Abstract:Aim To explore the predictive value of serum free triiodothyronine (FT3) on the long-term prognosis of patients with coronary heart disease after percutaneous coronary intervention (PCI). Methods All the subjects were from a prospective cohort study (PRACTICE study). In this study, 15 250 patients with coronary heart disease after PCI in the First Affiliated Hospital of Xinjiang Medical University were selected, and the clinical data, FT3 and creatinine were collected. All the subjects were followed up regularly, and the primary follow-up endpoints were all-cause mortality and cardiogenic mortality, the secondary endpoints were major adverse cardiovascular events (MACE) and major adverse cardiovascular and cerebrovascular events (MACCE). According to the admission criteria, 3 109 patients were finally included in this study. According to the baseline value of FT3, patients were divided into normal FT3 group (FT3:3.65～6.8 pmol/L, 1 446 cases) and low FT3 group (FT3＜3.65 pmol/L, 1 663 cases). Kaplan-Meier analysis was used for survival analysis, and Log-rank test was used for survival comparison. Multivariate Cox regression analysis was used to evaluate the risk factors of the follow-up results of the two groups. Results Compared with the normal FT3 group, all-cause mortality and cardiogenic mortality in the low FT3 group increased significantly (P＜0.05). Kaplan-Meier analysis showed that the cumulative risk of all-cause mortality and cardiogenic mortality increased in the low FT3 group (P＜0.05).Multivariate Cox regression analysis indicated that the risk of all-cause mortality increased by 1.639 folds in the low FT3 group (HR＝2.9,5%CI:1.385～5.348, P＝0.007), while no statistical difference was found in cardiogenic mortality after adjusting for multiple factors (P＝0.125). Conclusion The decrease in serum FT3 levels has important predictive value for all-cause mortality after PCI in patients with coronary heart disease.

Abstract:Aim To investigate the related influencing factors of major adverse cardiovascular events (MACE) in coronary heart disease (CHD) patients with type 2 diabetes mellitus (T2DM) based on prognostic nutritional index (PNI), and to construct a prediction model. Methods The clinical data of 391 patients with CHD combined with T2DM who were hospitalised in the Department of Cardiovascular Medicine of Hebei Provincial Peoples Hospital from January 2022 to January 2023 were collected and followed up for 1 year, and were divided into the MACE group (n＝99) and the non-MACE group (n＝292) according to the presence or absence of the occurrence of MACE, and were divided into the training set (n＝273) and the validation set (n＝118) in a ratio of 7∶3 by using the computer-generated random number method, and the patients in the training set were divided into the MACE (n＝67) group and the non-MACE group (n＝206) according to whether they had MACE or not. Lasso regression was used to screen the relevant influencing factors and to construct the prediction model of the column-line diagram, and the prediction model was validated by plotting receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results Lasso regression showed that the use of angiotensin receptor neprilysin inhibitor (ARNI), fasting blood glucose (FBG), C-reactive protein (CRP), platelet to lymphocyte ratio (PLR), lipoprotein(a) (Lp(a), and PNI were the predictors of the occurrence of MACE in patients with CHD combined with T2DM. A column-line graph prediction model was constructed and validated based on the above predictors, and the area under the ROC curve (AUC) was 0.838(95%CI:0.778～0.898) in the training set and 0.872(95%CI:0.803～0.942) in the validation set, with a good discriminatory degree of the model, and the C-values of the calibration curves in the training set and the validation set were 0.838 and 0.872, respectively, with good fit. The results of the decision curve analysis and the clinical impact curve showed that the column-line graph prediction model had a higher net yield of MACE in patients with CHD combined with T2DM, with high clinical utility. Conclusion PNI is an influential factor in the occurrence of MACE in patients with CHD combined with T2DM, and the column-line graphical model constructed on the basis of predictors such as PNI is convenient for clinical use and has high predictive value in predicting the occurrence of MACE in patients with CHD combined with T2DM.

