Triglyceride-glucose index linked to all-cause mortality in critically ill patients: a cohort of 3026 patients

Investigation of the connection between triglyceride-glucose (TyG) index and the risk of acute kidney injury in septic patients - a retrospective analysis utilizing the MIMIC-IV database

The TyG index serves as a valuable tool for evaluating insulin resistance. An elevated TyG has shown a strong association with the occurrence of acute kidney injury (AKI). Nevertheless, existing literature does not address the relationship between the TyG index and acute kidney injury in patients with sepsis. Sepsis patients were identified from the MIMIC-IV database and categorized into four groups according to quadrilles of their TyG index values. The primary outcome of this study was the incidence of AKI. The relationship between the TyG index and the risk of AKI in septic patients was evaluated using Cox proportional hazards and restricted cubic spline models. Subgroup analyses were conducted to investigate the prognostic value of the TyG index in different subgroups. A total of 2,616 patients with sepsis (57% of whom were male) were included in this study. The incidence of AKI was found to be 78%. Cox proportional hazards analysis revealed a significant correlation between the TyG index and the occurrence of AKI in septic patients. Furthermore, a restricted cubic spline model revealed an approximately linear relationship between a higher TyG index and an elevated risk of AKI in septic patients. The trend of the hazard ratio (HR) remained consistent across various subgroups. These findings emphasize the reliability of the TyG index as an independent predictor for the occurrence of AKI and unfavorable renal outcomes in sepsis patients. Nevertheless, establishing a causal relationship between the two requires demonstration through larger prospective studies.

The association between triglyceride glucose-body mass index and mortality in critically ill patients with respiratory failure: insights from ICU data

Respiratory failure (RF) lead to high mortality rates and extended hospital stays in intensive care unit (ICU). The Triglyceride-Glucose (TyG) index, a reliable surrogate marker for insulin resistance (IR), predicted adverse outcomes in various diseases. Combining weight-related indices like body mass index (BMI) with TyG to form the TyG-BMI enhanced the assessment of IR and its impact on patient outcomes. However, the association between TyG-BMI and outcomes in patients with RF remained underexplored. This study retrospectively analyzed data from the MIMIC-IV database, focusing on critically ill patients with RF. From an initial cohort of 19,429 patients, 2177 met the inclusion criteria and were divided into quartiles based on TyG-BMI values. Key clinical information was collected within the first 24 h of ICU admission, including demographics, lab results, vital signs, and scoring systems such as SAPS II and SOFA. Primary outcome was 28-day, secondary outcomes were 180-day and 1-year mortality. Data were analyzed using multivariable Cox regression models, Kaplan-Meier survival curves, and restricted cubic splines to assess the nonlinear relationship between TyG-BMI and mortality. The study found significant differences in baseline characteristics across TyG-BMI quartiles. Kaplan-Meier survival curves indicated a higher survival probability for patients in the lowest TyG-BMI quartile (Q1) compared to higher quartiles (Q2-Q4). Adjusted hazard ratios demonstrated a nonlinear association between higher TyG-BMI values and increased mortality risk at all three time points. The RCS-derived cut-off value of 269 for TyG-BMI was identified as a significant threshold, with higher TyG-BMI values correlating with lower mortality risks. Subgroup analyses reinforced these findings across different patient demographics and clinical profiles. Higher TyG-BMI was associated to lower short-term and long-term mortality, suggesting a potential protective effect. These findings highlighted the importance of the TyG-BMI as a robust prognostic marker, providing valuable insights for improving treatment strategies for patients with RF.

Association between the TyG index and the risk of in-hospital mortality from early sepsis-related acute kidney injury in critically ill patients: a secondary analysis of MIMIC-IV 2008-2022

OBJECTIVES

This study aims to investigate the relationship between the triglyceride-glucose (TyG) index in patients with early sepsis-associated acute kidney injury (SA-AKI) and the risk of in-hospital mortality.

DESIGN

Secondary data analysis.

SETTING

This study analysed secondary data from the Medical Information Mart for Intensive Care (MIMIC) 2008-2022.

PARTICIPANTS

A total of 1632 participants were enrolled in the final analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

A secondary data analysis study was conducted using data from the MIMIC IV 3.0 database. Participants were divided into four groups based on the quartiles of the TyG index. The primary outcome was all-cause in-hospital mortality. The association between the TyG index and in-hospital mortality among SA-AKI patients was assessed using multivariate COX proportional hazards regression analysis and restricted cubic spline regression analysis. Subgroup and sensitivity analyses were performed to verify the robustness of results.

RESULTS

A total of 1632 patients were included in the study. The in-hospital mortality rate was 31.13%, and the intensive care unit (ICU) mortality rate was 25.25%. Multivariate COX regression analysis showed that the TyG index was independently associated with an increased risk of in-hospital mortality (HR 1.14 (95% CI 1.02 to 1.27); p=0.02) and ICU mortality (HR 1.17; (95% CI 1.04 to 1.32); p=0.01). The restricted cubic spline regression model indicated that the risk of in-hospital and ICU mortality increased linearly with the increase in the TyG index. Sensitivity analysis demonstrated that the effect size and direction were consistent across different subgroups, and the results were stable.

CONCLUSION

A high TyG index is associated with increased mortality during hospitalisation in patients with SA-AKI. Larger-scale prospective studies are needed to confirm these findings.

Nonlinear association between triglyceride-glucose index and 28-day mortality in intensive care units: a multi-center retrospective cohort study

Background

The triglyceride-glucose (TyG) index, derived from the calculation of two biomarkers, fasting plasma glucose and triglyceride levels, is a reliable indicator of insulin resistance and has been demonstrated to be associated with the adverse clinical outcomes of patients in the intensive care unit (ICU). This study aims to investigate the relationship between the TyG index and the 28-day all-cause mortality of these patients during their ICU stay.

Methods

This study employed a multicenter retrospective cohort design, analyzing data from 18,883 ICU patients in the eICU database. We calculated the TyG index for each patient and assessed its association with 28-day all-cause mortality. The Cox proportional hazards model was utilized for analysis, adjusting for various clinical and laboratory variables to control for confounding factors. We performed sensitivity analyses, subgroup analyses, and interaction analyses to evaluate the robustness of the results.

Results

The study identified a significant positive correlation between the TyG index and 28-day all-cause mortality. Specifically, each one-unit increase in the TyG index corresponded to a 58% increase in mortality risk (HR=1.58, 95% CI: 1.25-2.00, P=0.0001). Additionally, the analysis revealed a non-linear threshold effect of the TyG index on mortality, with a cutoff point at 8.82; mortality was lower below this value and significantly increased above it. Sensitivity and subgroup analyses indicated robust findings, while E-value analysis suggested resilience against unmeasured confounding.

Conclusion

This study establishes the TyG index as an independent predictor of 28-day all-cause mortality in critically ill patients, highlighting its potential value in clinical management and risk assessment. By recognizing the non-linear effect of the TyG index, clinicians can more effectively adjust treatment strategies to reduce mortality among high-risk patients.

The relationship and differences in the triglyceride-glucose index and all-cause mortality in patients with coronary heart disease combined with cerebrovascular and other comorbidities: an analysis of the MIMIC-IV database

Objective

This study aims to investigate the predictive capability of the triglyceride-glucose index (TyG index) for all-cause mortality among patients with coronary heart disease (CHD), particularly in those with cerebrovascular disease (CVD) and other comorbidities, based on the MIMIC-IV database.

