Predictor Of Cardiovascular Events Research Articles

COPD Subtypes Are Differentially Associated With Cardiovascular Events and COPD Exacerbations

The coronary artery calcium score (CACS) and ratio of the pulmonary artery to aorta diameters (PA:A ratio) measured from chest CT scans have been established as predictors of cardiovascular events and COPD exacerbations, respectively. However, little is known about the reciprocal relationship between these predictors and outcomes. Furthermore, the prognostic implications of COPD subtypes on clinical outcomes remain insufficiently characterized. How can these two chest CT scan-derived parameters predict subsequent cardiovascular events and COPD exacerbations in different COPD subtypes? Using COPDGene study data, we assessed prospective cardiovascular disease (CVD) and COPD exacerbation risk in patients with COPD (Global Initiative for Chronic Obstructive Lung Disease spirometric grades 2-4), focusing on CACS and PA:A ratio at study enrollment, with logistic regression models. These outcomes were analyzed in three COPD subtypes: 1,042 patients with non-emphysema-predominant disease (NEPD) (low attenuation area at-950 Hounsfield units [LAA-950]< 5%), 1,324 patients with emphysema-predominant disease (EPD) (LAA-950≥ 10%), and 465 patients with intermediate emphysema disease (5%≤ LAA-950< 10%). Our study indicated significantly higher overall risk for cardiovascular events in patients with higher CACS (≥ median; OR, 1.61; 95%CI, 1.30-2.00) and increased COPD exacerbations in those with higher PA:A ratios (≥ 1; OR, 1.80; 95%CI, 1.46-2.23). Notably, patients with NEPD showed a stronger association between these indicators and clinical events than those with EPD (with CACS/CVD, NEPD vsEPD: OR, 2.02 vs1.41; with PA:A ratio/COPD exacerbation, NEPD vsEPD: OR, 2.50 vs1.65); the difference in ORs between COPD subtypes was statistically significant for CACS/CVD. Two chest CT scan parameters, CACS and PA:A ratio, hold distinct predictive values for cardiovascular events and COPD exacerbations that are influenced by specific COPD subtypes. ClinicalTrials.gov; No.: NCT00608764; URL: www. gov.

R2-CHA2DS2-VASc Score for Cardiovascular Event Prediction After Bioprosthetic Valve Replacement - Subanalysis From the BPV-AF Registry.

There are few studies evaluating the prognostic prediction method in atrial fibrillation (AF) patients after bioprosthetic valve (BPV) replacement. The R2-CHA2DS2-VASc score is increasingly used for the prediction of cardiovascular (CV) events in patients with AF, device implantation, and acute coronary syndrome. We aimed to evaluate the predictive value of the R2-CHA2DS2-VASc score for future CV events in AF patients after BPV replacement. The BPV-AF, an observational, multicenter, prospective registry, enrolled AF patients who underwent BPV replacement. The primary outcome measure was a composite of stroke, systemic embolism, CV events including heart failure requiring hospitalization, and cardiac death. A total of 766 patients was included in the analysis. The mean R2-CHA2DS2-VASc score was 5.7±1.8. Low (scores 0-1), moderate (scores 2-4), and high (scores 5-11) R2-CHA2DS2-VASc score groups consisted of 12 (1.6%), 178 (23.2%), and 576 (75.2%) patients, respectively. The median follow-up period was 491 (interquartile range 393-561) days. Kaplan-Meier analysis showed a higher incidence of the composite CV events in the high R2-CHA2DS2-VASc score group (log rank test; P<0.001). Multivariate Cox proportional hazards regression analysis revealed that the R2-CHA2DS2-VASc score as a continuous variable was an independent predictor of composite CV outcomes (hazard ratio 1.36; 95% confidence interval 1.18-1.55; P<0.001). The R2-CHA2DS2-VASc score is useful for CV risk stratification in AF patients after BPV replacement.

Thoracic versus coronary calcification for atherosclerotic cardiovascular disease events prediction

This study compared the prognostic value of quantified thoracic artery calcium (TAC) including aortic arch on chest CT and coronary artery calcium (CAC) score on ECG-gated cardiac CT.MethodsA total of...

