Early Detection Of Cardiovascular Disease Research Articles

Practicality and importance of selected endothelial dysfunction measurement techniques: review.

The measurement of endothelial dysfunction (ED) has importance in that it indicates the presence of coronary artery disease (Kuvin et al. in J Am Coll Cardiol 38(7):1843-1849, 2001) in addition to acting as a predictor of future adverse events (Halcox et al. in Circulation 106:653-658, 2002). Various tools, methods, and metrics exist that can provide an indicator of endothelial dysfunction. Given the significance of ED, it is of utmost importance to find a measurement technique that is reliable, while defining a metric providing a framework for an overall system that is practical, accurate, and repeatable. Success would provide a tool for the early detection of cardiovascular disease not only moving patients that are currently classified as asymptomatic to symptomatic, but also providing a method to monitor the efficacy of treatments.

MechanicalHeart

Listening to heart sounds is an important first step in evaluating the cardiovascular system and is important in the early detection of cardiovascular disease. We present and evaluate a framework for combining machine learning algorithms, crowd workers, and experts in the classification of heart sound recordings. The development of a hybrid human-machine framework is motivated by the past success in utilizing human computation to solve problems in medicine and the use of human-machine frameworks in other domains. We describe the methods that decide when and how to escalate the analysis of heart sounds to different resources and incorporate their decision into a final classification. Our framework was tested with a combination of machine classifiers and crowd workers from Amazon's Mechanical Turk. The results indicate a hybrid approach achieves greater performance than a baseline classifier alone, utilizing less expert resources while achieving similar performance, compared to a framework without the crowd.

A Disposable Blood-on-a-Chip for Simultaneous Measurement of Multiple Biophysical Properties.

Biophysical properties are widely used to detect pathophysiological processes of vascular diseases or clinical states. For early detection of cardiovascular diseases, it is necessary to simultaneously measure multiple biophysical properties in a microfluidic environment. However, a microfluidic-based technique for measuring multiple biophysical properties has not been demonstrated. In this study, a simple measurement method was suggested to quantify three biophysical properties of blood, including red blood cell (RBC) deformability, RBC aggregation, and hematocrit. To demonstrate the suggested method, a microfluidic device was constructed, being composed of a big-sized channel (BC), a parallel micropillar (MP), a main channel, a branch channel, inlet, and outlets. By operating a single syringe pump, blood was supplied into the inlet of the microfluidic device, at a periodic on-off profile (i.e., period = 240 s). The RBC deformability index (DI) was obtained by analyzing the averaged blood velocity in the branch channel. Additionally, the RBC aggregation index (AIN) and the hematocrit index (HiBC) were measured by analyzing the image intensity of blood flows in the MP and the BC, respectively. The corresponding contributions of three influencing factors, including the turn-on time (Ton), the amplitude of blood flow rate (Q0), and the hematocrit (Hct) on the biophysical indices (DI, AIN, and HiBC) were evaluated quantitatively. As the three biophysical indices varied significantly with respect to the three factors, the following conditions (i.e., Ton = 210 s, Q0 = 1 mL/h, and Hct = 50%) were maintained for consistent measurement of biophysical properties. The proposed method was employed to detect variations of biophysical properties depending on the concentrations of autologous plasma, homogeneous hardened RBCs, and heterogeneous hardened RBCs. Based on the observations, the proposed method exhibited significant differences in biophysical properties depending on base solutions, homogeneous hardened RBCs (i.e., all RBCs fixed with the same concentration of glutaraldehyde solution), and heterogeneous hardened RBCs (i.e., partially mixed with normal RBCs and homogeneous hardened RBCs). Additionally, the suggested indices (i.e., DI, AIN, and HiBC) were effectively employed to quantify three biophysical properties, including RBC deformability, RBC aggregation, and hematocrit.

Automatic Segmentation of Brachial Artery based on Fuzzy C-Means Pixel Clustering from Ultrasound Images

Automatic extraction of brachial artery and measuring associated indices such as flow-mediated dilatation and Intima-media thickness are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose the basic but important component of such decision-assisting medical software development – noise tolerant fully automatic segmentation of brachial artery from ultrasound images. Pixel clustering with Fuzzy C-Means algorithm in the quantization process is the key component of that segmentation with various image processing algorithms involved. This algorithm could be an alternative choice of segmentation process that can replace speckle noise-suffering edge detection procedures in this application domain.

The connection between the breast and heart in a woman: Breast cancer and cardiovascular disease.

