Diagnosis Of Coronary Disease Research Articles

SECT and DECT coronarography

Coronary artery disease is an atherosclerotic disease of the coronary arteries with consequent development of ischemic heart disease and is one of the leading causes of death in developed and developing countries. The “golden” standard in the diagnosis of coronary disease is invasive coronarography, but with the development of coronary CT angiography, a sub-millimetre precise assessment of the anatomy of coronary arteries and heart has been made possible. While in the earlier stages, SECT devices were used for the needs of coronary CT angiography with synchronization with the ECG, the development of DECT devices enabled a significant rise in the performance of coronary CT angiography in the form of a better assessment of anatomy and stenoses of the coronary arteries caused by plaque, the possibility of assessing heart perfusion, obtaining an image with a minimal amount of artifacts, a smaller amount of applied iodine contrast agent, better characterization of the atherosclerotic plaque and its components, and all of the above with a lower radiation dose for the patient. While most of the conducted research speaks in favour of DECT devices versus SECT devices, the issue of inadequate utilization of the numerous possibilities of DECT devices in everyday clinical practice remains. The DECT technique can be implemented in several ways, depending on the structure of the DECT device (on the number of radiation sources, the structure/arrangement of detectors, or the use of filters), but the question of which type of DECT technique/device to use depends on the disadvantages and advantages of individual devices as well as on the final goal of diagnostic procedures.

Valuable Predictors for Non-measurability of Fractional Flow Reserve Derived From Coronary Computed Tomography Angiography.

Background The fractional flow reserve (FFR) derived from coronary computed tomography (CT) angiography (FFRCT) is a variable tool for coronary disease diagnosis that non-invasively provides the value of FFR. It can add physiological information tocoronary CT angiography (CCTA) and reduce unnecessary invasive coronary angiography (CAG). However, it cannot be analyzed in some cases, which is also called "non-measurability." While FFRCT has become globally widespread, the current data on non-measurability are lacking. This study aimed to determine the rate of non-measurability and identify predictors thereof in routine clinical settings to explore potential approaches to reduce the non-measurability rate. Methods and results This retrospective observational single-center studyincluded consecutive patients who underwent FFRCTanalysis in Japan. The mean age of the overall population was 71.3 ± 10.6, and an FFRCTof ≤0.8 was seen in 47.6% of patients with a measurable FFRCT. Of the 307 enrolled patients, FFRCT analysis was not feasible in 21 cases (6.8%). Heart rate (HR) at a CT scan and coronary calcium scores (CCS) were significantly higher in patients with non-measurability than those in patients whose FFRCT was appropriately analyzed (HR: 69.6±8.9 bpm vs. 61.0±11.1 bpm; p < 0.01; CCS; 931.2 (290.8, 1451.3) vs. 322.9 (100.7, 850.0); p < 0.01). Multiplelogisticregression showed that HR was an independent predictor for non-measurability (odds ratio: 1.05; 95% confidential interval: 1.02, 1.09; p < 0.01)). Based on the receiver operating characteristic curve analysis, the optimal cut-off value of HR and CCS was 63 bpm (specificity: 67.1%; sensitivity: 76.2%) and 729.2 (specificity: 71.3%; sensitivity: 66.7%). In addition, the combination of two features (HR > 63 bpm and CCS > 729.2) showed a high negative predictive value (99.3%) for FFRCT non-measurability. Conclusions In this study, the rate of FFRCTnon-measurability was 6.8%. Higher HR at a CT scan and CCS were significantly associated with non-measurability, and in cases with both HR and CCS below a specified threshold, the likelihood of ruling out non-measurability could be significantly high. Our findings suggest that reducing the HR to ideally under 63 bpm at the time of the CT scan significantly ensures feasibility. Further study on large-scale cohorts is warranted.

Scale Mutualized Perception for Vessel Border Detection in Intravascular Ultrasound Images.

Vessel border detection in IVUS images is essential for coronary disease diagnosis. It helps to obtain the clinical indices on the inner vessel morphology to indicate the stenosis. However, the existing methods suffer the challenge of scale-dependent interference. Early methods usually rely on the hand-crafted features, thus not robust to this interference. The existing deep learning methods are also ineffective to solve this challenge, because these methods aggregate multi-scale features in the top-down way. This aggregation may bring in interference from the non-adjacent scale. Besides, they only combine the features in all scales, and thus may weaken their complementary information. We propose the scale mutualized perception to solve this challenge by considering the adjacent scales mutually to preserve their complementary information. First, the adjacent small scales contain certain semantics to locate different vessel tissues. Then, they can also perceive the global context to assist the representation of the local context in the adjacent large scale, and vice versa. It helps to distinguish the objects with similar local features. Second, the adjacent large scales provide detailed information to refine the vessel boundaries. The experiments show the effectiveness of our method in 153 IVUS sequences, and its superiority to ten state-of-the-art methods.

