The triglycerides-glucose index and the triglycerides to high-density lipoprotein cholesterol ratio are both effective predictors of in-hospital death in non-diabetic patients with AMI

Nonlinear relationship between blood urea nitrogen to albumin ratio and in-hospital mortality in non-diabetic patients with non-ST-segment elevation myocardial infarction

Background

The blood urea nitrogen (BUN) to albumin (ALB) ratio (BAR) is a novel biomarker that reflects both nutritional and inflammatory status and has been linked to the prognosis of various acute and chronic diseases. However, studies on its association with in-hospital prognosis in patients with non-ST-segment elevation myocardial infarction (NSTEMI) remain limited. Therefore, this study aimed to evaluate the relationship between BAR and in-hospital mortality in patients with NSTEMI.

Methods

This study included 772 non-diabetic NSTEMI patients. The predictive performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). Multivariable logistic regression was performed to identify the independent risk factors of in-hospital mortality. Subgroup analyses were conducted to evaluate the association between BAR and in-hospital mortality across different patient subgroups. Restricted cubic spline (RCS) function was applied to examine the nonlinear relationship between BAR and in-hospital mortality, and the two-piecewise logistic regression model was used for threshold effects analysis.

Results

A total of 40 patients died during hospitalization. BAR exhibited strong predictive performance for in-hospital mortality (AUC = 0.83; 95% CI: 0.77-0.89). Multivariate analysis indicated that BAR was an independent risk factor for in-hospital mortality (OR = 1.06; 95% CI: 1.01-1.12), with a significant increase in mortality risk observed in most subgroups as BAR increased. A nonlinear relationship with a saturation effect was observed between BAR and in-hospital mortality (P for non-linearity = 0.002), with an inflection point of 8.51. Further two-piecewise logistic regression analysis revealed that when BAR was <8.51, the risk of in-hospital mortality increased significantly (OR = 1.69, 95% CI: 1.16-2.53), whereas when BAR was ≥8.51, the association was not statistically significant (OR = 0.99, 95% CI: 0.92-1.06).

Conclusion

Baseline BAR serves as a simple, clinically useful prognostic biomarker of in-hospital mortality in non-diabetic NSTEMI patients. Additionally, we identified a nonlinear relationship with saturation effect between BAR and in-hospital mortality.

Triglyceride-glucose index and the risk of in-hospital and ICU all-cause mortality: a systematic review and meta-analysis of observational studies

Several studies have illustrated the association of the triglyceride glucose (TyG) index with in-hospital and intensive care unit (ICU) mortality. However, no studies have compiled this evidence and reached a conclusion. This study aimed to quantify the association of the TYG index with the risk of in-hospital and ICU mortality. An extensive search of databases including PubMed, Scopus, and Web of Science, was performed up to 21 Jan 2024. Nineteen studies were included in the meta-analysis. The outcomes were in-hospital mortality in 18 studies and ICU mortality in 8 studies. Among the 42,525 participants, 5233 in-hospital and 1754 ICU mortality cases were reported. The pooled analysis revealed that each unit increase in the TYG index was associated with a 33% and 45% increase in the risk of in-hospital (RR = 1.33; 95% CI: 1.23, 1.43; I squared = 90.3%) and ICU (RR: 1.45; 95% CI: 1.25, 1.67; I squared = 44.8%) mortality, respectively. Subgroup analysis revealed a stronger association between the TYG index and the risk of in-hospital mortality in patients with cardiovascular diseases than in those with cerebrovascular diseases (Pheterogeneity between Groups = 0.014). The findings of this study showed a positive association between the TyG index and the risk of in-hospital and ICU mortality. (PROSPERO registration ID: CRD420245414390).