Methods

Using the ICD-9/10 coding standards, eligible CHD patients were identified from the MIMIC-IV database (version 3.0) with defined inclusion and exclusion criteria to ensure sample representativeness. Patients were categorized into CVD and other comorbidity groups. Data on mortality rates at 90 days, 1 year, and overall were collected, along with the TyG index and relevant covariates associated with survival risk. Baseline analyses, Spearman correlation, and restricted cubic splines (RCS) were employed to assess the nonlinear relationship between the TyG index and mortality. Kaplan-Meier curves and Cox proportional hazards models were utilized to evaluate survival risk.

Results

A total of 1,872 CHD patients were included, with 578 having CVD and a mortality rate of 50.17%; 1,294 had other comorbidities with a mortality rate of 64.91%. RCS analysis indicated a nonlinear relationship between the TyG index and mortality risk. For patients with concurrent CVD, the lowest mortality risk occurred at a TyG index of 9.37 mmol/L, while for those with other comorbidities, the lowest risk was observed at 9.36 mmol/L. Cox regression analysis revealed a significant association between the TyG index and survival risk in all CHD patients (HR = 1.15, 95%CI: 1.04-1.28, P < 0.01). In patients with other comorbidities, an increase in the TyG index was significantly correlated with elevated mortality risk (HR = 1.21, 95%CI: 1.02-1.34, P < 0.01).

Conclusion

The TyG index exhibits a nonlinear relationship with mortality risk in CHD patients, with elevated levels significantly increasing mortality risk in those with other comorbidities. These findings suggest that the TyG index may serve as a critical metabolic marker for prognostic evaluation in CHD patients, warranting further clinical attention.

Triglyceride-glucose index and prognosis in non-diabetic critically ill patients: data from the eICU database

Background

The triglyceride-glucose (TyG) index is a marker for insulin resistance (IR) linked to diabetes complications and poor outcomes. Its connection to all-cause mortality in non-diabetic critically ill patients is unknown. This study aims to investigate the TyG index's impact on mortality in this population, evaluating how IR affects their prognosis.

Methods

This study is retrospective observational research utilizing data from the eICU Collaborative Research Database. A total of 14,089 non-diabetic critically ill patients were included and categorized into three groups based on the TyG index measured on the first day of admission (T1, T2, and T3). Kaplan-Meier survival analysis was performed to compare the 28-day mortality rates among the different groups. Cox proportional hazards models were used to assess the relationship between the TyG index and 28-day mortality. Additionally, we conducted sensitivity analyses, subgroup analyses, and interaction analyses to assess the robustness of the results.

Results

During the observation period, 730 patients (5.18%) died in the ICU, while 1,178 patients (8.36%) died in the hospital. The 28-day ICU mortality rate and hospital mortality rate significantly increased with higher TyG index values (P < 0.001). Cox proportional hazards models were used to assess the relationship between the TyG index and 28-day mortality. Specifically, Cox proportional hazards models were used to assess the relationship between the TyG index and 28-day mortality. Furthermore, the analysis showed a nonlinear effect of the TyG index on mortality in non-diabetic critically ill patients, with a critical point at 9.94. While Below 9.94, ICU and hospital mortality rates rose with higher TyG index values. But above 9.94, mortality didn't significantly increase despite further rises in the TyG index. Sensitivity and subgroup analyses confirmed the robustness of these results, and E-value analysis indicated strong resistance to unmeasured confounding factors.

Conclusion

The TyG index demonstrates a significant positive correlation with all-cause mortality in non-diabetic critically ill patients, exhibiting a nonlinear relationship. Consequently, the TyG index serves as a crucial tool for identifying high-risk patients, thereby assisting clinicians in formulating more effective monitoring and intervention strategies.

Associations of the triglyceride-glucose index with short-term mortality in patients with cardiogenic shock: a cohort study

BACKGROUND

Cardiogenic shock (CS) is a severe cardiac disorder with a high mortality rate. The triglyceride-glucose (TyG) index, a biomarker of insulin resistance, is associated with cardiovascular disease-related mortality. This study aimed to investigate the association between the TyG index and mortality in patients with CS.

METHODS

This retrospective cohort study analyzed 727 patients with CS from the Medical Information Mart for Intensive Care IV database. The TyG index was calculated as follows: ln[triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Outcomes included 28-day intensive care unit (ICU) mortality and 28-day in-hospital mortality. Kaplan-Meier survival curve models and Cox proportional hazards regression models were used to evaluate the prognostic significance of the TyG index. Receiver Operating Characteristic (ROC) curve analysis was used to determine the predictive efficacy of the TyG index for mortality. Subgroup analyses were conducted to determine the association between the TyG index and mortality across different groups.

RESULTS

Non-survivors had a significantly higher TyG index (ICU: 9.30 vs. 9.13, p = 0.008; in-hospital: 9.29 vs. 9.13, p = 0.004). Adjusted Cox models showed that each 1-unit increase in the TyG index increased ICU mortality risk by 24% (hazard ratio [HR] = 1.24, 95% confidence interval [CI]:1.04-1.48; p = 0.015) and in-hospital mortality by 44% (HR = 1.44, 95% CI:1.11-1.88; p = 0.007). The Quartile 4 TyG index ICU mortality was increased by 77% (HR = 1.77, 95% CI:1.09-2.89) compared to that for Quartile 1 and in-hospital mortality was increased by 61% (HR = 1.61, 95% CI:1.08-2.38). The area under the ROC curve (AUROC) showed a modest standalone predictive ability of 0.56, but when combined with clinical variables, the AUROC improved to 0.80 (ICU) and 0.78 (in-hospital). Subgroup analyses identified stronger associations in patients ≥ 60 years, females, non-septic, and those with acute myocardial infarction or heart failure.

CONCLUSIONS

The TyG index is significantly associated with short-term mortality in patients with CS and may serve as a useful biomarker for risk stratification.

TRIAL REGISTRATION

Not applicable.

The impact of the triglyceride-glucose index on the risk of respiratory failure in patients with COPD: a study from the MIMIC database and Chinese cohorts

BACKGROUND

The Triglyceride-Glucose (TyG) index, a reliable marker for insulin resistance, is now employed to assess the onset and prognosis of various conditions like acute coronary syndrome, chronic kidney disease, and ischemic stroke. However, whether the TyG index can be used to assess respiratory failure (RF) risk among Chronic obstructive pulmonary disease (COPD) patients remains uncertain. The present study aims to delve into the link between the TyG index and the risk of RF in COPD patients.

METHODS

Individuals with COPD were retrospectively acquired from the MIMIC-IV 2.2 (The Medical Information Mart for Intensive Care IV, version 2.2) database. The association between the TyG index and the probability of RF among COPD patients was evaluated using Cox proportional hazards models and restricted cubic spline (RCS) curves. Cumulative incidence curves were generated to appraise the RF risk across the quartile groups. Finally, 1188 patients were recruited from the First Hospital of Jiaxing City to externally validate the Cox modeling results for the primary outcome.

RESULTS

This study incorporated a total of 1,232 participants from MIMIC database. Among these individuals, 134 cases (10.9%) experienced RF. According to Cox regression analysis, a one-unit increment in the TyG index was linked to a 1.821-fold elevated risk of RF in the COPD population (HR, 1.821[95% CI 1.349-2.459], P < 0.001). High TyG index levels were significantly linked to a higher RF risk (HR, 3.510 [95% CI 1.885-6.535], P < 0.001). RCS curve analysis also signaled a linear correlation between the TyG index and RF risk (P-Nonlinear = 0.074).

CONCLUSION

There exists a certain correlation between high-level TyG index and the risk of RF occurrence in COPD patients, indicating promising prospects for utilizing the TyG index to assess the severity of COPD patients.

