Left atrial stiffness index - an early marker of left ventricular diastolic dysfunction in patients with coronary heart disease.

AIMS: To evaluate the correlation between left atrial stiffness index (LASI) and left ventricular diastolic function in patients with coronary heart disease (CHD) by Autostrain LA technique. METHODS: This was a retrospective analysis that included a total of 82 CHD patients who had suitable image quality for left atrial strain measurement. According to the 2016 ASE/EACVI guidelines for the echocardiographic assessment of diastolic dysfunction, the patients were divided into three groups: normal left ventricular diastolic function group (n = 26), indeterminate left ventricular diastolic function (n = 36), and left ventricular diastolic dysfunction (LVDD) (n = 20). The left atrial conduit strain (LAScd), Left atrial contractile strain (LASct), left atrial reservoir strain (LASr) and its derived parameters, including LASI and left atrial filling index (LAFI), were compared among the three groups. Furthermore, we conduct a correlation analysis between LASI and left ventricular diastolic function in patients with CHD. RESULTS: LASr and LAScd in normal group were higher than those in indeterminate group, LASr and LAScd in indeterminate group were higher than those in LVDD group, LASI in normal group was lower than that in indeterminate group, and LASI in indeterminate group was lower than that in LVDD group (P < 0.001). LASct in both normal and indeterminate groups was higher than that in LVDD group (P < 0.05). The LAFI of normal group was lower than that of indeterminate group and LVDD group (P < 0.001). LASI was positively correlated with E/e'(r = 0.822) (P < 0.001). LASr and E/e' were negatively correlated (r = -0.637) (P < 0.001). CONCLUSION: LASI is closely related to the changes of left ventricular diastolic function in CHD patients.

Diagnostic value of multimodal cardiovascular imaging technology coupled with biomarker detection in elderly patients with coronary heart disease.

Aims/Background Coronary heart disease is a common disease in the elderly and has a complex pathogenesis, which complicates the clinical diagnostic process. Thus, enhancing the diagnostic efficiency for coronary heart disease is imperative to improve the life expectancy of the elderly. This study aimed to explore the diagnostic value of multimodal cardiovascular imaging technology coupled with biomarker detection in elderly patients with coronary heart disease. Methods The medical records of 421 patients with suspected coronary heart disease obtained from the geriatric department of the First Affiliated Hospital of Hebei North University from February 2020 to February 2023 were retrospectively analysed. After excluding 10 patients who did not meet the inclusion criteria, the remaining 411 patients were included in this study. The included subjects had undergone coronary computed tomography angiography and were divided into coronary heart disease group (n=208) and non-coronary heart disease group (n=203) according to the diagnostic results. Multimodal cardiovascular imaging (coronary computed tomography angiography and echocardiography) and detection of serum biomarkers such as small dense low-density lipoprotein, lipoprotein a, and gamma-glutamyl transferase were performed in both groups. The clinical indicators of the two groups were compared, and the combined diagnostic efficacy of multimodal cardiovascular imaging and biomarker detection was evaluated. Results Compared to the non-coronary heart disease group, the coronary heart disease group had significantly higher levels of maximum area stenosis, total plaque volume, total plaque burden and fibrotic plaque volume (p < ..001), and lower left ventricular ejection fraction level (p < ..001). Additionally, the coronary heart disease group exhibited higher levels of left ventricular end-diastolic volume, left ventricular end-systolic volume and stroke volume than the non-coronary heart disease group (p < ..001), and had higher levels of small dense low-density lipoprotein, lipoprotein a and gamma-glutamyl transferase (p < ..001). Our results demonstrated that combined diagnosis had better diagnostic efficacy than individual approaches, marked by higher area under the curve and sensitivity of the former (p < ..001). Conclusion Multimodal cardiovascular imaging technology combined with biomarker detection can distinctly improve the accuracy of coronary heart disease diagnosis in elderly patients.

Plasma proteome association with coronary heart disease and carotid intima media thickness: results from the KORA F4 study.