Joint association of TyG index and LDL-C with all-cause and cardiovascular mortality among patients with cardio-renal-metabolic disease

Both triglyceride-glucose (TyG) index, as a surrogate marker of insulin resistance, and low-density lipoprotein cholesterol (LDL-C) are independent risk factors for long-term prognosis among patients with cardio-renal-metabolic (CRM) disease. However, the co-exposures of TyG index and LDL-C to mortality is unclear. The aim of this study is to investigate the joint effects and risk stratification of the TyG index and LDL-C on all-cause and cardiovascular mortality in CRM patients. We analyzed CRM patients from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), calculating TyG index as Ln[fasting triglyceride (mg/dL)×fasting glucose (mg/dL)/2] and using multivariable Cox regression models to assess the joint effects of TyG index and LDL-C on all-cause and cardiovascular mortality. The interaction between the TyG index and LDL-C to mortality was also evaluated. During a median follow-up of 7.6 years, 22.8% and 8.4% of patients died from all-cause and cardiovascular causes, respectively. Among patients with LDL-C < 2.6 mmol/L, no significant differences were observed in all-cause and cardiovascular mortality when comparing higher TyG index to the lowest tertile (T1). Specifically, the hazard ratio (HR) for all-cause mortality in the second (T2) and third tertiles (T3) were 0.81 (95% confidence interval(CI): 0.59-1.09) and 0.87 (95%CI: 0.62-1.22), respectively, with a P for trend of 0.468. For cardiovascular mortality, the HR for T2 and T3 compared to T1 were 0.80 (95%CI: 0.48-1.32) and 0.72 (95%CI: 0.45-1.15), respectively, with a P for trend of 0.173. However, elevated TyG index was related to markedly increased risk of all-cause and cardiovascular mortality in patients with LDL-C ≥ 2.6 mmol/L. Specifically, for all-cause mortality, HR for T2 and T3 compared to T1 were 1.01 (95%CI: 0.79-1.28) and 1.38 (95%CI: 1.07-1.79), respectively, with a P for trend of 0.009. For cardiovascular mortality, the HR was 1.09 (95% CI: 0.72-1.65) for T2 and 1.80 (95% CI: 1.18-2.75) for T3, with a P for trend of 0.005. Interactive analysis also demonstrated that a significant association of TyG index and LDL-C with the risk of all-cause (P for interaction = 0.011) and cardiovascular (P for interaction = 0.050) mortality was observed. The findings highlight that elevated TyG index can significantly increase the risk of all-cause and cardiovascular mortality only among CRM patients with LDL-C ≥ 2.6 mmol/L, but not among patients with LDL-C < 2.6 mmol/L.

Influence of sodium-glucose cotransporter 2 inhibitors on the triglyceride-glucose index in acute myocardial infarction patients with type 2 diabetes mellitus

Background

As a novel oral anti-hyperglycemic agent, sodium-glucose cotransporter 2 inhibitors (SGLT2-i) have been demonstrated to improve cardiovascular outcomes in acute myocardial infarction (AMI) patients with type 2 diabetes mellitus (T2DM). However, the mechanism responsible for the beneficial effects remains unclear. Recently, extensive studies have demonstrated a close relationship between elevated fasting triglyceride-glucose (TyG) index and the risk of AMI. Additionally, research has identified that SGLT2-i can reduce the TyG index in T2DM patients. However, it remains ambiguous whether the benefit of SGLT2-i in patients with AMI and T2DM is due to an improvement in the TyG index. Consequently, we aimed to assess the impact of SGLT2-i on the TyG index in AMI patients with T2DM.

Methods

A retrospective and cross-sectional study was conducted on 180 AMI patients with T2DM admitted to the chest pain center of the Second Affiliated Hospital of Anhui Medical University from January 2020 to January 2023. Based on the hypoglycemic regimens administered after admission, the patients were categorized into a control group (79 cases treated with sulfonylureas, α-glycosidase inhibitors, metformin, etc.) and a SGLT2-i group (101 cases administered with dapagliflozin or empagliflozin). Propensity score matching (PSM) was adopted to balance the baseline characteristics of patients and minimize selection bias to confirm the robustness of the results. After PSM, control group remained 32 patients, and SGLT2-i group remained 37 patients. All patients underwent regular follow-up after discharge, and comparisons were made between the two groups in terms of clinical indicators and major adverse cardiovascular events (MACEs) in 1 year. Univariate and Multivariate Cox regression analysis was performed to identify the predictors of MACE.

