bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carotid plaque score for stroke and cardiovascular risk prediction in a middle-aged cohort from the general population: the akershus cardiac examination 1950 study
Authors: Ihle-Hansen H , Vigen T V , Berge T B , Walle-Hansen M W H , Hagberg G H , Ihle-Hansen H I H , Thommessen B T , Ariansen I A , Rosjo H R R , Ronning O M R , Tveit A T , Lyngbakken M L 
Published: November 2023

Abstract

Background
Assessment of carotid atherosclerosis with ultrasound may have an unfilled potential in predicting stroke and cardiovascular events.

Purpose
We aimed to explore the predictive value of the carotid plaque score compared to the Systematic COronary Risk Evaluation (SCORE) 2 risk prediction algorithm, on incident stroke and major adverse cardiovascular events (MACE), and establish a prognostic cut-off for the carotid plaque score.

Methods
In the prospective Akershus Cardiac Eexamination (ACE) 1950 cohort study, carotid plaque score was calculated with ultrasound at inclusion in 2012-2015. The largest plaque diameter in each extra cranial segment of the carotid artery both sides was measured and scored from 0-3 points. The sum of each segment provided the carotid plaque score. Incident stroke and composite endpoint MACE (nonfatal stroke, nonfatal myocardial infarction, and cardiovascular death) was assessed by linkage to national registries throughout 2020.

Results
Carotid plaque score was available in 3650 (98.5%) of the participants, with mean age at inclusion was 63.9±0.64 years. Only 462 (12.7%) were free of plaque and the median carotid plaque score was 2 (IQR 1-4). By the end of 2020, 42 (1.2%) subjects had experienced a stroke and 145 (4.0%) a MACE. Carotid plaque score was a predictor of incident stroke (HR 1.25, 95%CI 1.15-1.36) and MACE (OR 1.21, 95%CI 1.14-1.27) after adjustment for SCORE2, and outperformed SCORE2 in predicting stroke (p=0.001). The best cut-off value for carotid plaque score determined by receiver operator characteristics area under the curve was ≥4 with a positive predictive value 2.5% and negative predictive value 99.3%.

Conclusion
Carotid plaque score is a strong predictor of incident stroke and MACE and outperforms SCORE2 for risk prediction in a middle-aged cohort recruited from the general population. A cut-off score of ≥4 seems to be suitable to identify high-risk subjects.Graphical AbstractCarotid plaque score distribution
Rapid access chest pain clinic; insights from 10 years of an australian experience
Authors: Shawki M , Azzopardi R , Al-Fiadh H , Liu F , Lin Y C , Sanders K , Al-Fiadh A 
Published: November 2023

Abstract

Introduction
Rapid Access Chest Pain Clinic (RACPC) has been established in the UK as a safe and cost-effective model for managing low to intermediate Cardiovascular Disease (CVD) risk chest pain patients. In our institute, this service was established in 2012 based on the UK model.

Purpose
This study aimed to assess the safety, efficacy, and cost-effectiveness of the RACPC at a large metropolitan health service in Australia to inform future models of care.
Patients and Methods: We conducted a retrospective analysis of consecutive patients who attended RACPC between 2012 and 2022. Patients aged 25-85 years with low to intermediate CVD risk chest pain and no previously known ischaemic heart disease were included. RACPC staff comprised of a multidisciplinary team of cardiologists, nurse practitioners, and cardiology liaison nurses. The primary outcome was to benchmark our clinic model against national peers. The secondary outcome was to examine the pattern and accuracy of requested cardiac imaging used in RACPC, identify the frequency of incidental findings resulting from imaging and determine the cost-effectiveness of RACPC.

Results
Over the ten-year study period, a total of 4,194 patients were seen. The median waiting time from referral to consultation was 15.5 days (5 - 21.5). Attendance rates gradually increased from 71% to 95% in the clinic's tenth year of operation. Furthermore, the number of missed appointments and cancellations decreased over the years, reaching 1% and 4%, respectively. A total of 1,758 CT Coronary Angiogram (CTCA); 1,629 functional assessments utilising either Transthoracic Stress Echocardiogram (TSE) or Myocardial Perfusion Scan (MPS), and 174 Invasive Angiography (IA) procedures were requested. 1.2% of the cohort had IA without any prior non-invasive cardiac imaging. CTCA was the most frequently requested modality and resulted in the highest rates of incidental findings (24%) such as pulmonary nodules and vascular anomalies, often leading to further investigations. The rate of non-invasive cardiac imaging resulting in IA for CTCA, TSE and MPS were 7.3%, 2.5%, and 6.4%, respectively. Revascularisation rate for positive IA, CTCA, TSE and MPS were 33.3%, 34.6%, 26.7% and 20% respectively. At our health service, and for the purpose of comparison, we encountered an average of 52 patients/year with low to intermediate CVD risk hospitalised for chest pain assessment with an average length of stay of 2.35 days at a cost of 250,000 Australian Dollars ($4808/patient). Whilst at RACPC, an average of 419 patients/year were seen with a total cost of around 62,400 A$ ($149/patient).