BACKGROUND AND AIMS: Atherosclerosis is the main cause of stroke and coronary heart disease (CHD), both leading mortality causes worldwide. Proteomics, as a high-throughput method, could provide helpful insights into the pathological mechanisms underlying atherosclerosis. In this study, we characterized the associations of plasma protein levels with CHD and with carotid intima-media thickness (CIMT), as a surrogate measure of atherosclerosis. METHODS: The discovery phase included 1000 participants from the KORA F4 study, whose plasma protein levels were quantified using the aptamer-based SOMAscan proteomics platform. We evaluated the associations of plasma protein levels with CHD using logistic regression, and with CIMT using linear regression. For both outcomes we applied two models: an age-sex adjusted model, and a model additionally adjusted for body mass index, smoking status, physical activity, diabetes status, hypertension status, low density lipoprotein, high density lipoprotein, and triglyceride levels (fully-adjusted model). The replication phase included a matched case-control sample from the independent KORA F3 study, using ELISA-based measurements of galectin-4. Pathway analysis was performed with nominally associated proteins (p-value < 0.05) from the fully-adjusted model. RESULTS: In the KORA F4 sample, after Bonferroni correction, we found CHD to be associated with five proteins using the age-sex adjusted model: galectin-4 (LGALS4), renin (REN), cathepsin H (CTSH), and coagulation factors X and Xa (F10). The fully-adjusted model yielded only the positive association of galectin-4 (OR = 1.58, 95% CI = 1.30-1.93), which was successfully replicated in the KORA F3 sample (OR = 1.40, 95% CI = 1.09-1.88). For CIMT, we found four proteins to be associated using the age-sex adjusted model namely: cytoplasmic protein NCK1 (NCK1), insulin-like growth factor-binding protein 2 (IGFBP2), growth hormone receptor (GHR), and GDNF family receptor alpha-1 (GFRA1). After assessing the fully-adjusted model, only NCK1 remained significant (ß = 0.017, p-value = 1.39e-06). Upstream regulators of galectin-4 and NCK1 identified from pathway analysis were predicted to be involved in inflammation pathways. CONCLUSIONS: Our proteome-wide association study identified galectin-4 to be associated with CHD and NCK1 to be associated with CIMT. Inflammatory pathways underlying the identified associations highlight the importance of inflammation in the development and progression of CHD.

Image testing based on biomedical drug loading in cardiovascular drug care simulation for coronary heart disease.

Coronary heart disease is a common cardiovascular disease, and its therapeutic effect is affected by the distribution and absorption of drugs in the body. Biomedical drug-carrying image testing technology can provide a quantitative assessment of drug distribution and absorption in the body. This study aims to explore the application of biomedical drug-carrying image testing technology in the simulation of cardiovascular drug care in coronary heart disease, so as to provide reference for the optimization of drug treatment plan and individualized treatment. The study collected clinical data and medication regiments of patients with coronary heart disease. Then, the imaging examination of patients was carried out by selecting appropriate drug loading markers using the biomedical drug loading image examination technology. Then quantitative analysis was used to process the image data to quantitatively evaluate the distribution and absorption of drugs in the cardiovascular system. The quantitative data of drug distribution and absorption in patients with coronary heart disease have been obtained successfully by means of biomedical imaging. These data reveal the dynamic changes of drugs in the cardiovascular system, and help doctors optimize drug therapy, improve treatment effectiveness, and achieve personalized treatment.

Development and implementation of a treatment pathway to reduce coronary angiograms - lessons from a failure.

BACKGROUND: The rates of coronary angiograms (CA) and related procedures (percutaneous intervention [PCI]) are significantly higher in Germany than in other Organisation for Economic Co-ordination and Development (OECD) countries. The current guidelines recommend non-invasive diagnosis of coronary heart disease (CHD); CA should only have a limited role in choosing the appropriate revascularisation procedure. The aim of the present study was to explore whether improvements in guideline adherence can be achieved through the implementation of regional treatment pathways. We chose four regions of Germany with high utilisation of CAs for the study. Here we report the results of the concomitant qualitative study. METHODS: General practitioners and specialist physicians (cardiologists, hospital-based cardiologists, emergency physicians, radiologists and nuclear medicine specialists) caring for patients with suspected CHD were invited to develop regional treatment pathways. Four academic departments provided support for moderation, provision of materials, etc. The study team observed session discussions and took notes. After the development of the treatment pathways, 45 semi-structured interviews were conducted with the participating physicians. Interviews and field notes were transcribed verbatim and underwent qualitative content analysis. RESULTS: Pathway development received little support among the participants. Although consensus documents were produced, the results were unlikely to improve practice. The participants expressed very little commitment to change. Although this attempt clearly failed in all study regions, our experience provides relevant insights into the process of evidence appraisal and implementation. A lack of organisational skills, ignorance of current evidence and guidelines, and a lack of feedback regarding one's own clinical behaviour proved to be insurmountable. CA was still seen as the diagnostic gold standard by most interviewees. CONCLUSIONS: Oversupply and overutilisation can be assumed to be present in study regions but are not immediately perceived by clinicians. The problem is unlikely to be solved by regional collaborative initiatives; optimised resource planning within the health care system combined with appropriate economic incentives might best address these issues.

