Prevalence and clinical implications of valvular calcification on coronary computed tomography angiography

Timing of Aortic Valve Intervention in the Management of Aortic Stenosis

Aortic stenosis (AS) affects about 12% of people aged ≥75 years. Accumulating evidence on the prognostic importance of cardiac damage in patients with asymptomatic and less than severe AS supports the proposition of advancing aortic valve replacement (AVR) to earlier disease stages. Potential benefits of earlier treatment, including prevention of cardiac damage progression and reduced cardiovascular hospitalizations, need to be balanced against the earlier procedural risk and subsequent lifetime management after AVR. Two small, randomized trials indicate that early surgical AVR may improve survival in patients with asymptomatic severe AS, and observational data suggest that AVR may reduce mortality even in patients with moderate AS. A clear understanding of the pathophysiology of cardiac damage secondary to AS is needed to develop strategies to select patients for earlier AVR. Noninvasive imaging can detect early cardiac damage, and indices such as fibrosis, global longitudinal strain, and myocardial work index have potential use to guide stratification of patients for earlier AVR. Ongoing randomized trials are investigating the safety and efficacy of AVR for patients with asymptomatic severe AS and those with moderate AS who have symptoms/evidence of cardiac damage. Pathophysiological considerations and accumulating evidence from clinical studies that support earlier timing of AVR for AS will need to be corroborated by the results of these trials. This review aims to evaluate the evidence for earlier AVR, discuss strategies to guide stratification of patients who may benefit from this approach, highlight the relevant ongoing randomized trials, and consider the consequences of earlier intervention.

Use machine learning models to identify and assess risk factors for coronary artery disease

Accurate prediction of coronary artery disease (CAD) is crucial for enabling early clinical diagnosis and tailoring personalized treatment options. This study attempts to construct a machine learning (ML) model for predicting CAD risk and further elucidate the complex nonlinear interactions between the disease and its risk factors. Employing the Z-Alizadeh Sani dataset, which includes records of 303 patients, univariate analysis and the Boruta algorithm were applied for feature selection, and nine different ML techniques were subsequently deployed to produce predictive models. To elucidate the intricate pathogenesis of CAD, this study harnessed the analytical capabilities of Shapley values, alongside the use of generalized additive models for curve fitting, to probe into the nonlinear interactions between the disease and its associated risk factors. Furthermore, we implemented a piecewise linear regression model to precisely pinpoint inflection points within these complex nonlinear dynamics. The findings of this investigation reveal that logistic regression (LR) stands out as the preeminent predictive model, demonstrating remarkable efficacy, it achieved an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.981 (95% CI: 0.952-1), and an Area Under the Precision-Recall Curve (AUPRC) of 0.993. The utilization of the 14 most pivotal features in constructing a dynamic nomogram. Analysis of the Shapley smoothing curves uncovered distinctive "S"-shaped and "C"-shaped relationships linking age and triglycerides to CAD, respectively. In summary, machine learning models could provide valuable insights for the early diagnosis of CAD. The SHAP method may provide a personalized risk assessment of the relationship between CAD and its risk factors.

Feasibility and Exploration of a Standardized Protocol for Cardiac CT Assessment of Rheumatic Mitral Disease

Rheumatic mitral valve disease often requires surgical interventions, such as percutaneous mitral commissurotomy, surgical mitral valve repair, or replacement, especially in severe cases. This necessitates a precise preoperative assessment of the extent of mitral valve disease. Currently, transthoracic echocardiography, the gold standard for preoperative assessment, has limitations, such as restricted acoustic windows and dependence on the operator, which can affect the evaluation of subvalvular structures and calcification of the mitral valve. Previous studies have shown that cardiac computed tomography (CT), with its high resolution, strong multiplanar reconstruction capabilities, and sensitivity to calcifications, can effectively overcome these limitations. Therefore, this study aims to summarize and evaluate the effectiveness of cardiac CT in examining mitral valve leaflets, annulus, and subvalvular structures. It also reviews the feasibility and guiding significance of using cardiac CT to assess characteristic rheumatic mitral valve lesions.

Calcification of surgical aortic bioprostheses and its impact on clinical outcome

AIMS

Aortic valve calcification (AVC) of surgical valve bioprostheses (BPs) has been poorly explored. We aimed to evaluate in vivo and ex vivo BP AVCs and its prognosis value.