Triglyceride-glucose index is a significant predictor of hospital mortality in non-diabetic critically ill patients with ischemic stroke: a retrospective cohort study of the MIMIC-IV database

BACKGROUND AND AIMS

The relationship between the TyG index and outcomes in non-diabetic patients with ischemic stroke admitted to intensive care unit (ICU) has not been validated. This study aims to investigate the correlation between the TyG index and mortality in non-diabetic ICU patients with ischemic stroke.

METHODS

We collected data from ICU patients (≥ 18 years) with ischemic stroke and no diabetes. The primary outcome was hospital mortality, and the secondary outcomes were 30-day mortality following admission, hospital length of stay (LOS) and ICU LOS. Cox proportional hazards models and generalized linear models were employed to evaluate association between the TyG index and mortality and LOS, respectively. Nonlinear associations between the TyG index and outcomes were assessed using restricted cubic spline regression models.

RESULTS

A total of 1122 eligible patients were included in this study. The hospital mortality was 10.61%, and 30-day mortality was 16.93%. Multivariate Cox proportional hazards models and generalized linear models revealed the higher of TyG was significantly associated with increased hospital mortality [adjusted HR (95% CI) 1.22 (1.02-1.46), P = 0.0264], 30-day mortality [adjusted HR (95% CI) 1.26 (1.10-1.44), P = 0.0011] and prolonged hospital LOS [adjusted difference (95% CI) 0.52 (0.06-0.97), P = 0.0276].

CONCLUSIONS

TyG index is a significant predictor of hospital mortality, 30-day mortality, and LOS in non-diabetic ICU patients with ischemic stroke, which could aid clinical decision-making in managing ischemic stroke.

Associations of the triglyceride-glucose index with mortality mediated by blood urea nitrogen among critically ill patients: a cohort study

Previous studies have shown that an elevated triglyceride-glucose (TyG) index is associated with all-cause mortality in patients. However, the potential mediating effect of blood urea nitrogen (BUN) within these associations has not been reported. The focus of this study was to investigate the potential mediating effect of BUN within these associations. This was a retrospective cohort study of patients in the eICU Collaborative Research Database (eICU-CRD) from 208 different ICUs in the United States between 2014 and 2015 that explored. The primary endpoint of the study was all-cause mortality within 28 days of ICU admission. In addition, the following formula was used to calculate the TyG index: Ln [fasting TG (mg/dL) × FBG (mg/dL)/2]. Cox regression model and subgroup analysis were performed to assess the associations of TyG index with 28-day mortality. The mediating effect of BUN was assessed to investigate the potential mechanism of the associations between TyG index and mortality using the mediation package in R 4.2.0. Of the 14,414 patients with a mean age of 64.1 years, 809 (5.61%) died within 28 days of ICU admission. The proportion of women was 57.9% and the mean TyG index was 8.97 ± 0.82. In the multivariable-adjusted model, the high tertile showed an even stronger association with 28-day ICU mortality than the low tertile, with a hazard ratio (HR) of 1.27 (95% CI: 1.05, 1.53; P = 0.014). Mediation analysis showed that BUN mediated 12.4% of the association between the TyG index and mortality. Our study showed that an elevated TyG index was associated with an increased risk of mortality in critically ill patients. The association appeared to be partially mediated by BUN.

The role of TyG index as a predictor of all-cause mortality in hospitalized patients with acute pancreatitis: a retrospective study utilizing the MIMIC-IV database

BACKGROUND

The TyG index is widely recognized as a reliable indicator for cardiovascular disease risk and as a biomarker for assessing insulin resistance(IR). However, its significance in the context of patients with acute pancreatitis(AP) needs further exploration. This study aimed to investigate the association between the TyG index and the risk of all-cause mortality in critically ill patients with AP.

METHODS

Data for this retrospective study were obtained from the MIMIC IV2.2 database. The participants were divided into four groups based on the TyG index tertiles. The primary outcome measured was in-hospital all-cause mortality. We employed Cox proportional hazards regression analysis and restricted cubic splines to evaluate the correlation between the TyG index and clinical outcomes in patients with AP.

RESULTS

The study included 586 patients, of which 44.71% were male. The rates of mortality observed in the hospital stay and in the ICU stay were 19.28% and 12.97%. By conducting multivariable Cox proportional hazards, it was determined that the TyG index was independently associated with a heightened risk of in-hospital mortality [HR(95%CI) of 1.38(1.03-1.87, P=0.033)] and in ICU mortality [1.65(1.12-2.44), P=0.012]. The analysis using restricted cubic splines showed that there was a consistent and gradually increasing risk of all-cause mortality as the TyG index increased. This indicates that a higher TyG index is associated with a higher risk of mortality.

CONCLUSION

In critically ill patients with AP, the TyG index shows a notable correlation with all-cause death in both hospital and ICU. The TyG index can be useful in identifying insulin resistance at an early stage in patients with AP, thereby improving risk assessment and guiding subsequent interventions.

Association between triglyceride-glucose index and mortality in critically ill patients with atrial fibrillation: a retrospective cohort study

BACKGROUND

The triglyceride-glucose (TyG) index, an emerging surrogate marker of insulin resistance, has been implicated in adverse cardiovascular outcomes. However, its prognostic value in critically ill patients with atrial fibrillation (AF) remains unclear. This study aimed to investigate the association between the TyG index and all-cause mortality in this high-risk population.

METHODS

We identified critically ill patients with AF from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and categorized them into tertiles based on their TyG index levels. The primary outcome was 30-day mortality, with 90-day and 365-day all-cause mortality as secondary outcomes. Cox proportional hazards regression analysis and restricted cubic splines were used to elucidate the relationship between the TyG index and all-cause mortality. Kaplan-Meier survival analysis was performed to visualize survival differences among the tertiles.

RESULTS

A total of 1473 patients were included; the 30-day, 90-day, and 365-day all-cause mortality rates were 26.8%, 33.3%, and 41.1%, respectively. Multivariate Cox proportional hazards analysis revealed that the TyG index was independently associated with mortality at 30 days [hazard ratio (HR) (95% confidence interval (CI)) 1.26 (1.09-1.45), P = 0.002], 90 days [HR (95% CI) 1.27 (1.11-1.45), P < 0.001], and 365 days [HR (95% CI) 1.24 (1.10-1.40), P < 0.001]. Restricted cubic splines regression showed a positive linear association between the TyG index and mortality risk. Kaplan-Meier survival curves further confirmed the significant survival disparities across TyG index tertiles.

CONCLUSIONS

A significant linear association was observed between higher TyG index and increased all-cause mortality at 30, 90, and 365 days in critically ill patients with AF. This underscores the role of the TyG index as a key prognostic indicator for risk stratification and management in intensive care.

Association Between Low Triglyceride-Glucose Index and Mortality in Acute Decompensated Heart Failure Patients Without Diabetes

Background

The relationship between a low TyG index and mortality risk in Acute Decompensated Heart Failure (ADHF) also remains unclear. This study aimed to investigate the association between a low TyG index and 1-year mortality in ADHF patients without diabetes.

Methods

A total of 652 hospitalized patients with ADHF without diabetes from January, 2020 to May, 2023 were included in this retrospective study. The primary outcomes were all-cause mortality and cardiovascular mortality within one year. The association between the TyG index and both all-cause and cardiovascular mortality was investigated using restricted cubic splines and multivariate Cox proportional hazards models.

