence of MACEs. Conversely, the slowest heart rate [OR: 1.075; 95% CI: (1.022, 1.131); p = 0.005] and frequent PVCs [OR: 2.685; 95% CI: (1.204, 5.987); p = 0.016] demonstrated a positive association with MACEs. Furthermore, SDNN [OR: 0.957; 95% CI: (0.933, 0.981); p = 0.001], DC [OR: 0. 702; 95% CI: (0.526, 0.938); p = 0.017]) and DC4 [OR: 0.020; 95% CI: (0.001, 0.664); p = 0.029] were negatively associated with cardiac death. The ROC analysis results indicated that SDNN was an effective predictor of both MACEs [AUC: 0.688 (95% CI: 0.601-0.776)] and cardiac death [AUC: 0.752 (95% CI: 0.625-0.879)]. HRV, DC metrics, and frequent PVCs obtained by 24 h Holter monitoring were associated with the risk of MACEs in STEMI patients. These metrics can help clinicians identify at-risk patients early so that timely interventions.

Emergency Department Blood Pressure Treatment and Outcomes in Adults Presenting with Severe Hypertension

Background: Patients who present to the emergency department (ED) with severe hypertension defined as a systolic blood pressure (SBP) ≥180 millimeters of mercury (mm Hg) or diastolic (DBP) ≥120 (mm Hg) without evidence of acute end-organ damage are often deemed high risk and treated acutely in the ED. However, there is a dearth of evidence from large studies with long-term follow-up for the assessment of major adverse cardiovascular events (MACE). We conducted the largest study to date of patients presenting with severe hypertension to identify predictors of MACE and examine whether blood pressure at discharge is associated with heightened risk. Methods: We enrolled ED patients with a SBP of 180–220 mm Hg but without signs of end-organ damage and followed them for one year. The primary outcome was MACE within one year of discharge. Secondarily, we performed a propensity-matched analysis to test whether SBP ≤160 mm Hg at discharge was associated with reduced MACE at 30 days. Results: A total of 12,044 patients were enrolled. The prevalence of MACE within one year was 1,865 (15.5%). Older age, male gender, history of cardiovascular disease, cerebrovascular disease, diabetes, smoking, presentation with chest pain, altered mental status, dyspnea, treatment with intravenous and oral hydralazine, and oral metoprolol were independent predictors for one-year MACE. Additionally, discharge with an SBP ≤160 mm Hg was not associated with 30-day MACE-free survival after propensity matching (hazard ratio 0.99, 95% confidence interval 0.78–1.25, P = 0.92). Conclusion: One-year MACE was relatively common in our cohort of ED patients with severe hypertension without acute end-organ damage. However, discharge blood pressure was not associated with 30-day or one-year MACE, suggesting that BP reduction in and of itself is not beneficial in such patients.

NAFLD and MAFLD independently increase the risk of major adverse cardiovascular events (MACE): a 20-year longitudinal follow-up study from regional Australia

Background and aimsThe association between fatty liver disease (FLD) and cardiovascular disease (CVD) in an Australian context has yet to be defined. The primary aim of this study was to investigate the association between FLD and 3-point major adverse cardiovascular events (MACE).MethodsThis was a longitudinal follow-up study of a randomly sampled adult cohort from regional Australia between 2001 and 2003. Baseline covariates included demographic details, anthropometry, health and lifestyle data, and laboratory tests. Non-alcoholic fatty liver disease (NAFLD) and metabolic-(dysfunction) associated fatty liver disease (MAFLD) were diagnosed in participants with fatty liver index (FLI) ≥ 60 and meeting other standard criteria. ICD-10 codes were used to define clinical outcomes linked to hospitalisations. Three-point MACE defined as non-fatal myocardial infarction (MI) and cerebrovascular accident (CVA) and CVD death.ResultsIn total, 1324 and 1444 participants met inclusion criteria for NAFLD and MAFLD analysis, respectively. Over 23,577 and 25,469 person-years follow-up, NAFLD and MAFLD were independent predictors for 3-point MACE, adjusting for demographic covariates and known cardiometabolic risk factors, whilst considering non-CVD death as a competing event (NAFLD: sub-hazard ratio [sHR] 1.56, 95% confidence interval [CI 1.12–2.19]; MAFLD: sHR 1.51, 95% CI 1.11–2.06). The results held true on several sensitivity analyses.ConclusionsBoth forms of FLD increase the risk for CVD independent of traditional cardiometabolic risk factors.