Noninvasive liver fibrosis markers are independently associated with carotid atherosclerosis risk in patients with nonalcoholic fatty liver disease

Objective Nonalcoholic fatty liver disease (NAFLD) is considered an independent risk factor for cardiovascular disease (CVD). The overall morbidity and mortality of CVD increase with higher fibrosis stage in NAFLD. Carotid atherosclerosis (CAS) is an important predictor of cardiovascular events. However, the relationship between liver fibrosis degree and the risk of CAS in NAFLD patients remains uncertain. We aimed to investigate the relationship between noninvasive liver fibrosis markers and CAS risk in patients with NAFLD. Materials and Methods This study included 3,302 participants with NAFLD. Participants were divided into a CAS group and a non-CAS group based on carotid artery ultrasound results. They were then stratified into quartiles using various noninvasive liver fibrosis markers (fibrosis-4 (FIB-4), modified FIB-4 (mFIB-4), aminotransferase to platelet ratio index (APRI), aminotransferase to alanine aminotransferase ratio (AAR), AAR-to-platelet ratio index (AARPRI), and Forns index) to assess the associations between these markers and the risk of CAS. Results In the NAFLD population, individuals with CAS exhibited elevated levels of blood pressure, glucose, lipids, and noninvasive liver fibrosis markers (p < 0.001). The higher quartiles of noninvasive liver fibrosis markers, including FIB-4, mFIB-4, AAR, AARPRI, and Forns index, were significantly associated with increased risks of CAS, even after adjusting for multiple CVD risk factors. Conclusions In individuals with NAFLD, increased noninvasive liver fibrosis markers were independently associated with elevated CAS risk, which may be beneficial in assessing the risk of CVD in individuals with NAFLD.

Coronary computed tomographic angiography-derived anatomic and hemodynamic plaque characteristics in prediction of cardiovascular events.

This study investigated the association of anatomic and hemodynamic plaque characteristics based on deep learning coronary computed tomography angiography (CCTA) with high-risk plaques that caused subsequent major adverse cardiovascular events (MACE). A retrospective analysis was conducted on patients who underwent CCTA between 1month and 3years prior to the occurrence of a MACE. Deep learning and computational fluid dynamics algorithms based on CCTA were applied to extract adverse plaque characteristics (low-attenuation plaque, positive remodeling, napkin-ring sign, and spotty calcification), and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [△FFRCT], wall shear stress [WSS], and axial plaque stress [APS]). Correlation analysis, logistic regression, and Cox proportional risk analysis were conducted to understand the relationship between these measures and the occurrence of MACE and assess the value of hemodynamic parameters in predicting the incidence of MACE events and their prognosis. Our study included 86 patients with a total of 134 vessels exhibiting plaque formation and 83 culprit vessels with a subsequent coronary event. Culprit vessels had percent diameter stenosis [%DS] (0.54 ± 0.16 vs. 0.62 ± 0.13, P = 0.003), larger non-calcified plaque volume (45.8 vs. 101.7, P < 0.001), larger low-attenuation plaque volume (3.6 vs. 14.5, P < 0.001), more lesions with ≥ 3 adverse plaque characteristics (APC) (4 vs.26, P = 0.002), and worse hemodynamic features of adverse plaque. FFRCT demonstrated better visualization of maximum achievable flow in the presence of coronary stenosis and better correlation with the stenosis severity, while maximum of wall shear stress (WSSmax) was highly correlated with low-attenuation plaques and APC. The inclusion of hemodynamic parameters improved the efficacy of the predictive model, and a high WSS suggested a higher probability of MACE. Hemodynamic parameters based on CCTA are significantly correlated with plaque morphology. Importantly, integrating CCTA-derived parameters can refine the predictive performance of MACE occurrence.