METHODS AND RESULTS

Between 2011 and 2019, AVC was assessed using in vivo computed tomography (CT) in 361 patients who had undergone surgical valve replacement 6.4 ± 4.3 years earlier. Ex vivo CT scans were performed for 37 explanted BPs. The in vivo CT scans were interpretable for 342 patients (19 patients [5.2%] were excluded). These patients were 77.2 ± 9.1 years old, and 64.3% were male. Mean in vivo AVC was 307 ± 500 Agatston units (AU). The AVC was 562 ± 570 AU for the 183 (53.5%) patients with structural valve degeneration (SVD) and 13 ± 43 AU for those without SVD (P < 0.0001). In vivo and ex vivo AVCs were strongly correlated (r = 0.88, P < 0.0001). An in vivo AVC > 100 AU (n = 147, 43%) had a specificity of 96% for diagnosing Stage 2-3 SVD (area under the curve = 0.92). Patients with AVC > 100 AU had a worse outcome compared with those with AVC ≤ 100 AU (n = 195). In multivariable analysis, AVC was a predictor of overall mortality (hazard ratio [HR] and 95% confidence interval = 1.16 [1.04-1.29]; P = 0.006), cardiovascular mortality (HR = 1.22 [1.04-1.43]; P = 0.013), cardiovascular events (HR = 1.28 [1.16-1.41]; P < 0.0001), and re-intervention (HR = 1.15 [1.06-1.25]; P < 0.0001). After adjustment for Stage 2-3 SVD diagnosis, AVC remained a predictor of overall mortality (HR = 1.20 [1.04-1.39]; P = 0.015) and cardiovascular events (HR = 1.25 [1.09-1.43]; P = 0.001).

CONCLUSION

CT scan is a reliable tool to assess BP leaflet calcification. An AVC > 100 AU is tightly associated with SVD and it is a strong predictor of overall mortality and cardiovascular events.

Scoring model based on cardiac CT and clinical factors to predict early good mitral valve repair in rheumatic mitral disease

OBJECTIVE

We aimed to evaluate the mitral valve calcification and mitral structure detected by cardiac computed tomography (cardiac CT) and establish a scoring model based on cardiac CT and clinical factors to predict early good mitral valve repair (EGMR) and guide surgical strategy in rheumatic mitral disease (RMD).

MATERIALS AND METHODS

This is a retrospective bi-center cohort study. Based on cardiac CT, mitral valve calcification and mitral structure in RMD were quantified and evaluated. The primary outcome was EGMR. A logical regression algorithm was applied to the scoring model.

RESULTS

A total of 579 patients were enrolled in our study from January 1, 2019, to August 31, 2022. Of these, 443 had baseline cardiac CT scans of adequate quality. The calcification quality score, calcification and thinnest part of the anterior leaflet clean zone, and papillary muscle symmetry were the independent CT factors of EGMR. Coronary artery disease and pulmonary artery pressure were the independent clinical factors of EGMR. Based on the above six factors, a scoring model was established. Sensitivity = 95% and specificity = 95% were presented with a cutoff value of 0.85 and 0.30 respectively. The area under the receiver operating characteristic of external validation set was 0.84 (95% confidence interval [CI] 0.73-0.93).

CONCLUSIONS

Mitral valve repair is recommended when the scoring model value > 0.85 and mitral valve replacement is prior when the scoring model value < 0.30. This model could assist in guiding surgical strategies for RMD.

CLINICAL RELEVANCE STATEMENT

The model established in this study can serve as a reference indicator for surgical repair in rheumatic mitral valve disease.

KEY POINTS

• Cardiac CT can reflect the mitral structure in detail, especially for valve calcification. • A model based on cardiac CT and clinical factors for predicting early good mitral valve repair was established. • The developed model can help cardiac surgeons formulate appropriate surgical strategies.

Different prognostic significance of coronary artery and aortic valve calcium in patients with chest pain

OBJECTIVES

Coronary artery calcification (CorCa) identifies high cardiovascular risk in the general population. In this setting, aortic valve calcification (AoCa) showed contradictory results. Our goal has been to assess the prognostic power of CorCa and AoCa in patients with chest pain who underwent an ECG-gated cardiac multidetector CT (cardiac-MDCT).

