Triglyceride glucose index is associated with obstructive coronary artery disease in hypertensive patients.

BACKGROUND: Hypertension is a leading risk of coronary artery disease (CAD). Triglyceride glucose index (TyG) is a surrogate of insulin resistance (IR). Few studies explore the association between TyG and the incidence of obstructive CAD (OCAD) in hypertensive patients. METHODS: We retrospectively screened 1841 hypertensive subjects who were free of a history of CAD and underwent coronary computed tomography angiography (CCTA) because of chest pain. TyG index was calculated as ln (fasting TG [mg/dL] * fasting glucose [mg/dL]/2). The outcome of this research was OCAD, which was defined as the presence of diameter stenosis ≥ 50% in any of the four major epicardial coronary arteries detected on CCTA. RESULTS: A total of 310 (16.8%) patients developed obstructive CAD. The restricted cubic spline (RCS) analysis showed a J-shaped relationship between TyG and OCAD and the OR for OCAD increased as the TyG rose over 8.61 (OR perSD) 1.64, 95% CI 1.13-2.54, p = 0.008). After full adjustments for confounding covariates, patients with TyG index in tertile 3 (T3) had 2.12 times (95% CI 1.80 to 3.81) and in T2 had 2.01 times (95% CI 1.40 to 2.88) as high as the risk of OCAD compared with patients in T1 (p for trend = 0.001). When regarding TyG as a continuous variable, 1-SD increase elevated 49% (OR (95%CI), 1.49 (1.30-1.74)) risk of obstructive CAD (p = 0.007). This positive effect was still consistent across the subgroups (p for interaction > 0.05). CONCLUSION: TyG index was associated with the incidence of obstructive CAD in hypertensive patients.

Predictive value of machine learning algorithm of coronary artery calcium score and clinical factors for obstructive coronary artery disease in hypertensive patients.

BACKGROUND: The addition of coronary artery calcium score (CACS) to prediction models has been verified to improve performance. Machine learning (ML) algorithms become important medical tools in an era of precision medicine, However, combined utility by CACS and ML algorithms in hypertensive patients to forecast obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CCTA) is rare. METHODS: This retrospective study was composed of 1,273 individuals with hypertension and without a history of CAD, who underwent dual-source computed tomography evaluation. We applied five ML algorithms, coupled with clinical factors, imaging parameters, and CACS to construct predictive models. Moreover, 80% individuals were randomly taken as a training set on which 5-fold cross-validation was done and the remaining 20% were regarded as a validation set. RESULTS: 16.7% (212 out of 1,273) of hypertensive patients had obstructive CAD. Extreme Gradient Boosting (XGBoost) posted the biggest area under the receiver operator characteristic curve (AUC) of 0.83 in five ML algorithms. Continuous net reclassification improvement (NRI) was 0.55 (95% CI (0.39-0.71), p < 0.001), and integrated discrimination improvement (IDI) was 0.04 (95% CI (0.01-0. 07), p = 0.0048) when the XGBoost model was compared with traditional Models. In the subgroup analysis stratified by hypertension levels, XGBoost still had excellent performance. CONCLUSION: The ML model incorporating clinical features and CACS may accurately forecast the presence of obstructive CAD on CCTA among hypertensive patients. XGBoost is superior to other ML algorithms.

Predictive value of CAC score combined with clinical features for obstructive coronary heart disease on coronary computed tomography angiography: a machine learning method.

OBJECTIVE: We investigated the predictive value of clinical factors combined with coronary artery calcium (CAC) score based on a machine learning method for obstructive coronary heart disease (CAD) on coronary computed tomography angiography (CCTA) in individuals with atypical chest pain. METHODS: The study included data from 1,906 individuals undergoing CCTA and CAC scanning because of atypical chest pain and without evidence for the previous CAD. A total of 63 variables including traditional cardiovascular risk factors, CAC score, laboratory results, and imaging parameters were used to build the Random forests (RF) model. Among all the participants, 70% were randomly selected to train the models on which fivefold cross-validation was done and the remaining 30% were regarded as a validation set. The prediction performance of the RF model was compared with two traditional logistic regression (LR) models. RESULTS: The incidence of obstructive CAD was 16.4%. The area under the receiver operator characteristic (ROC) for obstructive CAD of the RF model was 0.841 (95% CI 0.820-0.860), the CACS model was 0.746 (95% CI 0.722-0.769), and the clinical model was 0.810 (95% CI 0.788-0.831). The RF model was significantly superior to the other two models (p < 0.05). Furthermore, the calibration curve and Hosmer-Lemeshow test showed that the RF model had good classification performance (p = 0.556). CAC score, age, glucose, homocysteine, and neutrophil were the top five important variables in the RF model. CONCLUSION: RF model was superior to the traditional models in the prediction of obstructive CAD. In clinical practice, the RF model may improve risk stratification and optimize individual management.