450-P: Pulse Pressure as a Predictor of Cardiovascular Events in Cardiovascular Disease Patients with Differing Glycemic State

450-P: Pulse Pressure as a Predictor of Cardiovascular Events in Cardiovascular Disease Patients with Differing Glycemic State

Modulation of the intestinal microbiota as a new strategy for the prevention and treatment of comorbid chronic cardiovascular diseases and colorectal cancer in one patient. Review

To date, the etiological causes of adverse outcomes associated with cardiovascular diseases and concomitant colorectal cancer in one patient, especially over 60 years of age, are multifactorial: from undiagnosed timely above-mentioned pathological conditions to poor adherence to treatment. It is a multi-level approach that is the future guarantee of reducing the burden on public health as a result of these most common nosologies.The aim of the work is to evaluate discussions between different experts with an analysis of fundamental and clinical studies based on world literature in the search for new prospects for the treatment of patients with cardiovascular pathology and comorbid colorectal cancer based on the composition and function of the intestinal microbiota.A literature search was conducted in the PubMed electronic database using the keywords: intestinal microbiota, cardio-oncology, oncosurgery, colorectal cancer, cardiovascular diseases. Additional sources were identified through literature cross-referencing. Search period: 2023.The gut microbiome is a potential marker for better risk stratification of cardiovascular diseases, colorectal cancer, and prediction of shortand long-term major adverse cardiovascular and cancer events. To develop clear recommendations and conclusions, additional research is required.

448-P: The A Body Shape Index and Type 2 Diabetes Are Mutually Independent Predictors of Cardiovascular Events In Patients with Established Coronary Artery Disease

448-P: The A Body Shape Index and Type 2 Diabetes Are Mutually Independent Predictors of Cardiovascular Events In Patients with Established Coronary Artery Disease

Letter by Andreotti et al Regarding Article, “Inflammation and Cholesterol as Predictors of Cardiovascular Events Among 13 970 Contemporary High-Risk Patients With Statin Intolerance”

Letter by Andreotti et al Regarding Article, “Inflammation and Cholesterol as Predictors of Cardiovascular Events Among 13 970 Contemporary High-Risk Patients With Statin Intolerance”

The association of carotid plaque burden and composition and the coronary artery calcium score in intermediate cardiovascular risk patients.

Both the carotid ultrasound and coronary artery calcium (CAC) score quantify subclinical atherosclerosis and are associated with cardiovascular disease and events. This study investigated the association between CAC score and carotid plaque quantity and composition. Adult participants (n = 43) without history of cardiovascular disease were recruited to undergo a carotid ultrasound. Maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (CIMT), and plaque score were measured. Grayscale pixel distribution analysis of ultrasound images determined plaque tissue composition. Participants then underwent CT to determine CAC score, which were also categorized as absent (0), mild (1-99), moderate (100-399), and severe (400+). Spearman correlation coefficients between carotid variables and CAC scores were computed. The mean age of participants was 63 ± 11 years. CIMT, TPA, MPH, and plaque score were significantly associated with CAC score (ρ = 0.60, p < 0.0001; ρ = 0.54, p = 0.0002; ρ = 0.38, p = 0.01; and ρ = 0.49, p = 0.001). Echogenic composition features %Calcium and %Fibrous tissue were not correlated to a clinically relevant extent. There was a significant difference in the TPA, MPH, and plaque scores of those with a severe CAC score category compared to lesser categories. While carotid plaque burden was associated with CAC score, plaque composition was not. Though CAC score reliably measures calcification, carotid ultrasound gives information on both plaque burden and composition. Carotid ultrasound with assessment of plaque features used in conjunction with traditional risk factors may be an alternative or additive to CAC scoring and could improve the prediction of cardiovascular events in the intermediate risk population.