Diagnostic accuracy of artificial intelligence-enabled vectorcardiography versus myocardial perfusion SPECT in patients with suspected or known coronary heart disease.

AIM: The present study evaluated with myocardial perfusion SPECT (MPS) the diagnostic accuracy of an artificial intelligence-enabled vectorcardiography system (Cardisiography, CSG) for detection of perfusion abnormalities. METHODS: We studied 241 patients, 155 with suspected CAD and 86 with known CAD who were referred for MPS. The CSG was performed after the MPS acquisition. The CSG results (1) p-factor (perfusion, 0: normal, 1: mildly, 2: moderately, 3: highly abnormal) and (2) s-factor (structure, categories as p-factor) were compared with the MPS scores. The CSG system was not trained during the study. RESULTS: Considering the p-factor alone, a specificity of >78% and a negative predictive value of mostly >90% for all MPS variables were found. The sensitivities ranged from 17 to 56%, the positive predictive values from 4 to 38%. Combining the p- and the s-factor, significantly higher specificity values of about 90% were reached. The s-factor showed a significant correlation (p=0.006) with the MPS ejection fraction. CONCLUSIONS: The CSG system is able to exclude relevant perfusion abnormalities in patients with suspected or known CAD with a specificity and a negative predictive value of about 90% combining the p- and the s-factor. Since it is a learning system there is potential for further improvement before routine use.

Associations of Abdominal Muscle Density and Area and Incident Cardiovascular Disease, Coronary Heart Disease, and Stroke: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Muscle density is inversely associated with all-cause mortality, but associations with cardiovascular disease (CVD) risk are not well understood. This study evaluated the association between muscle density and muscle area and incident total CVD, coronary heart disease (CHD), and stroke in diverse men and women. METHODS AND RESULTS: Adult participants (N=1869) in the Multi-Ethnic Study of Atherosclerosis Ancillary Body Composition Study underwent computer tomography scans of the L2-L4 region of the abdomen. Muscle was quantified by density (Hounsfield units) and area in cm2. Sex-stratified Cox proportional hazard models assessed associations between incident total CVD, incident CHD, and incident stroke across sex-specific percentiles of muscle area and density, which were entered simultaneously into the model. Mean age for men and women at baseline were 64.1 and 65.1 years, respectively, and median follow-up time was 10.3 years. For men, associations between muscle density and incident CVD were inverse but not significant in fully adjusted models (P trend=0.15). However, there was an inverse association between density and CHD (P trend=0.02; HR, 0.26 for 95th versus 10th percentile), and no association with stroke (P trend=0.78). Conversely, for men, there was a strong positive association between muscle area and incident CVD (HR, 4.19 for 95th versus 10th percentile; P trend<0.001). Associations were stronger for CHD (HR, 6.18 for 95th versus 10th percentile; P trend<0.001), and null for stroke (P trend=0.67). Associations for women were mostly null. CONCLUSIONS: For men, abdominal muscle density is associated with lower CHD risk, whereas greater muscle area is associated with markedly increased risk of CHD.

Changes and Significance of 2D-STI and Right Ventricular Function Parameters in Evaluating Cardiac Function in Patients with Coronary Heart Disease and Atrial Fibrillation.