The Predictive Value of Aortic Calcification on Computed Tomography for Major Cardiovascular Events.

As the prevalence of cardiovascular disease continues to increase, early identification of patients at high risk of major adverse cardiovascular events (MACE) using reliable diagnostic modalities is important. Transcatheter aortic valve implantation (TAVI) is a minimally invasive percutaneous procedure used to replace the aortic valve with a bioprosthetic one, often without the need for surgery. Extra coronary calcification in the ascending and/or descending thoracic aorta, aortic arch, and abdominal aorta has recently been identified as a method to quantify the extent of atherosclerotic cardiovascular disease. However, its definitive role in the prediction of MACE remains unclear. We performed a comprehensive review to summarize the current literature on the diagnostic and predictive value of thoracic and abdominal aortic calcification, as quantified in computed tomography, for the association, risk stratification, and prediction of MACE and after TAVI procedures. Despite increasing evidence, the predictive role of thoracic calcification still remains unproven, with a need for carefully tailored studies to confirm these findings.

Brain natriuretic peptide is a long-term cardiovascular predictor in carotid endarterectomy

Background In noncardiac surgery, several biomarkers are known to play a role in predicting long-term complications, such as major adverse cardiovascular events (MACE), myocardial infarction, or death. Carotid endarterectomy (CEA) is considered a low to medium-risk surgery for carotid stenosis aimed at preventing stroke events. Brain natriuretic peptide (BNP) is a biomarker with potential prognostic value regarding MACE. Since its role in patients undergoing CEA is unknown, this study aims to assess the potential role of BNP as a short and long-term predictor of all-cause mortality and MACE in patients undergoing CEA. Methods From a prospective database, patients who underwent CEA under regional anesthesia (RA) at a tertiary hospital center were enrolled, and a post hoc analysis was conducted. Patients on which BNP levels were measured up to fifteen days before surgery, and two groups based on the BNP threshold (200 pg/mL) were defined and compared. Kaplan Meier survival curves and adjusted hazard ratios (aHR) were assessed by multivariable Cox regression. The primary outcome was the incidence of long-term MACE and all-cause mortality. Secondary outcomes included the incidence of AMI and AHF. Results A total of 89 patients were evaluated. The mean age of the cohort was 71.2 ± 8.7 years, with 71 (79.8%) males, and presented a median follow-up of 30 [13.5–46.4] months. BNP > 200 pg/mL has demonstrated positive predictive value for MACE (aHR: 5.569, confidence interval (CI): 2.441–12.7, p < 0.001) and all-cause mortality (aHR: 3.469, CI: 1.315–9.150, p = 0.018). Conclusion BNP has been demonstrated to independently predict long-term all-cause mortality, MACE and AMI following CEA. It serves as a low-cost, ready-to-use biomarker, although further studies are necessary.

The predictive value of mBDNF for major adverse cardiovascular events in stable coronary artery disease patients with depressive symptoms: A single-center, 5-year follow-up study

BackgroundMyokines play vital roles in both stable coronary artery disease (SCAD) and depression. Meanwhile, there is a pressing necessity to find effective biomarkers for early predictor of major adverse cardiovascular events (MACE) in SCAD patients with depressive symptoms. MethodsA single-center, 5-year follow-up study was investigated. MACE was defined as composite end points, including cardiovascular death, non-fatal stroke, non-fatal myocardial infarction, coronary artery revascularization, or hospitalization for unstable angina. ResultsA total of 116 SCAD patients were enrolled, consisting of 30 cases (25.9%) without depressive symptoms and 86 cases (74.1%) with depressive symptoms. During the follow-up, 3 patients (2.6%) were lost. Out of 113 patients, 51 (45.1%) experienced MACE. In the subgroup of 84 SCAD patients with depressive symptoms, 44 cases (52.4%) of MACE were observed. Finally, mature brain-derived neurotrophic factor (mBDNF), pro-brain-derived neurotrophic factor, receptor activator of nuclear factor-κB ligand, smoking history, hypertension and cystatin C were incorporated into the predictive model. ConclusionsDepressive symptoms represent an independent risk factor for MACE in patients with SCAD. Additionally, low mBDNF expression may be an important early predictor for MACE in SCAD patients with depressive symptoms. The predictive model may exhibit a commendable predictive performance for MACE in SCAD patients with depressive symptoms.