Serum albumin and white matter hyperintensities

People living with HIV and those diagnosed with alcohol use disorders (AUD) relative to healthy individuals commonly have low levels of serum albumin, substantiated as an independent predictor of cardiovascular events. White matter hyperintensities (WMH)—a neuroimaging feature of cerebral small vessel disease—are also related to cardiovascular disease. Despite consensus regarding associations between high levels of urine albumin and WMH prevalence, and low serum albumin levels and impaired cognitive functioning, relations between serum albumin and WMH burdens have rarely been evaluated. Here, a sample including 160 individuals with AUD, 142 living with HIV, and 102 healthy controls was used to test the hypothesis that serum albumin would be inversely related to WMH volumes and directly related to cognitive performance in the two diagnostic groups. Although serum albumin and periventricular WMH volumes showed an inverse relationship in both AUD and HIV groups, this relationship persisted only in the HIV group after consideration of traditional cardiovascular (i.e., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes), study-relevant (i.e., race, socioeconomic status, hepatitis C virus status), and disease-specific (i.e., CD4 nadir, HIV viral load, HIV duration) factors. Further, serum albumin contributed more significantly than periventricular WMH volume to variance in performance on a verbal learning and memory composite score in the HIV group only. Relations in both HIV and AUD groups between albumin and hematological red blood cell markers (e.g., hemoglobin, hematocrit) suggest that in this sample, serum albumin reflects hematological abnormalities. Albumin, a simple serum biomarker available in most clinical settings, may therefore help identify periventricular WMH burden and performance levels in specific cognitive domains in people living with HIV. Whether serum albumin contributes mechanistically to periventricular WMH in HIV will require additional investigation.

Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management.

Acute coronary syndrome (ACS) is a severe cardiovascular disease with globally rising incidence and mortality rates. Traditional risk assessment tools are widely used but are limited due to the complexity of the data. This study introduces a gated Transformer model utilizing machine learning to analyze electronic health records (EHRs) for an enhanced prediction of major adverse cardiovascular events (MACEs) in ACS patients. The model's efficacy was evaluated using metrics such as area under the curve (AUC), precision-recall (PR), and F1-scores. Additionally, a patient management platform was developed to facilitate personalized treatment strategies. Incorporating a gating mechanism substantially improved the Transformer model's performance, especially in identifying true-positive cases. The TabTransformer+Gate model demonstrated an AUC of 0.836, a 14% increase in average precision (AP), and a 6.2% enhancement in accuracy, significantly outperforming other deep learning approaches. The patient management platform enabled healthcare professionals to effectively assess patient risks and tailor treatments, improving patient outcomes and quality of life. The integration of a gating mechanism within the Transformer model markedly increases the accuracy of MACE risk predictions in ACS patients, optimizes personalized treatment, and presents a novel approach for advancing clinical practice and research.

Association between essential metals, adherence to healthy lifestyle behavior, and ankle-brachial index

BackgroundAnkle-brachial index (ABI) is a noninvasive diagnostic method for peripheral arterial disease (PAD) and a predictor of cardiovascular events. ObjectiveThe present study aimed to evaluate the association between individual or combined essential metals and ABI, as well as assess the collective impact of essential metals when coupled with healthy lifestyle on ABI. MethodsA total of 2865 participants were recruited in Wuhan Tongji Hospital between August 2018 and March 2019. Concentrations of essential metals in urine were measured by inductively coupled plasma mass spectrometer. ResultsThe results of general linear regression models demonstrated that after adjusting for confounding factors, there was a positive association between ABI increase and per unit increase of log 10-transformed, creatinine-corrected urinary Cr (β (95 % CI): 0.010 (0.004, 0.016), PFDR = 0.007), Fe (β (95 % CI): 0.010 (0.003, 0.017), PFDR = 0.018), and Co (β (95 % CI): 0.013 (0.005, 0.021), PFDR = 0.007). The WQS regression revealed a positive relationship between the mixture of essential metals and ABI (β (95 % CI): 0.006 (0.003, 0.010), P < 0.001), with Cr and Co contributing most to the relationship (weighted 45.48 % and 40.14 %, respectively). Compared to individuals with unfavorable lifestyle and the lowest quartile of Cr, Fe and Co, those with favorable lifestyle and the highest quartile of Cr, Fe and Co exhibited the most increase in ABI (β (95 % CI): 0.030 (0.017, 0.044) for Cr, β (95 % CI): 0.027 (0.013, 0.040) for Fe, and β (95 % CI): 0.030 (0.016, 0.044) for Co). ConclusionIn summary, our study indicates that adequate essential metal intake together with healthy lifestyle behaviors perform crucial roles in PAD protection.