Objective: To investigate the changes and clinical significance of two-dimensional speckle tracking imaging (2D-STI) and echocardiography in patients with coronary heart disease (CHD) and atrial fibrillation (AF). Methods: In this study, 102 patients with CHD accompanied by AF were selected as the case group, and 100 patients with CHD but without AF were selected as the control group. All patients received conventional echocardiography and 2D-STI, and the right heart function parameters and right heart strain parameters were compared. The relationship between the above indicators and the occurrence of adverse endpoint events in patients from the case group was analyzed by a logistic regression model. Results: The values of right ventricular ejection fraction (RVEF), right ventricular systolic volume (RVSV), and tricuspid valve systolic displacement (TAPSE) in the case group were lower than those in the control group, and the differences were statistically significant (P < .05). The values of right ventricular end-diastolic volume (RVEDV) and right ventricular end-systolic volume (RVESV) in the case group were higher than those in the control group, and the differences were statistically significant (P < .05). The values of right ventricular longitudinal strain in the basal segment (RVLSbas), right ventricular longitudinal strain in the middle segment (RVLSmid), right ventricular longitudinal strain in the apical segment (RVLSapi), and right ventricular longitudinal strain in the free wall (RVLSfw) in the case group were higher than those in the control group, and the differences were statistically significant (P < .05). The number of coronary lesions ≥2 branches, cardiac function class ≥III, coronary stenosis ≥70%, reduced RVEF, increased RVLSbas, RVLSmid, RVLSapi, and RVLSfw were found to be independent risk factors for adverse endpoint events in patients with CHD and AF (P < 0.05). Conclusion: In patients with CHD accompanied by AF, the right ventricular systolic function and myocardial longitudinal strain capacity decreases, and the decreased right ventricular function was closely related to the occurrence of adverse endpoint events.

Coronary Artery Calcium Score and Polygenic Risk Score for the Prediction of Coronary Heart Disease Events.

Importance: Coronary artery calcium score and polygenic risk score have each separately been proposed as novel markers to identify risk of coronary heart disease (CHD), but no prior studies have directly compared these markers in the same cohorts. Objective: To evaluate change in CHD risk prediction when a coronary artery calcium score, a polygenic risk score, or both are added to a traditional risk factor-based model. Design, Setting, and Participants: Two observational population-based studies involving individuals aged 45 years through 79 years of European ancestry and free of clinical CHD at baseline: the Multi-Ethnic Study of Atherosclerosis (MESA) study involved 1991 participants at 6 US centers and the Rotterdam Study (RS) involved 1217 in Rotterdam, the Netherlands. Exposure: Traditional risk factors were used to calculate CHD risk (eg, pooled cohort equations [PCEs]), computed tomography for the coronary artery calcium score, and genotyped samples for a validated polygenic risk score. Main Outcomes and Measures: Model discrimination, calibration, and net reclassification improvement (at the recommended risk threshold of 7.5%) for prediction of incident CHD events were assessed. Results: The median age was 61 years in MESA and 67 years in RS. Both log (coronary artery calcium+1) and polygenic risk score were significantly associated with 10-year risk of incident CHD (hazards ratio per SD, 2.60; 95% CI, 2.08-3.26 and 1.43; 95% CI, 1.20-1.71, respectively), in MESA. The C statistic for the coronary artery calcium score was 0.76 (95% CI, 0.71-0.79) and for the polygenic risk score, 0.69 (95% CI, 0.63-0.71). The change in the C statistic when each was added to the PCEs was 0.09 (95% CI, 0.06-0.13) for the coronary artery calcium score, 0.02 (95% CI, 0.00-0.04) for the polygenic risk score, and 0.10 (95% CI, 0.07-0.14) for both. Overall categorical net reclassification improvement was significant when the coronary artery calcium score (0.19; 95% CI, 0.06-0.28) but was not significant when the polygenic risk score (0.04; 95% CI, -0.05 to 0.10) was added to the PCEs. Calibration of the PCEs and models with coronary artery calcium and/or polygenic risk scores was adequate (all χ2<20). Subgroup analysis stratified by the median age demonstrated similar findings. Similar findings were observed for 10-year risk in RS and in longer-term follow-up in MESA (median, 16.0 years). Conclusions and Relevance: In 2 cohorts of middle-aged to older adults from the US and the Netherlands, the coronary artery calcium score had better discrimination than the polygenic risk score for risk prediction of CHD. In addition, the coronary artery calcium score but not the polygenic risk score significantly improved risk discrimination and risk reclassification for CHD when added to traditional risk factors.

On the nonlinear relationship between wall shear stress topology and multi-directionality in coronary atherosclerosis.