Prognostic value of myocardial deformation parameters for outcome prediction in tetralogy of Fallot

The prognostic value of myocardial deformation parameters in adults with repaired tetralogy of Fallot (rTOF) has not been well-elucidated. We therefore aimed to explore myocardial deformation parameters for outcome prediction in adults with rTOF using cardiovascular magnetic resonance imaging (CMR). Adults with rTOF and at least moderate pulmonary regurgitation (PR) were identified from an institutional prospective CMR registry. Left (LV) and right ventricular (RV) global strain were recorded in longitudinal (GLS), circumferential (GCS) and radial (GRS) directions. Major adverse cardiovascular events (MACE) were defined as a composite of mortality, resuscitated sudden death, sustained ventricular tachycardia (>30seconds) or heart failure (hospital admission >24hours). In patients with pulmonary valve replacement (PVR), pre-and post-PVR CMR studies were analysed to assess for predictors of complete RV reverse remodelling, which we defined as RV end-diastolic volume indexed (RVEDVi) <110ml/m2. Logistic regression models were used to estimate the odds ratio (OR) per unit change in absolute strain value associated with clinical outcomes and receiver operator characteristic (ROC) curves were constructed with area under the curve (AUC) for select CMR variables. We included 307 patients (age 35±13 years, 59% male). During 6.1 years (3.3-8.8) of follow-up, pulmonary valve replacement (PVR) was performed in 142 (46%) and MACE occurred in 31 (10%). On univariate analysis, baseline biventricular ejection fraction (EF), mass and all strain parameters were associated with MACE. After adjustment for LVEF, only LVGLS remained independently predictive of MACE (OR 0.822 [0.693-0.976] p=0.025). Receiver operator curves identified an absolute LVGLS value less than 15 and LVEF <51% as thresholds for MACE prediction (AUC 0.759 [0.655-0.840] and 0.720 [0.608-0.810]). After adjusting for baseline RVEDVi, RVGCS (OR 1.323 [1.094-1.600] p=0.004), LVGCS (OR 1.276 [1.029-1.582] p=0.027) and LVGRS (OR 1.101 [1.0210-1.200], p=0.028) were independent predictors of complete remodelling post-PVR remodelling. Biventricular strain parameters predict clinical outcomes and post-PVR remodelling in rTOF. Further study will be necessary to establish the role of myocardial deformation parameters in clinical practice.

Machine Learning in Hypertrophic Cardiomyopathy: Nonlinear Model From Clinical and CMR Features Predicting Cardiovascular Events

BackgroundThe cumulative burden of hypertrophic cardiomyopathy (HCM) is significant, with a noteworthy percentage (10%-15%) of patients with HCM per year experiencing major adverse cardiovascular events (MACEs). A current risk stratification scheme for HCM had only limited accuracy in predicting sudden cardiac death (SCD) and failed to account for a broader spectrum of adverse cardiovascular events and cardiac magnetic resonance (CMR) parameters. ObjectivesThis study sought to develop and evaluate a machine learning (ML) framework that integrates CMR imaging and clinical characteristics to predict MACEs in patients with HCM. MethodsA total of 758 patients with HCM (67% male; aged 49 ± 14 years) who were admitted between 2010 and 2017 from 4 medical centers were included. The ML model was built on the internal discovery cohort (533 patients with HCM, admitted to Fuwai Hospital, Beijing, China) by using the light gradient-boosting machine and internally evaluated using cross-validation. The external test cohort consisted of 225 patients with HCM from 3 medical centers. A total of 14 CMR imaging features (strain and late gadolinium enhancement [LGE]) and 23 clinical variables were evaluated and used to inform the ML model. MACEs included a composite of arrhythmic events, SCD, heart failure, and atrial fibrillation–related stroke. ResultsMACEs occurred in 191 (25%) patients over a median follow-up period of 109.0 months (Q1-Q3: 73.0-118.8 months). Our ML model achieved areas under the curve (AUCs) of 0.830 and 0.812 (internally and externally, respectively). The model outperformed the classic HCM Risk-SCD model, with significant improvement (P < 0.001) of 22.7% in the AUC. Using the cubic spline analysis, the study showed that the extent of LGE and the impairment of global radial strain (GRS) and global circumferential strain (GCS) were nonlinearly correlated with MACEs: an elevated risk of adverse cardiovascular events was observed when these parameters reached the high enough second tertiles (11.6% for LGE, 25.8% for GRS, −17.3% for GCS). ConclusionsML-empowered risk stratification using CMR and clinical features enabled accurate MACE prediction beyond the classic HCM Risk-SCD model. In addition, the nonlinear correlation between CMR features (LGE and left ventricular pressure gradient) and MACEs uncovered in this study provides valuable insights for the clinical assessment and management of HCM.