Abstract:Aim To detect the changes of serum cardiotrophin-1 (CT-1) and angiopoietin-like protein 3 (ANGPTL3) levels in patients with coronary heart disease (CHD) complicated with heart failure (HF) after percutaneous coronary intervention (PCI), and analyze their relationship with prognosis. Methods 199 patients with CHD complicated with HF who underwent PCI in the Second Affiliated Hospital of Zhengzhou University from March 2022 to March 2023 were selected. The serum CT-1 and ANGPTL3 levels of patients with different New York Heart Association (NYHA) cardiac function grades were compared before surgery. The prognosis was followed up after PCI, and the patients who had major adverse cardiovascular event (MACE) were included in the poor prognosis group, and the rest were included in the good prognosis group. The general data and serum CT-1 and ANGPTL3 levels were compared between the poor prognosis group and the good prognosis group. Logistic regression model was used to analyze the influencing factors of poor prognosis after surgery in patients with CHD and HF. The predictive value of serum CT-1 and ANGPTL3 alone and in combination were analyzed. Results Compared with the patients with cardiac function grade Ⅰ, the serum CT-1 and ANGPTL3 levels of the patients with cardiac function grade Ⅱ, Ⅲ and Ⅳ were increased (P＜0.05). Compared with the patients with cardiac function grade Ⅱ, the serum CT-1 and ANGPTL3 levels of the patients with cardiac function grade Ⅲ and Ⅳ were increased (P＜0.05). Compared with the patients with cardiac function grade Ⅲ, the serum CT-1 and ANGPTL3 levels of the patients with acrdiac function grade Ⅳ were increased (P＜0.05). Spearman correlation analysis showed that the serum CT-1 and ANGPTL3 levels were positively correlated with NYHA cardiac function grade (r＝0.8,5%CI:0.408~0.613, P＜0.001, r＝0.7,5%CI:0.666~0.794, P＜0.001). The poor prognosis rate of patients was 17.93%. Compared with the good prognosis group, the serum CT-1 and ANGPTL3 levels of the poor prognosis group were increased (P＜0.05). Logistic regression model analysis showed that smoking, diabetes, lesion vessel number≥3, irregular medication outside the hospital, serum CT-1 and ANGPTL3 levels were the influencing factors of poor prognosis in patients with CHD complicated with HF (P＜0.05). ROC curve analysis showed that the sensitivity and area under the curve (AUC) of combined serum CT-1 and ANGPTL3 levels for predicting poor prognosis of patients with CHD complicated with HF were higher than those of either marker alone, while the specificity was basically similar to that of single-marker prediction. Conclusion Serum CT-1 and ANGPTL3 levels are abnormally elevated in patients with CHD complicated with HF after PCI, and are closely related to the cardiac function and prognosis.

Abstract:Aim To explore the predictive value of serum D-dimer and the soluble receptor for advanced glycation end products (sRAGE) levels in the short-term poor prognosis of elderly patients with coronary heart disease after percutaneous coronary intervention (PCI). Methods The clinical data of 316 elderly patients with coronary heart disease first diagnosed in Huanggang Central Hospital from April 2019 to June 2020 were collected. According to whether the patients had major adverse cardiovascular events (MACE) during the follow-up period, they were divided into MACE group (n＝52) and non MACE group (n＝264). The independent influencing factors of postoperative MACE were analyzed by univariate analysis and multivariate Logistic regression, the nomogram prediction model was established and verified according to the independent influencing factors of patient prognosis. The threshold effect of D-dimer and sRAGE levels was determined by curve fitting and threshold effect analysis, and the influence of D-dimer and sRAGE levels on MACE was evaluated by Kaplan-Meier curve. Results During the one-year postoperative period, 52(16.46%) of the 316 elderly patients with coronary heart disease who were included experienced MACE. Body mass index (BMI), proportion of hypertension, proportion of diabetes, GRACE score, number of stents, apoliporotein (Apo) B, ApoB/ApoA, low density lipoprotein cholesterol (LDLC), liporotein (a) [Lp(a)] and D-dimer levels of patients in the MACE group were higher than those in the non MACE group, and sRAGE levels were lower than those in the non MACE group, with statistically significant differences(P＜0.05). Multivariate Logistic regression analysis showed that high GRACE score, high Lp(a) and high D-dimer levels were independent risk factors for MACE in elderly patients with coronary heart disease after PCI treatment, and high sRAGE level was protective factor (P＜0.05). Curve fitting found that the probability of MACE increased with the increase of D-dimer level and the decrease of sRAGE level. The Kaplan-Meier curve shows that the incidence of MACE in patients with higher D-dimer levels is significantly higher than that in patients with low D-dimer levels (P＜0.001), and the incidence of MACE in patients with lower sRAGE levels is significantly higher than patients with higher sRAGE levels (P＜0.001). The nomogram model was constructed based on independent prognostic factors, and its consistency index was 0.796 (95%CI:0.723～0.834), ROC curve AUC was 0.851 (95%CI:0.806～0.892), which has a good degree of discrimination. Conclusion High level of D-dimer and low level of sRAGE are important risk factors for MACE after PCI in elderly patients with coronary heart disease, and have a high predictive value for short-term adverse prognosis after PCI.