METHODS

A total of 528 patients without previous known coronary artery disease, with chest pain who underwent a cardiac-MDCT multidetector, were retrospectively recruited. The primary endpoint included death, acute coronary syndrome, stroke, and heart failure.

RESULTS

A total of 61 patients (11.6%) had an event during a mean follow-up of almost 6 years (5.95 ± 2.98). The most frequent event was acute coronary syndrome (6.4%). Total mortality was 4.5%. Patients with CorCa > 0 had more events than those without CorCa (17.3% versus 4.3%; p < 0.001). Likewise, when only patients without AoCa were considered (n = 118), clinical events were more frequent in those with CorCa (12.7% versus 3.6%; p = 0.004). After excluding patients with coronary artery disease, events were more frequent in those with CorCa (12.6% versus 4.3%; p = 0.004). The higher the Agatston score, the more frequent the events. Patients with AoCa  > 0 had more events than those without (16.5% versus 7.3%; p < 0.001), but in patients without CorCa, no difference in events was seen (6.2% versus 3.6%; p = 0.471). A Cox regression analysis showed age, smoking, prior stroke, and CorCa but not AoCa to be independently related to events.

CONCLUSIONS

In summary, CorCa, but not AoCa, is related to cardiovascular events in patients with chest pain who undergo a cardiac-MDCT.

CLINICAL RELEVANCE STATEMENT

We show that coronary artery calcification, but not aortic valve calcification, detected in a coronary CT scan is tightly related to cardiovascular events. Although this is a message already shown by other groups in the general population, we do believe that this work is unique because it is restricted to patients with chest pain sent to coronary CT. In other words, our work deals with what we face in our routine everyday practice.

KEY POINTS

• The presence and the amount of coronary artery calcification are associated with cardiovascular events in patients with chest pain. • Aortic valve calcification is not associated with cardiovascular events in patients with chest pain.

Predictive value of valvular calcification for the recurrence of persistent atrial fibrillation after radiofrequency catheter ablation

BACKGROUND

Valvular calcification (VC) is an independent risk factor for cardiovascular diseases. The relationship between VC and atrial fibrillation is not clear.

HYPOTHESIS

We treated the aortic valve, mitral valve, and tricuspid valve as a whole and considered the possible association between VC and recurrence of persistent atrial fibrillation (PsAF) after radiofrequency catheter ablation (RFCA).

METHODS

This study involved 2687 PsAF patients who underwent RFCA. Data were collected to explore the relationship between VC and outcome. VC was defined by echocardiography in aortic valve, mitral valve, or tricuspid valve. After 1 year follow-up, subgroup analysis, mixed model regression analysis, and score system analysis were performed. The external validation of 133 patients demonstrated the accuracy of this clinical prediction model.

RESULTS

Overall, 2687 inpatients were assigned to the recurrence group (n = 682) or the no recurrence group (n = 2005) with or without VC. Compared to patients with no recurrence, the incidence of VC was higher in recurrence patients. Recurrence was present in 18.5%, 34.9%, 39.3%, and 52.0% of the four groups, which met VC numbers of 0, 1, 2, and 3, respectively. After adjustment for potential confounding factors, VC was an independent risk factor for AF recurrence in several models. For multivariable logistic regression, a scoring system was established based on the regression coefficient. The receiver operating characteristic area of the scoring system was 0.787 in the external validation cohort.

CONCLUSIONS

VC was an independent risk factor for AF recurrence in PsAF after RFCA. The scoring system may be a useful clinical tool to assess AF recurrence.

Noncontrast cardiac computed tomography-derived mitral annular calcification scores in mitral valve disease

BACKGROUND AND AIMS

Mitral annular calcification (MAC) by computed tomography (CT) is reported as an independent predictor of poor outcomes. However, it currently remains unclear if quantitative MAC parameters provide more value for mitral valve disease (MVD) management, therefore, we examined the prognostic value of MAC scores using noncontrast cardiac-CT in MVD patients.