Risk factors for MACE and bleeding in atrial fibrillation patients undergoing surgery: Insights from the bridge trial

IntroductionPatients with atrial fibrillation (AF) undergoing elective procedures are at risk for Major Adverse Cardiovascular Events (MACE) and symptomatic bleeding. We aimed to identify risk factors to guide perioperative risk stratification. MethodsWe conducted a post-hoc analysis of the “Bridging Anticoagulation in Patients who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery” randomized trial. The primary outcomes were MACE and symptomatic bleeding. Our statistical approach encompassed standard univariate analysis, logistic stepwise regression, and Cox regression models. Additional interaction analyses evaluated the interplay between low-molecular-weight heparin bridge therapy and other identified risk factors. ResultsAmong a total of 1,813 participants (mean age 71.6 ± 8.8, 73.3 % male), MACE occurred in 25 (1.4 %) individuals, with pre-procedure clopidogrel use (adjusted hazard ratio [aHR] 7.73, 95 % CI 2.63-22.72, p < 0.001) and CHA2DS2-VASc score ≥ 5 (aHR 2.89, 95 % CI 1.26-6.63, p = 0.012) identified as risk factors. Symptomatic bleeding occurred in 57 (3.1 %) individuals, with bridge therapy (aHR 1.84, 95 % CI 1.07-3.19, p = 0.029), renal disease (aHR 2.50, 95 % CI 1.34-4.67, p = 0.004), post-procedure aspirin use (aHR 2.86, 95 % CI 1.66-4.91, p < 0.001), post-procedure nonsteroidal anti-inflammatory drug use excluding aspirin (aHR 3.40, 95 % CI 1.22-9.43, p = 0.019), and major surgery (aHR 3.94, 95 % CI 2.26-6.85, p < 0.001) identified as risk factors. The interactions between risk factors and bridging therapy on MACE and symptomatic bleeding outcomes were not significant (p > 0.05). ConclusionWe identified predictors for MACE and symptomatic bleeding in AF patients undergoing elective procedures. These insights may help guide perioperative decisions to reduce the risk of adverse outcomes.

Eicosapentaenoic Acid and the Outcomes in Older Patients Undergoing Atrial Fibrillation Ablation.

A lower serum eicosapentaenoic acid (EPA) to arachidonic acid (AA) ratio (EPA/AA) level correlates with cardiovascular events. Nevertheless, elevated serum EPA levels increase the risk of new-onset atrial fibrillation (AF) in older patients. The relationship between the EPA/AA and outcomes post-AF ablation remains unclear. This study investigated the impact of the EPA/AA on AF recurrence and cardiovascular events after AF ablation in older patients. This retrospective cohort study examined consecutive patients with AF aged ≥65 years who underwent a first-time AF ablation. We compared the 3-year AF recurrence and 5-year major adverse cardiovascular event (MACE) rates between patients divided into high and low EPA/AA levels defined as above and below the median EPA/AA value before ablation. MACE was defined as heart failure hospitalizations, strokes, coronary artery disease, major bleeding, and cardiovascular death. Among the 673 included patients, the median EPA/AA value was 0.35. Compared with the low EPA/AA group, the high EPA/AA group had a significantly higher cumulative incidence of AF recurrence (39.3% versus 27.6%; log-rank P=0.004) and lower cumulative incidence of MACE (13.8% versus 25.5%, log-rank P=0.021). A high EPA/AA level was determined as an independent predictor of AF recurrence (hazard ratio [HR], 1.75 95% CI, 1.24-2.49; P=0.002) and MACE (HR, 0.60 [95% CI, 0.36-0.99]; P=0.046). The EPA/AA was associated with AF recurrence and MACE after ablation in patients with AF aged ≥65 years.

Peri-coronary fat attenuation index combined with high-risk plaque characteristics quantified from coronary computed tomography angiography for risk stratification in new-onset chest pain individuals without acute myocardial infarction.