Serum alkaline phosphatase levels are associated with coronary artery calcification patterns and plaque vulnerability.

OBJECTIVES: This study aimed to investigate the association of serum alkaline phosphatase (ALP) with calcification patterns and plaque morphology detected by intravascular ultrasound (IVUS) in acute coronary syndrome (ACS) patients. BACKGROUND: ALP has been shown to predict vascular calcification and long-term cardiovascular events. However, the relationship between ALP and vascular calcification patterns or plaque morphology remains unclear. METHODS: In total, 328 ACS patients who underwent IVUS examinations were screened from January 2017 to December 2018; among them, 234 eligible participants were grouped according to the tertiles of ALP levels (<68, 68-80, and >80 IU/L). Demographic data and IVUS parameters were documented and analyzed. RESULTS: After adjusting for potential confounders, independent associations were observed between ALP and the presence of coronary calcification, spotty calcification, minimum lumen area (MLA) ≤ 4.0 mm2 , and plaque burden (PB) > 70%. Compared with the lowest ALP tertile group, the highest ALP group had higher risks of calcification (odds ratio [OR], 2.85; 95% confidence interval [95%CI], 1.38-5.90; p = .005), spotty calcification (OR, 1.86; 95%CI, 1.09-3.84; p = .012), MLA≤4.0 mm2 (OR, 3.32; 95%CI, 1.51-7.28; p = .003), and PB > 70% (OR, 4.59; 95%CI, 1.83-11.50; p = .001). Similar results were found when ALP was analyzed as a continuous variable or a category variate according to the cut-off value determined by the receiver operating characteristic curve analysis. Furthermore, the model including clinical factors and ALP significantly improved the predictive power for coronary calcification, spotty calcification, MLA≤4.0 mm2 , and PB > 70%. CONCLUSION: Our findings suggest that ALP may be a potential predictive biomarker for calcification and plaque vulnerability.

Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.

BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after conventional therapy for patients with acute coronary syndrome (ACS). Timely identification of PR improves the risk stratification and prognosis of ACS patients. METHODS: A derivation cohort of 110 patients with ACS who underwent pre-intervention optical coherence tomography (OCT) were matched 1:1 to the PR and intact fibrous cap (IFC) groups according to traditional risk factors. Candidate PR proteins were identified via mass spectrometry (MS)-based proteomics using unbiased machine learning methods and were further validated by enzyme-linked immunosorbent assay (ELISA) in an external validation cohort of 85 patients with ACS. The performance of candidate biomakers was assessed using the receiver operating characteristic curve analysis. RESULTS: 1121 proteins were identified and 535 filtered proteins were used for analysis. Nine candidate proteins were screened by five machine learning algorithms. Three proteins (APOC3, RAB39A, and KNG1) were significantly different between the PR and IFC in validation cohort. The performance of plasm APOC3, RAB39A, and KNG1 for differentiating PR and IFC was superior to that of the conventional biomarkers and risk factors. CONCLUSION: The proteins (APOC3, RAB39A, and KNG1) serve as a potential novel diagnostic tool to identify PR in ACS patients.

Association of triglyceride glucose index levels ​​with calcification patterns and vulnerability of plaques: an intravascular ultrasound study.

PURPOSE: High triglyceride glucose (TyG) index level is one of the risks for cardiovascular events. The purpose of this research was to examine the correlation of the triglyceride glucose (TyG) index levels with plaque characteristics and calcification types determined by intravascular ultrasound (IVUS) in acute coronary syndrome (ACS) patients. METHODS: A total of 234 acute coronary syndromes (ACS) participants who completed intravascular ultrasound (IVUS) and coronary angiography (CAG) were finally enrolled. RESULTS: Logistic regression analysis manifested that the TyG index was independently correlated with the occurrence of coronary calcification, minimum lumen area (MLA) ≤ 4.0 mm², plaque burden (PB) > 70%, and spotty calcification. Taking the lowest group as a reference, the risk of coronary calcification (OR, 2.57; 95%CI, 1.04-6.35; p = 0.040), MLA ≤ 4.0 mm² (OR, 7.32; 95%CI, 2.67-20.01; p < 0.001), PB > 70% (OR, 2.68; 95%CI, 1.04-6.91; p = 0.041), and spotty calcification (OR, 1.48; 95%CI, 0.59-3.71; p = 0.407) was higher in the highest TyG index group. TyG index was converted into a dichotomous variable or a continuous variable for analysis, and we found that a similar result was observed. In addition, optimal predictive models consisting of clinical variables and the TyG index distinctly improved the ability to predict the prevalence of coronary calcification and MLA ≤ 4.0 mm² (p < 0.05). CONCLUSION: The TyG index may serve as a potential predictor for calcification patterns and plaque vulnerability.

Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance.

BACKGROUND: This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function. METHODS: The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson's correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of -0.037 (limits of agreement: -0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78). CONCLUSIONS: This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis.

The Predictive Value of Lp(a) for Adverse Cardiovascular Event in ACS Patients With an Achieved LDL-C Target at Follow Up After PCI.

Low-density lipoprotein cholesterol (LDL-C) is a traditional and important risk factor for atherosclerotic cardiovascular disease (CVD). Recently, lipoprotein (a) (lp(a)) attracts considerable attention as a residual risk factor for CVD. However, the roles of lp(a) in acute coronary syndrome (ACS) patients with well-controlled LDL-C (≤1.8mmol/L) after percutaneous coronary intervention (PCI) remain unclear. Current study results demonstrated that occurrence of major adverse cardiovascular events (MACE) and recurrent myocardial infarction (MI) increased with the Lp(a) increasing in patients with LDL-C≤1.8mmol/L at 1-month follow-up. In relatively low-risk patients presented with ACS and underwent PCI (LDL-C ≤1.8mmol/L at 1-month follow-up), lp(a) is still independently related to adverse prognosis. Further researches of targeted therapy against lp(a) are warranted.

The protective effect of Na+/Ca2+ exchange blocker kb-r7943 on myocardial ischemia-reperfusion injury in hypercholesterolemic rat.

KB-R7943 reduces lethal reperfusion injury under normal conditions, but its effectiveness under certain pathological states is in dispute. In the present study, we sought to determine the effect of KB-R7943 in hyperlipidemic animals and assess if the K ATP (+) are involved in the protective mechanisms. In group 1 (G1), isolated rat hearts underwent 25 min global ischemia (GI) and 120 min reperfusion (R). In group 2 (G2), G1 was repeated but the animals were subjected to a 1.5 % cholesterol-enriched diet during 6 weeks (hypercholesterolemic animals). In group 3 (G3), G2 was repeated but 1 µM KB-R7943 was added to the perfusate for 10 min from the start of reperfusion. In group 4 (G4), G3 was repeated, and glibenclamide (K ATP (+) , blocker, 0.3 µM) was administered. The infarct size was measured by triphenyltetrazolium. The infarct size was 35 ± 5.0 % in G1 and 46 ± 8.7 % in G2 (P < 0.05); KB-R7943 reduced the infarct size (28.6 ± 3.3 % in G3 vs. G2, P < 0.05). In addition, KB-R7943 attenuated apoptotic cell (G3 vs. G2, P < 0.05), but glibenclamide abolished the effect reached by KB-R7943. Thus, diet-induced hypercholesterolemia enhances myocardial injury; KB-R7943 reduces infarct size and apoptosis in hyperlipidemic animals through the activation of K(+)ATP channels.

Protective effect of Na(+)/Ca (2+) exchange blocker KB-R7943 on myocardial ischemia-reperfusion injury in hypercholesterolemic rats.