A two-step log-linear procedure for graphical representation and inference of associations in cross-classified data for disease diagnosis.

Biometrical sciences and disease diagnosis in particular, are often concerned with the analysis of associations for cross-classified data, for which distance association models give us a graphical interpretation for non-sparse matrices with a low number of categories. In this framework, usually binary exploratory and response variables are present, with analysis based on individual profiles being of great interest. For saturated models, we show the usual linear relationship for log-linear models is preserved in full dimension for the distance association parameterization. This enables a two-step procedure to facilitate the analysis and the interpretation of associations in terms of unfolding after the overall and main effects are removed. The proposed procedure can deal with cross-classified data for profiles by binary variables, and it is easy to implement using traditional statistical software. For disease diagnosis, the problems of a degenerate solution in the unfolding representation, and that of determining significant differences between the profile locations are addressed. A hypothesis test of independence based on odds ratio is considered. Furthermore, a procedure is proposed to determine the causes of the significance of the test, avoiding the problem of error propagation. The equivalence between a test for equality of odds ratio pairs and the test for equality of location for two profiles in the unfolding representation in the disease diagnosis is shown. The results have been applied to a real example on the diagnosis of coronary disease, relating the odds ratios with performance parameters of the diagnostic test.

IFCnCov: An IoT‐based smart diagnostic architecture for COVID‐19

AbstractPerforming a coronary disease diagnosis remotely is challenging now‐a‐days. COVID‐19 is a worldwide pandemic, and methods for detecting COVID‐19 are hampered by insufficient data and a lack of validation testing. Internet of Things (IoT) applications that rely on cloud computing (CC) are being studied in an effort to improve e‐Healthcare systems, even though CC presents substantial latency, bandwidth, energy consumption, security and privacy issues and so forth. The extension to CC, fog computing (FC), can overcome these said limitations. This study aims to diagnose COVID‐19 patients to fight the outbreak remotely. This study proposes IFCnCov, which enables remote users to diagnose COVID‐19 disease in real‐time using integrated IoT, FC, and CC principles, as well as ensemble learning (EL) and deep learning (DL). The proposed system is a two‐layered architecture, trained with DL approaches to two different datasets: a symptom‐based dataset and a chest x‐rays imaging dataset obtained from the Kaggle repository employing several evaluative measures. From various experiments, this proposed IFCnCov achieves comparatively enhanced accuracies of 97.71% and 98.64%, precision of 97.38% and 98.52%, sensitivity of 98.19% and 98.92%, specificity of 97.21% and 98.34%, and F1‐scores of 97.79% and 98.72% in the first and second stages respectively, which also outperforms some other considered state‐of‐the‐art works. Additionally, this work is validated in terms of several network parameters, including scalability, energy consumption, network utilization, jitter, processing time, throughput, and arbitration time.

Treat-to-Target or High-Intensity Statin in Patients With Coronary Artery Disease