This study aims to evaluate the role of the peri-coronary Fat Attenuation Index (FAI) and High-Risk Plaque Characteristics (HRPC) in the assessment of coronary heart disease risk. By conducting coronary CT angiography and coronary angiography on 217 patients with newly developed chest pain (excluding acute myocardial infarction), their degree of vascular stenosis, FAI, and the presence and quantity of HRPC were assessed. The study results demonstrate a correlation between FAI and HRPC, and the combined use of FAI and HRPC can more accurately predict the risk of major adverse cardiovascular events (MACE). Additionally, the study found that patients with high FAI were more prone to exhibit high-risk plaque characteristics, severe stenosis, and multiple vessel disease. After adjustment, the combination of FAI and HRPC improved the ability to identify and reclassify MACE. Furthermore, the study identified high FAI as an independent predictor of MACE in patients undergoing revascularization, while HRPC served as an independent predictor of MACE in patients not undergoing revascularization. These findings suggest the potential clinical value of FAI and HRPC in the assessment of coronary heart disease risk, particularly in patients with newly developed chest pain excluding acute myocardial infarction.

Coronary computed tomography angiography-derived total coronary plaque burden associated with subsequent cardiovascular outcomes following percutaneous coronary intervention.

To investigate the association of coronary plaque burden variables derived from coronary computed tomography angiography (CCTA) before patients underwent their first percutaneous coronary intervention (PCI) procedure and major adverse cardiovascular events (MACEs) after PCI. Patients who underwent CCTA before their first PCI were included retrospectively. A radiologist and a cardiologist analyzed CCTA images on a dedicated workstation. The coronary plaque burden variables included total plaque volume, total percent atheroma volume, volumes and fractions of total low-attenuation plaque, total fibrous plaque, and total calcified plaque. The primary outcomes were MACEs, a composite of all-cause death, nonfatal myocardial infarction, nonfatal stroke, and unscheduled coronary revascularization. A total of 230 patients were included in the final analysis. During a median follow-up of 4.8 years, 67 MACEs occurred. Total plaque volume, total percent atheroma volume, volumes of total low-attenuation plaque and total fibrous plaque but not their fractions were independent predictors for MACEs. Compared with the first tertiles, the hazard ratio of the third tertile of total plaque volume, total percent atheroma volume, total low-attenuation plaque volume, and total fibrous plaque volume were 2.06 (95% CI: 1.03-4.15), 2.15 (95% CI: 1.02-4.51), 3.04 (95% CI: 1.45-6.36), and 2.23 (95% CI: 1.11-4.46), respectively. Neither total calcified plaque volume nor fraction was associated with MACEs independently. Selected pre-PCI CCTA-derived variables, including total percent atheroma volume, volumes of total plaque, total low-attenuation plaque and total fibrous plaque, were significantly associated with MACEs after PCI, suggesting that CCTA before PCI reveals the residual risk after revascularization. The coronary plaque burden variables derived from coronary computed tomography angiography before percutaneous coronary intervention are independently associated with major adverse cardiovascular events, which could be instrumental in optimizing patient management. Coronary plaque burden is associated with cardiovascular events in patients with coronary artery disease. Selected total plaque burden variables derived from coronary computed tomography angiography before percutaneous coronary intervention were associated with poor prognosis. Routine coronary computed tomography angiography before percutaneous coronary intervention might be helpful in reducing future risks.

Predicting major adverse cardiovascular events within 3 years by optimization of radiomics model derived from pericoronary adipose tissue on coronary computed tomography angiography: a case-control study

BackgroundCoronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years.MethodsThis retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness.ResultsThe diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit.ConclusionThe CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

Coronary artery disease severity and risk stratification of patients with non ST-elevation acute coronary syndrome using CHA2DS2-VASc-HSF score