METHODS

Between January 2020 and December 2021, we prospectively enrolled 300 consecutive patients with MVD (MAC-present = 80 and MAC-absent = 220) undergoing preoperative cardiac-CT and mitral valve (MV) surgery. Noncontrast cardiac-CT images were used to qualitatively detect MAC (present or absent) and evaluate MAC scores. For analyses, we also collected baseline clinical data, intraoperative conversion (from MV repair to MV replacement), and follow-up arrhythmia data.

RESULTS

Compared with the MAC-absent group, MAC-present patients were older (62 ± 7 vs. 58 ± 9 years, p < .001), mostly women (55% vs. 39.5%, p = .017), and also had aortic valve calcification (57.5% vs. 23.2%, p < .001), mitral stenosis (82.5% vs. 61.8%, p < .001), atrial fibrillation (30% vs. 11.8%, p < .001), and larger left atrial end-diastolic dimension (LADD, 49 [44-56] versus 46 [41-50], p = .001]. Furthermore, MAC-present patients underwent more MV replacements (61.8% vs. 82.5%, p = .001) and experienced a higher intraoperative conversion prevalence (11.8% vs. 61.3%, p < .001). Multiple logistic regression analyses showed that the female gender (odds ratio [OR]/95% confidence interval [CI]/p = 2.001/1.042-3.841/0.037) and MAC scores (OR/95% CI/p = 10.153/4.434-23.253/p < .001) were independent predictors of intraoperative conversion. During a follow-up of 263 ± 134 days, MAC-present patients had more arrhythmias (42.5% vs. 9.5%, p < .001). Also, MAC-scores (hazard ratio [HR]/95% CI/p = 6.841/3.322-14.089/p < .001) and LADD (HR/95% CI/p = 1.039/1.018-1.060/p < .001) were independently associated with arrhythmias by Cox regression analyses.

CONCLUSIONS

Noncontrast cardiac CT-derived MAC-scores showed a high risk for intraoperative conversion and follow-up arrhythmias in MVD-patients.

The Influence of Aortic Valve Disease on Coronary Hemodynamics: A Computational Model-Based Study

Aortic valve disease (AVD) often coexists with coronary artery disease (CAD), but whether and how the two diseases are correlated remains poorly understood. In this study, a zero-three dimensional (0-3D) multi-scale modeling method was developed to integrate coronary artery hemodynamics, aortic valve dynamics, coronary flow autoregulation mechanism, and systemic hemodynamics into a unique model system, thereby yielding a mathematical tool for quantifying the influences of aortic valve stenosis (AS) and aortic valve regurgitation (AR) on hemodynamics in large coronary arteries. The model was applied to simulate blood flows in six patient-specific left anterior descending coronary arteries (LADs) under various aortic valve conditions (i.e., control (free of AVD), AS, and AR). Obtained results showed that the space-averaged oscillatory shear index (SA-OSI) was significantly higher under the AS condition but lower under the AR condition in comparison with the control condition. Relatively, the overall magnitude of wall shear stress was less affected by AVD. Further data analysis revealed that AS induced the increase in OSI in LADs mainly through its role in augmenting the low-frequency components of coronary flow waveform. These findings imply that AS might increase the risk or progression of CAD by deteriorating the hemodynamic environment in coronary arteries.

The year 2021 in the European Heart Journal: Cardiovascular Imaging Part II

The European Heart Journal-Cardiovascular Imaging was launched in 2012 and has during these years become one of the leading multimodality cardiovascular imaging journals. The journal is currently ranked as Number 19 among all cardiovascular journals. It has an impressive impact factor of 9.130. The most important studies published in our Journal from 2021 will be highlighted in two reports. Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease, while Part I of the review has focused on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging.

Are Non-Invasive Modalities for the Assessment of Atherosclerosis Useful for Heart Failure Predictions?

Heart failure (HF) is becoming an increasingly common issue worldwide and is associated with significant morbidity and mortality, making its prevention an important clinical goal. The criteria evaluated using non-invasive modalities such as coronary artery calcification, the ankle-brachial index, and carotid intima-media thickness have been proven to be effective in determining the relative risk of atherosclerotic cardiovascular disease. Notably, risk assessments using these modalities have been proven to be superior to the traditional risk predictors of cardiovascular disease. However, the ability to assess HF risk has not yet been well-established. In this review, we describe the clinical significance of such non-invasive modalities of atherosclerosis assessments and examine their ability to assess HF risk. The predictive value could be influenced by the left ventricular ejection fraction. Specifically, when the ejection fraction is reduced, its predictive value increases because this condition is potentially a result of coronary artery disease. In contrast, using these measures to predict HF with a preserved ejection fraction may be difficult because it is a heterogeneous condition. To overcome this issue, further research, especially on HF with a preserved ejection fraction, is required.