BACKGROUND AND OBJECTIVE: In this paper we investigate twelve multi-directional/topological wall shear stress (WSS) derived metrics and their relationships with the formation of coronary plaques in both computational fluid dynamics (CFD) and dynamic fluid-structure interaction (FSI) frameworks. While low WSS is one of the most established biomechanical markers associated with coronary atherosclerosis progression, alone it is limited. Multi-directional and topological WSS derived metrics have been shown to be important in atherosclerosis related mechanotransduction and near-wall transport processes. However, the relationships between these twelve WSS metrics and the influence of both FSI simulations and coronary dynamics is understudied. METHODS: We first investigate the relationships between these twelve WSS derived metrics, stenosis percentage and lesion length through a parametric, transient CFD study. Secondly, we extend the parametric study to FSI, both with and without the addition of coronary dynamics, and assess their correlations. Finally, we present the case of a patient who underwent invasive coronary angiography and optical coherence tomography imaging at two time points 18 months apart. Associations between each of the twelve WSS derived metrics in CFD, static FSI and dynamic FSI simulations were assessed against areas of positive/negative vessel remodelling, and changes in plaque morphology. RESULTS: 22-32% stenosis was the threshold beyond which adverse multi-directional/topological WSS results. Each metric produced a different relationship with changing stenoses and lesion length. Transient haemodynamics was impacted by coronary dynamics, with the topological shear variation index suppressed by up to 94%. These changes appear more critical at smaller stenosis levels, suggesting coronary dynamics could play a role in the earlier stages of atherosclerosis development. In the patient case, both dynamics and FSI vs CFD changes altered associations with measured changes in plaque morphology. An appendix of the linear fits between the various FSI- and CFD-based simulations is provided to assist in scaling CFD-based results to resemble the compliant walled characteristics of FSI more accurately. CONCLUSIONS: These results highlight the potential for coronary dynamics to alter multi-directional/topological WSS metrics which could impact associations with changes in coronary atherosclerosis over time. These results warrant further investigation in a wider range of morphological settings and longitudinal cohort studies in the future.

Risk score for coronary heart disease (CHD-RISK) and hemodynamically significant aortic valve stenosis.

BACKGROUND AND AIM: Multiple studies have investigated the association between coronary heart disease (CHD) risk factors and aortic valve stenosis (AS). However, limited studies have explored the relationship between CHD risk scores and AS. Whether incident risk scores for coronary heart disease (CHD-RISK) may be applied to predict AS remains unclear. We aim to investigate the association between AS and CHD-RISK. METHODS AND RESULTS: We included 4791 participants (age 54.6 ± 5.0 yrs, 58.7% women, 81% were of European origin), and CHD-RISK was estimated in 1990-1992. The participants were then followed-up until December 31, 2013. The primary outcome was hemodynamic significant AS identified by Doppler echocardiography in 2011-2013. We used multivariate-logistic regression models to assess the associations between CHD-RISK and AS. During follow-up, 963 (20.1%) cases of AS were identified. Per-standard deviation (6%) increase in CHD-RISK was associated with OR 95% Cl [1.194, 95% CI 1.068 to 1.335, p = 0.002] risk of AS in the fully adjusted models. Results were similar when stratified by quintiles of CHD-RISK, using the lowest quintiles <0.94% of CHD-RISK as the reference, 0.94%-2.26%, 2.26%-4.83%, 4.83%-9.21%, and >9.21% were; 1.33 (95% CI, 0.99-1.78, p = 0.055), 1.64 (95% CI, 1.17-2.29, p = 0.004), 2.23 (95% CI, 1.49-3.32, p = <0.001), 2.66 (95% CI, 1.65-4.31, p = <0.001) respectively. CONCLUSIONS: CHD-RISK was associated with AS. CHD-RISK and AS were high in females, age ≥55 yrs, current smokers, and BMI ≥ 30 kg/m2. This investigation suggests CHD-RISK may be applied to forecast AS risk similar to CHD. Future studies are required to detect, manage, and establish better treatment strategies in these high-risk subgroups.

Decreased Regional Spontaneous Brain Activity and Cognitive Dysfunction in Patients with Coronary Heart Disease: a Resting-state Functional MRI Study.

OBJECTIVES: Chronic coronary heart disease (CHD) is correlated with an increased risk of cognitive impairment (CI), but the mechanisms underlying these changes remain unclear. The aim of the present study was to explore the potential changes in regional spontaneous brain activities and their association with CI, to explore the pathophysiological mechanisms underlying CI in patients with CHD. MATERIALS AND METHODS: A total of 71 CHD patients and 73 matched healthy controls (HCs) were included in this study. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess the participants' cognitive functions. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation(fALFF) values were calculated to determine regional spontaneous brain activity. Coronary artery calcium (CAC) score provides a measure of the total coronary plaque burden. Mediation analyses were performed to test whether CHD's effects on cognitive decline are mediated by decreased regional spontaneous brain activity. RESULTS: Patients with CHD had significantly lower MMSE and MoCA scores than the HCs. Compared with the HCs, the patients with CHD demonstrated significantly decreased ReHo and fALFF values in the bilateral medial superior frontal gyrus (SFGmed), left superior temporal gyrus (TPOsup) and left middle temporal gyrus (TPOmid). Impaired cognitive performance was positively correlated with decreased activities in the SFGmed. Mediation analyses revealed that the decreased regional spontaneous brain activity in the SFGmed played a critical role in the relationship between the increase in CAC score and the MoCA and MMSE scores. CONCLUSION: The abnormalities of spontaneous brain activity in SFGmed may provide insights into the neurological pathophysiology underlying CHD associated with cognitive dysfunction.