Results

Significant differences were observed between the two groups in terms of various parameters before PSM, included age, proportion of insulin use, Gensini score, serum creatinine (Cr), total cholesterol (TC), and cardiac troponin I (cTnI). After PSM, there were no statistically significant differences in baseline clinical indicators and laboratory tests. The median follow-up period was 11 months in both cohorts. The comparison of follow-up results between the two groups after matching confirmed statistically significant differences in triglyceride (TG) reduction index reduction, left ventricular end-diastolic diameter (LVDD) reduction, and white blood cell (WBC) reduction in the SGLT2-i group (all P<0.05). Additionally, a higher incidence of MACEs was observed in the control group (P=0.01). Univariate analysis showed that usage of SGLT2-i, Cr, low-density lipoprotein cholesterol (LDL-C), TyG index at baseline, and changes of TyG index (TyG at follow-up minus TyG at baseline) were associated with the risk of MACE. However, multivariate analysis showed only usage of SGLT2-i was associated with the risk of MACE [hazard ratio (HR) =0.077; 95% confidence interval (CI): 0.009-0.682; P=0.02].

Conclusions

In AMI patients with T2DM, the use of SGLT2-i was associated with a lower risk of MACE and an improvement of TyG index during 11 months follow-up. Our findings offer new insights into the cardio-protective mechanisms of SGLT2-i in the context of AMI.

The triglyceride-glucose index as an indicator of latent atherogenicity of the plasma lipid profile in healthy men with normolipidaemia

OBJECTIVES

The triglyceride-glucose (TyG) index is a novel diagnostic marker for various metabolic and cardiovascular diseases. However, little is known about the association of the TyG index with plasma atherogenicity, especially with its latent forms. The aim of this study was to assess the potential of the use of the TyG index as a marker of atherogenic risk.

METHODS

A total of 202 men with normolipidaemia, aged 20-60 years, were enrolled in this study. Fasting biochemical parameters were measured. The TyG index was calculated as ln[triglyceride(mg/dL)×glucose(mg/dL)]/2. The diagnostic ability of the TyG index for detecting atherogenic risk was tested by receiver operating characteristic (ROC) curve analysis.

RESULTS

A substantial portion of normolipidaemic men had deviations from the reference values for the indices calculated using apolipoproteins. Unfavorable values for the apolipoprotein (apo) B/apoA-I ratio, low-density lipoprotein cholesterol/apoB (LDL-C/apoB) ratio, and the atherogenic index (ATH index) were observed in 32.7%, 31.7%, and 14.4% of men, respectively. The results of ROC curve analysis showed that the TyG index had good diagnostic ability for identifying unfavorable apolipoprotein indices in normolipidaemic men.

CONCLUSIONS

Thus, the TyG index can be a valuable additional marker for assessing latent atherogenic risk; it can provide useful information for the diagnosis and treatment of early atherosclerosis.

Prognostic value of novel atherogenic indices in patients with acute myocardial infarction with and without type 2 diabetes

AIMS

Atherogenic indices: Triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, Atherogenic Index of Plasma (AIP), Atherogenic Coefficient (AC), Castelli's Risk Index I and II (CRI-I, CRI-II) are used in clinical studies as surrogates of major adverse cardiac and cerebrovascular events (MACCE). Risk prediction of MACCE in patients with acute myocardial infarction (AMI) has vital role in clinical practice. We aimed to assess prognostic value of these indices following AMI.

METHODS

We analyzed patients with AMI with and without T2DM and the prognostic values of atherogenic indices for in-hospital death and MACCE within 12 months after AMI.

RESULTS

Of 2461 patients, 152 in-hospital deaths (6.2 %) were reported (74 patients [7.4 %] with T2DM and 78 [5.3 %] without T2DM; p = 0.042). MACCE occurred in 22.7 % of patients (29.7 % with T2DM and 17.9 % without T2DM; p < 0.001). TG/HDL-C and AIP were higher in T2DM patients compared to those without T2DM (p < 0.001). Long-term MACCE was more prevalent in patients with T2DM (p < 0.001). The AUC-ROC for predicting in-hospital death based on TG/HDL-C and AIP was 0.57 (p = 0.002).

CONCLUSIONS

None of the atherogenic indices was an independent risk factor for in-hospital death or MACCE at 12-month follow-up in patients with AMI. AIP was an independent risk factor for death at 12-month follow-up.