Abstract:Aim To investigate the clinical value of real-time three-dimensional echocardiography (RT-3DE) combined with autostrain right ventricle (RV) technology in evaluating right ventricular function in patients with coronary heart disease (CHD)involving the right coronary artery stenosis. Methods A total of 132 patients with suspected CHD were enrolled. According to the results of coronary angiography, they were divided into control group without coronary artery stenosis of 50%, CHD without involving the right coronary artery stenosis group (simple CHD group), CHD involving the right coronary artery stenosis group. The three groups of subjects were analyzed by conventional echocardiography, autostrain RV technology and RT-3DE. Results Compared with control group, at the basal levels of the right ventricular free wall-longitudinal strain (Basal RVFWSL), at the middle levels of the right ventricular free wall-longitudinal strain (Medial RVFWSL), at the apical levels of the right ventricular free wall-longitudinal strain (Apical RVFWSL), right ventricular free wall-longitudinal strain (RVFWSL), right ventricular 4 chamber longitudinal strain (RV4CSL), right ventricular ejection fraction (RVEF), right ventricular stroke volume (RVSV) and right ventricular stroke volume index (RVSVI) were decreased, while right ventricular end-systolic volume (RVESV), right ventricular end-systolic volume index (RVESVI) were increased in simple CHD group and CHD involving the right coronary artery stenosis group. The differences were statistically significant (all P＜0.05). ROC curve analysis showed that RVFWSL of two-dimensional speckle tracking imaging (2D-STI) and RVEF of RT-3DE had higher diagnostic efficiency, with a sensitivity of 90.9% and a specificity of 95.3%. Conclusions RT-3DE combined with autostrain RV technology can improve the accuracy of evaluating right ventricular dysfunction in patients with CHD involving the right coronary artery stenosis, which provides a basis for early clinical treatment and has good application value.

Abstract:Aim To study the distribution of CYP2C19, ABCB1, and PON1 genotypes and their correlation with clopidogrel resistance in patients with coronary heart disease in Taian. Methods A total of 594 patients with coronary heart disease who were treated with clopidogrel during hospitalization in Taian Central Hospital from January 2019 to March 2020 were selected. Fluorescence in situ hybridization was used to detect CYP2C19*2 (rs4244285), CYP2C19*3 (rs4986893), CYP2C19*17 (rs12248560), ABCB1 (rs1045642) and PON1 (rs662) gene types. Results CYP2C19*2, CYP2C19*3, CYP2C19*17 genotypes in patients with coronary heart disease in Taian were mainly with homozygous (GG). The frequencies of CYP2C19*2 GG, CYP2C19*3 GG, CYP2C19*17 CC, ABCB1 CT and PON1 AG were 48.0%, 89.6%, 97.0%, 46.8% and 47.1% respectively. There was no significant difference in CYP2C19*2, CYP2C19*3, CYP2C19*17, ABCB1, PON1 genotype distribution and allele distribution between male and female patients (P＞0.05). Significant regional differences in the frequency of CYP2C19 alleles and the distribution of metabolic types were found in patients with coronary heart disease in Taian. Among 594 patients included in the study, there were 287 patients with a risk level of clopidogrel resistance ≥ 2 in the composite evaluation of patients, approximately 48.3% of the total number of patients. This indicated that clopidogrel resistance was present in 48.3% of patients on the regular dose of clopidogrel. Of the 287 people with a risk level ≥ 2,6 had a normal CYP2C19 metabolic type, representing approximately 7.7% of the total number of patients. Conclusion There were gene polymorphisms observed in CYP2C19*2, CYP2C19*3, CYP2C19*17, ABCB1 and PON1 distribution in patients with coronary heart disease in Taian, and ABCB1 and PON1 gene polymorphisms would had an impact on the outcome of medication guidance in approximately 7.7%.