Clinical Predictors of Coronary Artery Ectasia.

Coronary artery ectasia (CAE) is defined as abnormal dilation of a coronary artery ≥1.5 times the normal segment. We aimed to determine the prevalence and clinical predictors of CAE. This was a prospective analysis performed on 6465 patients undergoing coronary angiography. Patients were divided based on the presence or absence of CAE and compared for angiographic characteristics and clinical risk factors. The prevalence of CAE was 7%, CAE associated with coronary artery stenosis was 5.4%, and isolated CAE was 1.6%. The mean age of presentation in CAE patients was 60 years, with male predominance (83.8%) and stable angina was the most common presentation. The left anterior descending artery (LAD) (51.7%) was the most commonly involved vessel, with diffuse ectasia more commonly seen in right coronary artery and discrete ectasia in LAD. Type 4 CAE was the most common type (92.4%). Hypertension, diabetes, smoking, dyslipidemia, and obesity were found in 62.4%, 35.3%, 45.3%, 54.9%, and 23.3%, respectively in CAE patients, with significant association with smoking (Odds Ratio = 3.06). The prevalence of CAE was 7% and was frequently associated with atherosclerotic coronary disease. Smoking was a significant predisposing factor for CAE.

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

Objective: To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Methods: Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical examination centers in China were included in this retrospective study. Two radiologists, who were not aware of the study design, independently evaluated the coronary angiography images of each subject to make CHD diagnosis. A deep learning model using convolutional neural networks (CNN) was used to label the fundus images according to the presence or absence of CHD, and the model was proportionally divided into training and test sets for model training. The prediction performance of the model was evaluated in the test set using monocular and binocular fundus images respectively. Prediction efficacy of the algorithm for cardiovascular risk factors (e.g., age, systolic blood pressure, gender) and coronary events were evaluated by regression analysis using the area under the receiver operating characteristic curve (AUC) and R2 correlation coefficient. Results: The study retrospectively collected 51 765 fundus images from 25 222 subjects, including 10 255 patients with CHD, and there were 14 419 male subjects in this cohort. Of these, 46 603 fundus images from 22 701 subjects were included in the training set and 5 162 fundus images from 2 521 subjects were included in the test set. In the test set, the deep learning model could accurately predict patients' age with an R2 value of 0.931 (95%CI 0.929-0.933) for monocular photos and 0.938 (95%CI 0.936-0.940) for binocular photos. The AUC values for sex identification from single eye and binocular retinal fundus images were 0.983 (95%CI 0.982-0.984) and 0.988 (95%CI 0.987-0.989), respectively. The AUC value of the model was 0.876 (95%CI 0.874-0.877) with either monocular fundus photographs and AUC value was 0.885 (95%CI 0.884-0.888) with binocular fundus photographs to predict CHD, the sensitivity of the model was 0.894 and specificity was 0.755 with accuracy of 0.714 using binocular fundus photographs for the prediction of CHD. Conclusion: The deep learning model based on fundus photographs performs well in identifying coronary heart disease and assessing related risk factors such as age and sex.

Intracoronary Ultrasound Imaging Combined with Traditional Chinese Medicine Nursing Applied in the Treatment of Coronary Heart Disease Patients with Phlegm and Blood Stasis Syndrome.