Results

The study enrolled a total of 652 patients with acute decompensated heart failure (ADHF) who were free from diabetes (70.6% male). Within one year, there were 72 deaths from all causes and 40 deaths from cardiovascular disease. In multivariate Cox proportional hazards models, a significant negative relationship was observed between the TyG index and both all-cause mortality (hazard ratio [HR] = 0.371, 95% confidence interval [CI] 0.201-0.685) and cardiovascular mortality (HR = 0.336, 95% CI 0.151-0.744). The restricted cubic spline analysis illustrated a decrease in the risk of all-cause and cardiovascular mortality as the TyG index increased. Hypertension, BMI, age, atrial fibrillation significantly interacted with the TyG index in relation to all-cause mortality, while hypertension specifically interacted with the TyG index regarding cardiovascular mortality.

Conclusion

In patients diagnosed with ADHF without diabetes, a lower TyG index is strongly related to a higher risk of 1-year all-cause and cardiovascular mortality. Therefore, it is important to pay close attention to low TyG index levels and implement appropriate measures in clinical practice.

The TyG index correlation with invasive ventilator in critically ill patients: A retrospective analysis of the MIMIC-IV database

BACKGROUND

Insulin resistance is common in critically ill patients. It is not known whether it is associated with the use of invasive ventilation. This study investigated the relationship between the triglyceride glycemic index (TyG) and the risk of invasive ventilator use in critically ill patients admitted to the intensive care unit (ICU).

METHODS

The study utilized the Medical Information Mart for Intensive Care-IV database. All patients were divided into three groups according to the TyG index. The study employed univariable and multivariable logistic regression analysis, competing risk analysis, and 4-knot multivariate restricted cubic spline regression. ROC curves were used to determine if the TyG index improves the predictive value of disease scores.

RESULTS

Out of 2196 participants, 51.9 % had invasive ventilation. Multivariable logistic regression analyses and competing risk analyses revealed that the risk of Invasive ventilator use was significantly higher in the highest quartile of the TyG index. Meanwhile, the RCS analysis indicated S-typed relationships between the TyG index and invasive ventilator use, with inflection points at 9.40, respectively. The TyG index had an incremental effect on the AUC of existing severity of illness scores to predict invasive ventilation.

CONCLUSION

This study shows that an increased TyG index is a significant risk factor for invasive ventilation in patients in the ICU.

Triglyceride-glucose index correlates with the incidences and prognoses of cardiac arrest following acute myocardial infarction: data from two large-scale cohorts

BACKGROUND

The triglyceride-glucose (TyG) index, renowned for its efficacy and convenience in assessing insulin resistance, has been validated as a reliable indicator for various cardiovascular conditions. The current study aims for clarifying the link of TyG with the incidences and prognoses of cardiac arrest (CA) following acute myocardial infarction (AMI).

METHODS

Our analysis is a multicenter, retrospective study utilizing data from the Medical Information Mart for Intensive Care IV and the eICU Collaborative Research Database. Patients with AMI for whom TyG could be calculated within the first 24 h after admission were included. The main endpoints were in-hospital and ICU mortalities. Correlations between TyG and outcomes were evaluated using logistic regression models, restricted cubic splines (RCS), as well as correlation and linear analyses. Overlap weighting (OW), inverse probability of treatment weighting (IPTW), and propensity score matching (PSM) methodologies were utilized to balance the cohorts, thereby minimizing potential biases. Subgroup analyses were performed in accordance with identified modifiers.

RESULTS

In total, 5208 individuals diagnosed with AMI, among whom 371 developed CA, were ultimately included. Higher TyG levels were observed among AMI populations with CA compared to those without [9.2 (8.7-9.7) vs. 9.0 (8.5-9.4)], and TyG demonstrated a moderate discriminatory capacity for identifying CA occurrences within entire AMI populations. Multivariate logistic regressions revealed TyG serves a significant risk indicator for both in-hospital (OR 1.711) and ICU mortalities (OR 1.520) in AMI-CA patients, and it is also associated with prolonged LOSs. RCS analyses confirmed linear relationships of ascending TyG with increased mortality risks for AMI-CA (P for nonlinearity: 0.592 and 0.816, respectively), which persisted following PSM, OW, and IPTW adjustments. Subgroup analyses further identified a strong link of the TyG with mortality rates among elders, females, individuals with BMI < 28 kg/m2, and those with hypertension.

CONCLUSIONS

Elevated TyG levels were found to apparently correlate with higher prevalence and adverse outcomes regarding CA in patients with AMI. Our findings point a fresh insight into the significance of the TyG in critically ill coronary conditions.

Glycemic variability and its association with short and long term clinical outcomes in critically ill patients with cerebral hemorrhage

Cerebral hemorrhage is a major cause of mortality and disability. This study investigates the association between glycemic variability (GV) and short- and long-term clinical outcomes such as poor outcomes at discharge, mortality at 90 days and 1 year and intensive care unit (ICU) /hospital length of stay (LOS) in ICU patients with critically ill cerebral hemorrhage. This retrospective analysis examined 732 ICU patients with non-traumatic cerebral hemorrhage from the Medical Information Mart for Intensive Care (MIMIC)-IV database. GV was quantified as the ratio of standard deviation to mean glucose during ICU stay. To assess associations between GV and clinical outcomes (poor outcomes at discharge, 90-day and 1-year mortality, ICU/hospital LOS), the study employed logistic regression, Cox proportional hazards models, and linear regression. Additionally, non-linear relationships were explored through restricted cubic spline analysis. The investigation further incorporated subgroup and sensitivity analyses to ensure robustness of findings. To evaluate the incremental predictive value of GV, the study utilized receiver operating characteristic (ROC) curve analysis, net reclassification improvement, and integrated discrimination improvement, thereby providing a comprehensive assessment of GV's clinical utility. Higher GV was significantly associated with increased risk of poor outcomes at discharge and 90-day and 1-year mortality in both patient groups. GV showed a linear association with poor outcomes at discharge but a non-linear association with 90-day and 1-year mortality. GV thresholds of ≥ 0.11 for non-traumatic cerebral hemorrhage increased mortality risks. Cohort showed non-linear relationships between GV and ICU/hospital LOS. GV's impact was stronger in non-hypertensive and male patients. Adding GV to existing severity scores improved their predictive ability for adverse outcomes. In patients with non-traumatic cerebral hemorrhage admitted to the ICU, GV demonstrates an independent association with poor outcomes over both short-term and long-term time horizons. Furthermore, GV is associated with extended durations of both ICU and overall hospital stays in this patient population. These findings underscore the importance of glycemic control in this patient population and suggest that GV could be a valuable prognostic indicator and potential therapeutic target.

Association between Triglyceride-Glucose Index and Prognosis in Critically Ill Patients with Acute Coronary Syndrome: Evidence from the MIMIC Database

Background: This study aimed to investigate the association between triglyceride-glucose (TyG) index and prognosis in critically ill patients with acute coronary syndrome (ACS), exploring potential heterogeneity of the association among patient subgroups with different characteristics. Methods: Records of patients with ACS were extracted from the MIMIC-IV database. The association between TyG index and mortality was analyzed using Cox proportional-hazard regression model, while potential non-linear associations were assessed using restricted cubic spline (RCS) regression. Meanwhile, linear regression model was used to explore the association between TyG index and length of stay in hospital or ICU. Subpopulation Treatment Effect Pattern Plot (STEPP) was utilized to explore the potential heterogeneous subgroups. Time-dependent Receiver Operating Characteristic (ROC) curve analyses were performed to compare the predictive ability of different Cox proportional-hazard regression models (with or without TyG index). Results: A total of 849 patients were enrolled. Multivariate Cox regression analyses demonstrated that TyG index was significantly associated with 28-day mortality (HR:2.13 [95%CI: 1.23-3.68], P<0.01) and 365-day mortality (HR:1.65 [95%CI: 1.11-2.47], P<0.01). RCS regression analyses revealed an inverted U-shaped association between TyG index and 28-day mortality (P for non-linearity=0.027) and a linear association between TyG index and 365-day mortality (P for non-linearity =0.086). There were subgroups specified by age for 28-day mortality (P for interaction=0.04) and 365-day mortality (P for interaction<0.01), with a cut-off point of 70 years old obtained by STEPP. TyG index was associated with a higher risk of mortality in subgroups aged ≤ 70 years old. Time-dependent ROC curve suggested that TyG index could slightly improve the prediction of mortality. A higher TyG index was associated with longer time of stay in hospital (β: 1.79 [95%CI: 0.06-3.52], P=0.04). Conclusions: A higher TyG index is associated with both short-term and long-term all-cause mortality in critically ill patients with ACS, especially in short-term all-cause mortality. TyG index is associated with higher mortality risk in patient subgroups aged ≤ 70 years old. A higher TyG index is associated with longer time of stay in hospital. TyG index may serve as a useful prognostic marker for patient management and strategic decision-making in clinical settings.