Abstract:Aim To explore the feasibility of using machine learning algorithms combined with coronary computed tomography (CT) derived perivascular fat attenuation index (FAI) and plaque information to evaluate myocardial ischemia in stable coronary heart disease patients. Methods A retrospective analysis was conducted on the clinical and imaging data of patients who underwent preoperative coronary CT angiography (CCTA), invasive coronary angiography (ICA), and flow reserve fraction (FFR) measurements at Zhongshan Hospital Affiliated to Fudan University from April 2019 to October 2021. 206 patients with stable coronary heart disease were selected. The semi-automatic plaque analysis software was used for quantification of plaque and lumen parameters and perivascular FAI measurement, with manual delineation of a 40 mm segment of the coronary artery starting 10 mm from the ostium for perivascular FAI measurement. Differences in plaque characteristics, perivascular FAI, and coronary perivascular FAI between stable coronary heart disease patients with FFR≤0.8 and FFR＞0.8 were compared. The diagnostic performance of combining perivascular FAI, coronary perivascular FAI, and plaque features using machine learning algorithms for myocardial ischemia in stable coronary heart disease patients was evaluated through ROC curves. Results 206 stable coronary heart disease patients were divided into FFR≤0.8 group (50 cases) and FFR＞0.8 group (156 cases). The mean periplaque FAI of patients with FFR≤0.8 was －69.28±5.65 HU, significantly higher than that of patients with FFR＞0.8 at －80.10±7.75 HU (P＜0.001). Further analysis was conducted using machine learning models, including XGBoost, random forest, and Logistic regression models, all of which had an accuracy rate of over 0.8 in diagnosing myocardial ischemia. Among them, the XGBoost model performed the best with an accuracy of 0.903, an F1 value of 0.774, and an AUC of 0.931, indicating its high effectiveness in diagnosing myocardial ischemia. Conclusion The combination of FAI and machine learning algorithm XGBoost model is a new method for diagnosing myocardial ischemia, which has better diagnostic value in evaluating myocardial ischemia in stable coronary heart disease patients.

Abstract:Aim To investigate the correlation between serum remnant lipoprotein cholesterol(RLP-C), triglyceride levels(TG) and coronary heart disease(CHD) in middle-aged people. Methods A total of 439 middle-aged individuals who were hospitalized in the Department of Cardiology of Liuzhou Peoples Hospital from January 2015 to December 2022 and underwent coronary angiography were selected as the research subjects. They were divided into CHD group (190 cases) and control group (249 cases) according to the results of coronary angiography. The general clinical data and laboratory tests of the subjects were collected,and RLP-C was calculated based on blood lipid profile. Bivariate Spearman correlation, multivariate Logistic regression, and restricted cubic spline graph were used to analyze the correlation between RLP-C, TG, and CHD in these middle-aged participants. Receiver operating characteristic (ROC) curve was used to evaluate the value of RLP-C and TG in predicting CHD. Results The age in CHD group was older than that in control group, proportion of male, proportion of smoking history, incidence of hypertension, incidence of diabetes, incidence of hyperlipidemia, body mass index (BMI), systolic blood pressure(SBP), fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), TG, low density lipoprotein cholesterol (LDLC), RLP-C were higher than those in control group, while high density lipoprotein cholesterol (HDLC) was lower than that in control group (P＜0.05). The Spearman correlation analysis results showed positive correlation between RLP-C, TG, LDLC and CHD (r＝0.7,0.279, and 0.105, respectively, P＜0.05), and negative correlation between HDLC and CHD (r＝－0.340, P＜0.001) in these studied population. Multivariate Logistic regression analysis showed that whether as continuous or categorical variables, RLP-C and TG were independent risk factors for CHD (P＜0.05), HDLC was independent protective factor for CHD (P＜0.05). Compared with lowest quartile group, The OR (95%CI) of CHD incidence in 3rd and 4th quartile group of RLP-C were 2.648(1.364~5.144) and 2.847(1.468~5.520) respectively; The OR (95%CI) of CHD incidence in 3rd and 4th quartile group of TG were 3.043(1.520~6.092) and 3.520(1.811~6.842) respectively. The restricted cubic spline graph revealed that RLP-C, TG were positively nonlinearly correlated with CHD (P for overall＜0.001, P for nonlinear＝0.2,0.001, respectively). Subgroup analysis showed that the relationship between RLP-C, TG and CHD was more significant in females than in males. ROC curve analysis showed that the areas under the curve (95%CI) of RLP-C, TG in predicting CHD were 0.632(0.580~0.685) (P＜0.001) and 0.663(0.612~0.713) (P＜0.001) in general, meanwhile, 0.735(0.659~0.811) (P＜0.001) and 0.740(0.666~0.813) (P＜0.001) in females. Conclusion RLP-C and TG are independent risk factors for CHD in middle-aged people, and their correlation with CHD are greater than that of LDLC. They may become the main targets for the prevention and treatment of CHD, and should be given clinical attention.