This study was to explore the effect of traditional Chinese medicine (TCM) nursing intervention based on intracoronary ultrasound imaging on patients with coronary heart disease (CHD) and phlegm and blood stasis syndrome (PBSS). 100 hospitalized patients with CHD with Qi deficiency and blood stasis syndrome (QDBSS) were rolled into the experimental (Exp) group (routine nursing intervention) and control (Ctrl) group (TCM nursing intervention, syndrome differentiation nursing), with 50 patients in each group. They underwent the intracoronary ultrasound imaging scanning. The results showed that after intervention, the plaque load (45.08 ± 6.02%), plaque eccentricity index (0.47 ± 0.08%), vascular remodeling index (0.53 ± 0.11%), and vascular external elastic membrane area (8.67 ± 3.06 mm2) of the Exp group were notably inferior to those of the Ctrl group (60.22 ± 5.82%, 0.59 ± 0.08%, 0.71 ± 0.09%, and 10.56 ± 2.31 mm2). The total effective rate in the Exp group (88%) was greatly superior to that of the Ctrl group (68%). In terms of TCM symptom scores, the TCM symptom scores of chest pain, chest tightness, and shortness of breath in the Exp group after intervention (1.07 ± 0.21 points, 0.75 ± 0.27 points, and 0.58 ± 0.12 points) were notably inferior to those in the Ctrl group (1.62 ± 0.28 points, 1.03 ± 0.21 points, and 0.79 ± 0.14 points). In the Exp group, after intervention, the degree of physical activity limitation (67.05 ± 5.08 points), the stable state of angina pectoris (65.28 ± 3.76 points), the frequency of angina pectoris attack (85.92 ± 2.97 points), the degree of treatment satisfaction (75.39 ± 5.94 points), the cognition score of disease (63.56 ± 5.84 points), the levels of triglyceride (1.27 ± 0.41 mmol/L), and total cholesterol (2.24 ± 0.41 mmol/L) were remarkably inferior to the Ctrl group (52.97 ± 4.31 points, 50.77 ± 4.69 points, 71.36 ± 3.77 points, 64.08 ± 5.64 points, 51.77 ± 6.33 points, 2.09 ± 0.57 mmol/L, and 3.06 ± 0.84 mmol/L) (P < 0.05). It suggested that intracoronary ultrasound imaging can clearly display the coronary plaques of patients and accurately evaluate the clinical efficacy of patients with CHD. The TCM nursing program can greatly improve the angina symptoms and quality of life of patients with CHD and PBSS, reduce blood lipid levels, and effectively improve the clinical efficacy of patients.

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

BACKGROUND: Segment-specific variations of carotid intima-media thickness (CIMT) have not been assessed in South Asian populations. The purpose of this study was to determine if segment-specific CIMTs or a composite-CIMT score is a better risk predictor of coronary heart disease in South Asian populations. METHODS: A comparative prospective study was conducted from November 2019 to October 2020 in a hospital in Colombo, Sri Lanka. Based on pre-defined inclusion and exclusion criteria, cases (having a diagnosis of Coronary Heart Disease (CHD), n = 338) and controls (non-CHD group, n = 356) were recruited. Ultrasound examination of the common carotid (CCA), the carotid bulb (CB) and the internal carotid segments (ICA) of the carotid vessels was conducted by a radiologist, and CIMTs were measured. A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived. RESULTS: 694 participants were enrolled (male n = 399, 57.5%). The mean (±SD) age of the study sample was 60.2 (±9.86) years. There were variations in segment-specific values between the left and right vessels. The mean composite-CIMT value of the CHD group was significantly higher than that of the non-CHD group. A composite-CIMT score of 0.758 had a sensitivity of 98.4% and a specificity of 64.6% in distinguishing CHD from non-CHD groups (Area under the curve (AUC): 0.926). CONCLUSIONS: Carotid artery segment-specific CIMT variations were present in this population. The composite CIMT score is better than segment-specific CIMTs in predicting CHD and may be used to predict CHD in this population.

Aberrant Spontaneous Brain Activity in Coronary Heart Disease Using Fractional Amplitude of Low-Frequency Fluctuations: A Preliminary Resting-State Functional MRI Study.