Conclusion
RACPC is a safe, efficient, and cost-effective model of care, with CTCA being the preferred modality of imaging due to its high diagnostic accuracy, high negative predictive value and high rate of significant incidental findings.
Pulse wave velocity has an additive prognostic value to SCORE2 in apparently healthy subjects at 6 years of follow up
Authors: Ikonomidis I , Thymis J , Georgiopoulos G , Kolliou G , Katogiannis K , Pavlidis G , Kountouri A , Korakas E , Kostelli G , Lambadiari V , Stamatelopoulos K 
Published: November 2023

Abstract

Backround/Aim: Arterial stiffness is involved in the clinical course of atherogenesis. The purpose of this study was to investigate whether altered arterial wall properties of confers predictively and additively to estimation of cardiovascular risk.

Methods
Pulse wave velocity carotid-femoral (PWVc-f), the gold standard method to assess arterial stiffness, was measured non-invasively by Complior device. Increased PWV(c-f), especially above 10 m/s, indicates increased arterial stiffness. We measured baseline PWV(c-f) in 747 apparently healthy subjects (51.99±13.41 years old, 43.8% males), without established cardiovascular disease and calculated SCORE2 in each subject according to ESC guidelines.We prospectively monitored the occurrence of major cardiovascular events (MACEs-death, myocardial infarction, stroke) during a 6-year follow-up period using electronic records and clinic visits.

Results
Fifty-seven MACEs were documented during follow-up. In univariate analysis, subjects with increased PWV were found to exert greater risk for MACEs (hazard ratio (HR):1.12, 95%CI: 1.09-1.15, p&lt;0.001). PWV remained a significant predictor for MACEs in a model including sex, age, hyperlipidemia, diabetes, hypertension, current smoking, family history of coronary artery disease and treatment with ACEi/ARBs or lipid lowering agents after using backward elimination (HR:1.13; 95% CI: 1.08-1.18, p&lt;0.001). PWV was an independent and additive predictor of outcome when added in a model including solely SCORE2 (HR:1.10; 95% CI: 1.07-1.14,p&lt;0.001; Chi-square change:20.08, p&lt;0.001; C-statistic increase from 0.592 to 0.685) and also in a model encompassing risk factors not included in SCORE2, namely diabetes (HR:1.07; 95% CI: 1.04-1.11,p&lt;0.001; Chi-square change: 43.12, p&lt;0.001; C-statistic increase from 0.613 to 0.698). The HR of PWV for the prediction of MACE remained similar in subjects younger or older than the age of 50 years (p&gt;0.05).

Conclusion
Arterial stiffness is an independent and additive predictor to conventional risk factors and SCORE2 for adverse outcome at 6 years follow-up.
Prognostic change of adding coronary calcium score and genetic risk score to European SCORE2 in a moderate risk region
Authors: Temtem M , Palma Dos Reis R , Serrao M , Santos M , Sa D , Sousa F , Rodrigues M , Freitas S , Henriques E , Borges S , Guerra G , Ornelas I , Drumond A , Sousa A C , Mendonca M I 
Published: November 2023

Abstract

Introduction
Cardiovascular disease is a public health issue remaining the leading cause of death worldwide. One of its main contributors is coronary artery disease (CAD), a complex multifactorial disease with the influence of hereditary and environmental factors.
It’s crucial to improve cardiovascular risk assessment which is a real challenge in our daily clinical practice. SCORE 2 enhanced the identification of individuals at higher risk of developing CAD, but it remains scanty. Coronary Artery Calcification (CAC) score and Genetic contributions could improve CV risk stratification in primary prevention.

Purpose
Evaluate the impact of including CAC score and Genetic Risk Score (GRS) to the European SCORE2 in MACE prediction and cardiovascular risk stratification in our asymptomatic population.