Cardiovascular disease remains the leading cause of death in women in the United States and is a major public health issue for all women, but it is of increasing concern to breast cancer survivors. Advancements in early detection and breast cancer therapy have resulted in over 90% of women surviving 5 years past their diagnosis of breast cancer. Nonetheless, with increased survivorship from breast cancer, there has been an increase in cardiovascular disease in these women. The consequences of the treatments for breast cancer may increase the risk for cardiovascular disease. Additionally, there is an overlap of risk factors common to both breast cancer and cardiovascular disease. The increased risk of cardiovascular disease in women who survive breast cancer must be recognized, with a focus on the prevention and early detection of cardiovascular disease.

Systemic vascular dysfunction is associated with emphysema burden in mild COPD.

Cardiovascular diseases play a major role in morbidity and mortality in the earlier stages of COPD. We hypothesized that systemic vascular dysfunction would be present even in patients who are currently considered at "low-risk" for negative cardiovascular outcomes, i.e., those with largely preserved FEV1, few exacerbations and only mild burden of respiratory symptoms (GOLD spirometric grade 1, clinical group A). 16 patients (FEV1 = 86 ± 13%) and 16 age- and gender-matched controls underwent measurements of: a) central arterial stiffness by pulse wave velocity, b) brachial flow-mediated dilation and c) forearm muscle oxygenation by near-infrared spectroscopy. Computed tomography quantified emphysema (% of low attenuation areas (LAA)) and airway disease. Patients and controls were well matched for key clinical variables including co-morbidities burden. Thirteen patients presented with more than 5% LAA: emphysema extension was negatively related to transfer factor for carbon monoxide (TLCO) (r = -0.63; p = .01). Compared to controls, patients had higher central arterial stiffness, lower normalized (to shear stress) flow-mediated dilation, delayed time to peak flow-mediated dilation and poorer muscle oxygenation (p < .05). TLCO and emphysema, but not airway disease, were significantly related to each of these functional abnormalities (r values ranging from 0.51 to 0.66; p < .05). Systemic vascular dysfunction is present in the earlier stages of COPD, particularly in patients with greater emphysema burden and low TLCO. Regardless FEV1, patients showing those structural and functional abnormalities might be at higher risk of negative events thereby deserving closer follow-up for early detection of cardiovascular disease.

Detecting miRNA biomarkers from extracellular vesicles for cardiovascular disease with a microfluidic system.

According to World Health Organization reports, cardiovascular diseases (CVDs) are amongst the major causes of death globally and are responsible for over 18 million deaths every year. Traditional detection methods for CVDs include cardiac computerized tomography scans, electrocardiography, and myocardial perfusion imaging scans. Although diagnosis of CVDs through such bio-imaging techniques is common, these methods are relatively costly and cannot detect CVDs in their earliest stages. In contrast, the levels of certain micro RNA (miRNA) biomarkers extracted from extracellular vesicles (EVs) in the bloodstream have been recognized as promising indicators for early CVD detection. However, detection and quantification of miRNA using existing methods are relatively labor-intensive and time-consuming. In this study, a new integrated microfluidic system equipped with highly sensitive field-effect transistors (FETs) was capable of performing EV extraction, EV lysis, target miRNA isolation and miRNA detection within 5 h. The limit of detection was within the physiological range (femtomolar) for two targeted miRNAs, miR-21 and miR-126, meaning that this integrated microfluidic system has the potential to be used as a tool for early detection of CVDs.

From 4D Medical Images (CT, MRI, and Ultrasound) to 4D Structured Mesh Models of the Left Ventricular Endocardium for Patient-Specific Simulations.

With cardiovascular disease (CVD) remaining the primary cause of death worldwide, early detection of CVDs becomes essential. The intracardiac flow is an important component of ventricular function, motion kinetics, wash-out of ventricular chambers, and ventricular energetics. Coupling between Computational Fluid Dynamics (CFD) simulations and medical images can play a fundamental role in terms of patient-specific diagnostic tools. From a technical perspective, CFD simulations with moving boundaries could easily lead to negative volumes errors and the sudden failure of the simulation. The generation of high-quality 4D meshes (3D in space + time) with 1-to-1 vertex becomes essential to perform a CFD simulation with moving boundaries. In this context, we developed a semiautomatic morphing tool able to create 4D high-quality structured meshes starting from a segmented 4D dataset. To prove the versatility and efficiency, the method was tested on three different 4D datasets (Ultrasound, MRI, and CT) by evaluating the quality and accuracy of the resulting 4D meshes. Furthermore, an estimation of some physiological quantities is accomplished for the 4D CT reconstruction. Future research will aim at extending the region of interest, further automation of the meshing algorithm, and generating structured hexahedral mesh models both for the blood and myocardial volume.