BackgroundRisk stratification assessment of patients with non-ST elevation acute coronary syndrome (NSTE ACS) plays an important role in optimal management and defines the patient’s prognosis. This study aimed to evaluate the ability of CHA2DS2-VASc-HSF score (comprising of the components of the CHA2DS2-VASc score with a male instead of female sex category, hyperlipidemia, smoking, and family history of coronary artery disease respectively) to predict the severity and complexity of CAD and its efficacy in stratification for major adverse cardiovascular events (MACE) in patients with NSTE ACS without known atrial fibrillation.MethodsThis study included 200 patients (males 72.5%, mean age 55.8 ± 10.1 years) who were admitted with NSTE ACS. CHA2DS2-VASC-HSF score was calculated on admission. Patients were classified into three groups according to their CHA2DS2-VASC-HSF score: low score group (< 2; 29 patients), intermediate score group (2–4; 83 patients), and high score group (≥ 5; 88 patients). Coronary angiography was conducted and the Syntax score (SS) was calculated. Clinical follow-up at 6 months of admission for the development of MACE was recorded.ResultsSS was significantly high in the high CHA2DS2-VASc-HSF score group compared with low and intermediate score groups. CHA2DS2-VASc-HSF score had a significant positive strong correlation with syntax score (r = 0.64, P < 0.001). Smoking, vascular disease, hyperlipidemia, and CHA2DS2-VASc-HSF score were independent predictors of high SS. For the prediction of severe and complex CAD, CHA2DS2-VASc-HSF score had a good predictive power at a cut-off value ≥ 5 with a sensitivity of 86% and specificity of 65%. Hypertension, vascular disease, high SS, and CHA2DS2-VASc-HSF score were independent predictors of MACE. CHA2DS2-VASC-HSF score ≥ 4 was identified as an effective cut-off point for the development of MACE with 94% sensitivity and 70% specificity.ConclusionsCHA2DS2-VASC-HSF score is proposed to be a simple bedside score that could be used for the prediction of the severity and complexity of CAD as well as a risk stratification tool for the development of MACE in NSTE ACS patients.

Assessing Glycosylated Hemoglobin Thresholds for Development of Cardiovascular Disease by Racial and Ethnic Groups.

Diabetes is the strongest risk factor for cardiovascular disease, and although glycosylated hemoglobin (HbA1c) levels are known to vary by race, no racial and ethnic-specific diagnostic thresholds exist for diabetes in prediction of cardiovascular disease events. The purpose of this study is to determine whether HbA1c thresholds for predicting major adverse cardiovascular events (MACEs) differ among racial and ethnic groups. This is a retrospective cohort study of Kaiser Permanente Northern California adult members (n=309 636) with no history of cardiovascular disease who had HbA1c values and race and ethnicity data available between 2014 and 2019. Multivariable logistic regression was used to evaluate the odds of MACEs by the following racial and ethnic groups: Filipino, South Asian, East Asian, Black, White, and Hispanic. A Youden index was used to calculate HbA1c thresholds for MACE prediction by each racial and ethnic group, stratified by sex. Among studied racial and ethnic groups, South Asian race was associated with the greatest odds of MACEs (1.641 [95% CI, 1.456-1.843]; P<0.0001). HbA1c was a positive predictor for MACEs, with an odds ratio of 1.024 (95% CI, 1.022-1.025) for each 0.1% increment increase in HbA1c. HbA1c values varied between 6.0% and 7.6% in MACE prediction by race and ethnicity and sex. White individuals, South Asian individuals, East Asian women, and Black men had HbA1c thresholds for MACE prediction in the prediabetic range, between 6.0% and 6.2%. Black women, Hispanic men, and East Asian men had HbA1c thresholds of 6.2% to 6.6%, less than the typical threshold of 7.0% that is used as a treatment goal. Findings suggest that the use of race and ethnic- and sex-specific HbA1c thresholds may need to be considered in treatment goals and cardiovascular disease risk estimation.

The Role of QRS Complex and ST-Segment in Major Adverse Cardiovascular Events Prediction in Patients with ST Elevated Myocardial Infarction: A 6-Year Follow-Up Study.

as a relatively high number of ST-segment elevation myocardial infarction (STEMI) patients develop major adverse cardiovascular events (MACE) following percutaneous coronary intervention (PCI), our aim was to determine the significance, and possible predictive value of QRS complex width and ST-segment elevation. our patient sample included 200 PCI-treated STEMI patients, which were divided into two groups based on the following duration of symptoms: (I) less than 6 h, and (II) 6 to 12 h. For every patient, an ECG was performed at six different time points, patients were followed for up to six years for the occurrence of MACE. the mean age was 60.6 ± 11.39 years, and 142 (71%) were male. The 6-12 h group had significantly wider QRS complex, higher ST-segment elevation, lower prevalence of ST-segment resolution as well as MACE prevalence (p < 0.05). ECG parameters, QRS width, and magnitude of ST-segment elevation were proved to be independent significant predictors of MACE in all measured time points (p < 0.05). Even after controlling for biomarkers of myocardial injury, these ECG parameters remained statistically significant predictors of MACE (p < 0.05). our study highlights that wider QRS complex and a more pronounced ST-segment elevation are associated with longer total ischemic time and higher risk of long-term MACE.

