Early Diagnosis Of Coronary Artery Disease Research Articles

Preliminary study of metabonomic changes during the progression of atherosclerosis in miniature pigs.

To explore potential biomarkers for early diagnosis of atherosclerosis (AS) and provide basic data for further research on AS, the characteristics of serum metabolomics during the progression of AS in mini-pigs were observed dynamically. An AS model in Bama miniature pigs was established by a high-cholesterol and high-fat diet. Fasting serum samples were collected monthly for metabolomics and serum lipid detection. At the end of the treatment period, pathological analysis of the abdominal aorta and coronary artery was performed to evaluate the lesions of AS, thereby distinguishing the susceptibility of mini-pigs to AS. The metabolomics was detected using a high-resolution untargeted metabolomic approach. Statistical analysis was used to identify metabolites associated with AS susceptibility. Based on pathological analysis, mini-pigs were divided into two groups: a susceptible group (n = 3) and a non-susceptible group (n = 6). A total of 1318 metabolites were identified, with significant shifting of metabolic profiles over time in both groups. Dynamic monitoring analysis highlighted 57 metabolites that exhibited an obvious trend of differential changes between two groups with the advance of time. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis indicated significant disorders in cholesterol metabolism, primary bile acid metabolism, histidine metabolism, as well as taurine and hypotaurine metabolism. During the progression of AS in mini-pigs induced by high-cholesterol/high-fat diet, the alterations in serum metabolic profile exhibited a time-dependent pattern, accompanied by notable disturbances in lipid metabolism, cholesterol metabolism, and amino acid metabolism. These metabolites may become potential biomarkers for early diagnosis of AS.

Novel CAD Diagnosis Method Based on Search, PCA, and AdaBoostM1 Techniques.

Background: Cardiovascular diseases (CVDs) are the primary cause of mortality worldwide, resulting in a growing number of annual fatalities. Coronary artery disease (CAD) is one of the basic types of CVDs, and early diagnosis of CAD is crucial for convenient treatment and decreasing mortality rates. In the literature, several studies use many features for CAD diagnosis. However, due to the large number of features used in these studies, the possibility of early diagnosis is reduced. Methods: For this reason, in this study, a new method that uses only five features-age, hypertension, typical chest pain, t-wave inversion, and region with regional wall motion abnormality-and is a combination of eight different search techniques, principal component analysis (PCA), and the AdaBoostM1 algorithm has been proposed for early and accurate CAD diagnosis. Results: The proposed method is devised and tested on a benchmark dataset called Z-Alizadeh Sani. The performance of the proposed method is tested with a variety of metrics and compared with basic machine-learning techniques and the existing studies in the literature. The experimental results have shown that the proposed method is efficient and achieves the best classification performance, with an accuracy of 91.8%, ever reported on the Z-Alizadeh Sani dataset with so few features. Conclusions: As a result, medical practitioners can utilize the proposed approach for diagnosing CAD early and accurately.

Fluorescent probe-mediated labeling and real-time tracking of lipid droplet dynamics in foam cells formation

The aberrant deposition of lipid droplets (LDs) is a pivotal feature in foam cells formation and has significant implications for understanding the pathogenesis and early diagnosis of atherosclerosis (AS). In this study, we engineered a fluorescent probe, PyTPA-LD, for the reliable tracking of intracellular LDs. Through the application of PyTPA-LD, we monitored LD generation during the transition of macrophages induced by oxidized low-density lipoprotein (ox-LDL) into foam cells. Furthermore, we observed dynamic changes in lysosomes and LDs during lipophagy in this transitional process. Our study unveiled the dual role of lysosomes in LD formation: the degradation and release of ox-LDL within lysosomes promote LDs formation, while concurrently, lipophagy contributes to LDs clearance. This novel perspective provides a comprehensive understanding of the dynamic generation and clearance of LDs during foam cells formation. This work offers crucial insights into the pathogenic mechanisms underlying AS, deepening our understanding of AS development and providing valuable insights into lipid metabolism-related diseases.