Comparison of atherosclerotic cardiovascular disease (ASCVD) and Framingham risk scores (FRS) in an Iranian population

BackgroundFramingham risk score (FRS) and Atherosclerotic Cardiovascular Disease risk score (ASCVDrs) are widely used tools developed based on the American population. This study aimed to compare the ASCVDrs and FRS in an Iranian population. MethodThe participants of the Fasa Adult Cohort Study and the patients of the cardiovascular database of Vali-Asr Hospital of Fasa, aged 40–80 years, were involved in the present cross-sectional study. After excluding non-eligible participants, the individuals with a history of myocardial infarction or admission to the cardiology ward due to heart failure were considered high-risk, and the others were considered low-risk. The discriminative ability of FRS and ASCVDrs was evaluated and compared using receiver operating characteristic curve analysis. The correlation and agreement of ASCVDrs and FRS were tested using Cohen Kappa and Spearman. ResultsFinally, 8983 individuals (mean age:53.9 ± 9.5 y, 49.2 % male), including 1827 high-risk participants, entered the study. ASCVDrs detected a greater portion of participants as high-risk in comparison with FRS (28.7 % vs. 15.7 %). ASVD (AUC:0.794) had a higher discriminative ability than FRS (AUC:0.746), and both showed better discrimination in women. Optimal cut-off points for both ASCVDrs (4.36 %) and FRS (9.05 %) were lower than the original ones and in men. Compared to FRS, ASCVDrs had a higher sensitivity (79.3 % vs. 71.6 %) and lower specificity (64.5 % vs. 65.1 %). FRS and ASCVDrs had a moderate agreement (kappa:0.593,p-value<0.001) and were significantly correlated (Spearman:0.772,p-value<0.001). ConclusionsASCVDrs had a more accurate prediction of cardiovascular events and identified a larger number of people as high-risk in the Iranian population.

#941 Pentraxin-3 as a marker of coronary artery disease in hemodialysis patients

Abstract Background and Aims Pentraxin-3 (PTX3), a novel inflammatory biomarker, has been recognized as a predictor of cardiovascular events in the general population, including coronary artery disease (CAD). Although PTX3 is elevated in dialysis patients, its potential diagnostic value for the estimation of CAD severity is still insufficiently studied. The aim of this study was to evaluate the association between PTX3 and CAD in hemodialysis patients. Method This cross-sectional study included 60 angina-free chronic hemodialysis patients (60% men, mean age 60 ± 11 years, mean dialysis vintage 26 ± 14 months). Coronary artery calcium score (CACS) and coronary computed tomography angiography (CCTA) were performed to evaluate CAD burden and stenosis severity, which was defined as significant if obstructing more than 50% of the vessel lumen. PTX3 was quantified using an enzyme-linked immunosorbent assay kit. Results Significant coronary artery stenosis was detected in 24 (40%) patients, of which the majority (17; 70.83%) had one-vessel disease. PTX3 was 194.82 ± 68.58 ng/mL in patients with significant CAD, whereas 83.55 ± 11.89 ng/mL in those without significant coronary artery stenosis (p = 0.028). PTX3 levels tend to increase in patients with CACS higher than 200 Agatston units, however statistically significant difference was not reached (p = 0.504). PTX3 levels correlated with age (p &amp;lt; 0.05) and c-reactive protein (p = 0.007), while negatively correlated with body mass index (p &amp;lt; 0.05). Conclusion PTX3 is significantly increased in hemodialysis patients with coronary artery disease. Further studies should elucidate if including PTX3 as a marker for detecting CAD prior to invasive imaging could improve cardiovascular risk stratification even in angina-free hemodialysis patients.