Farmers Have Hearts: The Prevalence of Risk Factors for Cardiovascular Disease Among a Subgroup of Irish Livestock Farmers

ABSTRACT Objectives: Despite international findings that farmers have better health outcomes than other occupation groups, Irish farmers are found to be a high-risk group for cardiovascular disease (CVD). Early detection of CVD through preventive health measurements, such as screening of high-risk groups, can contribute to a reduction of CVD cases. Farmers, however, represent a “challenging” group in terms of engaging in preventive health behaviors. This study examined the prevalence of cardiovascular risk factors among male Irish livestock farmers who participated in heart screening as part of a workplace health intervention. Methods: In this cross-sectional study, data were collected from a convenience sample (N = 310) of farmers. Consent included permission to analyze the heart screening results and to participate in two follow-up questionnaires by phone at Week 1 (n = 224) and Week 12 (n = 172). All data were entered onto the Statistical Package for the Social Sciences (SPSS version 22) and both descriptive and inferential statistics were compiled. Results: Almost one in two (46%; n = 140) farmers had high blood pressure (≥140/≥90 mm Hg), and 46% (n = 140) had elevated total cholesterol. One third of farmers were found to be obese (35%; n = 110). The vast majority (83%; n = 255) had at least four risk factors for CVD based on the outcomes of the heart screening. Conclusion: The study findings in relation to obesity and the prevalence of multiple risk factors for CVD are a particular cause of concern and shed considerable light on the current excess burden of CVD among farmers in Ireland.

Abstract 107: Cardiovascular Risk Predictors Among Black and African American Women: A Preliminary Analysis of the P4 Study

Objective: To identify predictors that allow for early detection of cardiovascular disease in African American women Background: Cardiovascular (CV) mortality is high in African Americans in the United States. Cardiovascular disease (CVD) remains the leading cause of death in African American females. We hypothesize that certain cardiovascular risk factors are predictors of abnormal peripheral vascular compliance. We aim to identify determinants of abnormal vascular compliance by assessing the association between known CVD risk factors and the extent of vascular compliance Methods: This cross-sectional study utilized survey responses and results from a noninvasive screening tool. The study included only African American women. Traditional CV risk factors were independent variables (history of hypertension, high serum lipids, family or personal history of CVD). The instrument employed biomarkers that detect blood vessel elasticity. Outcome measures included small and large vessel compliance. Both survey responses and screening results were obtained from 70 consecutive participants. We conducted a univariate and bivariate descriptive analysis. A Chi-square or Fishers exact test was used to determine the significance as appropriate. We adjusted for potential confounders in our multivariable analysis. SAS 9.4 software was used for all the data analyses Results: Our study indicates that personal history of cardiovascular disease is strongly associated with abnormal small vessel compliance (Pvalue - 0.01). Family history of cardiovascular disease is strongly associated with abnormal large artery compliance (Pvalue - 0.02). History of cardiovascular disease in both parents is associated with abnormal large artery compliance (Pvalue - 0.04). Interestingly, Living Situation (Living alone) was associated with abnormal large artery compliance (Pvalue - 0.03) Conclusion: Family and personal history of CVD, and living alone have strong associations with abnormal vascular compliance. Cardiovascular mortality is high in Black and African American females. Identifying predictors of abnormal vascular compliance can allow for early disease detection and intervention.

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

Complementary role of cardiovascular imaging and laboratory indices in early detection of cardiovascular disease in systemic lupus erythematosus.