Curcumin Equipped Nanozyme-Like Metal-Organic Framework Platform for the Targeted Atherosclerosis Treatment with Lipid Regulation and Enhanced Magnetic Resonance Imaging Capability.

Atherosclerotic cardiovascular disease (ASCVD) has become the leading cause of death worldwide, and early diagnosis and treatment of atherosclerosis (AS) are crucial for reducing the occurrence of acute cardiovascular events. However, early diagnosis of AS is challenging, and oral anti-AS drugs suffer from limitations like imprecise targeting and low bioavailability. To overcome the aforementioned shortcomings, Cur/MOF@DS is developed, a nanoplatform integrating diagnosis and treatment by loading curcumin (Cur) into metal-organic frameworks with nanozymes and magnetic resonance imaging (MRI) properties. In addition, the surface-modification of dextran sulfate (DS) enables PCN-222(Mn) effectively target scavenger receptor class A in macrophages or foam cells within the plaque region. This nanoplatform employs mechanisms that effectively scavenge excessive reactive oxygen species in the plaque microenvironment, promote macrophage autophagy and regulate macrophage polarization to realize lipid regulation. In vivo and in vitro experiments confirm that this nanoplatform has outstanding MRI performance and anti-AS effects, which may provide a new option for early diagnosis and treatment of AS.

Cardiac troponins and coronary artery calcium score: a systematic review

An early diagnosis of atherosclerosis, particularly in subclinical status, can play a remarkable role in reducing mortality and morbidity. Because of coronary artery calcification (CAC) nature in radiation exposure, finding biomarkers associated with CAC could be useful in identifying individuals at high risk of CAC score. In this review, we focused on the association of cardiac troponins (hs-cTns) and CAC to achieve insight into the pathophysiology of CAC. In October 2022, we systematically searched Web of Science, Scopus, PubMed, and Embase databases to find human observational studies which have investigated the association of CAC with cardiac troponins. To appraise the included articles, we used the Newcastle Ottawa scale (NOS). Out of 520 records, 10 eligible studies were included. Based on findings from longitudinal studies and cross-sectional analyses, troponin T and I were correlated with occurrence of CAC and its severity. Two of the most important risk factors that affect the correlation between hs-cTns serum levels and CAC were age and gender. The elevation of cardiac troponins may affect the progression of CAC and future cardiovascular diseases. Verifying the association between cardiac troponins and CAC may lead to identify individuals exposed to enhanced risk of cardiovascular disease (CVD) complications and could establish innovative targets for pharmacological therapy.

Serum Trimethylamine N-Oxide, Choline, Betaine, and Carnitine levels among Coronary Artery Disease patients

Background and aimRecent studies have linked Trimethylamine N-oxide (TMAO) to cardiovascular diseases; our study aimed to analyze the association between coronary artery disease (CAD) and TMAO. MethodsPubMed, Scopus, Embase, and Web of Science were searched using terms; such as “CAD” and “TMAO”. Only observational controlled studies were included. RevMan software version 5.4 was used for the analysis. ResultsA significant association was found between the CAD group and increased serum TMAO levels compared with the control group (MD = 1.16, 95% CI = 0.54 to 1.78, p-value =0.0003). This association remained significant among acute coronary syndrome (ACS) patients (MD=0.98, 95% CI =0.73 to 1.23, p-value <0.00001) and was also detected among young and old CAD patients (MD = 0.35, 95% CI = 0.06 to 0.64, p-value = 0.02 and MD = 1.36, 95% CI = 0.71 to 2.01, p-value <0.0001, respectively). On further analysis of intestinal metabolites, we detected an insignificant association between choline, betaine, carnitine, and CAD. According to our sensitivity analysis, TMAO is an acceptable discriminatory marker for CAD (0.721, SE was 0.0816, 95% CI 0.561 to 0.881). ConclusionTMAO is an acceptable discriminatory marker for CAD, with significantly higher levels among these patients regardless of their age. Other metabolites didn't show such an association. The role of serum level TMAO in the early diagnosis of CAD should be further explored.