Reverse-mode activation of the Na(+)/Ca(2+) exchanger (NCX) during reperfusion following ischemia contributes to Ca(2+) overload and cardiomyocyte injury. KB-R7943, a selective reverse-mode NCX inhibitor, reduces lethal reperfusion injury under non-ischemic conditions. However, the effectiveness of this compound under ischemic conditions is unclear. In the present study, we studied the effects of KB-R7943 in an animal model of hyperlipidemia. We further assessed whether the K ATP (+) channels are involved in potential protective mechanisms of KB-R7943. Twelve rats were fed normal chow, while 48 animals were fed a high cholesterol diet. The hearts from the control and hypercholesterolemic rats were subjected to 25 min of global ischemia followed by a 120-min reperfusion. Before this, hearts from hypercholesterolemic rats either received no intervention (cholesterol control group) or were pre-treated with 1 µM KB-R7943 and 0.3 µM of K ATP (+) blocker glibenclamide or glibenclamide alone. The infarction sizes (triphenyltetrazolium assay) were 35 ± 5.0 % in the control group, 46 ± 8.7 % in the cholesterol control group (p < 0.05 vs. control group), 28.6 ± 3.3 % in the KB-R7943 group (p < 0.05 vs. cholesterol control group), 44 ± 5 % in the KB-R7943 and glibenclamide group, and 47 ± 8.5 % in the glibenclamide group (p < 0.05 vs. control group). Further, KB-R7943 attenuated the magnitude of cell apoptosis (p < 0.05 vs. cholesterol control group). These beneficial effects were abolished by glibenclamide. In conclusion, diet-induced hypercholesterolemia enhances myocardial injury. Selective reverse-mode NCX inhibitor KB-R7943 reduces the infarction size and apoptosis in hyperlipidemic animals through the activation of K ATP (+) channels.

Comparative antiapoptotic effects of KB-R7943 and ischemic postconditioning during myocardial ischemia reperfusion.

We examined whether KB-R7943 reduced infarct size by attenuating apoptosis during reperfusion and also compared antiapoptotic effects of KB-R7943 and IPost. For this purpose, isolated rat hearts underwent 30-min global ischemia and 120-min reperfusion. Ischemic postconditioning (IPost) (n = 15; three cycles of 10-s reperfusion/10-s ischemia or three cycles of 30-s reperfusion/30-s ischemia) and KB-R7943 (n = 15; 1 µM KB-R at the onset of reperfusion or before ischemia) were compared with controls (n = 12; ischemia-reperfusion only). Myocardial injury was determined by TTC staining, TUNEL assay and caspase-3 activity. AKT and eNOS phosphorylation were measured by immunoblotting. We found that IPost (10 s), Pre KB-R, and Reperf KB-R reduced infarct size (29 ± 4.1, 35 ± 5.0, 28.6 ± 3.4 %, respectively, vs. controls 46 ± 8.7 %; P < 0.05) and attenuated cell apoptosis (TUNEL-positive cardiomyocyte nuclei) in the myocardium (P < 0.01). Moreover, IPost (10 s), Pre KB-R and Reperf KB-R significantly decreased caspase-3 activation caused by myocardial ischemia-reperfusion. However, IPost (30 s) did not show any effect on necrosis and apoptosis. Akt, eNOS phosphorylation, at 30 min of reperfusion/IPost-10 s was significantly higher than other groups. In conclusion, KB-R7943 was as effective as IPost in reducing necrosis and inhibiting apoptosis and it might be an ideal pharmacological agent to provide a more amenable approach to cardioprotection.

Blood pressure levels in patients with subclinical thyroid dysfunction: a meta-analysis of cross-sectional data.

The relationship between subclinical thyroid dysfunction and blood pressure is controversial and has received insufficient attention. The aim of this study was to assess whether blood pressure levels in patients with subclinical thyroid dysfunction differ from those of euthyroid subjects. A meta-analysis of all cross-sectional studies was performed to compare the blood pressure levels in patients with subclinical thyroid dysfunction with those of healthy controls. A computer-based online retrieval of databases (MEDLINE and EMBASE) and manual searches were undertaken to identify articles that addressed the association between subclinical thyroid dysfunction and blood pressure levels and were published through 2010, using no language restrictions. The meta-analysis was performed using STATA 11 (Stata). Seven cross-sectional studies were examined. In patients with subclinical hypothyroidism, the pooled estimate of the weighted mean difference (WMD) of increased blood pressure revealed a significant difference in both systolic blood pressure (SBP; WMD with 95% confidence interval (CI) 1.89 mm Hg (0.98-2.80), P<0.05) and diastolic blood pressure (DBP; WMD with 95% CI 0.75 mm Hg (0.24-1.27), P<0.05). However, in patients with subclinical hyperthyroidism, the pooled estimate of the WMD of increased blood pressure revealed no significant difference in SBP (WMD with 95% CI -0.75 mm Hg (-1.81 to 0.31)) or DBP (WMD with 95% CI -0.64 mm Hg (-2.36 to 1.08)). The present meta-analysis indicates that subclinical hypothyroidism is associated with increased SBP and DBP, whereas subclinical hyperthyroidism is not. Further investigation is needed to confirm blood pressure levels in patients with subclinical thyroid dysfunction.