In patients with coronary artery disease, some guidelines recommend initial statin treatment with high-intensity statins to achieve at least a 50% reduction in low-density lipoprotein cholesterol (LDL-C). An alternative approach is to begin with moderate-intensity statins and titrate to a specific LDL-C goal. These alternatives have not been compared head-to-head in a clinical trial involving patients with known coronary artery disease. To assess whether a treat-to-target strategy is noninferior to a strategy of high-intensity statins for long-term clinical outcomes in patients with coronary artery disease. A randomized, multicenter, noninferiority trial in patients with a coronary disease diagnosis treated at 12 centers in South Korea (enrollment: September 9, 2016, through November 27, 2019; final follow-up: October 26, 2022). Patients were randomly assigned to receive either the LDL-C target strategy, with an LDL-C level between 50 and 70 mg/dL as the target, or high-intensity statin treatment, which consisted of rosuvastatin, 20 mg, or atorvastatin, 40 mg. Primary end point was a 3-year composite of death, myocardial infarction, stroke, or coronary revascularization with a noninferiority margin of 3.0 percentage points. Among 4400 patients, 4341 patients (98.7%) completed the trial (mean [SD] age, 65.1 [9.9] years; 1228 females [27.9%]). In the treat-to-target group (n = 2200), which had 6449 person-years of follow-up, moderate-intensity and high-intensity dosing were used in 43% and 54%, respectively. The mean (SD) LDL-C level for 3 years was 69.1 (17.8) mg/dL in the treat-to-target group and 68.4 (20.1) mg/dL in the high-intensity statin group (n = 2200) (P = .21, compared with the treat-to-target group). The primary end point occurred in 177 patients (8.1%) in the treat-to-target group and 190 patients (8.7%) in the high-intensity statin group (absolute difference, -0.6 percentage points [upper boundary of the 1-sided 97.5% CI, 1.1 percentage points]; P < .001 for noninferiority). Among patients with coronary artery disease, a treat-to-target LDL-C strategy of 50 to 70 mg/dL as the goal was noninferior to a high-intensity statin therapy for the 3-year composite of death, myocardial infarction, stroke, or coronary revascularization. These findings provide additional evidence supporting the suitability of a treat-to-target strategy that may allow a tailored approach with consideration for individual variability in drug response to statin therapy. ClinicalTrials.gov Identifier: NCT02579499.

An optimized segmentation of main vessel in coronary angiography images via removing the overlapping pacemaker

Coronary angiography (CAG) as a typical imaging modality for the diagnosis of coronary diseases hasbeen widely employed in clinical practices. For CAG-based computer-aided diagnosis systems, accurate vessel segmentation plays a fundamental role. However, patients with bradycardia usually have a pacemaker which frequently interferes the vessel segmentation. In this case, the segmentation of vessels will be hard. To mitigate interferences of pacemakers and then extract main vessels more effectively in CAG images, we propose an approach. At first, a pseudo CAG (pCAG) image is generated through a part of a CAG sequence, in which the pacemaker exists. Then, a local feature descriptor is employed to register the relative location of pacemaker between the pCAG image and the target CAG image. Finally, combining the registration result and segmentation results of main vessels and pacemaker, interferences of pacemaker are removed and the segmentation of main vessels is improved. The proposed method is evaluated based on 11 CAG images with pacemakers acquired in clinical practices. An optimization ratio of the Dice coefficient is 12.04%, which demonstrates that our method can remove overlapping pacemakers and achieve the improvement of main vessel segmentation in CAG images.Our method can further become a helpful component in a CAG-based computer-aided diagnosis system, improving its diagnosis accuracy and efficiency.

Implantación de un protocolo de angio-TC coronaria basado en el índice de masa corporal: reducción de dosis, calidad de imagen y rendimiento diagnóstico

ObjectivesTo evaluate the relation between the coronary calcium score and the posterior choice of kilovoltage according to radiologists’ criteria in a standard coronary CT angiography protocol to rule out coronary disease.To quantify the reduction in ionizing radiation after linking kilovoltage to patients’ body mass index in a low-dose protocol with iterative model reconstruction.To evaluate the image quality and diagnostic performance of the low-dose protocol. Material and methodsWe compared anthropometric characteristics, calcium score, kilovoltage levels, size-specific dose estimates (SSDE), and the dose-length product (DLP) between a group of 50 patients who were prospectively recruited to undergo coronary CT angiography with a low-dose protocol and a historical group of 50 patients who underwent coronary CT angiography with the standard protocol. We correlated these parameters, the number of coronary segments that could not be evaluated with and without temporal padding, the attenuation, and the signal-to-noise ratio in the ascending aorta in the low-dose protocol with excellent imaging quality according to a semiquantitative scale. To calculate the diagnostic performance per patient, we used 24-month clinical follow-up including all tests as the gold standard. ResultsIn the standard protocol, the presence of coronary calcium correlated with the selection of high kilovoltage (P=0.02); this correlation was not found in the low-dose protocol (P=0.47). Median values of SSDE and DLP were significantly (P<0.001) lower and less dispersed in the low-dose protocol [9.22 mGy (IQR 7.84-12.1 mGy) vs. 26.5 mGy (IQR 21.3-36.3 mGy) in the standard protocol] and [97mGy*cm (IQR 78-134mGy*cm) vs. 253mGy*cm (IQR 216-404mGy*cm) in the standard protocol], respectively.The overall quality of the images obtained with the low-dose protocol was considered good or excellent in 96% of the studies. The parameters associated with image quality in a multivariable model (C statistic=0.792) were heart rate (estimated coefficient, -0,12 [95% confidence interval: -0.2, -0.04]; P<0.01) and the SSDE (estimated coefficient, -0,26 [95% confidence interval: -0.51, -0.01]; P<0.05).The CAD-RADS modifier for a not fully evaluable or diagnostic study was used on two occasions (4%); the final measures for the diagnosis of coronary disease were sensitivity 100%, specificity 94%, and efficacy 94%. ConclusionsIn the standard protocol, the radiologist selects higher kilovoltage for CT angiography studies for patients whose previous calcium score indicates the presence of coronary calcium. In the low-dose protocol, linking kilovoltage with body mass index enables the dose of radiation to be reduced by 65% while obtaining excellent or good image quality in 96% of studies and excellent diagnostic performance.