Serum trimethylamine N-oxide levels among coronary artery disease and acute coronary syndrome patients: a systematic review and meta-analysis

Background and Aim: Recent studies have linked trimethylamine N-oxide (TMAO) to cardiovascular diseases; our study aimed to analyze the association between coronary artery disease (CAD), acute coronary syndrome (ACS), and TMAO. Methods: PubMed, Scopus, Embase, and Web of Science were searched using terms such as ʻCADʼ and ʻTMAOʼ. Only observational controlled studies were included. RevMan software version 5.4 was used for the analysis. Results: A significant association was found between the CAD group and increased serum TMAO levels compared with the control group (MD=1.16, 95% CI=0.54–1.78, P=0.0003). This association remained significant among acute coronary syndrome patients (MD=0.98, 95% CI=0.73–1.23, P&lt;0.00001) and was also detected among young and old CAD patients (MD=0.35, 95% CI=0.06–0.64, P=0.02 and MD=1.36, 95% CI=0.71–2.01, P&lt;0.0001, respectively). On further analysis of intestinal metabolites, the authors detected an insignificant association between choline, betaine, carnitine, and CAD. According to our sensitivity analysis, TMAO is an acceptable diagnostic marker for CAD (0.721, SE was 0.0816, 95% CI: 0.561–0.881). Conclusion: TMAO is an acceptable diagnostic marker for CAD, with significantly higher levels among these patients regardless of their age. Other metabolites did not show such an association. The role of serum level TMAO in the early diagnosis of CAD should be further explored.

A novel HClO-activatable lysosome-targeted fluorescent probe for imaging and diagnosis of atherosclerosis

Atherosclerosis (AS) is a systemic vascular disease that typically takes decades before overt disease manifests itself. Due to this silent course, it is essential to create disease predictors before clinical lesions develop. In AS, dysfunction of lysosome induced by the accumulation of HClO changes cytokine secretion from macrophages. The formation of foam cells with an elevated HOCl level is regarded as an iconic feature of the early AS lesion. However, fluorescent probes targeting lysosome to monitor the variations of HClO level during the AS procedure have not reported. In this work, we firstly report a lysosome-targeted fluorescence probe, Lys-HClO, for evaluating AS by mapping the fluctuation of HClO with high selectivity and sensitivity. Meanwhile, probe Lys-HClO can be located in lysosome and successfully used to detected endogenous and exogenous HClO in cells. Furthermore, probe Lys-HClO was effectively applied to imaging endogenous HClO in zebrafish. Notably, with the assistance of probe Lys-HClO, we successfully monitored the significant up regulation of HClO in aorta of high-fat diet (HFD) -induced AS. These results indicate that Lys-HClO was a prospective image tool in studying early diagnosis of AS.

Inflammatory atherosclerotic plaque identification by SPECT/CT imaging of LFA-1 using [111In] In-DANBIRT in a novel dyslipidemic rat model.

Atherosclerosis is prevalent globally, closely associated with dyslipidemia and other metabolic dysfunction. Early diagnosis of atherosclerosis is challenging due to limited diagnostic capabilities that need to be expanded with animal models with enhanced vascular biology like rats. Our previous research showed [111In] In-DANBIRT has potential as a diagnostic tool for detecting atherosclerosis in mice. The primary aim of the present study is to evaluate [111In] In-DANBIRT in a novel atherosclerotic rat with early- and late-stage atherosclerosis and metabolic disease. We characterized metabolic and body composition differences in these novel dyslipidemic rats under different diets using serum chemistry and dual-energy X-ray absorptiometry (DEXA) scan, respectively. We performed 1-h post-injection in vivo molecular imaging of ApoE knockout, lean Zucker (LZ) male rats at baseline and followed them into 10weeks of either normal or high-fat/cholesterol diet implementation (22weeks of age). We identified significant differences in body composition and metabolic changes in ApoE knockout rats compared to ApoE wildtype rats. Our findings indicate an increased uptake of [111In] In-DANBIRT in ApoE knockout, lean Zucker (LZ) rats, particularly in the descending aorta, a location where early-stage atherosclerosis is commonly found. Our findings, however, also revealed that the ApoE knockout, Zucker diabetic fatty (ZDF) model has high mortality rate, which may be attributed to alterations of critical enzymes involved in regulating metabolism and liver function. Our results are highly encouraging as they demonstrated the potential of [111In] In-DANBIRT to detect early-stage atherosclerosis in rats that might otherwise go unnoticed by other methods, showcasing the high sensitivity of [111In] In-DANBIRT. Our future studies will aim to establish a viable T2D atherosclerosis model in rats with more advanced stages of the disease to further demonstrate the reliability of [111In] In-DANBIRT as a diagnostic tool for patients in all stages of atherosclerosis.