Background Cardiovascular disease (CVD) has been documented in >50% of systemic lupus erythematosus (SLE) patients, due to a complex interplay between traditional risk factors and SLE-related factors. Various processes, such as coronary artery disease, myocarditis, dilated cardiomyopathy, vasculitis, valvular heart disease, pulmonary hypertension and heart failure, account for CVD complications in SLE. Methods Electrocardiogram (ECG), echocardiography (echo), nuclear techniques, cardiac computed tomography (CT), cardiovascular magnetic resonance (CMR) and cardiac catheterization (CCa) can detect CVD in SLE at an early stage. ECG and echo are the cornerstones of CVD evaluation in SLE. The routine use of cardiac CT and nuclear techniques is limited by radiation exposure and use of iodinated contrast agents. Additionally, nuclear techniques are also limited by low spatial resolution that does not allow detection of sub-endocardial and sub-epicardial lesions. CCa gives definitive information about coronary artery anatomy and pulmonary artery pressure and offers the possibility of interventional therapy. However, it carries the risk of invasive instrumentation. Recently, CMR was proved of great value in the evaluation of cardiac function and the detection of myocardial inflammation, stress-rest perfusion defects and fibrosis. Results An algorithm for CVD evaluation in SLE includes clinical, laboratory, ECG and echo assessment as well as CMR evaluation in patients with inconclusive findings, persistent cardiac symptoms despite normal standard evaluation, new onset of life-threatening arrhythmia/heart failure and/or as a tool to select SLE patients for CCa. Conclusions A non-invasive approach including clinical, laboratory and imaging evaluation is key for early CVD detection in SLE.

The risk factors and prevention of cardiovascular disease: the importance of electrocardiogram in the diagnosis and treatment of acute coronary syndrome.

Acute coronary syndrome is a leading cause of emergency medical treatment and hospitalization in Poland. High-speed electrocardiogram (ECG) has shown good accuracy of the initial diagnosis and of the final diagnosis in treated cardiac patients. Initial diagnosis and definitive diagnosis were analyzed statistically (P<0.0001). Although much is said about the prevention of sudden death in heart failure, the elimination of risk factors health care in Poland does not pay due attention to the need for early diagnosis and ECG analysis (at the stage of prevention). This article presents the inclusion of ECG in the prevention process and shows that it allows for early detection of cardiovascular diseases. In Poland, ST-segment elevation myocardial infarction patients are identified in the ambulance that reduces time to door-to-balloon.

Foamy Monocytes Are Enriched in cis-7-Hexadecenoic Fatty Acid (16:1n-9), a Possible Biomarker for Early Detection of Cardiovascular Disease

Human monocytes respond to arachidonic acid, a secretory product of endothelial cells, by activating the de novo pathway of fatty acid biosynthesis, resulting in the acquisition of a foamy phenotype due to accumulation of cytoplasmic lipid droplets. Recruitment of foamy monocytes to endothelium is a key step in the formation of atherosclerotic plaques. Here we describe that lipid droplets of foamy monocytes are enriched in a rather uncommon fatty acid, cis-7-hexadecenoic acid (16:1n-9), a positional isomer of palmitoleic acid. 16:1n-9 was found to possess an anti-inflammatory activity both invitro and invivo that is comparable with that of omega-3 fatty acids and clearly distinguishable from the effects of palmitoleic acid. Selective accumulation in neutral lipids of phagocytic cells of an uncommon fatty acid reveals an early phenotypic change that may provide a biomarker of proatherogenicity, and a potential target for intervention in the early stages of cardiovascular disease.

Characteristics of beat-to-beat photoplethysmography waveform indexes in subjects with metabolic syndrome

Metabolic syndrome (MetS) increases the risk of the subsequent development of cardiovascular disease. This study aimed to determine if the harmonic indexes of finger photoplethysmography (PPG) waveforms can be used to discriminate different arterial pulse transmission conditions between MetS and healthy subjects. Three-minute PPG signals were obtained in 65 subjects, who were assigned to 3 age-matched groups (MS, with no less than three MetS factors; pre-MS, with one or two MetS factors; Control: with no MetS factor). FDT (foot delay time) and amplitude proportions (Cn) and their standard deviations (SDn) and coefficients of variations (CVn) were calculated for harmonics 1 to 10 of the PPG waveform. FDT was smaller in MS than in Control. C1 and C2 values were significantly smaller, whereas C4–C9 values were significantly or appeared to be larger in MS than in pre-MS. Most of the SDn and CVn values were largest in MS. This study is the first to demonstrate that harmonic-analysis indexes of the beat-to-beat PPG waveform can provide information about MetS-induced changes in the arterial pulse transmission and cardiovascular regulatory activities. The present findings may therefore be useful in developing a noninvasive and easy-to-perform technique that could improve the early detection of cardiovascular diseases.

Uncovering heart failure with preserved ejection fraction in patients with type 2 diabetes in primary care: time for a change.

