The relationship between triglyceride-glucose index and prospective key clinical outcomes in patients hospitalised for coronary artery disease.

BACKGROUND: The triglyceride-glucose (TyG) index is regarded as a dependable alternative for assessing insulin resistance (IR), given its simplicity, cost-effectiveness, and strong correlation with IR. The relationship between the TyG index and adverse outcomes in patients with coronary heart disease (CHD) is not well established. This study examines the association of the TyG index with long-term adverse outcomes in hospitalized CHD patients. METHODS: In this single-center prospective cohort study, 3321 patients hospitalized with CHD were included. Multivariate Cox regression models were employed to assess the associations between the TyG index and the incidence of all-cause mortality and major adverse cardiovascular events (MACEs). To examine potential nonlinear associations, restricted cubic splines and threshold analysis were utilized. RESULTS: During a follow-up period of 9.4 years, 759 patients (22.9%) succumbed to mortality, while 1291 (38.9%) experienced MACEs. Threshold analysis demonstrated a significant "U"-shaped nonlinear relationship with MACEs, with different hazard ratios observed below and above a TyG index of 8.62 (below: HR 0.71, 95% CI 0.50-0.99; above: HR 1.28, 95% CI 1.10-1.48). Notably, an increased risk of all-cause mortality was observed only when the TyG index exceeded 8.77 (HR 1.53, 95% CI 1.19-1.96). CONCLUSIONS: This study reveals a nonlinear association between the TyG index and both all-cause mortality and MACEs in hospitalized CHD patients with CHD. Assessing the TyG index, particularly focusing on individuals with extremely low or high TyG index values, may enhance risk stratification for adverse outcomes in this patient population.

Global trans-lesional computed tomography-derived fractional flow reserve gradient is associated with clinical outcomes in diabetic patients with non-obstructive coronary artery disease.

BACKGROUND: Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (CT-FFR) enables physiological assessment and risk stratification, which is of significance in diabetic patients with nonobstructive coronary artery disease (CAD). We aim to evaluate prognostic value of the global trans-lesional CT-FFR gradient (GΔCT-FFR), a novel metric, in patients with diabetes without flow-limiting stenosis. METHODS: Patients with diabetes suspected of having CAD were prospectively enrolled. GΔCT-FFR was calculated as the sum of trans-lesional CT-FFR gradient in all epicardial vessels greater than 2 mm. Patients were stratified into low-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR < 0.20), high-gradient without flow-limiting group (CT-FFR > 0.75 and GΔCT-FFR ≥ 0.20), and flow-limiting group (CT-FFR ≤ 0.75). Discriminant ability for major adverse cardiovascular events (MACE) prediction was compared among 4 models [model 1: Framingham risk score; model 2: model 1 + Leiden score; model 3: model 2 + high-risk plaques (HRP); model 4: model 3 + GΔCT-FFR] to determine incremental prognostic value of GΔCT-FFR. RESULTS: Of 1215 patients (60.1 ± 10.3 years, 53.7% male), 11.3% suffered from MACE after a median follow-up of 57.3 months. GΔCT-FFR (HR: 2.88, 95% CI 1.76-4.70, P < 0.001) remained independent risk factors of MACE in multivariable analysis. Compared with the low-gradient without flow-limiting group, the high-gradient without flow-limiting group (HR: 2.86, 95% CI 1.75-4.68, P < 0.001) was associated with higher risk of MACE. Among the 4 risk models, model 4, which included GΔCT-FFR, showed the highest C-statistics (C-statistics: 0.75, P = 0.002) as well as a significant net reclassification improvement (NRI) beyond model 3 (NRI: 0.605, P < 0.001). CONCLUSIONS: In diabetic patients with non-obstructive CAD, GΔCT-FFR was associated with clinical outcomes at 5 year follow-up, which illuminates a novel and feasible approach to improved risk stratification for a global hemodynamic assessment of coronary artery in diabetic patients.

Incremental diagnostic value of perivascular fat attenuation index for identifying hemodynamically significant ischemia with severe calcification.