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning

Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are prone to incorrectly filter out the near-wall blood flow signal, resulting in poor velocimetric accuracy. In addition, the Doppler coherent compounding acts as a low-pass filter, which also leads to low values of blood flow velocity estimated by the above methods. Motivated by this status quo, here we propose a deep learning estimator that combines clutter filtering and blood flow velocimetry based on the adaptive property of one-dimensional convolutional neural network (1DCNN). The estimator is operated by first extracting the blood flow signal from the original Doppler echo signal through an affine transformation of the 1D convolution, and then converting the extracted signal into the desired blood flow velocity using a linear transformation function. The effectiveness of the proposed method is verified by simulation as well as in vivo carotid artery data. Compared with typical velocimetry methods such as high-pass filtering (HPF) and singular value decomposition (SVD), the results show that the normalized root means square error (NRMSE) obtained by 1DCNN is reduced by 54.99 % and 53.50 % for forward blood flow velocimetry, and 70.99 % and 69.50 % for reverse blood flow velocimetry, respectively. Consistently, the in vivo measurements demonstrate that the goodness-of-fit of the proposed estimator is improved by 8.72 % and 4.74 % for five subjects. Moreover, the estimation time consumed by 1DCNN is greatly reduced, which costs only 2.91 % of the time of HPF and 12.83 % of the time of SVD. In conclusion, the proposed estimator is a better alternative to the current blood flow velocimetry, and is capable of providing more accurate diagnosis information for vascular diseases in clinical applications.

A dual-lock-controlled mitochondria-targeted ratiometric fluorescence probe for simultaneous detection of atherosclerosis-related HClO and viscosity

Precise detection of inflammatory microenvironment-related viscosity and hypochlorous acid (HClO) contributes to illuminating the pathogenesis and further diagnosing of atherosclerosis (AS). Herein, a dual-lock-controlled mitochondria-targeted fluorescence probe (NS) for simultaneous imaging of HClO and viscosity in AS-related foam cells is presented. NS performs linear increase in green-fluorescence along with increased viscosity (excited at 425 nm), permitting “off–on” fluorescence imaging of viscosity. Meanwhile, upon HClO activation, NS exhibits red-shifted and enhanced fluorescence in orange, thus leading to ratiometric fluorescence quantification of HClO (excited at 465 nm). Such dual-lock-controlled effect makes NS realize simultaneous imaging of viscosity and HClO with high sensitivity and selectivity via “off–on” and ratiometric fluorescence readouts, respectively. Besides, endowed with mitochondria-targeting capacity, NS achieves in situ imaging of mitochondria viscosity and HClO in living RAW264.7 cells. Importantly, for the first time, NS realizes simultaneous imaging of mitochondria viscosity and HClO in macrophage-derived foam cells, revealing the close association between HClO level and viscosity change in mitochondria during foaming translation of macrophages in atherogenesis. This work not only provides a novel strategy and tool to image organelle-located viscosity and HClO in living systems, but also holds great potential in early diagnosis of AS.