Undetected heart failure appears to be an important health problem in patients with type 2 diabetes and aged ≥ 60 years. The prevalence of previously unknown heart failure in these patients is high, steeply rises with age, and is overall higher in women than in men. The majority of the patients with newly detected heart failure have a preserved ejection fraction. A diagnostic algorithm to detect or exclude heart failure in these patients with variables from the medical files combined with items from history taking and physical examination provides a good to excellent accuracy. Annual screening appears to be cost-effective. Both unrecognised heart failure with reduced and with preserved ejection fraction were associated with a clinically relevant lower health status in patients with type 2 diabetes. Also the prognosis of these patients was worse than of those without heart failure. Existing disease-management programs for type 2 diabetes pay insufficient attention to early detection of cardiovascular diseases, including heart failure. We conclude that more attention is needed for detection of heart failure in older patients with type 2 diabetes.

Oxidative Stress: An Effective Prognostic Tool for an Early Detection of Cardiovascular Disease in Menopausal Women.

Background. Menopause, a form of reproductive aging, is marked by many hormonal variations which cause imbalance in the oxidative processes resulting in onset of endothelial dysfunction leading to cardiovascular disease (CVD). We aimed to analyze the effect of oxidative stress in an early detection of CVD in all menopausal women both normolipidemic and hyperlipidemic. Methods and Results. Study included 523 menopausal women (265 CVD and 258 non-CVD). They were screened for lipid profile, serum malondialdehyde (MDA), serum LDL carbonyl protein, and serum superoxide dismutase (SOD). Pearson's correlation was observed between MDA and atherogenic index of plasma (AIP) in both normolipidemic (r = 0.650; p < 0.001) and hyperlipidemic (r = 0.207; p < 0.01) CVD group as compared to non-CVD menopausal women. Significant correlation was also observed between LDL carbonyl content and AIP in normolipidemic (r = 0.650; p < 0.001) and hyperlipidemic (r = 0.248; p < 0.01) CVD menopausal women as compared to non-CVD ones. Conclusion. Strong correlation between atherogenic index of plasma and oxidative stress in CVD menopausal women reveals oxidative stress as an effective prognostic tool for an early detection of cardiovascular risk.

Technological Innovations in Magnetic Resonance for Early Detection of Cardiovascular Diseases.

Most recent technical innovations in cardiovascular MR imaging (CMRI) are presented in this review. They include hardware and software developments, and novelties in parametric mapping. All these recent improvements lead to high spatial and temporal resolution and quantitative information on the heart structure and function. They make it achievable ambitious goals in the field of magnetic resonance, such as the early detection of cardiovascular pathologies. In this review article, we present recent innovations in CMRI, emphasizing the progresses performed and the solutions proposed to some yet opened technical problems.

Cuffless and Continuous Blood Pressure Estimation from the Heart Sound Signals.

Cardiovascular disease, like hypertension, is one of the top killers of human life and early detection of cardiovascular disease is of great importance. However, traditional medical devices are often bulky and expensive, and unsuitable for home healthcare. In this paper, we proposed an easy and inexpensive technique to estimate continuous blood pressure from the heart sound signals acquired by the microphone of a smartphone. A cold-pressor experiment was performed in 32 healthy subjects, with a smartphone to acquire heart sound signals and with a commercial device to measure continuous blood pressure. The Fourier spectrum of the second heart sound and the blood pressure were regressed using a support vector machine, and the accuracy of the regression was evaluated using 10-fold cross-validation. Statistical analysis showed that the mean correlation coefficients between the predicted values from the regression model and the measured values from the commercial device were 0.707, 0.712, and 0.748 for systolic, diastolic, and mean blood pressure, respectively, and that the mean errors were less than 5 mmHg, with standard deviations less than 8 mmHg. These results suggest that this technique is of potential use for cuffless and continuous blood pressure monitoring and it has promising application in home healthcare services.

A Web Based Cardiovascular Disease Detection System

Cardiovascular Disease (CVD) is one of the most catastrophic and life threatening health issue nowadays. Early detection of CVD is an important solution to reduce its devastating effects on health. In this paper, an efficient CVD detection algorithm is identified. The algorithm uses patient demographic data as inputs, along with several ECG signal features extracted automatically through signal processing techniques. Cross-validation results show a 98.29 % accuracy for the decision tree classification algorithm. The algorithm has been integrated into a web based system that can be used at anytime by patients to check their heart health status. At one end of the system is the ECG sensor attached to the patient's body, while at the other end is the detection algorithm. Communication between the two ends is done through an Android application.