The association between the triglyceride‒glucose index and short-term mortality in ICU patients with sepsis-associated acute kidney injury

BACKGROUND

The triglyceride-glucose (TyG) index has emerged as a novel marker for insulin resistance and is commonly observed in patients suffering from sepsis-associated acute kidney injury (SA-AKI). This study explored the correlation between the TyG index and short-term all-cause mortality among SA-AKI patients.

METHODS

We performed a retrospective analysis of ICU patients with SA-AKI using data from the MIMIC-IV database. The primary outcomes were 28-day and 90-day all-cause mortality. Multivariate Cox proportional hazards regression, restricted cubic spline (RCS) models, and Kaplan‒Meier (K‒M) survival analyses were used to examine the associations between the TyG index and mortality. Subgroup and sensitivity analyses were conducted to ensure the robustness of the findings.

RESULTS

The study included 4971 SA-AKI patients, with 2873 males (57.8%), an average age of 65.4 years (± 15.8), and an average TyG index of 9.10 (± 0.70). RCS analysis revealed a U-shaped relationship between the TyG index and mortality. When the TyG index was below 9.04, the risk of mortality at both 28 days and 90 days was reduced (adjusted HRs of 0.695, 95% CI: 0.542-0.890 and 0.691, 95% CI: 0.557-0.858, respectively). In contrast, values above 9.04 were associated with increased mortality, though the relationship was not statistically significant (adjusted HRs of 1.026, 95% CI: 0.855-1.231 and 1.012, 95% CI: 0.863-1.188, respectively). K‒M analysis revealed higher mortality rates for patients with either high (T3) or low (T1) TyG indices than for those with moderate (T2) TyG indices. Sensitivity analyses confirmed these associations even after excluding patients with diabetes, cerebrovascular diseases, or ICU stays of less than 2 days.

CONCLUSION

The TyG index is significantly and nonlinearly associated with short-term all-cause mortality in SA-AKI patients; however, establishing a causal relationship between the two requires validation through larger prospective studies.

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.

Estimated pulse wave velocity is associated with all-cause and cardiovascular mortality in individuals with stroke: A national-based prospective cohort study

Extensive evidence underscores the potential of estimated pulse wave velocity (ePWV) as a robust tool for predicting disease prevalence and mortality. However, its comparative effectiveness in forecasting all-cause and cardiovascular disease (CVD) mortality, particularly among stroke populations, remains inadequately characterized in relation to the traditional Framingham Risk Score (FRS) model. This prospective study included 1202 individuals with stroke from the National Health and Nutrition Examination Survey conducted between 1999 and 2014, with comprehensive follow-up data. Survey-weighted Cox regression models were employed to examine the association between ePWV and the risks of all-cause and CVD mortality. Subgroup analyses were performed to evaluate the stability of ePWV in predicting these outcomes. A generalized additive model was utilized to explore the dose-response relationship between ePWV and mortality risk. Receiver operating characteristic curves were then used to assess and compare the prognostic capabilities of ePWV and FRS models for 10-year all-cause and CVD mortality. After adjustment for relevant covariates, each 1 m/s increase in ePWV was associated with a 44% and 65% increase in all-cause and CVD mortality, respectively. ePWV demonstrated consistent prognostic performance across the majority of stroke subpopulations. Notably, ePWV exhibited a nonlinear relationship with all-cause mortality (P for nonlinearity = .045) while maintaining a linear association with CVD mortality (P for nonlinearity = .293). Furthermore, ePWV outperformed the FRS model in predicting 10-year all-cause (Integrated Discrimination Improvement = 0.061, 95% confidence interval: 0.031-0.095, P = .007) and CVD mortality (95% confidence interval: 0.005-0.083, P = .02). ePWV is an independent risk factor for both all-cause and CVD mortality in individuals with stroke, demonstrating superior predictive value compared to the traditional FRS model for forecasting these outcomes.

Impact of surrogates for insulin resistance on mortality and life expectancy in primary care: a nationwide cross-sectional study with registry linkage (LIPIDOGRAM2015)

Background

Insulin resistance (IR) is an important risk factor for multiple chronic diseases, increasing mortality and reducing life expectancy. The associations between emerging surrogates for IR, triglyceride-glucose index (TyG) and TyG-related indicators, with all-cause mortality and life expectancy in middle-aged and older patients in primary care are unclear.

Methods

This study originated from the Polish primary care cohort LIPIDOGRAM2015, including patients aged ≥45 years. Baseline fasting triglycerides and fasting glucose were used to derive TyG. Other TyG-related indicators included TyG-adjusted body mass index (TyG-BMI), TyG-adjusted waist circumference (TyG-WC), TyG-adjusted waist-to-hip, and TyG-adjusted waist-to-height. In this longitudinal analysis, we assessed associations between TyG-related indicators with total all-cause mortality, premature (age at death ≤75 years) all-cause mortality and years of life lost (YLL).

Findings

We included 10,688 patients (mean age 61.8 ± 9.3 years; 63.5% female). Cumulative total and premature all-cause mortality were 7.2% and 4.6%, respectively, during 5.7 years (IQR 5.6-5.7) of follow-up. Lowest (Q1) and highest quartile (Q4) of TyG-BMI and TyG-WC were associated with total all-cause mortality (second quartile [Q2]: reference; TyG-BMI: Q1: aHR 1.33, 95% CI 1.07-1.65, Q4: aHR 1.28, 95% CI 1.03-1.58; TyG-WC: Q1: aHR 1.44, 95% CI 1.14-1.82, Q4: aHR 1.29, 95% CI 1.04-1.59), similar results for premature all-cause mortality. Within age 45-80 years, compared with Q2 and third quartile, YLL were 4.49 and 5.46 years for TyG-BMI Q1 and Q4, respectively, 3.24 and 5.31 years for TyG-WC Q1 and Q4, respectively.

Interpretation

TyG-BMI and TyG-WC demonstrated a U-shaped association with total and premature all-cause mortality. Low and high levels of TyG-BMI and TyG-WC were associated with reduced life expectancy. Despite the relatively short follow-up period, significant associations were still observed, but longer follow-up studies are required to further explore these relationships.

Funding

Polish Lipid Association, College of Family Physician in Poland, Valeant in Poland.