Prediction of Coronary Artery Disease Using Machine Learning Techniques with Iris Analysis

Coronary Artery Disease (CAD) occurs when the coronary vessels become hardened and narrowed, limiting blood flow to the heart muscles. It is the most common type of heart disease and has the highest mortality rate. Early diagnosis of CAD can prevent the disease from progressing and can make treatment easier. Optimal treatment, in addition to the early detection of CAD, can improve the prognosis for these patients. This study proposes a new method for non-invasive diagnosis of CAD using iris images. In this study, iridology, a method of analyzing the iris to diagnose health conditions, was combined with image processing techniques to detect the disease in a total of 198 volunteers, 94 with CAD and 104 without. The iris was transformed into a rectangular format using the integral differential operator and the rubber sheet methods, and the heart region was cropped according to the iris map. Features were extracted using wavelet transform, first-order statistical analysis, a Gray-Level Co-Occurrence Matrix (GLCM), and a Gray Level Run Length Matrix (GLRLM). The model's performance was evaluated based on accuracy, sensitivity, specificity, precision, score, mean, and Area Under the Curve (AUC) metrics. The proposed model has a 93% accuracy rate for predicting CAD using the Support Vector Machine (SVM) classifier. With the proposed method, coronary artery disease can be preliminarily diagnosed by iris analysis without needing electrocardiography, echocardiography, and effort tests. Additionally, the proposed method can be easily used to support telediagnosis applications for coronary artery disease in integrated telemedicine systems.

Predicting Factors of Atherosclerosis in Children with Beta-Thalassemia Major

Background: Atherosclerosis is an important cardiovascular disorder in beta-thalassemia major patients. The present study aimed to predict factors of atherosclerosis in children with beta-thalassemia major.&#x0D; Materials and Methods: This cross-sectional study was conducted on 36 patients with beta-thalassemia major and 36 healthy children as the control group. The carotid intima-media thickness (CAIMT) and osteoprotegerin (OPG) were compared between groups.&#x0D; Results: The mean age of the patients in the case and control groups were 13.5 ± 3.7 and 13 ± 3.1 years old, respectively. Significant differences in CAIMT in the right (P = 0.001) and left (P = 0.001) arteries were recorded between the two groups. The mean serum OPG in the beta-thalassemia group was significantly higher than the control group (3.9 ng/ml and 1.4 ng/ml, respectively, P=0.001).&#x0D; Conclusion: CAIMT is a non-invasive method for diagnosing atherosclerosis. According to the significant difference between groups, serum OPG could be helpful in the diagnosis of early atherosclerosis in beta-thalassemia major.

A Prediction Model Created by Comparing Tree-Based Methods To Assess Coronary Artery Disease

Aim: As people's quality of life and habits have changed, Coronary Artery Disease (CAD) has become the leading cause of death globally. It is a complicated cardiac disease with various risk factors and a wide range of symptoms. An early and accurate diagnosis of CAD allows for the quick administration of appropriate treatment, which contributes to a decreased mortality rate. Machine learning (ML) algorithms for CAD prediction and treatment decisions are quickly being developed and implemented in clinical practice. Predictive models based on machine learning algorithms may aid health personnel in the early diagnosis of CAD, lowering mortality. Thus, this study goal is to forecast the elements that may be connected with CAD using tree-based approaches, which are one of the machine learning methods, and to discover which factor is more effective on CAD. Material and Methods: The open-access heart disease dataset was used within the scope of the study to investigate the risk factors related with CAD. The data set used contains the values of 333 patients, as well as 20 input and 1 target variables. The 10-fold cross validation approach was employed in the modeling, and the data set was divided as 80%: 20% as training and test datasets. For model assessment, the measures of accuracy (ACC), balanced accuracy (b-ACC), sensitivity (SE), specificity (SP), positive predictive value (ppv), negative predictive value (npv), and F1-score were utilized. Results: The values of ACC, b-ACC, SE, SP, ppv, npv, and F1-score performance metrics were 9 98.5%, 98.8%, 97.7%, 100%, 100%, 95.8% and 98.8%, respectively, as a consequence of the estimate model results created with the XGBoost approach, which has the best performance among tree-based models. When the groups with or without CAD were compared, a statistically significant difference was found in terms of the age variable. There is also a significant relationship between the active, lifestyle, ihd, dm, ecgpatt, qwave variables and the presence/absence of the CAD variable. When the variable significance values obtained as a result of modeling with the highest performing XGBoost are examined, it is seen that the variables that most associated with CAD are ekgpatt: normal, ekgpatt: ST-depression, ekgpatt: T-inversion, qwave: yes, age, bpdias, height, LDL, HR, IVSD: with LVH, bpsyDM. Conclusion: According to the performance criteria of the forecasting models used, CAD gave distinctively successful results in forecasting. By identifying risk factors associated with CAD, the proposed machine learning models can provide clinicians with practical, cost-effective and beneficial assistance in making accurate predictive decisions.