Objective: This study is aimed at exploring the spontaneous brain activity changes by measuring the fractional amplitude of low-frequency fluctuations (fALFF) and their relationship with clinical characteristics in patients with coronary heart disease (CHD). Methods: Coronary heart disease patients (n = 25) and age, gender, and education level-matched control subjects (controls, n = 35) were included. The grey matter volume (GMV) and fALFF values were calculated to assess the difference in brain structure and function between the two groups, respectively. Correlation analyses between the fALFF values and clinical characteristics were further assessed in CHD patients. In addition, receiver operating characteristic (ROC) curves were conducted to access the diagnostic ability of the fALFF method. Results: There was no significant difference in GMV between the CHD and control groups. Compared with the control group, patients with CHD showed significantly decreased fALFF in the left precentral/postcentral gyrus and increased fALFF in the right inferior cerebellum. Patients with a history of myocardial infarction (MI) showed significantly decreased fALFF values of the right inferior cerebellum than patients without MI. There was no significant correlation between the fALFF values in specific brain regions and disease duration. Furthermore, the ROC curves of abnormal brain regions showed the perfect accuracy of the fALFF value in distinguishing between CHD patients and controls. Conclusion: CHD demonstrated aberrant neural activity in specific brain regions mainly related to sensorimotor networks and pain processing, which may contribute to understanding the underlying neurological mechanism of CHD.

Association between triglyceride glucose index and carotid artery plaque in different glucose metabolic states in patients with coronary heart disease: a RCSCD-TCM study in China.

BACKGROUND: The triglyceride glucose (TyG) index serves as a surrogate indicator of insulin resistance. However, there is limited evidence on the association between the TyG index and carotid artery plaque (CAP) in patients with coronary heart disease (CHD). METHODS: The 10,535 CHD patients were divided according to TyG index quartiles (Q1: TyG index < 8.52; Q2: 8.52 ≤ TyG index < 8.93; Q3: 8.93 ≤ TyG index ≤ 9.40; Q4: TyG index > 9.40). The presence or absence of CAP was determined by carotid ultrasonography. Logistic regression was used to analyze the relationship between the TyG index and CAP in CHD patients. The relationship between the TyG index and CAP in according to sex, age groups, and glucose metabolism states were also assessed. RESULTS: The baseline analysis showed that there were significant differences in related parameters among CHD patients divided into four groups according to the quartile of the TyG index. In the multi-adjusted modles, compared to Q1 of the TyG index, the odds ratios (OR) for Q4 of the TyG index for CAP were 1.37 (95% confidence interval [CI] 1.28-1.47) in CHD patients. The association between the TyG index and CAP in female (OR: 1.35; 95% CI 1.29-1.43) was higher than that in male (OR: 1.20; 95% CI 1.13-1.27). The OR value of middle-aged (≤ 60 years old) patients (OR: 1.34; 95% CI 1.26-1.42) was higher than that in elderly (> 60 years old) patients (OR: 1.16; 95% CI 1.11-1.22). In different glucose metabolism states, the TyG index of CHD patients was significantly related to the risk of CAP, with the highest OR value observed for diabetes (OR: 1.36; 95% CI 1.26-1.46). CONCLUSIONS: The TyG index and CAP showed a significant association in CHD patients. This association between TyG index and CAP in CHD patients is higher in female than in male, and the association in middle-aged and elderly patients is higher than that in elderly patients. In the condition of DM, the association between TyG index and carotid artery plaque in CHD patients is higher.

Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.

BACKGROUND: Automated segmentation of coronary arteries is a crucial step for computer-aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation of the coronary artery is challenging in X-ray coronary angiography (XCA) due to the low signal-to-noise ratio and confounding background structures. METHODS: A novel ensemble framework for coronary artery segmentation in XCA images is proposed, which utilizes deep learning and filter-based features to construct models using the gradient boosting decision tree (GBDT) and deep forest classifiers. The proposed method was trained and tested on 130 XCA images. For each pixel of interest in the XCA images, a 37-dimensional feature vector was constructed based on (1) the statistics of multi-scale filtering responses in the morphological, spatial, and frequency domains; and (2) the feature maps obtained from trained deep neural networks. The performance of these models was compared with those of common deep neural networks on metrics including precision, sensitivity, specificity, F1 score, AUROC (the area under the receiver operating characteristic curve), and IoU (intersection over union). RESULTS: With hybrid under-sampling methods, the best performing GBDT model achieved a mean F1 score of 0.874, AUROC of 0.947, sensitivity of 0.902, and specificity of 0.992; while the best performing deep forest model obtained a mean F1 score of 0.867, AUROC of 0.95, sensitivity of 0.867, and specificity of 0.993. Compared with the evaluated deep neural networks, both models had better or comparable performance for all evaluated metrics with lower standard deviations over the test images. CONCLUSIONS: The proposed feature-based ensemble method outperformed common deep convolutional neural networks in most performance metrics while yielding more consistent results. Such a method can be used to facilitate the assessment of stenosis and improve the quality of care in patients with CAD.