Investigation of the Relationship Between Triglycerides-Glucose İndex and Coronary Slow Flow: A Retrospective Case-Control Study

Comparison of TyG and modified TyG indices in predicting coronary slow flow phenomenon

BACKGROUND

The coronary slow flow phenomenon (CSFP) represents a common condition in patients with ischemia and non-obstructive coronary artery disease (INOCA). The triglyceride-glucose index (TyG) and relative modified indices have been established to be associated with CSFP. However, comparison of the clinical value of TyG and its modified indices in predicting CSFP has not been evaluated.

MATERIALS AND METHODS

INOCA patients were retrospectively enrolled. According to the corrected TIMI counts, the patients were divided into the CSFP group and the non-CSFP group. A total of 4,627 patients were enrolled in our study. Among them, 69 patients were divided into the CSFP group, while 586 patients were divided into the non-CSFP group. Demographic, clinical risk factors, and laboratory results, including TyG and its modified indices, were compared between the two groups. The prognostic value of TyG and its modified indices in CSFP was compared using the area under the curve (AUC).

RESULTS

Most of the demographic and clinical risk factors between CSFP patients and non-CSFP patients were comparable. For patients with CSFP, the patients were more likely to have chronic kidney disease (CKD) (39.13% vs. 20.31%, p < 0.001) and less likely to have anti-diabetic therapy (14.49% vs. 27.13%, p = 0.023). The patients with CSFP also had higher body weight index (BMI) (p < 0.001), higher levels of uric acid (UA), triglyceride (TG) (p = 0.017), total cholesterol (TC) (p = 0.016) and low-density lipoprotein cholesterol (LDL-C) (p = 0.006), homocysteine (p < 0.001) and uric acid (p < 0.002). Both TyG and its modified indices, including TyG-WC, TyG-BMI were demonstrated to be independently associated with CSFP in multi-variable logistic analysis after adjusting other co-variables.Further receiver operating characteristic (ROC) curve demonstrated that TyG-WC showed the best performance in predicting CSFP compared with other indices. Subgroup analysis revealed that the predictive value of TyG-WC in CSFP was consistent in different subgroups except that the predictive value was better in male patients compared with female patients, CONCLUSIONS: Our investigation reveals that TyG, TyG-WC and TyG-BMI were independent risk factors for CSFP. TyG-WC showed a better predictive performance than other indices in predicting CSFP.

Correlation between admission blood glucose, fibrinogen, and slow blood flow during primary PCI for acute ST segment elevation myocardial infarction

Backgroud

Coronary slow flow (CSF) is a common phenomenon of coronary microcirculation dysfunction, and is closely related to elevated blood glucose and fibrinogen (FIB) levels. However, whether immediate blood glucose and FIB levels affect coronary blood flow during primary percutaneous coronary intervention (PCI) remains unclear.

Objective

To explore the correlation between admission blood glucose (ABG), fibrinogen (FIB) and slow blood flow during primary PCI for acute ST segment elevation myocardial infarction (STEMI).

Methods

A total of 497 patients who underwent coronary angiography in the cardiology department of the 904th Hospital of the Joint Logistics Support Force from December 2018 to December 2022 due to STEMI were selected consecutively, and then were divided into two groups based on whether slow blood flow occurred during primary PCI: slow blood flow group (n = 117) and control group (n = 380). Detecting the ABG, FIB and other indicators of patients in each group, and using logistic regression analysis and receiver operating characteristic (ROC) curve to analyze independent risk factors for slow blood flow during primary PCI, and further evaluating the prognosis of patients.

Results

The levels of ABG and FIB in patients with slow blood flow were significantly higher than those in the control group (P < 0.05). The results of multivariate logistic regression analysis suggested that FIB and ABG were independent risk factors for slow blood flow during primary PCI (both P < 0.05). ROC curve analysis showed that ABG, FIB, and their combination all had predictive value for slow blood flow during primary PCI (all P < 0.05), and the area under the curve (AUC) of the combined indicator was higher than that of any single indicator, with statistical significance (P < 0.05). KM curve analysis suggested that the prognosis of patients in slow blood flow group were poor.

Conclusion

Both elevated ABG and FIB could predict slow blood flow during primary PCI, and the diagnostic value of the combined indicator was superior to that of any single indicator, which could be used for the evaluation of slow blood flow during primary PCI, so as to evaluate the prognosis of patients with STEMI.

Triglyceride-glucose index correlates with the occurrence and prognosis of acute myocardial infarction complicated by cardiogenic shock: data from two large cohorts

BACKGROUND

Triglyceride-glucose (TyG) index, a dependable indicator of insulin resistance, has been identified as a valid marker regarding multiple cardiovascular diseases. Nevertheless, the correlation of TyG index with acute myocardial infarction complicated by cardiogenic shock (AMICS) remains uncertain. Our study aims for elucidating this relationship by comprehensively analyzing two large-scale cohorts.