PURPOSE: To explore the incremental value of perivascular fat attenuation index (FAI) to identify hemodynamically significant ischemia in severe calcified vessels. METHODS: Patients who underwent coronary computed tomographic angiography (CCTA) examination at Chinese PLA General Hospital from 2017 to 2020 and subsequently underwent fractional flow reserve (FFR) examination within 1 month were consecutively included. Several CCTA-derived indices were measured, including the coronary artery calcification score (CACS), lesion length, ≥CAD-RADS 4 proportion, perivascular FAI and CT-FFR. The included vessels were divided into a nonsevere calcification group and a severe calcification group according to the quartile of CACS. FFR ≤ 0.80 represents the presence of hemodynamically significant ischemia. RESULTS: A total of 124 patients with 152 vessels were included (age: 61.1 ± 9.2 years; male 64.5%). Significant differences in lesion length (28.4 ± 14.2 vs. 23.1 ± 12.3 mm, P = 0.021), perivascular FAI (-73.0 ± 7.5 vs. -79.0 ± 7.4 HU, P < 0.001) and CT-FFR (0.78 ± 0.06 vs. 0.86 ± 0.04, P < 0.001) were noted between the FFR ≤ 0.80 group (47 vessels) and the FFR > 0.80 group (105 vessels). Furthermore, the perivascular FAI in the FFR ≤ 0.80 group was significantly greater than that in the FFR > 0.80 group (nonsevere calcification: -73.2 ± 7.5 vs. -78.2 ± 7.4 HU, P = 0.002; severe calcification: -72.8 ± 7.7 vs. -82.7 ± 6.3 HU, P < 0.001). In discriminating hemodynamically significant ischemia, the specificity and accuracy of CT-FFR were significantly affected by severe calcification, which demonstrated a significantly declining trend (P = 0.033 and P = 0.010, respectively). The diagnostic performance of CT-FFR in the severe calcification group was lower than that in the nonsevere calcified group. However, perivascular FAI showed good discriminative performance in the severe calcification group. In combination with perivascular FAI, the predictive value of CT-FFR in identifying hemodynamically significant ischemia with severe calcification increased from an AUC of 0.740 to 0.919. CONCLUSION: For coronary artery with severe calcification, the diagnostic performance of CT-FFR in discriminating flow-limiting lesions could be greatly impaired. Perivascular FAI represents a potential reliable imaging marker to provide incremental diagnostic value over CT-FFR for identifying hemodynamically significant ischemia with severe calcification.

Validation of hemodynamic stress calculation in coronary computed tomography angiography versus intravascular ultrasound.

Background: Development in computational fluid dynamics and 3D construction could facilitate the calculation of hemodynamic stresses in coronary computed tomography angiography (CCTA). However, the agreement between CCTA derived stresses and intravascular ultrasound/intravascular coronary angiography (IVUS/ICA)-derived stresses remains undetermined. Thus, the purpose of this study is to investigate if CCTA can serve as alternative to IVUS/ICA for hemodynamic evaluation. Methods: In this retrospective study, 13 patients (14 arteries) with unstable angina who underwent both CCTA and IVUS/ICA at an interval of less than 7 days were consecutively included at the Chinese PLA General Hospital within the year of 2021. Slice-level minimal lumen area (MLA), percent area stenosis, velocity, pressure, Reynolds number, wall shear stress (WSS) and axial plaque stress (APS) were determined by both modalities. The agreement between CCTA and IVUS/ICA was assessed using the intraclass correlation coefficient (ICC), Pearson's correlation coefficient and Bland-Altman analysis. Results: CCTA overestimated the degree of area stenosis (50.22%±16.15% vs. 36.41%±19.37%, P=0.004) with the MLA showing no significant difference (5.81±2.24 vs. 6.72±2.04 mm2, P=0.126). No statistical difference was observed in WSS (6.57±6.26 vs. 5.98±5.55 Pa, P=0.420) and APS (16.03±1,159.45 vs. -1.27±890.39 Pa, P=0.691) between CCTA and IVUS. Good correlation was found in velocity (ICC: 0.796, 95% CI: 0.752-0.833), Reynolds number (ICC: 0.810, 95% CI: 0.768-0.844) and WSS (ICC: 0.769, 95% CI: 0.718-0.810), while the ICC of APS was (ICC: 0.341, 95% CI: 0.197-0.458), indicating a relatively poor correlation. Conclusions: CCTA can serve as a satisfactory alternative to the reference standard, IVUS/ICA in morphology simulation and hemodynamic stress calculation, especially in the calculation of WSS.

Machine Learning Model-Based Simple Clinical Information to Predict Decreased Left Atrial Appendage Flow Velocity.