Association of the triglyceride glucose index with all cause and CVD mortality in the adults with diabetes aged < 65 years without cardiovascular disease

Although the triglyceride-glucose (TyG) index has been established as a valuable predictor for cardiovascular disease (CVD) and cardiovascular mortality, there is limited research exploring its association with all-cause or CVD mortality specifically in adults with diabetes aged < 65 years without cardiovascular disease. This study aimed to investigate the relationship between the TyG index and both all-cause and CVD mortality in this population within the United States. Our study recruited 1778 adults with diabetes aged < 65 years without cardiovascular disease from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Mortality outcomes were determined by linking to National Death Index (NDI) records up to December 31, 2019. Cox regression modeling was employed to examine the association between the TyG index and mortality in this population. The nonlinear relationship between the TyG index and mortality was assessed using restricted cubic splines (RCS). Additionally, subgroup analyses and interaction tests were conducted to explore potential effect modifiers. A total of 1788 participants were included in the final cohort, with an average age of 49.61 ± 0.32 years. During a median follow-up of 7.92 years, the occurrence of 150 all-cause deaths and 33 CVD-related deaths were recorded. To investigate the independent association between the TyG index and the risks of all-cause and CVD mortality, three Cox regression models were developed. In Model 1, a significant positive association was observed between the TyG index and the risk of all-cause mortality (HR 1.38, 95% CI 1.09-1.74). This association persisted in the minimally adjusted model (HR 1.44, 95% CI 1.13-1.83), which was adjusted for age, gender and race. Even after full adjustment, this positive association remained significant (HR 1.91, 95% CI 1.36-2.70). We also found that the relationship between the TyG index and all-cause mortality was linear. Subgroup analyses revealed no significant interactions between the TyG index and the stratification variables. However, we did not observe a significant association between the TyG index and CVD mortality in this population. Our results suggested that a significantly positive association between the TyG index and all-cause mortality. The positive association between the TyG index and all-cause mortality was linear. We did not observe a significant association between the TyG index and CVD mortality.

Association between triglyceride-glucose index and all-cause mortality in critically ill patients with acute myocardial infarction: analysis of the MIMIC-IV database

Background

Currently, the clinical evidence regarding the prognostic significance of the TyG index in acute myocardial infarction (AMI) patients remains unclear. Our research analyzed the correlation between the TyG index and the risk of mortality in patients with AMI, in order to evaluate the influence of the TyG index on the prognosis of this population.

Methods

1205 ICU patients with AMI were analyzed in this retrospective cohort analysis, and the necessary data were obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The study conducted Kaplan-Meier analysis to compare all-cause mortality rates across four groups of patients. The study included logistic regression and Cox regression analysis to examine the correlation among the TyG index and the risk of in-hospital, 28-day, and 90-day mortality.

Results

In our study, 176 (14.61%) patients experienced in-hospital deaths, 198 (16.43%) patients died within 28 days of follow-up, and 189 (23.98%) patients died within 90 days of follow-up. Logistic regression and Cox proportional hazard analyses revealed that the TyG index was an independent predictor of in-hospital, 28-day, and 90-day mortality (OR: 1.406, 95% CI 1.141-1.731, p = 0.001; HR: 1.364, 95% CI 1.118-1.665, p = 0.002; HR: 1.221, 95% CI 1.024-1.445, p = 0.026, respectively). The restricted cubic spline regression model showed that the risk of in-hospital, 28-day, and 90-day mortality increased linearly with increasing TyG index.

Conclusions

The TyG index was significantly associated with an increased risk of mortality in AMI patients. Our findings suggested that the TyG index may be instrumental in identifying patients at high risk for adverse outcomes following AMI.

Association of TyG index with mortality at 28 days in sepsis patients in intensive care from MIMIC IV database

The relationship between the triglyceride‒glucose (TyG) index and the clinical prognosis of septic patients in intensive care units (ICUs) remains unclear. This study aimed to explore the correlation between the TyG index and 28-day all-cause mortality in septic patients. A retrospective observational cohort study was conducted, including 8955 septic patients from the MIMIC IV 2.2 database. The primary outcome was 28-day all-cause mortality. Multivariate logistic regression analysis and restricted cubic spline regression analysis were used to assess the relationship between the TyG index and 28-day all-cause mortality in septic patients. Subgroup analyses and sensitivity analyses were performed to further validate the robustness of the results. A total of 8955 septic patients were included, 5219 (58.3%) of whom were male, with a mean age of 66.3 (15.8) years and an average TyG index of 9.08 (0.70) and the number of deaths within 28 days was 1639 (18.3%). The RCS curve demonstrated a U-shaped relationship between the TyG index and 28-day all-cause mortality (nonlinear P value = 0.0003). The risk of 28-day all-cause mortality was negatively associated with the TyG index until it decreased to 9.03 (adjusted odds ratio [OR] 0.727, 95% confidence interval [CI] 0.577-0.915). However, when the TyG index exceeded 9.03, the odds ratio for 28-day all-cause mortality significantly increased (adjusted OR 1.185, 95% CI 1.001-1.404). These findings were consistent across subgroups and various sensitivity analyses. Our study revealed a nonlinear U-shaped relationship between the TyG index and 28-day all-cause mortality, with a critical point at a TyG index of 9.03. Our results suggest that the TyG index may be a novel and important factor for the short-term clinical prognosis of critically ill septic patients.

The potential of insulin resistance indices to predict non-alcoholic fatty liver disease in patients with type 2 diabetes

BACKGROUND

The triglyceride-glucose (TyG) index and related parameters, as well as the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), have been developed as insulin resistance markers to identify individuals at risk for non-alcoholic fatty liver disease (NAFLD). However, its use for predicting NAFLD in patients with type 2 diabetes mellitus (T2DM) remains unclear. In this study, we aimed to observe the performance of insulin resistance indices in diagnosing NAFLD combined with T2DM and to compare their diagnostic values in clinical practice.

PATIENTS AND METHODS

Overall, 268 patients with T2DM from the Endocrinology Department of Jiangsu Provincial Hospital of Traditional Chinese Medicine were enrolled in this study and divided into two groups: an NAFLD group (T2DM with NAFLD) and a T2DM group (T2DM without NAFLD). General information and blood indicators of the participants were collected, and insulin resistance indices were calculated based on these data. Receiver operating characteristic (ROC) analysis was conducted to calculate the area under the curve (AUC) for insulin resistance-related indices, aiming to assess their ability to discriminate between T2DM patients with and without NAFLD.

RESULTS

ROC analysis revealed that among the five insulin resistance-related indices, four parameters (TyG, TyG-body mass index [BMI], TyG-waist circumference [WC], and TyG- (waist-hip ratio [WHR]) exhibited high predictive performance for identifying NAFLD, except for HOMA-IR (AUCs:0.710,0.738,0.737 and 0.730, respectivly). TyG-BMI demonstrated superior predictive value, especially in males. For males, the AUC for TyG-BMI was 0.764 (95% confidence interval [CI] 0.691-0.827). The sensitivity and specificity for male NAFLD were 90.32% and 47.89%, respectively. Moreover, in the Generalized linear regression models, there were positive associations of TyG, TyG-BMI, TyG-WC, TyG-WHR, and HOMA-IR with controlled attenuation parameter (CAP), with β values of 21.30, 0.745, 0.247, and 2.549 (all P < 0.001), respectively.

CONCLUSION

TyG-BMI is a promising predictor of NAFLD combined with T2DM, particularly in lean male patients.

Association between the triglyceride glucose index and short-term mortality in septic patients with or without obesity: a retrospective cohort study

BACKGROUND

Sepsis is a significant contributor to both intensive care unit (ICU) admissions and mortality among patients in ICU, with a rising prevalence of obesity. There is a lack of extensive research on the correlation between TyGI and findings in patients with sepsis, especially in obese patients.