METHODS

Utilizing records from the eICU Collaborative Research Database and the Medical Information Mart for Intensive Care IV, the link between TyG and the incidence and prognosis of AMICS was assessed multicentrally and retrospectively by logistic and correlation models, as well as restricted cubic spline (RCS). Propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and overlap weighting (OW) were employed to balance the potential confounders. Subgroup analyses were performed according to potential modifiers.

RESULTS

Overall, 5208 AMI patients, consisting of 375 developing CS were finally included. The TyG index exhibited an apparently higher level in AMI populations developing CS than in those who did not experienced CS [9.2 (8.8-9.7) vs. 9.0 (8.5-9.5)], with a moderate discrimination ability to recognize AMICS from the general AMI (AUC: 0.604). Logistic analyses showed that the TyG index was significantly correlated with in-hospital and ICU mortality. RCS analysis demonstrated a linear link between elevated TyG and increased risks regarding in-hospital and ICU mortality in the AMICS population. An increased mortality risk remains evident in PSM-, OW- and IPTW-adjusted populations with higher TyG index who have undergone CS. Correlation analyses demonstrated an apparent link between TyG index and APS score. Subgroup analyses presented a stable link between elevated TyG and mortality particularly in older age, females, those who are overweight or hypertensive, as well as those without diabetes.

CONCLUSIONS

Elevated TyG index was related to the incidence of CS following AMI and higher mortality risks in the population with AMICS. Our findings pointed a previously undisclosed role of TyG index in regard to AMICS that still requires further validation.

Triglyceride-Glucose Index as a Predictor of Major Adverse Cardiovascular Events in Post-PCI Patients Diagnosed with In-Stent Restenosis

Background

The triglyceride-glucose index (TyG) is a reliable indicator for predicting the prognosis of patients with coronary heart disease (CAD) after percutaneous coronary intervention (PCI). However, its influence on patients with in-stent restenosis (ISR) is unclear. This study was designed to evaluate the association between the TyG index and the occurrence of major adverse cardiovascular events (MACEs) after PCI in patients with ISR.

Methods

This retrospective study included 1654 patients who underwent PCI between 2016 and 2022 at Nanjing First Hospital. Patients were stratified into three groups based on the quantile level of the TyG index. The TyG index was determined as Ln (triglycerides [mg/dL] × fasting plasma glucose [mg/dL]/2).

Results

Individuals with the highest TyG index showed an increased risk of MACEs compared to those with the lowest level of the TyG index (HR 1.60; 95% CI 1.11-2.30; P = 0.01). When analyzing the TyG index as a continuous variable, each standard deviation increase was associated with an HR of 1.51 (95% CI: 1.11-2.05; P = 0.01). For the male subgroup and the diabetes subgroup, this trend was even more pronounced (HR 1.269; 95% CI 1.055-1.527; P = 0.011; HR 1.385; 95% CI 1.125-1.706; P = 0.002). Additionally, the landmark analysis showed that patients with the highest level of TyG had an increased risk of MACEs 6 months after the PCI (P = 0.019).

Conclusion

Elevated TyG index is associated with increased risk of adverse cardiovascular events in patients with ISR, and the extent of increase in the risk is more significant in male patients with diabetes.

Comparison of the Effect of Non-HDL-C/HDL-C Ratio on Coronary Slow Flow with Other Non-Traditional Lipid Markers

Background

Coronary slow flow (CSF) is a microvascular disease characterized by delayed opacification of the epicardial coronary arteries during angiography. The main pathogenesis of CSF is endothelial dysfunction caused by diffuse atherosclerosis. Dyslipidemia is one of the primary factors raising the risk of atherosclerosis. Compared to conventional lipid profiles, non-traditional lipid profiles more accurately reflect dyslipidemic status. In this work, we compared the non-high density lipoprotein-cholesterol (HDL-C)/HDL-C ratio (NHHR) with other conventional and non-conventional lipid profiles in order to determine its impact on CSF.

Methods

A total of 9112 subjects who underwent coronary angiography were screened retrospectively, of whom 130 subjects with CSF and 130 subjects with normal CF were included. Multivariate regression analysis was used to identify independent predictors of CSF. Additionally, in order to predict CSF, the diagnostic accuracies of NHHR and other non-traditional lipid profiles were examined.