Importance of incidental coronary artery calcification in early diagnosis of obstructive coronary artery disease.

The early diagnosis of coronary artery disease (CAD) enables early intervention for the modifiable risk factors of the disease. Coronary artery calcification (CAC) detected incidentally on standard noncontrast chest computed tomography (CT) provides an opportunity for the early diagnosis of CAD. The purpose of this study was to demonstrate that CAC should be routinely reported when evaluating thoracic CT examinations. Routine reporting of CAC will contribute to the early diagnosis of CAD. The present study included 279 patients who underwent conventional coronary angiography (CAG) and CT within one month before undergoing CAG. The CAG and CT images of the patients were evaluated retrospectively. The levels of coronary artery stenosis were determined in reference to the CAG images. The CAC scores of the patients were calculated using the Weston method based on their chest CT images. The mean age of the patients was 63.2 ± 11.5 (range, 41-93) years, and 172 (61.6%) of them were men. The Weston score (WS) was 0 in 18.9% of the patients with obstructive CAD (OCAD), whereas it was ≥ 7 in 27.9% of patients. All patients with a WS of ≥ 7 had OCAD. All patients without luminal stenosis or < 50% stenosis had a WS of < 7. The CAC score is useful for the diagnosis of CAD and OCAD. If CAC is identified on standard noncontrast chest CT, it should be scored and reported accordingly. The WS can be used for CAC scoring.

Early Diagnosis of Coronary Artery Disease by Inflammatory Biomarkers of Atherosclerosis in Patients with Angina.

Early diagnosis of coronary artery disease (CAD) in patients with chest pain is a challenge. Currently diagnosis of CAD is confirmed by coronary angiography, which is invasive and not easily available in developing countries. Therefore, it is imperative to establish noninvasive biomarker for early diagnosis of CAD in patients with angina and determine the diagnostic accuracy of inflammatory biomarkers of atherosclerosis in comparison to angiography and correlate with severity of CAD in patients with angina. Diagnostic accuracy study was carried out in tertiary care hospitals, Rawalpindi, Pakistan. Total of 58 patients aged 55.24 ± 11.61 years, with chest pain and troponin-I -ve, having coronary artery stenosis ≥50% were included as cases of CAD and 55 subjects having stenosis <50% were included as controls. Nuclear factor kappa-B (NF-κB), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and high-sensitivity C-reactive protein (hs-CRP) were analyzed on immunoassay analyzers. The receiver operating characteristic curve analysis revealed significant (P < 0.05) high area under curve (95% confidence interval) with sensitivity and specificity of NF-κB 0.76 (0.65-0.85), 73% and 65%; TNF-α 0.72 (0.61-0.81), 71% and 69%; IL-6 0.62 (0.52-0.71), 64% and 53% and hs-CRP 0.62 (0.52-0.71), and 53% and 56% in CAD patients compared to controls. There was significant positive correlation between NF-κB (r = 0.44), TNF-α (r = 0.37), IL-6 (r = 0.23), and hs-CRP (r = 0.23) with severity of CAD by Gensini score. The inflammatory biomarkers, especially NF-κB and TNF-α, have highest diagnostic accuracy and indicate severity of atherosclerosis in patients with angina. These markers may be used as noninvasive biomarkers to exclude healthy individuals before undergoing angiography.

New Progress in Early Diagnosis of Atherosclerosis.