Impact of micro- and macrovascular complications of type 2 diabetes on quality of life: Insights from the DISCOVER prospective cohort study.

BackgroundThe key goals of management in patients with type 2 diabetes (T2D) are to prolong life and improve quality of life. Micro‐ and macrovascular complications of T2D not only increase the risk of morbidity and mortality, but cross‐sectional studies indicate they may also worsen quality of life. We prospectively examined the association of complications that developed during the follow‐up with concurrent changes in quality of life.Materials and methodsDISCOVER is a multinational, prospective, observational cohort study of T2D patients enrolled at initiation of second‐line glucose‐lowering therapy. Quality of life was assessed with the SF‐36 Physical (PCS) and Mental Components Summary (MCS) scores at baseline, 6 months, and 1, 2 and 3 years. Hierarchical repeated measures regression models for PCS and MCS were constructed with complications included as time‐dependent covariates; first each complication was modelled alone and then second including all interval complications (to account for different complications occurring in the same patient).ResultsAmong 7830 patients with T2D from 30 countries (mean age 56.6 years, 47.6% women, mean duration of T2D 5.6 years), baseline mean SF‐36 PCS was 48.0 ± 7.8 and SF‐36 MCS was 45.5 ± 10.4. At baseline, 1422 (18.2%) patients had a known microvascular complication, and 966 (12.3%) had a macrovascular complication. Over the 3 years of the study, 641 (12.0%) developed a new microvascular complication (most commonly neuropathy) and 372 (5.8%) developed a new macrovascular complication (most commonly coronary disease). New diagnoses of coronary disease, peripheral artery disease, heart failure and neuropathy were each associated with subsequent moderate reductions in SF‐36 PCS (range 0.7 to 1.6 points) and new cerebrovascular disease was associated with a reduction in SF‐36 MCS (2.6 points). Results were consistent when all interval complications were considered in the same model.ConclusionIn a prospective, multinational study of patients with T2D, the development of macrovascular complications and neuropathy was associated with decreases in both physical and mental quality of life. Our results provide additional support for clinicians to focus on the prevention, detection and management of the complications of T2D.

Diagnostic value of 256 MDCT in diagnosis of coronary disease in atrial fibrillation patients

Objectives: To determine the diagnostic value of 256 MDCT in the diagnosis of coronary artery disease in patients with atrial fibrillation.Materials and methods: We prospectively enrolled 48 patients with atrial fibrillation who underwent 256 MDCT coronary CT angiography scan at Huu Nghi Hospital from 07/2020 to 07/2021 and evaluated diagnosis value of this technique using invasive coronary angiography as golden standard.Results: At patient-based analysis, sensitivity, specificity, positive predictive value and accuracy are 100%, 83.3% and 83.3%, respectively. At vessel-based analysis, sensitivity, specificity, positive predictive value, negative predictive value and accuracy are 98.4%, 81.7%, 80.3%, 98.5% and 88.9%, respectively. At segment-based analysis sensitivity, specificity, positive predictive value, negative predictive value and accuracy are 96.7%, 93.8%, 78.4%, 99.2 % and 94.4%, respectively. "Conclusion: 256 MDCT coronary angiography scan is a diagnostic method with high accuracy in diagnosing coronary artery disease in patients with atrial fibrillation.