Nomograms Based on the Albumin/Neutrophil-to-Lymphocyte Ratio Score for Predicting Coronary Artery Disease or Subclinical Coronary Artery Disease

Purpose

To develop and validate two nomograms incorporating the albumin/neutrophil-to-lymphocyte ratio score (ANS) for predicting the risk of coronary artery disease (CAD) or subclinical CAD.

Patients and Methods

Four hundred fifty patients with suspected CAD who underwent coronary computed tomographic angiography were consecutively enrolled between September 2015 and June 2017. Nomograms were established based on independent predictors of CAD or subclinical CAD.

Results

In total, 437 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, age ≥65 years, smoking, hypertension, diabetes, dyslipidemia, ischemic stroke, and ANS were independent predictors of CAD and subclinical CAD. The areas under the curve of each nomogram were 0.799 (95% CI: 0.752-0.846) and 0.809 (95% CI: 0.762-0.856), respectively. The calibration curve and decision curve analysis showed good performance for the diagnostic nomograms. The prediction of CAD or subclinical CAD by the ANS was not modified by the independent predictors (all, p for interaction >0.05).

Conclusion

Our ANS-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD or subclinical CAD.

Factors predicting the occurrence of aortic valve calcification in patients with coronary artery calcification in China

OBJECTIVES

In patients with coronary artery calcification (CAC), a predictor of adverse cardiovascular events, coronary computed tomography angiography (CCTA) also shows valvular calcification. In this study, we evaluated common clinical indicators in CAC patients with aortic (AoVC) and mitral valve (MVC) calcification.

METHODS

CAC and valvular calcification were quantified using the Agatston score in 636 hospitalised patients with CAC who underwent CCTA.

RESULTS

Valvular calcification was found in 30.5% of patients, with 25.2% (160 patients) showing AoVC. Age was an independent predictor of AoVC in both men (odds ratio (OR), 1.086; 95% confidence interval (CI), [1.054-1.119]; p < 0.001) and women (OR, 1.109; CI, [1.066-1.154]; p < 0.001). In men, we also found that a history of cerebral infarction was an independent predictor of AoVC (OR, 2.402; CI, [1.177-4.902]; p < 0.05). The independent predictors of AoVC in the 60- to 69-years age group were BMI (OR, 1.181; CI, [1.061-1.316]; p < 0.01) and history of cerebral infarction (OR, 3.187; CI, [1.283-7.919]; p < 0.05).

CONCLUSIONS

Age is a key independent predictor of AoVC in CAC patients. History of cerebrovascular disease was also an independent predictor of AoVC, but only in men and patients aged 60-69 years. Our results indicate that a history of cerebral infarction may be used as a risk factor when identifying AoVC in patients with CAC.

Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment

OBJECTIVES

To calculate the coronary artery calcification score (CACS) obtained from coronary artery computed tomography angiography (CCTA) examination and combine it with the influencing factors of coronary artery calcification (CAC), which is then analyzed by machine learning (ML) to predict the probability of coronary heart disease(CHD).

METHODS

All patients who were admitted to the Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University from January 2019 to March 2022, suspected of CHD, and underwent CCTA inspection were retrospectively selected. The degree of CAC was quantified based on the Agatston score. To compare the correlation between the CACS and clinical-related factors, we collected 31 variables, including hypertension, diabetes, smoking, hyperlipidemia, among others. ML models containing the random forest (RF), radial basis function neural network (RBFNN),support vector machine (SVM),K-Nearest Neighbor algorithm (KNN) and kernel ridge regression (KRR) were used to assess the risk of CHD based on CACS and clinical-related factors.

RESULTS

Among the five ML models, RF achieves the best performance about accuracy (ACC) (78.96%), sensitivity (SN) (93.86%), specificity(Spe) (51.13%), and Matthew's correlation coefficient (MCC) (0.5192).It also has the best area under the receiver operator characteristic curve (ROC) (0.8375), which is far superior to the other four ML models.

