Background and Aims

In the era of personalized medicine, it is of utmost importance to be able to identify subjects at highest cardiovascular risk. To date, single biomarkers have failed to markedly improve estimation of cardiovascular risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In this study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV-events in the primary prevention setting of the EPIC-Norfolk study, followed by validation in the PLIC cohort.

Methods

368 proteins were measured in a nested case-control sample of 822 individuals from the EPIC-Norfolk prospective cohort study and 702 individuals from the PLIC cohort. Using tree-based ensemble and boosting methods, we constructed a protein-based prediction model, an optimized clinical risk algorithm and a model combining both.

Results

In the derivation cohort we defined a panel of 50 proteins, which outperformed the clinical risk algorithm in prediction of myocardial infarction (AUC 0.754 vs 0.722;p<0.0001) during a median follow-up of 20 years. The clinically more relevant prediction of events occurring within 3 years showed an AUC of 0.680 using the clinical risk algorithm and an AUC of 0.803 for the protein model(p<0.0001). The predictive value of the protein panel was confirmed in the validation cohort.

Conclusions

In primary prevention setting, a protein-based model outperforms a model comprising clinical risk factors in predicting the risk of CV-events. Validation in a large prospective primary prevention cohort is required in order to address the value for future clinical implementation in CV-prevention.

Background and Aims

Carotid endarterectomy (CEA) is the gold standard to treat patients with symptomatic carotid artery stenosis. However, 20% of these patients develop a major adverse cardiovascular event (MACE) within three years after surgery. Since we cannot identify this high-risk patient, expensive add-on therapy cannot be used cost-efficiently.

Plasma extracellular vesicles (EVs) are involved in atherothrombotic processes and may serve as biomarkers to identify the patient at risk for MACE. For this we determined the predictive ability of preoperative 4 EVs protein levels (Cystatin C (CC), Serpin G1(SG1), Serpin F2(SF2) and CD14) for MACE.

Methods

From the Athero-Express Biobank, 40 cases (MACE) were randomly selected and matched to 40 controls (no MACE) on age, sex and cardiovascular risk factors. MACE was defined as myocardial infarction, stroke and cardiovascular death within three years after CEA. Three plasma subfractions of EVs (HDL-, LDL- and TEX-fraction) were isolated from preoperative blood samples and levels of CC, SG1, SF2 and CD14 were measured by Luminex. Cox-proportional hazard regression modelling was performed for univariate analysis. Backward stepwise regression modelling was performed to develop the best model of combined markers.

Results

The best prediction model included CD14 and SG1, both in the LDL-fraction. This combined model showed a discriminative ability in terms of Area Under the Curve (AUC) of 0.82, 95% CI, 0.73-0.91.

Conclusions

Combination of two EVs proteins, determined in a preoperative blood-test, can accurately identify high-risk patients for MACE after CEA. Validation of results will be performed in the total cohort of the Athero-Express Biobank.

Background and Aims

This study was designed to address the question whether a combined near-infrared spectroscopy(NIRS) – intravascular ultrasound(IVUS) imaging predicts cardiovascular outcomes in Asian patients with coronary artery disease(CAD).

Methods

The Ajou NIRS registry enrolled 597 patients who underwent coronary angiography with NIRS-IVUS imaging analysis for ischemic heart diseases from Jan, 2015 to Aug, 2019 in an Asian single center. Residual maximum lipid core burden index in 4 mm segment (maxLCBI_4mm) from non-treated lesions after PCI. The major adverse cardiovascular events(MACE) was defines as the composite all cause death, non-fetal MI, stroke or revascularization during follow-up.

Results

398 patients were assessed for this study after excluding patients who had non-analyzable vessels or clinical follow up less than 1 year. The median value of residual maxLCBI_4mm was 112[0, 289.0]. Average mean follow-up period was 1064.5±382.7 days. 32 patients(8%) had non-stent related events (2 all cause death, 5 non-fetal MI, 1 stroke and 31 revascularization). There were no differences of clinical parameters including lipid profiles between the patients with MACE and without. Patients with MACE had higher value of residual maxLCBI_4mm compared with those without(301.5 vs 94, p=0.003). By ROC curve analysis, the value of maxLCBI_4mm was 260.5 as a predictor for MACE(AUC 0.697, sensitivity 70.0 %, and specificity 73.5%).

Conclusions

Residual lipid core burden assessed by using NIRS-IVUS imaging in non-stented coronary arteries can be used as a predictor to identify patients at high risk for future cardiovascular events in Asian population. Ethnic difference in the absolute value of maxLCBI_4mm should be verified in larger studies.

Background and Aims

The neonatal coagulation system is not fully developed at birth. Reliable reference values in newborns and during early childhood are not well described, complicating clinical decision making within thrombosis and hemostasis. The aim of this study is to evaluate values of coagulation parameters at birth and two months after birth, and to test whether cord blood measurements can be used as proxy for neonatal venous blood measurements.

Methods

The Copenhagen Baby Heart and COMPARE studies comprise 13,000 cord blood samples and 450 parallel venous neonatal blood samples, with a two-month follow-up in 200 children.

Results

At birth, medians in girls and boys were 32 s and 33 s for Activated Partial Thromboplastin Time (APTT), 1.4 and 1.4 for International Normalized Ratio (INR), 47% and 45% for factor II+VII+X, and 314×10⁹/L and 300×10⁹/L for thrombocytes. Two months after birth, corresponding values were 30 s and 31 s for APTT, 1.1 and 1.1 for INR, 77% and 83% for factor II+VII+X, and 493×10⁹/L and 452×10⁹/L for thrombocytes. Correlation coefficients between cord blood and neonatal venous blood were 0.7 for APTT, INR, and factor II+VII+X, and 0.8 for thrombocytes.

Conclusions

Coagulation parameters are not as extreme at birth as previously reported and are close to adult values two months after birth. Further, for these parameters cord blood can be used as proxy for neonatal venous blood. The present data has the potential to form the scientific basis for well-defined age- and sex-dependent reference intervals, improving clinical decision making within thrombosis and hemostasis.