The association of triglyceride-glucose index with major adverse cardiovascular and cerebrovascular events after acute myocardial infarction: a meta-analysis of cohort studies

BACKGROUND

Insulin resistance (IR) is indicated to be linked with adverse outcomes of acute myocardial infarction (AMI), for its pro-inflammatory and pro-thromboplastic function. The triglyceride-glucose (TyG) index is a newly developed substitute marker for IR. The aim of this pooled analysis was to provide a summary of the relationship of TyG index with occurrences of major adverse cardiovascular and cerebrovascular events (MACCEs) among populations suffering from AMI.

METHODS

Cohorts reporting multivariate-adjusted hazard ratios of TyG index with MACCEs or its independent events were identified through systematically searching PubMed, MEDLINE, Web of science, Embase and Cochrane databases. Results were combined using a random-effects model.

RESULTS

21 cohorts comprising 20403 individuals were included. Compared to individuals in the lowest TyG category, patients in the highest TyG category exhibited elevated risks of both MACCEs (P < 0.00001) and all-cause death (P < 0.00001). These findings were in line with the results as TyG analyzed as continuous variables (MACCEs: P = 0.006; all-cause death: P < 0.00001). Subgroup analysis demonstrated that diabetic status, type of AMI, nor the reperfusion therapy did not destruct this correlation (for subgroups, all P < 0.05).

CONCLUSION

All these indicated that higher TyG index could potentially predict MACCEs and all-cause death in patients with AMI as an independent indicator.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes

BACKGROUND

Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR.

METHODS

Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM.

RESULTS

Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively.

CONCLUSIONS

TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

Association of the metabolic score for insulin resistance with cardiovascular diseases, cardiovascular and all-cause mortality in Chinese hypertensive population

Importance

Little is known about the relationship between the metabolic score for insulin resistance (METS-IR) and the prognosis of hypertensive patients in China.

Objective

To investigate the association between the novel non-insulin-based METS-IR index and the cardiovascular composite endpoints and all-cause mortality in Chinese hypertensive participants.

Design setting and participants

This cohort study used data from the China H-Type Hypertension Project, a long-term prospective cohort consisting of 14234 hypertensive patients in southern China, with a baseline from March to August 2018. The median follow-up period for participants was 3.94 years, as of 2022. The data analysis period is from July 2023 to September 2023.

Exposures

METS-IR index of participants in the Chinese H-type hypertension project. The calculation formula for METS-IR is (Ln (2 × FPG) +TG) × BMI/Ln (HDL-C).

Main outcomes and measures

Cardiovascular events and cardiovascular, all-cause mortality were identified by linking the cohort database with the health care system through October, 2023.

Results

A total of 14220 participants were included in this study. The prevalence rates of cardiovascular disease (CVD), cardiovascular death, and all-cause death were 2.59% (369/14220), 2.79% (397/14220), and 5.66% (805/14220), respectively. After adjusting for confounding factors in the multivariate logistic regression analysis models, the METS-IR index was significantly positively correlated with CVD, and cardiovascular, all-cause mortality, whether as a categorical or continuous variable. Layered analysis showed that the METS-IR index of hypertensive participants in different subgroups was positively correlated with the endpoint event.

Conclusions and relevance

This large, prospective cohort study demonstrated that the METS-IR index, a new IR evaluation index, were independently associated with a higher risk of the cardiovascular composite endpoint and all-cause mortality among Chinese hypertensive population. Importantly, our finding provides an independent indicator for evaluating the prognosis of hypertensive patients.

The potential role of the triglyceride-glucose index in left ventricular systolic function and in-hospital outcomes for patients with acute myocardial infarction

BACKGROUND

A limited number of small-sample cohort studies have investigated the association between the triglyceride-glucose index and in-hospital prognosis. Moreover, the translational potential role of left ventricular systolic function - measured by left ventricular ejection fraction - combined with the triglyceride-glucose index in prioritizing patients with acute myocardial infarction at high risk of in-hospital major adverse cardiovascular events remains unknown.

AIM

To explore the potential role of the triglyceride-glucose index in left ventricular systolic function and in-hospital major adverse cardiovascular events in patients with acute myocardial infarction.

METHODS

The Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome project (CCC-ACS) was analysed for this study.