Methods
945 asymptomatic subjects (mean age 52.9±6.8 years, 74.0% male) selected from the prospective arm of the GENEMACOR study were followed up during 5.4±4.1 years. The population was categorized according to SCORE2 into three risk groups (low-intermediate &lt;5%; high 5-10%; very high &gt;10%). CAC score was performed by cardiac computed tomography and reported as Agatston units according to the Hoff Nomogram in low, moderate and high-risk categories. The GRS was created from 33 genetic variants associated with CAD by GWAS, choosing those with a hazard ratio (HR) higher than 1. Multivariable Cox proportional hazard ratios (HR) with 95% conﬁdence intervals (95% CI) assessed the variables independently associated with CV events occurrence. We evaluated the discriminative ability of the Score2, CAC score and GRS using the Harrel C statistics.

Results
Cox regression analysis showed that the highest categories of SCORE2, CAC and GRS remained in the equation with an HR of 16.6 (p=0.008), HR of 3.6 (p=0.006) and HR of 3.2 (p=0.022), respectively, when compared with the lowest categories.
C-statistic demonstrated that the predictive value for MACE was 0.671 for SCORE2, increased to 0.799 (p=0.002) when adding CAC score and improved to 0.808 (p=0.012) when adding mGRS (Table 1), showing a better discrimination capacity for MACE.

Conclusions
Our results highlight the importance of adding CAC score and GRS to SCORE2 in primary prevention to improve cardiovascular risk stratification and MACE prediction.
Larger prospective multicenter cohorts with longer follow-up should reproduce and validate these findings.
Improving risk stratification of recurrent myocardial infarction in a large real-world dataset using machine learning
Authors: Chodick G , Vered Z , Elgui K , Mathieu T , Trichelair P , Zachlederova M , Rousset A 
Published: November 2023

Abstract

Background
Patient (pt) risk stratification for cardiovascular (CV) events is key to determine the appropriate approach to secondary prevention. Several risk scores have been developed (SCORE2, EUROASPIRE, Thrombolysis in Myocardial Infarction [TIMI] risk score for secondary prevention [TRS 2°P]); these are based on few predictors and have low discriminatory power. Machine learning methods using real-word data (RWD) from electronic health records (EHR) databases and capable of handling a multitude of commonly available variables can serve as powerful tools to improve the discriminatory power and generate efficient and clinically relevant risk scores.

Purpose
This study used a non-linear machine learning model to build an improved risk score for secondary CV events from a large Israeli EHR database.

Methods
Records of pts with a first record of atherosclerotic CV disease (ASCVD) admission or coronary procedure and available follow-up data (mean: 1052 days) from the period of 01/2005–11/2020 were considered (n=77432 [67% coronary artery disease, 21% carotid artery disease, 12% peripheral artery disease], a stratified 1:1 randomization by cause of admission yielding in training set [n=38716] and test set [n=38716]). The model’s performance was assessed by comparison with TRS 2°P score on the test set independent of the training set.
Twenty-six covariates commonly used in clinical routine and widely available in EHR have been selected and a gradient boosting trees algorithm was applied to the pt data at baseline after the original event to predict recurrent myocardial infarction (MI). The ability of the model to discriminate pts was evaluated using the concordance index (c-index), which expresses how well a predicted risk score describes the observed events (1 implies perfect concordance, 0.5 implies random concordance).

Results
Prediction accuracy of our model showed a c-index for a future MI of 0.74 (95% confidence interval [CI]: 0.72, 0.76) which is significantly higher than 0.57 (95% CI: 0.56, 0.58) obtained with TRS 2°P. Our 2-tier risk score has successfully discriminated a low-risk group (74% of cohort) with a 3-year MI prevalence of 5% from a high-risk group (26% of cohort) that had a 5-fold higher prevalence (26.6%) (Figure 1).
In comparison, the 3-tier TRS 2°P yielded an unbalanced distribution of group sizes with a disproportionate intermediate risk group (22% low, 67% intermediate, 11% of high-risk) with a limited clinical discriminatory power (7.1%, 10,2% and 15.6% of observed events, respectively) (Figure 2).

Conclusions
Our machine learning based risk score model created on a large set of RWD with a long follow-up seems to offer substantial gain of performance compared to the TRS 2°P. The present 2-tier model shows significant gain of accuracy and clinical discriminatory power paving the way for more individualized prevention strategies.Figure 1Figure 2
Plasma proteomics identify fibroblast growth factor 5 as a biomarker for genetically proven Familial Hypercholesterolemia
Authors: Baragetti A , Mattavelli E , Pellegatta F , Alieva A S , Grigore L , Reutova O , Shlyakhto E V , Catapano A L 
Published: November 2023

Abstract

Background
Subjects affected by genetically proven heterozygous Familial Hypercholesterolemia (FH) present lifelong exposure to high Low Density Lipoprotein Cholesterol ("LDL-C burden") causing premature ACVD. Nevertheless, the diagnosis of FH is still far from being optimal due to shortcomings of the clinical algorithms in detecting this form of severe ACVD since early decades of life (1) and because a significant proportion of FH present comparable LDL-C levels to that of subjects who are hypercholesterolemic but are not diagnosed as FH ("non-FH") (2).