Global Hypothesis Test to Compare the Predictive Values of Diagnostic Tests Subject to a Case-Control Design

Use of a case-control design to compare the accuracy of two binary diagnostic tests is frequent in clinical practice. This design consists of applying the two diagnostic tests to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. This manuscript studies the comparison of the predictive values of two diagnostic tests subject to a case-control design. A global hypothesis test, based on the chi-square distribution, is proposed to compare the predictive values simultaneously, as well as other alternative methods. The hypothesis tests studied require knowing the prevalence of the disease. Simulation experiments were carried out to study the type I errors and the powers of the hypothesis tests proposed, as well as to study the effect of a misspecification of the prevalence on the asymptotic behavior of the hypothesis tests and on the estimators of the predictive values. The proposed global hypothesis test was extended to the situation in which there are more than two diagnostic tests. The results have been applied to the diagnosis of coronary disease.

Privileged Modality Distillation for Vessel Border Detection in Intracoronary Imaging.

Intracoronary imaging is a crucial imaging technology in coronary disease diagnosis as it visualizes the internal tissue morphologies of coronary arteries. Vessel border detection in intracoronary images (VBDI) is desired because it can help the succeeding procedures of computer-aided disease diagnosis. However, existing VDBI methods suffer from the challenge of vessel-environment variability (i.e. high intra- and inter-subject diversity of vessels and their surrounding tissues appeared in images). This challenge leads to the ineffectiveness in the vessel region representation for hand-crafted features, in the receptive field extraction for deeply-represented features, as well as performance suppression derived from clinical data limitation. To solve this challenge, we propose a novel privileged modality distillation (PMD) framework for VBDI. PMD transforms the single-input-single-task (SIST) learning problem in the single-mode VBDI to a multiple-input-multiple-task (MIMT) problem by using the privileged image modality to help the learning model in the target modality. This learns the enriched high-level knowledge with similar semantics and generalizes PMD on diversity-increased low-level image features for improving the model adaptation to diverse vessel environments. Moreover, PMD refines MIMT to SIST by distilling the learned knowledge from multiple to one modality. This eliminates the reliance on privileged modality in the test phase, and thus enables the applicability to each of different intracoronary modalities. A structure-deformable neural network is proposed as an elaborately-designed implementation of PMD. It expands a conventional SIST network structure to the MIMT structure, and then recovers it to the final SIST structure. The PMD is validated on intravascular ultrasound imaging and optical coherence tomography imaging. One modality is the target, and the other one can be considered as the privileged modality owing to their semantic relatedness. The experiments show that our PMD is effective in VBDI (e.g. the Dice index is larger than 0.95), as well as superior to six state-of-the-art VBDI methods.

TESTE CARDIOPULMONAR NO DIAGNÓSTICO DE DOENÇA CORONARIANA: ACURÁCIA DA CURVA DO PULSO DE OXIGÊNIO

Exercise induced myocardial ischemia may interfere in the increase of systolic volume and cause deflection in oxygen PuO2 curve. It could assess a reduced systolic volume. In systematic literature review, we founded a few manuscripts dealing with that matter: nine publications during 22 years, including 339 patients. The sensitivity and the specificity of PuO2 deflection were, respectively, 51% e 60%, reaching 87% and 74% when associated to VO2/ work rate slope. In sub group with extensive ischemia, peak PuO2 was reduced (12.8±3.8 vs. 16.4±4.6 ml/bpm - p < 0.05), showing the flattening of the curve during severe ischemia. After myocardial revascularization, it was related an increase in PuO2 (from 11.76 to 13.27 ml/bpm). There are indications that the use of cardiopulmonary testing may be useful in the diagnosis of coronary disease, detecting cases with the severe disease.

Recommended methods to compare the accuracy of two binary diagnostic tests subject to a paired design

ABSTRACTThis manuscript assesses different methods to compare the sensitivities and the specificities of two diagnostic tests. It studies the comparison conditioning on the disease status and testing each hypothesis test individually to an error , a global hypothesis test to simultaneously compare the parameters, and the individual comparison of the parameters along with the multiple comparison methods of Bonferroni and Holm. Simulation experiments were carried out to study the global type I errors and the global powers of the different methods, providing some general rules of application. When the prevalence is small and the sample size is small or moderate, it is recommended to compare the parameters individually along with the method of Bonferroni or Holm; in any other situation, it is recommended to compare the parameters simultaneously through a global test. The results were applied to an example of the diagnosis of coronary disease.