Background: Transesophageal echocardiography (TEE) is the first technique of choice for evaluating the left atrial appendage flow velocity (LAAV) in clinical practice, which may cause some complications. Therefore, clinicians require a simple applicable method to screen patients with decreased LAAV. Therefore, we investigated the feasibility and accuracy of a machine learning (ML) model to predict LAAV. Method: The analysis included patients with atrial fibrillation who visited the general hospital of PLA and underwent transesophageal echocardiography (TEE) between January 2017 and December 2020. Three machine learning algorithms were used to predict LAAV. The area under the receiver operating characteristic curve (AUC) was measured to evaluate diagnostic accuracy. Results: Of the 1039 subjects, 125 patients (12%) were determined as having decreased LAAV (LAAV < 25 cm/s). Patients with decreased LAAV were fatter and showed a higher prevalence of persistent AF, heart failure, hypertension, diabetes and stroke, and the decreased LAAV group had a larger left atrium diameter and a higher serum level of NT-pro BNP than the control group (p < 0.05). Three machine-learning models (SVM model, RF model, and KNN model) were developed to predict LAAV. In the test data, the RF model performs best (R = 0.608, AUC = 0.89) among the three models. A fivefold cross-validation scheme further verified the predictive ability of the RF model. In the RF model, NT-proBNP was the factor with the strongest impact. Conclusions: A machine learning model (Random Forest model)-based simple clinical information showed good performance in predicting LAAV. The tool for the screening of decreased LAAV patients may be very helpful in the risk classification of patients with a high risk of LAA thrombosis.

CT-Based Leiden Score Outperforms Confirm Score in Predicting Major Adverse Cardiovascular Events for Diabetic Patients with Suspected Coronary Artery Disease.

OBJECTIVE: Evidence supports the efficacy of coronary computed tomography angiography (CCTA)-based risk scores in cardiovascular risk stratification of patients with suspected coronary artery disease (CAD). We aimed to compare two CCTA-based risk score algorithms, Leiden and Confirm scores, in patients with diabetes mellitus (DM) and suspected CAD. MATERIALS AND METHODS: This single-center prospective cohort study consecutively included 1241 DM patients (54.1% male, 60.2 ± 10.4 years) referred for CCTA for suspected CAD in 2015-2017. Leiden and Confirm scores were calculated and stratified as < 5 (reference), 5-20, and > 20 for Leiden and < 14.3 (reference), 14.3-19.5, and > 19.5 for Confirm. Major adverse cardiovascular events (MACE) were defined as the composite outcomes of cardiovascular death, nonfatal myocardial infarction (MI), stroke, and unstable angina requiring hospitalization. The Cox model and Kaplan-Meier method were used to evaluate the effect size of the risk scores on MACE. The area under the curve (AUC) at the median follow-up time was also compared between score algorithms. RESULTS: During a median follow-up of 31 months (interquartile range, 27.6-37.3 months), 131 of MACE were recorded, including 17 cardiovascular deaths, 28 nonfatal MIs, 64 unstable anginas requiring hospitalization, and 22 strokes. An incremental incidence of MACE was observed in both Leiden and Confirm scores, with an increase in the scores (log-rank p < 0.001). In the multivariable analysis, compared with Leiden score < 5, the hazard ratios for Leiden scores of 5-20 and > 20 were 2.37 (95% confidence interval [CI]: 1.53-3.69; p < 0.001) and 4.39 (95% CI: 2.40-8.01; p < 0.001), respectively, while the Confirm score did not demonstrate a statistically significant association with the risk of MACE. The Leiden score showed a greater AUC of 0.840 compared to 0.777 for the Confirm score (p < 0.001). CONCLUSION: CCTA-based risk score algorithms could be used as reliable cardiovascular risk predictors in patients with DM and suspected CAD, among which the Leiden score outperformed the Confirm score in predicting MACE.

Impact of atherosclerotic extent on clinical outcome for diabetic patients with non-obstructive coronary artery disease.