CONCLUSION

Computer ML model analysis confirmed the importance of CACS in predicting the occurrence of CHD, especially the outstanding RF model, making it another advancement of the ML model in the field of medical analysis.

Global Burden and Improvement Gap of Non-Rheumatic Calcific Aortic Valve Disease: 1990-2019 Findings from Global Burden of Disease Study 2019

The aim of this study was to explore the most updated changing trends of non-rheumatic calcific aortic valve disease (nrCAVD) and reveal possible improvements. We analyzed the age-standardized rates (ASRs) of prevalence, incidence, disability-adjusted life-years (DALYs), and mortality trends of nrCAVD from 1990 to 2019 using data from the Global Burden of Disease (GBD) study 2019. The relations between ASRs and socio-demographic index (SDI) were analyzed with Pearson's correlation coefficients. Decomposition and frontier analysis were employed to reveal the contribution proportion of influence factors and regions where improvement can be achieved. In 2019, there were 9.40 million (95% uncertainty interval (UI): 8.07 to 10.89 million) individuals with nrCAVD globally. From 1990 to 2019, the prevalence rate of nrCAVD increased by 155.47% (95% IU: 141.66% to 171.7%), with the largest increase observed in the middle SDI region (821.11%, 95% UI: 709.87% to 944.23%). Globally, there were no significant changes in the mortality rate of nrCAVD (0.37%, 95% UI: -8.85% to 7.99%). The global DALYs decreased by 10.97% (95% UI: -17.94% to -3.46%). The population attributable fraction (PAF) of high systolic blood pressure increased in the population aged 15-49 years, while it declined slightly in population aged 50+ years. Population growth was the main contributing factor to the increased DALYs across the globe (74.73%), while aging was the driving force in the high-SDI region (80.27%). The Netherlands, Finland, Luxembourg, Germany, and Norway could reduce DALY rates of nrCAVD using their socio-demographic resources. According to these results, we revealed that the burden of nrCAVD increased markedly from 1990 to 2019 in high-SDI and high-middle-SDI regions. There was a downward trend in the mortality due to nrCAVD since 2013, which is possibly owing to profound advances in transcatheter aortic valve replacement. Some countries may reduce burdens of nrCAVD using their socio-demographic resources.

Evaluating Medical Therapy for Calcific Aortic Stenosis: JACC State-of-the-Art Review

Despite numerous promising therapeutic targets, there are no proven medical treatments for calcific aortic stenosis (AS). Multiple stakeholders need to come together and several scientific, operational, and trial design challenges must be addressed to capitalize on the recent and emerging mechanistic insights into this prevalent heart valve disease. This review briefly discusses the pathobiology and most promising pharmacologic targets, screening, diagnosis and progression of AS, identification of subgroups that should be targeted in clinical trials, and the need to elicit the patient voice earlier rather than later in clinical trial design and implementation. Potential trial end points and tools for assessment and approaches to implementation and design of clinical trials are reviewed. The efficiencies and advantages offered by a clinical trial network and platform trial approach are highlighted. The objective is to provide practical guidance that will facilitate a series of trials to identify effective medical therapies for AS resulting in expansion of therapeutic options to complement mechanical solutions for late-stage disease.

Calcific aortic valve disease: from molecular and cellular mechanisms to medical therapy

Calcific aortic valve disease (CAVD) is a highly prevalent condition that comprises a disease continuum, ranging from microscopic changes to profound fibro-calcific leaflet remodelling, culminating in aortic stenosis, heart failure, and ultimately premature death. Traditional risk factors, such as hypercholesterolaemia and (systolic) hypertension, are shared among atherosclerotic cardiovascular disease and CAVD, yet the molecular and cellular mechanisms differ markedly. Statin-induced low-density lipoprotein cholesterol lowering, a remedy highly effective for secondary prevention of atherosclerotic cardiovascular disease, consistently failed to impact CAVD progression or to improve patient outcomes. However, recently completed phase II trials provide hope that pharmaceutical tactics directed at other targets implicated in CAVD pathogenesis offer an avenue to alter the course of the disease non-invasively. Herein, we delineate key players of CAVD pathobiology, outline mechanisms that entail compromised endothelial barrier function, and promote lipid homing, immune-cell infiltration, and deranged phospho-calcium metabolism that collectively perpetuate a pro-inflammatory/pro-osteogenic milieu in which valvular interstitial cells increasingly adopt myofibro-/osteoblast-like properties, thereby fostering fibro-calcific leaflet remodelling and eventually resulting in left ventricular outflow obstruction. We provide a glimpse into the most promising targets on the horizon, including lipoprotein(a), mineral-binding matrix Gla protein, soluble guanylate cyclase, dipeptidyl peptidase-4 as well as candidates involved in regulating phospho-calcium metabolism and valvular angiotensin II synthesis and ultimately discuss their potential for a future therapy of this insidious disease.