Association between anthropometric parameters and coronary calcification

Several studies have reported an association between obesity and the presence of coronary artery calcification (CAC), but it is still unclear which parameter would be most useful in screening for coronary calcification. This study aimed to evaluate the association between anthropometric parameters and coronary calcification. A cross-sectional study was developed involving patients attended by outpatient care, without previous diagnosis of coronary disease. The CAC was evaluated by computerized tomography, considering the coronary calcium score (CCS)> 0 as the presence of calcification and 0 as absence. The anthropometric variables studied were: body mass index, waist circumference (WC), waist-hip ratio (WHR), waist-to-height ratio (Et al), conicity index (CI), neck circumference, neck-thigh ratio, waist-thigh ratio (WThR) and body adiposity index. A total of 129 patients were evaluated, with a mean age of 55.6±11.7 years. CAC was observed in 41.9% of patients. In the male sex, the CCS had a higher correlation with the WHR (r=0.416, p=0.016) and in females, the CI and WThR (r=0.305, p=0.003 and r=0.328, p=0.001, respectively). In the logistic regression model, the only anthropometric parameter that remained associated to CAC was WC (OR=3.9). In conclusion, it was observed that several anthropometric parameters were associated with CAC, and WC was the only anthropometric parameter that remained associated to CAC in the adjusted analysis.

A12004 Diagnostic Accuracy and Influencing Factors of High-pitch Spiral with Low Tube Voltage and Low Concentration of Contrast Agent in Coronary CT Angiography

Objectives: To investigate the diagnostic accuracy of high-pitch spiral using low-tube-voltage and low concentration iodinated media in third-generation. Methods: 93 patients were randomized two groups (group A,n = 43 and group B,n = 50). 43 in group A were divided in two groups, 27 bmp < 70 in group A1 and 16 bmp ≥ 70 in group A2. The contrast-medium of group A group B was 30–35 ml 70–75 ml respectively. Utilising the high-pitch spiral for CCTA inspection. Comparing diagnostic accuracy among these three groups with using of catheterization coronary angiography as the standard of reference. Results: (1)The diagnostic accuracy of mild, moderate and severe coronary stenosis in group A1, A2 and B was 95.9%,93.2%,93.2%; 93.2%,90.9%,95.5%; 96.6%,96.6%, 97.9%respectively. (2) The sensitivity, specificity, positive predictive value and negative predictive value of these groups for the diagnosis of coronary disease were 94.7%, 94.3%, 94.7%, 94.3%; 88.9%, 88.2%, 92.3%, 83.3%;96.4%,96.8%,97.6%,95.2% respectively. (3) The diagnostic accuracy of coronary disease was 94.5%,88.6% and 96.6% respectively. (4) Diagnostic Kappa values of these groups were 0.890, 0.763,0.930 respectively. Conclusion: High-pitch spiral with low tube voltage and low concentration results in a high diagnostic accuracy for stenosis detection in patients with low heart rate with very low radiation dose.

Protective effect of yerba mate intake on the cardiovascular system: a post hoc analysis study in postmenopausal women.

The prevalence of cardiovascular and metabolic diseases is increased in postmenopausal women, which contributes to the burden of illnesses in this period of life. Yerba mate (Ilex paraguariensis) is a native bush from Southern South America. Its leaves are rich in phenolic components, which may have antioxidant, vasodilating, hypocholesterolemic, and hypoglycemic proprieties. This post hoc analysis of the case-control study nested in the Obesity and Bone Fracture Cohort evaluated the consumption of yerba mate and the prevalence of hypertension, dyslipidemia, and coronary diseases in postmenopausal women. Ninety-five postmenopausal women were included in this analysis. A questionnaire was applied to evaluate the risk factors and diagnosis of cardiovascular diseases and consumption of yerba mate infusion. Student's t-test and chi-square test were used to assess significant differences between groups. The group that consumed more than 1 L/day of mate infusion had significantly fewer diagnoses of coronary disease, dyslipidemia, and hypertension (P<0.049, P<0.048, and P<0.016, respectively). Furthermore, the serum levels of glucose were lower in the group with a higher consumption of yerba mate infusion (P<0.013). The serum levels of total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides were similar between the groups. This pragmatic study points out the benefits of yerba mate consumption for the cardiovascular and metabolic systems. The ingestion of more than 1 L/day of mate infusion was associated with fewer self-reported cardiovascular diseases and lower serum levels of glucose. Longitudinal studies are needed to evaluate the association between yerba mate infusion and reduction of cardiovascular diseases in postmenopausal women.