Background and aims: The prognostic impact of non-obstructive coronary artery disease (CAD) has long been underestimated due to its mild stenosis (<50% stenosis). We aim to investigate the prognostic value of atherosclerotic extent in DM patients with non-obstructive CAD. Methods: The analysis was based on a single center cohort of DM patients referred for coronary computed tomography angiography (CCTA) due to suspect CAD in 2015-2017. Based on coronary stenosis combined with segment involvement score (SIS), the study population were divided into four groups: normal (0% stenosis), non-obstructive SIS<3, non-obstructive SIS≥3 and obstructive (≥50% stenosis). The intra-class correlation (ICC) was used to test the inter-and intra-reviewer agreement. Multivariate Cox model and Kaplan-Meier method were used to evaluate the effect size of atherosclerotic extent on the prognosis. Results: In total, 1241 patients (age 60.2 ± 10.4 years, 54.1% male) were included, of which 50.2% were non-obstructive. During a median follow-up of 2.6 years, 131 MACEs (10.6%) were adjudicated, including 17 cardiovascular deaths, 28 non-fatal myocardial infarctions, 64 unstable anginas requiring hospitalization and 22 strokes. Incremental event rates could be observed across the four groups. After adjustment for age, gender, hyperlipidemia and presence of high-risk plaque, Hazard Ratio (HR) for non-obstructive SIS<3, non-obstructive SIS≥3 and the obstructive group was 1.84 (95%CI: 0.70-4.79), 3.71 (95%CI: 1.37-10.00) and 5.46 (95%CI: 2.18-13.69), respectively. Compared with non-obstructive SIS<3, non-obstructive SIS≥3 showed a significantly higher risk (HR:2.02 95%CI:1.11-3.68, p = 0.021). Similar results were demonstrated when Leiden risk score was used for sensitivity analysis. Conclusion: In DM patients with non-obstructive CAD, atherosclerotic extent was associated with higher risk of major adverse cardiac events at long-term follow-up. Efforts should be made to determine risk stratification for the management of DM patients with non-obstructive CAD.

Prognostic Value of Atherosclerotic Extent in Diabetic Patients with Nonobstructive Coronary Artery Disease.

METHODS AND RESULTS: 813 DM patients (mean age 58.9 ± 9.9 years, 48.1% male) referred for CCTA due to suspected CAD in 2015-2017 were consecutively included. During a median follow-up of 31.77 months, 50 major adverse cardiovascular events (MACEs) (6.15%) were experienced, including 2 cardiovascular deaths, 14 nonfatal myocardial infarctions, 27 unstable anginas requiring hospitalization, and 7 strokes. Three groups were defined based on coronary stenosis combined with Leiden score as normal, nonobstructive Leiden < 5, and nonobstructive Leiden ≥ 5. Cox models were used to assess the prognosis of plaque burden within these groups. An incremental incidence of MACE rates was observed. After adjustment for age, gender, and presence of high-risk plaque, the group of Leiden ≥ 5 showed a higher risk than Leiden < 5 (HR: 1.88, 95% CI: 1.03-3.42, p = 0.039). Similar results were observed when segment involvement score (SIS) was used for sensitivity analysis. CONCLUSION: Atherosclerotic extent was associated with the prognosis of DM patients with nonobstructive coronary artery disease, highlighting the importance of better risk stratification and management.

Lipoprotein(a) is associated with coronary atheroma progression: analysis from a serial coronary computed tomography angiography study.

BACKGROUND: Lipoprotein(a) [Lp(a)] has been closely related to coronary atherosclerosis and might affect perivascular inflammation due to its proinflammatory properties. However, there are limited data about Lp(a) and related perivascular inflammation on coronary atheroma progression. Therefore, this study aimed to investigate the associations between Lp(a) and the perivascular fat attenuation index (FAI) with coronary atheroma progression detected by coronary computed tomography angiography (CCTA). METHODS: Patients who underwent serial CCTA examinations without a history of revascularization and with available data for Lp(a) within one month before or after baseline and follow-up CCTA imaging scans were considered to be included. CCTA quantitative analyses were performed to obtain the total plaque volume (TPV) and the perivascular FAI. Coronary plaque progression (PP) was defined as a ≥ 10% increase in the change of the TPV at the patient level or the presence of new-onset coronary atheroma lesions. The associations between Lp(a) or the perivascular FAI with PP were examined by multivariate logistic regression. RESULTS: A total of 116 patients were ultimately enrolled in the present study with a mean CCTA interscan interval of 30.80 ± 13.50 months. Among the 116 patients (mean age: 53.49 ± 10.21 years, males: 83.6%), 32 patients presented PP during the follow-up interval. Lp(a) levels were significantly higher among PP patients than those among non-PP patients at both baseline [15.80 (9.09-33.60) mg/dLvs. 10.50 (4.75-19.71) mg/dL,P = 0.029] and follow-up [20.60 (10.45-34.55) mg/dLvs. 8.77 (5.00-18.78) mg/dL,P = 0.004]. However, there were no differences in the perivascular FAI between PP group and non-PP group at either baseline or follow-up. Multivariate logistic regression analysis showed that elevated baseline Lp(a) level (OR = 1.031, 95% CI: 1.005-1.058,P = 0.019) was an independent risk factor for PP after adjustment for other conventional variables. CONCLUSIONS: Lp(a) was independently associated with coronary atheroma progression beyond low-density lipoprotein cholesterol and other conventional risk factors. Further studies are warranted to identify the inflammation effect exhibited as the perivascular FAI on coronary atheroma progression.