RESULTS

We included 43,796 patients with acute myocardial infarction. Patients with a higher triglyceride-glucose index showed an increased risk of major adverse cardiovascular events (adjusted odds ratio 1.46, 95% confidence interval 1.31-1.63). Interaction analyses revealed that left ventricular ejection fraction modified the relationship between the triglyceride-glucose index and major adverse cardiovascular events. Furthermore, patients with acute myocardial infarction were categorized by the triglyceride-glucose index and left ventricular ejection fraction; the low left ventricular ejection fraction/high triglyceride-glucose index group showed the highest risk of major adverse cardiovascular events (adjusted odds ratio 2.14, 95% confidence interval 1.58-2.89).

CONCLUSIONS

In a comprehensive nationwide acute myocardial infarction registry conducted in China, a higher triglyceride-glucose index was found to be associated with in-hospital major adverse cardiovascular events, and this was particularly evident among patients with a lower left ventricular ejection fraction. Moreover, the triglyceride-glucose index combined with left ventricular ejection fraction was helpful for risk stratification of patients with acute myocardial infarction.

Development and Validation of a Nomogram Model for Predicting in-Hospital Mortality in non-Diabetic Patients with non-ST-Segment Elevation Acute Myocardial Infarction

Non-ST-segment elevation acute myocardial infarction (NSTEMI) is a life-threatening clinical emergency with a poor prognosis. However, there are no individualized nomogram models to identify patients at high risk of NSTEMI who may undergo death. The aim of this study was to develop a nomogram for in-hospital mortality in patients with NSTEMI to facilitate rapid risk stratification of patients. A total of 774 non-diabetic patients with NSTEMI were included in this study. Least Absolute Shrinkage and Selection Operator regression was used to initially screen potential predictors. Univariate and multivariate logistic regression (backward stepwise selection) analyses were performed to identify the optimal predictors for the prediction model. The corresponding nomogram was constructed based on those predictors. The receiver operating characteristic curve, GiViTI calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. The nomogram model consisting of six predictors: age (OR = 1.10; 95% CI: 1.05-1.15), blood urea nitrogen (OR = 1.06; 95% CI: 1.00-1.12), albumin (OR = 0.93; 95% CI: 0.87-1.00), triglyceride (OR = 1.41; 95% CI: 1.09-2.00), D-dimer (OR = 1.39; 95% CI: 1.06-1.80), and aspirin (OR = 0.16; 95% CI: 0.06-0.42). The nomogram had good discrimination (area under the curve (AUC) = 0.89, 95% CI: 0.84-0.94), calibration, and clinical usefulness. In this study, we developed a nomogram model to predict in-hospital mortality in patients with NSTEMI based on common clinical indicators. The proposed nomogram has good performance, allowing rapid risk stratification of patients with NSTEMI.

Predictive Value of D-Dimer for In-Hospital Mortality in Non-Diabetic Patients with Non-ST-segment Elevation Myocardial Infarction

Elevated circulating D-dimer levels have been shown to be a predictor of in-hospital mortality in a variety of diseases; however, the relationship between D-dimer and the in-hospital prognosis of non-ST-segment elevation myocardial infarction (NSTEMI) remains unclear. This retrospective study included 662 non-diabetic patients with NSTEMI. Independent risk factors were identified by multivariate analyses, and the receiver operating characteristic (ROC) curve analyses were performed to compare the predictive value of D-dimer, albumin (ALB), and D-dimer to albumin ratio (DAR) for in-hospital death in NSTEMI. Logistic regression model with restricted cubic spline (RCS) was used to further explore the linear or nonlinear relationship between D-dimer and the risk of death. In-hospital mortality occurred in 38 (5.7%) patients. Multivariate analysis showed that D-dimer (per increase of 500 ng) was identified as an independent predictor for in-hospital mortality in non-diabetic patients with NSTEMI (OR = 1.19, 95% CI: 1.03-1.40, P = 0.036). D-dimer demonstrated good predictive performance for in-hospital mortality with an area under the ROC curve (AUC) value of 0.75 (95% CI: 0.66-0.83), and there was no significant difference in the predictive ability of D-dimer, ALB (AUC = 0.70, 95% CI: 0.61-0.79) and DAR (AUC = 0.75, 95% CI: 0.66-0.84). In addition, RCS analysis showed a linear relationship between D-dimer and the risk of in-hospital mortality (P for nonlinear = 0.747). D-dimer can be used as a simple, reliable and valuable biomarker for predicting in-hospital mortality in non-diabetic patients with NSTEMI and is linearly associated with the risk of death.