Purpose
We previously demonstrated that targeted proteomics identify subjects at high Atherosclerotic Cardiovascular Diseases (ACVD) risk in the general populations beyond the known risk factors (3). Hence, we now tested whether targeted proteomics may differentiate FH subjects from the general population and from "non-FH".

Methods
We compared the plasma relative abundance of 264 proteins (Proximity Extension Assay; Olink) in 133 genetically proven FH with that of 586 normocholesterolemic subjects ("controls") and that of 55 non-FH (LDL-C between 190-220 mg/dL, not on statins). We trained and validated a Machine Learning (ML) boosting prediction model (4) in these cohorts to identify the protein markers representative of FH (Random Forest classifiers).

Results
Fibroblast Growth Factor 5 (FGF-5) resulted as the most powerful plasma protein in differentiating FH subjects from the controls, with an excellent performance (Area Under the Curve (AUC)=0.995 (0.985-1.000); sensitivity=100%; specificity=99.54%; P&lt;0.0001). FGF-5 also emerged as the top protein in differentiating the FH subjects from non-FH (AUC= 1.000 (0.914-1.000; sensitivity=100%, specificity=100% and P&lt;0.001). Finally, when the two groups were matched for LDL-C, FGF-5 still differentiated the FH from the non-FH subjects, (AUC=1.000 (0.914-1.000), sensitivity=100%, specificity=100%, p&lt;0.001).

Conclusions
FGF-5 allows a clear-cut identification of FH versus controls and, of even more importance, from non-FH with the same LDL-C. The LDL-C burden might be responsible for our findings.
A comprehensive analysis of 30 Biomarkers and their association with cardiovascular outcomes and mortality in the UK Biobank
Authors: Lee C J Y , Honigberg M C , Kany S , Choi S H , Andersson C , Hall A W , Roselli C , Hindy G , Wang M , Khera A V , Natarajan P , Torp-Pedersen C , Elllinor P T 
Published: November 2023

Abstract

Background
The use of a comprehensive panel of circulating biomarkers in risk estimation of cardiovascular disease and mortality in a general healthy population remains uncertain.

Methods
The individual association of 30 clinically available biomarkers with risk of incident heart failure (HF), atrial fibrillation (AF), stroke, myocardial infarction (MI), venous thromboembolism (VTE), and mortality was estimated within 5-years using separate logistic regression models in nearly 500,000 individuals in the UK Biobank; a prospective, population-based cohort recruited between 2006-2010.

Results
A total of 496,415 individuals were included (median age 58 years, 54% female). Higher concentrations of C-reactive protein, gamma-glutamyl transferase, cystatin C, and urate were associated with significantly higher odds, and albumin with lower odds, of all outcomes (Figure 1). Higher levels of sex hormone binding globulin were associated with a higher risk of AF for both sexes (men: Odds ratio [OR] per standard deviation [SD] 1.26, 95% confidence intervals [CI] 1.21-1.31; premenopausal women: OR per SD 1.20, 95% CI 1.09-1.31; postmenopausal women: OR per SD 1.41, 95% CI 1.12-1.77). No significant associations were found among pre- or postmenopausal women between estradiol and cardiovascular outcomes. For men, having estradiol ≥40 pmol/L was associated with a higher risk of mortality, HF and AF.

Conclusions
Several associations were found between multiple biomarkers and cardiovascular disease, and mortality, especially novel associations of hormonal markers associated with both lower and higher odds of cardiovascular disease. Further research is needed to validate these associations and explore the potential clinical applications of biomarker data.
Could a high epicardial adipose tissue volume increase the ability of the calcium score to discriminate cardiovascular events in an asymptomatic population?
Authors: Temtem M , Mendonca M I , Sousa J A , Serrao M , Santos M , Sa D , Sousa F , Freitas S , Borges S , Henriques E , Rodrigues M , Drumond A , Sousa A C , Palma Dos Reis R 
Published: November 2023

Abstract

Background
Evidence indicates that an elevated calcium score (CAC) is a risk marker for subclinical atherosclerosis and cardiovascular (CV) events in the asymptomatic population. Recent research has shown that high epicardial adipose tissue (EAT) volume is associated with coronary calcification and CV events It is unknown whether the association between the two risk markers improved the ability to predict CV events.