Insulin resistance, coronary artery lesion complexity and adverse cardiovascular outcomes in patients with acute coronary syndrome

BackgroundInsulin resistance (IR) is linked to both the complexity of coronary artery lesions and the prognosis of acute coronary syndrome (ACS). However, the precise extent of this correlation and its impact on adverse cardiovascular outcomes in ACS patients remain unclear. Therefore, this study aims to investigate the intricate relationship between IR, coronary artery lesion complexity, and the prognosis of ACS through a cohort design analysis.MethodA total of 986 patients with ACS who underwent percutaneous coronary intervention (PCI) were included in this analysis. IR was assessed using the triglyceride-glucose (TyG) index, while coronary artery lesion complexity was evaluated using the SYNTAX score. Pearson’s correlation coefficients were utilized to analyze the correlations between variables. The association of the TyG index and SYNTAX score with major adverse cardiovascular events (MACEs) in ACS was investigated using the Kaplan-Meier method, restricted cubic splines (RCS), and adjusted Cox regression. Additionally, a novel 2-stage regression method for survival data was employed in mediation analysis to explore the mediating impact of the SYNTAX score on the association between the TyG index and adverse cardiovascular outcomes, including MACEs and unplanned revascularization.ResultsDuring a median follow-up of 30.72 months, 167 cases of MACEs were documented, including 66 all-cause deaths (6.69%), 26 nonfatal myocardial infarctions (MIs) (2.64%), and 99 unplanned revascularizations (10.04%). The incidence of MACEs, all-cause death, and unplanned revascularization increased with elevated TyG index and SYNTAX score. Both the TyG index (non-linear, P = 0.119) and SYNTAX score (non-linear, P = 0.004) displayed a positive dose-response relationship with MACEs, as illustrated by the RCS curve. Following adjustment for multiple factors, both the TyG index and SYNTAX score emerged as significant predictors of MACEs across the total population and various subgroups. Mediation analysis indicated that the SYNTAX score mediated 25.03%, 18.00%, 14.93%, and 11.53% of the correlation between the TyG index and MACEs in different adjusted models, respectively. Similar mediating effects were observed when endpoint was defined as unplanned revascularization.ConclusionElevated baseline TyG index and SYNTAX score were associated with a higher risk of MACEs in ACS. Furthermore, the SYNTAX score partially mediated the relationship between the TyG index and adverse cardiovascular outcomes.

Contemporary Predictors of Major Adverse Cardiovascular Events Following Percutaneous Coronary Intervention: A Nationally Representative US Sample.

Background: Patient outcomes after percutaneous coronary intervention (PCI) have improved over the last 30 years due to better techniques, therapies, and care processes. This study evaluated contemporary predictors of post-PCI major adverse cardiovascular events (MACE) and summarized risk in a parsimonious risk prediction model. Methods: The Cardiovascular Patient-Level Analytical Platform (CLiPPeR) is an observational dataset of baseline variables and longitudinal outcomes from the American College of Cardiology's CathPCI Registry® and national claims data. Cox regression was used to evaluate 2-6 years of patient follow-up (mean: 2.56 years), ending in December 2017, after index PCI between 2012 and 2015 (N = 1,450,787), to examine clinical and procedural predictors of MACE (first myocardial infarction, stroke, repeat PCI, coronary artery bypass grafting, and mortality). Cox analyses of post-PCI MACE were landmarked 28 days after index PCI. Results: Overall, 12.4% (n = 179,849) experienced MACE. All variables predicted MACE, with cardiogenic shock, cardiac arrest, four diseased coronary vessels, and chronic kidney disease having hazard ratios (HRs) ≥ 1.50. Other major predictors of MACE were in-hospital stroke, three-vessel disease, anemia, heart failure, and STEMI presentation. The index revascularization and discharge prescription of aspirin, P2Y12 inhibitor, and lipid-lowering medication had HR ≤ 0.67. The primary Cox model had c-statistic c = 0.761 for MACE versus c = 0.701 for the parsimonious model and c = 0.752 for the parsimonious model plus treatment variables. Conclusions: In a nationally representative US sample of post-PCI patients, predictors of longitudinal MACE risk were identified, and a parsimonious model efficiently encapsulated them. These findings may aid in assessing care processes to further improve care post-PCI outcomes.