#2271 Cardiovascular event prediction in kidney transplant recipients: a new risk score derivation and internal validation

Abstract Background and Aims Kidney transplant recipients (KTRs) have a cardiovascular (CV) risk 3 to 5-fold higher than that of the general population.CV disease represents the main cause of death in KTRs, both due to the presence of traditional risk factors and factors strictly related to transplant. The main CV risk calculators proved to be poorly predictive in the KTR population. We, therefore, aimed to compare the performance of CV risk scores already in use and to develop and validate a CV risk score in our KTRs population. Method Our analysis included 371 adult KTRs in follow-up at the outpatient clinic from 1 January 2015 to 31 December 2016. The composite outcome was the occurrence of MACE. We compared the performance of three main CV risk calculators (Framingham Risk Score-FRS-, INDANA score and PORT score). Thereafter, we built a predictive model selecting study variables by backward stepwise Cox regression. The risk score for each variable was weighted according to the HR of the final multivariable model. Internal and external validation of the prediction score and its discriminative capacity was assessed via area under the curve (AUC) curve, and the calibration via the Hosmer–Lemeshow test. Results After a mean follow-up of 68 months, CV events occurred in 71 (19%) KTRs. FRS, INDANA and PORT were demonstrated to have low predictive power in our population (Fig. 1). The accuracy did not improve after adjustment for immunological and transplant-related variables. Therefore, we derived a model including significative variables at multivariate analysis: age, dialysis vintage, systolic blood pressure, eGFR and 24-hour proteinuria (Akaike information criteria 713). The model discrimination was good (Harrel's c: 0.73). According to the hazard ratio, 3 points have been attributed to age higher than 60 years and 24 h proteinuria higher than 1 g/d, 2 points to dialysis vintage longer than 5 years, systolic blood pressure higher than 140 mmHg and eGFR less than 30 ml/min/1.73 m2. The new score demonstrated good discrimination (AUC 0.70, Fig. 2) and calibration (Hosmer-Lemeshow test 11.34, P = 0.12). The new score was internally validated by 10-fold cross-validation (mean AUC 0.70, 95% CI 0.60-0.77). For each point of the new score, the risk of the event increased by 40% and a score higher than three was associated with a 4-fold increased risk of composite endpoint. Conclusion We confirmed the poor predictive power of the known CV risk assessment tools in our real-world KTRs population. Moreover, their discriminatory power was not improved by adjustment for the occurrence of biopsy-proven rejection, HLA compatibility and donor-specific antibody. A new score for CV event prediction including traditional risk factors, such as age and systolic blood pressure, and variables related to renal function and the effects of previous chronic kidney disease, was developed and internally validated.

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.

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.

Clinical use of polygenic risk scores for detection of peripheral artery disease and cardiovascular events.

We have previously shown that polygenic risk scores (PRS) can improve risk stratification of peripheral artery disease (PAD) in a large, retrospective cohort. Here, we evaluate the potential of PRS in improving the detection of PAD and prediction of major adverse cardiovascular and cerebrovascular events (MACCE) and adverse events (AE) in an institutional patient cohort. We created a cohort of 278 patients (52 cases and 226 controls) and fit a PAD-specific PRS based on the weighted sum of risk alleles. We built traditional clinical risk models and machine learning (ML) models using clinical and genetic variables to detect PAD, MACCE, and AE. The models' performances were measured using the area under the curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), and Brier score. We also evaluated the clinical utility of our PAD model using decision curve analysis (DCA). We found a modest, but not statistically significant improvement in the PAD detection model's performance with the inclusion of PRS from 0.902 (95% CI: 0.846-0.957) (clinical variables only) to 0.909 (95% CI: 0.856-0.961) (clinical variables with PRS). The PRS inclusion significantly improved risk re-classification of PAD with an NRI of 0.07 (95% CI: 0.002-0.137), p = 0.04. For our ML model predicting MACCE, the addition of PRS did not significantly improve the AUC, however, NRI analysis demonstrated significant improvement in risk re-classification (p = 2e-05). Decision curve analysis showed higher net benefit of our combined PRS-clinical model across all thresholds of PAD detection. Including PRS to a clinical PAD-risk model was associated with improvement in risk stratification and clinical utility, although we did not see a significant change in AUC. This result underscores the potential clinical utility of incorporating PRS data into clinical risk models for prevalent PAD and the need for use of evaluation metrics that can discern the clinical impact of using new biomarkers in smaller populations.

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.