Nomograms Based on the Advanced Lung Cancer Inflammation Index for the Prediction of Coronary Artery Disease and Calcification

Aim

To develop and validate 3 nomograms incorporating the advanced lung cancer inflammation index (ALI) that can aid in predicting the risk of coronary artery disease (CAD) and coronary artery calcification (CAC).

Methods

The study enrolled 562 consecutive patients with suspected CAD who underwent coronary computed tomographic angiography between September 2015 and June 2017. Independent risk factors for CAD, CAC, and CAD with CAC were identified via univariate and multivariate analysis, and nomograms were established based on the independent predictors identified. The area under the curve (AUC), calibration curve, and decision curve analysis were used to evaluate the nomograms. Correlations between ALI and other clinical indicators were examined via Spearman correlation analysis.

Results

In total, 549 patients with suspected CAD who underwent coronary computed tomographic angiography were included. Male sex, hypertension, diabetes, dyslipidemia, ischemic stroke, and ALI were independent predictors of both CAD and CAC. Male sex, hypertension, diabetes, dyslipidemia, and ALI were also identified as independent predictors of CAD with CAC. The AUC values for the nomograms developed using these risk factors were 0.739 (95% confidence interval [CI], 0.693-0.785), 0.728 (95% CI, 0.684-0.772), and 0.717 (95% CI 0.673-0.761), respectively. ALI was negatively correlated with neutrophil-to-lymphocyte ratio and CAC score and positively correlated with serum albumin levels and body mass index (all P < .05).

Conclusions

ALI is an independent predictor of CAD, CAC, and CAD with CAC. Our ALI-based nomograms can provide accurate and individualized risk predictions for patients with suspected CAD.

Cross-sectional study of aortic valve calcification and cardiovascular risk factors in older Danish men

OBJECTIVE

Aortic valve calcification (AVC) and coronary artery calcification (CAC) are predictors of cardiovascular disease (CVD), presumably sharing risk factors. Our objectives were to determine the prevalence and extent of AVC in a large population of men aged 60-74 years and to assess the association between AVC and cardiovascular risk factors including CAC and biomarkers.

METHODS

Participants from the DANish CArdioVAscular Screening and intervention trial (DANCAVAS) with AVC and CAC scores and without previous valve replacement were included in the study. Calcification scores were calculated on non-contrast CT scans. Cardiovascular risk factors were self-reported, measured or both, and further explored using descriptive and regression analysis for AVC association.

RESULTS

14 073 men aged 60-74 years were included. The AVC scores ranged from 0 to 9067 AU, with a median AVC of 6 AU (IQR 0-82). In 8156 individuals (58.0%), the AVC score was >0 and 215 (1.5%) had an AVC score ≥1200. In the regression analysis, all cardiovascular risk factors were associated with AVC; however, after inclusion of CAC ≥400, only age (ratio of expected counts (REC) 1.07 (95% CI 1.06 to 1.09)), hypertension (REC 1.24 (95% CI 1.09 to 1.41)), obesity (REC 1.34 (95% CI 1.20 to 1.50)), known CVD (REC 1.16 (95% CI 1.03 to 1.31)) and serum phosphate (REC 2.25 (95% CI 1.66 to 3.10) remained significantly associated, while smoking, diabetes, hyperlipidaemia, estimated glomerular filtration rate and serum calcium were not.

CONCLUSIONS

AVC was prevalent in the general population of men aged 60-74 years and was significantly associated with all modifiable cardiovascular risk factors, but only selectively after adjustment for CAC ≥400 AU.

TRIAL REGISTRATION NUMBER

NCT03946410 and ISRCTN12157806.