METHODS

This study used a retrospective cohort design and included patients with sepsis (≥18 years) from the Medical Information Mart for Intensive Care IV database. The association between TyGI and outcome was examined using multivariable logistic regression analysis.

RESULTS

8,840 patients with sepsis were included in the analysis. The in-ICU mortality rate was 9.7%. Non-survivors exhibited significantly greater TyGI levels than survivors [9.19(8.76-9.71) vs. 9.10(8.67-9.54), p < 0.001]. The adjusted multivariate regression model showed that elevated TyGI values were linked to a greater likelihood of death in ICU (odds ratio [OR] range 1.072-1.793, p < 0.001) and hospital (OR range 1.068-1.445, p = 0.005). Restricted Cubic Spline analysis revealed a nonlinear association between TyGI and in-ICU and in-hospital mortality risks within specified ranges. Subgroup analysis revealed interaction effects in the general obesity, abdominal obesity, and impaired fasting glucose subgroups (p = 0.014, 0.016, and < 0.001, respectively).

CONCLUSION

TyGI was associated with an increased sepsis-related short-term mortality risk and adverse outcomes after ICU admission.

Correlation of the triglyceride-glucose index and heart rate with 28-day all-cause mortality in severely ill patients: analysis of the MIMIC-IV database

BACKGROUND

Research has identified a link between the triglyceride-glucose index (TyG-i) and the risk of mortality in severely ill patients. However, it remains uncertain if the TyG-i affects mortality by influencing heart rate (HR).

METHODS

This study enrolled 3,509 severely ill participants from the Medical Information Mart for Intensive Care (MIMIC-IV) database who had triglyceride, glucose, and HR data upon entering the ICU. Cox regression models were applied to estimate the effect of the TyG-i and HR on 28-day all-cause mortality (ACM) and 28-day in-hospital mortality (IHM). Additionally, Kaplan-Meier (K-M) survival analysis was employed to explore outcome variations among different patient groups. The association of the TyG-i with HR, Sequential Organ Failure Assessment (SOFA) score, and Simplified Acute Physiology Score (SAPS) II was explored through linear regression analysis. Subgroup analysis explored potential interactions among patient characteristics, while sensitivity analysis gauged the robustness of the findings. Additionally, mediation analysis was conducted to assess whether elevated HR acts as an intermediary factor linking the TyG-i to both 28-day ACM and 28-day IHM.

RESULTS

During the 28-day follow-up, 586 cases (16.7%) died from all causes, and 439 cases (12.5%) died during hospitalisation. Cox results showed that individuals with a heightened TyG-i and elevated HR had the highest 28-day ACM (Hazard Ratio 1.70, P-value below 0.001) and 28-day IHM (Hazard Ratio 1.72, P-value below 0.001) compared to those with a reduced TyG-i and HR. The K-M curves showed that individuals with low TyG-i and low HR had the lowest incidence of 28-day ACM and 28-day IHM. The linear analysis results evidenced that the TyG-i was independently connected to HR (beta = 3.05, P-value below 0.001), and the TyG-i was also independently associated with SOFA score (beta = 0.39, P-value below 0.001) and SAPS II (beta = 1.79, P-value below 0.001). Subgroup analysis revealed a significant association in participants without hypertension, the interaction of an elevated TyG-i and HR strongly correlated with a higher 28-day death risk (interaction P-value below 0.05). Furthermore, HR mediated 29.5% of the connection between the TyG-i and 28-day ACM (P-value = 0.002), as well as 20.4% of the connection between the TyG-i and 28-day IHM (P-value = 0.002).

CONCLUSION

For severely ill patients, the TyG-i is distinctly correlated with HR, and elevated levels of both are strongly connected to greater 28-day ACM and 28-day IHM risks, especially in patients without hypertension. Furthermore, elevated HR mediates the connection between the TyG-i and 28-day mortality.

Triglyceride-glucose index and risk of all-cause and cardiovascular mortality in patients with cardiovascular disease: Analysis from 1999 to 2018 NHANES data

This research seeks to examine the correlation between the triglyceride-glucose index and the hazard of all-cause and cardiovascular death in individuals with cardiovascular disease (CVD). By evaluating the index, we can better anticipate and assess the risk and prognosis of CVD patients, and provide precise and individualized guidance for clinical treatment and management. Demographic and clinical data of 2185 CVD patients from 10 cycles of the National Health and Nutrition Examination Survey database from 1999 to 2018 were extracted for analysis. Employed the 3-level quantile method to group data, and a multivariate Cox proportional hazard model along with subgroup analysis to study the correlation between index and both mortalities. Additionally, restricted cubic spline examination was employed to assess the correlation, aiming to enhance the comprehension of their interrelation. Over the course of an average post-observation duration of 89.5 months involving 2185 CVD individuals, 607 patients suffered from all-cause mortality and 313 patients suffered from CVD-related mortality. An inverted U-shaped correlation was identified through restricted cubic spline analysis. During the multivariate COX regression analysis, it was found that individuals in the T2 and T3 had a dramatically lower hazard of both mortalities as opposed to those in the T1. The results were overall consistent across subgroup analyses according to age, gender, race, body mass index, diabetes, and hypertension, the interaction between these characteristics and the index was not remarkable (P > .05). Studies conducted on CVD individuals in the US have revealed a U-shaped correlation between triglyceride-glucose index and hazard of both all-cause and CVD-related death. However, further investigations are required to examine the particular function of index in forecasting the prognosis of CVD individuals. This will be helpful in accurately evaluating the risk and prognosis of CVD patients, and ultimately in developing more precise and personalized treatment and management strategies.

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study

BACKGROUND

Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop and test an individualized machine learning model to assess risk factors and predict in-hospital mortality in in these patients.

METHODS

From January 2012 to December 2021, this study collected data on elderly patients with heart failure and hypertension from the Chongqing Medical University Medical Data Platform. Least absolute shrinkage and the selection operator was used for recognizing key clinical variables. The optimal predictive model was chosen among eight machine learning algorithms on the basis of area under curve. SHapley Additive exPlanations and Local Interpretable Model-agnostic Explanations was employed to interpret the outcome of the predictive model.

RESULTS

This study ultimately comprised 4647 elderly individuals with hypertension and heart failure. The Random Forest model was chosen with the highest area under curve for 0.850 (95% CI 0.789-0.897), high accuracy for 0.738, recall 0.837, specificity 0.734 and brier score 0.178. According to SHapley Additive exPlanations results, the most related factors for in-hospital mortality in elderly patients with heart failure and hypertension were urea, length of stay, neutrophils, albumin and high-density lipoprotein cholesterol.

CONCLUSIONS

This study developed eight machine learning models to predict in-hospital mortality in elderly patients with hypertension as well as heart failure. Compared to other algorithms, the Random Forest model performed significantly better. Our study successfully predicted in-hospital mortality and identified the factors most associated with in-hospital mortality.

Triglyceride-glucose index is associated with all-cause mortality in critically ill patients with alcohol use disorder: a retrospective cohort study

BACKGROUND

The relationship between Triglyceride-glucose (TyG) index and clinical outcomes in patients with alcohol use disorder (AUD) is unclear. The aim of this study was to evaluate the association between TyG index and all-cause mortality in critically ill patients with AUD.

METHODS

We used data from the multi-parameter intelligent monitoring in intensive care IV (MIMIC-IV) database. The patients were equally divided into quartiles. Kaplan-Meier curves were used for survival analysis. The primary endpoint of the study was 28-day mortality, followed by 1-year mortality. We used Cox proportional hazard models to assess the relationship between TyG index and all-cause mortality at different endpoints.