Results

There were significantly higher non-traditional lipid profiles in the CSF group (all p < 0.001). Compared to other non-traditional lipid profiles, NHHR had a stronger association with thrombolysis in myocardial infarction frame count (r = 0.3593, p < 0.0001). In addition to NHHR, non-HDL-C, Castelli's risk index-II, atherogenic index of plasma, plasma glucose, dyslipidemia, smoking, and body mass index were identified as independent predictors of CSF. The ability of NHHR to detect CSF was superior to other non-traditional lipid profiles (area under the curve: 0.785; confidence interval: 0.730-0.840; p < 0.001).

Conclusions

NHHR was found to be a potent and reliable predictor of CSF. This indicates that NHHR can be used as a reliable biomarker for risk stratification of CSF.

Predictive value of triglyceride glucose index combined with neutrophil-to-lymphocyte ratio for major adverse cardiac events after PCI for acute ST-segment elevation myocardial infarction

Acute ST-segment elevation myocardial infarction (STEMI) is a severe cardiovascular disease that poses a significant threat to the life and health of patients. This study aimed to investigate the predictive value of triglyceride glucose index (TyG) combined with neutrophil-to-lymphocyte ratio (NLR) for in-hospital cardiac adverse event (MACE) after PCI in STEMI patients. From October 2019 to June 2023, 398 STEMI patients underwent emergency PCI in the Second People's Hospital of Hefei. Stepwise regression backward method and multivariate logistic regression analysis were used to screen the independent risk factors of MACE in STEMI patients. To construct the prediction model of in-hospital MACE after PCI in STEMI patients: Grace score model is the old model (model A); TyG combined with NLR model (model B); Grace score combined with TyG and NLR model is the new model (model C). We assessed the clinical usefulness of the predictive model by comparing Integrated Discrimination Improvement (IDI), Net Reclassification Index (NRI), Receiver Operating Characteristic Curve (ROC), and Decision Curve Analysis (DCA). Stepwise regression and multivariate logistic regression analysis showed that TyG and NLR were independent risk factors for in-hospital MACE after PCI in STEMI patients. The constructed Model C was compared to Model A. Results showed NRI 0.5973; NRI + 0.3036, NRI - 0.2937, IDI 0.3583. These results show that the newly developed model C predicts the results better than model A, indicating that the model is more accurate. The ROC analysis results showed that the AUC of Model A for predicting MACE in STEMI was 0.749. Model B predicted MACE in STEMI with an AUC of 0.685. Model C predicted MACE in STEMI with an AUC of 0.839. For DCA, Model C has a better net return between threshold probability 0.1 and 0.78, which is better than Model A and Model B. In this study, by combining TyG, NLR, and Grace score, it was shown that TyG combined with NLR could reasonably predict the occurrence of MACE after PCI in STEMI patients and the clinical utility of the prediction model.

Could Pan-Immune-Inflammation Value be a Marker for the Diagnosis of Coronary Slow Flow Phenomenon?

Inflammation plays a key role in the pathogenesis of the coronary slow flow phenomenon (CSFP). The newly developed inflammatory marker, pan-immune-inflammation value (PIV), is associated with adverse cardiovascular events. This study investigated the predictive value of PIV for diagnosing CSFP in comparison to other inflammation-based markers. A total of 214 patients, 109 in the CSFP group and 105 in the normal coronary flow (NCF) group, were retrospectively included in the study. Coronary flow was calculated using the Thrombolysis in Myocardial Infarction frame count method. In addition to PIV, other inflammatory markers such as neutrophil-lymphocyte ratio, platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) were calculated for the patients. The average age of patients was 50.3 ± 8.4, with a male ratio of 55.1%. Compared to the NCF group, patients in the CSFP group had higher levels of hyperlipidemia, glucose, triglyceride, NLR, PLR, SII, and PIV, while their high-density lipoprotein cholesterol (HDL-C), was lower (p < 0.05). Logistic regression analysis demonstrated that HDL-C, glucose, triglyceride, and PIV were independent predictor factors for CSFP (p < 0.05). PIV is a strong and independent predictor factor for CSFP and superior in predicting CSFP compared to other inflammatory markers.

Comparison of the effect of uric acid/albumin ratio on coronary slow flow with other inflammation-based markers

Background: Many inflammation-based markers (IBMs) have been shown to be closely related to coronary slow flow (CSF), but the effect of the uric acid/albumin ratio (UAR) on CSF and its relationship with other IBMs are not clearly known. In this study, we aimed to compare the effects of UAR and other IBMs on CSF. Methods: After the exclusion criteria, 126 patients with CSF detected on coronary angiography and 126 subjects with normal coronary flow as the control group were included in the study. Results: UAR was determined as an independent predictor for CSF. In addition, the UAR was superior to other IBMs in detecting CSF (p < 0.05 for all). Conclusion: This study is the first to investigate the effect of UAR on CSF in comparison with other IBMs.