Objective
Evaluate whether a high EAT volume added to the CAC score improves the predictive ability to discriminate CV events in an asymptomatic population without apparent cardiovascular disease (CVD).

Methods
A prospective cohort was performed with 1024 participants (mean age 51.6±8.2 years, 75.6% male) selected from controls of the GENEMACOR Study. CAC score was performed by cardiac computed tomography, and CAC severity was reported as an absolute Agatston unit stratified for age and sex- percentile (according to the Hoff Nomogram). EAT volume was measured with a quantitative semi-automated procedure using a postprocessing workstation-TeraRecon Aquarius Workstation (version 4.4.7, TeraRecon, Inc., San Mateo, CA, USA). We evaluated the discriminative ability of the CAC model without (model 1) and with EAT volume (model 2) using the ROC curve along with respective AUC and Harrel C statistics. Categorical free Net Reclassification Improvement (cfNRI) and Integrated Discrimination Index (IDI) reclassified patients.

Results
CAC model showed a C Index of 0.733 (95%CI 0.633-0.833), which increased to 0.756 (95%CI 0.638-0.874) when EAT volume was included in the model. The difference between the two C indexes was significant (delta C statistic=0.023; p=0.020). CfNRI reclassified 63.6% of the population (p=0.0003), and IDI improved the discrimination when EAT was included in CAC model (IDI=0.011; p=0.015).

Conclusion
Our findings displayed that the CAC score associated with a high EAT volume increased the predictive and discriminative ability to event occurrence. Improving the identification of high-risk patients at a subclinical stage could avoid atherosclerosis progression and events occurrence through preventive measures.
Long-term aspirin adherence and risk of cardiovascular events and death after myocardial infarction: A nationwide cohort study
Authors: Kristensen A M D , Pareek M P , Kragholm K , Prescott E 
Published: November 2023

Abstract

Background
Aspirin is mandatory in the acute phase after myocardial infarction (MI); however, the efficacy of aspirin for long-term secondary prevention is less established and may have changed with the addition of modern therapies and diagnostics methods.

Purpose
To investigate the effectiveness of adherence to long term aspirin therapy at different timepoints following MI.

Methods
Using Danish nationwide registries, we included patients ≥40 years with a first time MI undergoing percutaneous coronary intervention from 2004 through 2017, who were alive, not treated with anticoagulants, and had stayed adherent to aspirin at one year after the index event (Figure 1). We evaluated adherence to aspirin therapy as proportion of days covered (PDC) ≤80% and &gt;80% at four landmarks (2, 4, 6, and 8 years after MI, respectively). At each landmark, patients were excluded from the analysis if they had suffered a recurrent MI or stroke, died, emigrated or were on anticoagulant or P2Y12-inhibitor therapy. The absolute and relative risks of a composite of death, recurrent MI, or ischemic stroke at 2 years from each landmark were calculated through multivariable logistic regression analysis with average treatment effect modelling standardized to the distribution of age, sex, diabetes, hypertension, hypercholesterolemia, chronic kidney disease, cancer, peptic ulcer, former bleeding, and chronic obstructive pulmonary disease (as a proxy for smoking). Non-CVD death was used as a neutral comparator.

Results
A total of 40,114 individuals were included in the analysis. Suboptimal adherence to aspirin (PDC≤80%) increased from 10% at first landmark 2 years after MI to 19% at fourth landmark 8 years after MI (Figure 1). The standardized absolute risk of death, recurrent MI, or ischemic stroke was highest at the first landmark 2 years after MI for both PDC-groups (PDC&gt;80%: 8.34%, 95% confidence interval [CI]: 8.04-8.63% and PDC≤80%: 10.75%, 95% CI: 9.80-11.69%) (Figure 2). The standardized relative risk of the composite endpoint was significantly higher for patients with PDC≤80% at all landmarks. A trend towards a diminished protective effect of long-term aspirin therapy appeared from 4 years after the index MI and onwards, decreasing from 1.40 (95% CI: 1.26-1.53) at second landmark 4 years after MI to 1.20 (95% CI: 1.04-1.35) at fourth landmark 8 years after MI. Overall, we found no difference in the relative risk of non-CV death between PDC-groups.

Conclusion
Suboptimal adherence to long-term aspirin therapy following MI was associated with an increased risk of recurrent MI, ischemic stroke, or death, but the relative risk appeared to decrease slightly over time from 4 years after the index MI and onwards.Figure 1Figure 2