Abstract:The regulatory role of pericoronary adipose tissue (PCAT) in cardiovascular diseases is of paramount importance. PCAT exerts extensive pathophysiological effects on the cardiovascular system by secreting various bioactive substances, such as adipokines and cytokines. Currently, the attenuation value of PCAT can be detected via coronary computed tomography angiography (CCTA), a method that not only reflects the level of vascular inflammation but also holds significant clinical value in the detection and prognostic assessment of coronary heart disease plaques. Therefore, this article reviews the pathophysiological mechanisms of PCAT and its clinical significance in coronary heart disease.

Abstract:Aim To study the relationship between white blood cell count and clinical classification in patients with coronary heart disease and its clinical significance. Methods A total of 301 patients diagnosed with coronary heart disease in the Second Affiliated Hospital of Harbin Medical University from January 2022 to December 2023 were selected as the research subjects, and divided into stable angina pectoris (SAP) group and acute coronary syndrome (ACS) group based on their clinical manifestations and results of electrocardiogram, the differences of general data, biochemical indexes and cardiovascular indexes between the two groups were compared. Spearman correlation analysis was used to analyze the relationship between white blood cell count, neutrophil count and cardiovascular related indicators, including troponin I, N-terminal pro-brain natriuretic peptide (NT-proBNP), ejection fraction, left ventricular end-diastolic diameter (LVEDD), left atrial diameter, Gensini score, etc. ROC curve was employed to determine the cut-off point for diagnosing ACS and SAP classification of coronary heart disease based on white blood cell count, and dividing patients into a group with normal white blood cell level and a group with above normal white blood cell level based on this cut-off point, the differences between the two groups were compared. Results The ratio of hyperlipidaemia history, white blood cell count, neutrophil count, C-reactive protein, platelet count, total cholesterol (TC), low density lipoprotein cholesterol (LDLC), troponin I, NT-proBNP and Gensini score in the ACS group were significantly higher than those in the SAP group (all P＜0.05), while the ratio of aspirin use, the ratio of statin use, and ejection fraction in the ACS group were lower than those in the SAP group (all P＜0.05). Spearman correlation analysis results showed that white blood cell count was positively correlated with C-reactive protein (r＝0.443, P＜0.001), troponin I (r＝0.333, P＜0.001), NT-proBNP (r＝0.245, P＜0.001) and Gensini score (r＝0.341, P＜0.001), but negatively correlated with LVEDD (r＝－0.212, P＜0.001). Similarly, neutrophil count was positively correlated with C-reactive protein (r＝0.430, P＜0.001), troponin I (r＝0.325, P＜0.001), NT-proBNP (r＝0.292, P＜0.001) and Gensini score (r＝0.353, P＜0.001), but negatively correlated with LVEDD ( r＝－0.175, P＝0.002). The cut-off point of white blood cell count in the diagnosis of ACS was 9.35×109 L－1 (sensitivity was 56.7%, specificity was 93.1% ). The patients were divided into normal white blood cell level group (n＝202) and above normal white blood cell level group (n＝99). Hyperlipidemia, smoking history, TC, LDLC, C-reactive protein, troponin I, NT-proBNP and Gensini scores in above normal white blood cell level group were significantly higher than those in the normal white blood cell level group (all P＜0.05), while LVEDD was lower than that in the normal white blood cell level group (all P＜0.05). Conclusion White blood cell count can easily identify the high-risk type of coronary heart disease, and the cut-off point for the diagnosis of ACS is 9.35×109 L－1.