Coronary atherosclerosis is a potentially chronic circulatory condition that endangers human health. The biological cause underpinning cardiovascular disease is coronary atherosclerosis, and acute cardiovascular events can develop due to thrombosis, platelet aggregation, and unstable atherosclerotic plaque rupture. Coronary atherosclerosis is progressive, and three specific changes appear, with fat spots and stripes, atherosclerosis and thin-walled fiber atherosclerosis, and then complex changes in arteries. The progression and severity of cardiovascular disease are correlated with various levels of calcium accumulation in the coronary artery. The therapy and diagnosis of coronary atherosclerosis benefit from the initial assessment of the size and degree of calcification. This article will discuss the new progress in the early diagnosis of coronary atherosclerosis in terms of three aspects: imaging, gene and protein markers, and trace elements. This study intends to present the latest methods for diagnosing patients with early atherosclerosis through a literature review.

Celiac Disease Patients With Coronary Artery Disease: A Nationwide Population-Based Study.

BackgroundCoronary artery disease (CAD) is associated with celiac disease (CD) with limited evidence. However, the common risk factors linking CD and CAD are still lacking in the literature. Known CAD risk factors include hypertension, hyperlipidemia, type 2 diabetes, obesity, and tobacco use. Common risk factors linking CD and CAD are poorly documented.ObjectiveThere are three objectives: Firstly, to evaluate potential demographic differences between CD patients with CAD and without CAD. Secondly, to analyze the risk factors of CAD in CD patients. Lastly, to compare CD-CAD and matched non-CD CAD to determine whether there are additional CAD risks in individuals with CD.MethodsThe study is a nationwide retrospective case-control study. The National Inpatient Sample (NIS) database was used to identify patients admitted between 2016 and 2018 with a principal or secondary diagnosis of CD. We analyzed sociodemographic and clinical risk factors of CAD in CD patients and compared the CD-CAD population with the matched non-CD CAD cohort.ResultsOut of 23,441 hospitalizations with CD in 2016-2018, 4244 (18%) were found to have CAD. Established CAD risk factors identified in CD patients included hypertension, hyperlipidemia, type 2 diabetes, and a family history of CAD. In contrast, tobacco use is not a CAD risk factor in CD patients. Female patients with CD had 55% lesser odds of CAD than male patients. The odds of CAD in CD patients with hyperlipidemia were five times higher, 1.2 times higher with essential hypertension, and two times higher with type 2 diabetes. Patients with CAD had a higher prevalence of iron deficiency anemia (9.33% CD-CAD and 8.28% non-CAD CD Vs. 7.32% non-CD CAD).ConclusionsOur study confirms that, as with non-CD individuals, males and the White race are at increased CAD risk in the CD population. CD-CAD patients have a higher hyperlipidemia prevalence than non-CD CAD patients. CD patients with type 1 diabetes have an early diagnosis of CAD compared to CD patients with type 2 diabetes. Iron deficiency anemia is a statistically significant risk factor for CAD in CD patients.

Coronary calcium scoring as first-line test to detect and exclude coronary artery disease in patients presenting to the general practitioner with stable chest pain: protocol of the cluster-randomised CONCRETE trial

IntroductionIdentifying and excluding coronary artery disease (CAD) in patients with atypical angina pectoris (AP) and non-specific thoracic complaints is a challenge for general practitioners (GPs). A diagnostic and prognostic tool...

Coronary Artery Calcium Score - A Reliable Indicator of Coronary Artery Disease?

Coronary artery disease (CAD) is caused by atheromatous blockage of coronary vessels leading to acute coronary events that usually occur when a plaque ruptures and a thrombus forms. CAD is a known cause of significant cardiovascular events, accounting for more than 50% of the deaths in western countries, and most of the patients with CAD remain asymptomatic. The coronary artery calcium (CAC) score has been created as a measure of coronary atherosclerosis. This article has compiled various studies that conclude the clinical relationship between coronary artery calcium and the development of cardiovascular (CV) events by using the CAC score as a reliable indicator of CAD. This article has reviewed the pathophysiology and risk factors of CAD, along with various methods of CAC scoring. It also underlined the reliability of CAC scoring for early detection of CAD in asymptomatic individuals. We emphasized the importance of age-dependent risk factor analysis combined with practical screening tools like CAC scoring for early diagnosis of CAD can help direct the treatment and prevent deaths in asymptomatic individuals.