Ethnicity and the first diagnosis of a wide range of cardiovascular diseases: Associations in a linked electronic health record cohort of 1 million patients.

BackgroundWhile the association of ethnic group with individual cardiovascular diseases has been studied, little is known about ethnic differences in the initial lifetime presentation of clinical cardiovascular disease in contemporary populations.Methods and resultsWe studied 1,068,318 people, aged ≥30 years and free from diagnosed CVD at baseline (90.9% White, 3.6% South Asian and 2.9% Black), using English linked electronic health records covering primary care, hospital admissions, acute coronary syndrome registry and mortality registry (CALIBER platform). During 5.7 years median follow-up between 1997–2010, 95,224 people experienced an incident cardiovascular diagnosis. 69.9% (67.2%-72.4%) of initial presentation in South Asian <60 yrs were coronary heart disease presentations compared to 47.8% (47.3%-48.3%) in White and 40.1% (36.3%-43.9%) in Black patients. Compared to White patients, Black patients had significantly lower age-sex adjusted hazard ratios (HRs) for initial lifetime presentation of all the coronary disease diagnoses (stable angina HR 0.80 (95% CI 0.68–0.93); unstable angina– 0.75 (0.59–0.97); myocardial infarction 0.49 (0.40–0.62)) while South Asian patients had significantly higher HRs (stable angina– 1.67 (1.52–1.84); unstable angina 1.82 (1.56–2.13); myocardial infarction– 1.67 (1.49–1.87). We found no ethnic differences in initial presentation with heart failure (Black 0.97 (0.79–1.20); S Asian 1.04(0.87–1.26)). Compared to White patients, Black patients were more likely to present with ischaemic stroke (1.24 (0.97–1.58)) and intracerebral haemorrhage (1.44 (0.97–2.12)). Presentation with peripheral arterial disease was less likely for Black (0.63 (0.50–0.80)) and South Asian patients (0.70 (0.57–0.86)) compared with White patients.DiscussionWhile we found the anticipated substantial predominance of coronary heart disease presentations in South Asian and predominance of stroke presentations in Black patients, we found no ethnic differences in presentation with heart failure. We consider the public health and research implications of our findings.Trial RegistrationNCT02176174, www.clinicaltrials.gov

Paediatric-onset coronary artery anomalies in pregnancy: a single-centre experience and systematic literature review

Individuals with childhood-onset coronary artery anomalies are at increased risk of lifelong complications. Although pregnancy is thought to confer additional risk, a few data are available regarding outcomes in this group of women. We sought to define outcomes of pregnancy in this unique population. We performed a retrospective survey of women with paediatric-onset coronary anomalies and pregnancy in our institution, combined with a systematic review of published cases. We defined paediatric-onset coronary artery anomalies as congenital coronary anomalies and inflammatory arteriopathies of childhood that cause coronary aneurysms. Major cardiovascular events were defined as pulmonary oedema, sustained arrhythmia requiring treatment, stroke, myocardial infarction, cardiac arrest, or death. A total of 25 surveys were mailed, and 20 were returned (80% response rate). We included 46 articles from the literature, which described cardiovascular outcomes in 82 women (138 pregnancies). These data were amalgamated for a total of 102 women and 194 pregnancies; 59% of women were known to have paediatric-onset coronary artery anomalies before pregnancy. In 23%, the anomaly was unmasked during or shortly after pregnancy. The remainder, 18%, was diagnosed later in life. Major cardiovascular events occurred in 14 women (14%) and included heart failure (n=5, 5%), myocardial infarction (n=7, 7%), maternal death (n=2, 2%), cardiac arrest secondary to ventricular fibrillation (n=1, 1%), and stroke (n=1, 1%). The majority of maternal events (13/14, 93%) occurred in women with no previous diagnosis of coronary disease. Women with paediatric-onset coronary artery anomalies have a 14% risk of adverse cardiovascular events in pregnancy, indicating the need for careful assessment and close follow-up. Prospective, multicentre studies are required to better define risk and predictors of complications during pregnancy.

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography.

The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers. For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist's top 2 ranked segments in 78.3% of the 254 groups (Cohen's kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers' top 2 rankings, and 96.5% agreed with at least one observer's top 2 rankings. In comparison, agreement between the four observers' top ranked segment and the radiologist's top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68. The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.