RESULTS

A total of 537 AUD patients were included. Using TyG value as a continuous variable (HR 1.460, 95% CI 1.121-1.903, p = 0.005) and categorical variable (HR 1.447-3.477 from Q2 to Q4, with Q1 as reference), elevated TyG value was significantly associated with increased 28-day mortality. TyG was positively associated with 1-year mortality in AUD patients with an HR of 1.295 (95% CI 1.011-1.659, p = 0.041).

CONCLUSION

TyG index is positively associated with different clinical outcomes of critically ill AUD patients.

The triglyceride-glucose index dynamic trajectory reveals the association between the clinical subphenotype of insulin resistance and mortality in patients with sepsis

BACKGROUND

The relationship between the dynamic changes in insulin resistance (IR) and the prognosis of septic patients remains unclear. This study aims to investigate the correlation between the clinical subphenotype of IR represented by the triglyceride-glucose (TyG) index trajectory and the mortality rate among patients with sepsis.

METHODS

In this retrospective cohort study, we utilized data from septic patients within the Medical Information Mart for Intensive Care (MIMIC)-IV database version 2.0 to construct trajectories of the TyG index over 72 h. Subsequently, we computed the similarity among various TyG index trajectories with the dynamic time warping (DTW) algorithm and utilized the hierarchical clustering (HC) algorithm to demarcate distinct cluster and identified subphenotypes according to the trajectory trend. Subsequently, we assessed the mortality risk between different subphenotypes using analyses such as survival analysis and validated the robustness of the results through propensity score matching (PSM) and various models.

RESULTS

A total of 2350 patients were included in the study. Two trajectory trends: TyG index decreasing (n = 926) and TyG index increasing (n = 1424) were identified, which indicated corresponding to the clinical subphenotype of increased and alleviative IR respectively. The 28-day and in-hospital mortality for the increased IR group was 28.51% and 25.49% respectively. In comparison, patients in the alleviative IR group with a 28-day mortality of 23.54% and an in-hospital mortality of 21.60%. These subphenotypes exhibited distinct prognosis, time dependent Cox model showed the increased IR group with a higher 28-day mortality [hazard ratio (HR): 1.07, 95% confidence interval (CI): 1.02-1.12, P = 0.01] and in-hospital mortality [HR: 1.05, 95% CI: 1.00-1.11, P = 0.045] compared to the alleviative IR group. Sensitivity analyses with various models further validated the robustness of our findings.

CONCLUSION

Dynamic increase in the TyG index trajectory is associated with elevated mortality risk among patients with sepsis, which suggests that dynamic increased IR exacerbates the risk of poor outcomes in patients.

The nutritional metabolic risk index as a predictor of all-cause and cardiovascular mortality: A national cohort study

BACKGROUND

Recent studies show that malnutrition increases all-cause mortality by 1.11 times and cardiovascular mortality by 2.60 times. Similarly, metabolic syndrome raises overall mortality by 40% and cardiovascular mortality by 37%. This research assesses the Nutritional Metabolic Risk Index (NMRI) for predicting these mortality risks.

METHODS

We analyzed data from 14,209 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, where the NMRI was calculated based on the ratio of GNRI to TyG-WHtR. The relationship between NMRI and mortality was investigated using Kaplan-Meier methods and Cox regression models, with restricted cubic splines (RCS) employed to examine non-linear associations. The predictive capabilities of NMRI, GNRI, and TyG-WHtR for mortality were assessed using receiver operating characteristic curve (ROC) curve analysis.

RESULTS

Over a median follow-up period of 89 months, there were 1358 all-cause deaths and 345 cardiovascular deaths recorded. Cox regression analysis indicated that each unit increase in NMRI was associated with an 8% reduction in all-cause mortality risk and a 15% reduction in cardiovascular mortality risk. RCS analysis found a nonlinear negative correlation between NMRI and both all-cause and cardiovascular mortality. NMRI demonstrated superior predictive accuracy for all-cause mortality (AUC: 0.696, 95% CI: 0.682-0.710) and cardiovascular mortality (AUC: 0.713, 95% CI: 0.689-0.737) compared to GNRI and TyG-WHtR (P < 0.05).

CONCLUSIONS

The NMRI is inversely associated with the risk of all-cause and cardiovascular mortality in American adults.

Chronic low-grade inflammation associated with higher risk and earlier onset of cardiometabolic multimorbidity in middle-aged and older adults: a population-based cohort study

Evidence regarding the role of chronic low-grade inflammation in the progression of cardiometabolic diseases (CMDs) and cardiometabolic multimorbidity (CMM) is currently limited. This prospective cohort study, utilising data from the UK Biobank, included 273,804 adults aged 40-69 years initially free of CMD at baseline. CMM was defined as the coexistence of two or more CMDs, such as coronary artery disease, type 2 diabetes mellitus, hypertension and stroke. The aggregated inflammation score (INFLA-score), incorporating C-reactive protein, white blood cell count, platelet count and granulocyte-to-lymphocyte ratio, quantified chronic low-grade inflammation. Absolute risks (ARs), hazard ratios (HRs) and 95% confidence intervals (CIs) assessed the association of increased INFLA-score with the risk of CMMs and CMDs. The accelerated failure time model explored the effect of INFLA-score on the time to CMM onset, and a restricted cubic spline characterised the dose-dependent relationship between INFLA-score and CMM risk. After a median follow-up of 166.37 months, 13,755 cases of CMM were identified. In quartiles with increasing INFLA-score levels, CMM ARs were 4.41%, 4.49%, 5.04% and 6.01%, respectively; HR increased by 2%, 15% and 36%, respectively, compared to the lowest quartile. The INFLA-score and CMM risk relationship was nonlinear (P for nonlinear < 0.001), exhibiting a significant risk trend change at a score of 9. For INFLA-score < 9, CMM risk increased by 1.9% for each 1-point increase; for INFLA-score ≥ 9, the risk increased by 5.9% for each 1-point increase. Additionally, a higher INFLA-score was associated with an earlier onset of CMM (P < 0.001). Compared to the first INFLA-score quartile, the AFT model revealed adjusted median times to CMM occurrence were 2.92, 6.10 and 13.19 months earlier in the second, third and fourth quartile groups, respectively. Chronic low-grade inflammation is associated with a higher risk of cardiometabolic multimorbidity and earlier onset among middle-aged and older adults. Monitoring and screening the INFLA-score in adults without CMDs may improve early prevention of CMM.

Prognostic value of red blood cell distribution width-to-albumin ratio in ICU patients with coronary heart disease and diabetes mellitus

BACKGROUND

The red blood cell distribution width (RDW)-to-albumin ratio (RAR) has emerged as a potentially valuable prognostic indicator in diverse medical conditions. However, the prognostic significance of RAR in intensive care unit (ICU) patients with coronary heart disease (CHD) and diabetes mellitus (DM) remains uncertain and requires further investigation.

METHODS

This study aims to investigate the prognostic significance of RAR in ICU patients with coexisting CHD and DM through a retrospective cohort analysis using data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database (version 2.2). The study population included patients aged 18 years or older who were diagnosed with both CHD and DM. The primary endpoint was 1-year mortality, and the secondary endpoints included 30-day mortality, 90-day mortality, hospital length of stay (LOS), and ICU LOS.

RESULTS

A total of 3416 patients, of whom 64.64% were male, were included in the study. The 30-day mortality, 90-day mortality, and 1-year mortality were 7.08%, 7.44%, and 7.49%, respectively. After adjusting for confounding factors, multivariate Cox proportional risk analysis demonstrated that high RAR levels were associated with an increased risk of 30-day mortality (HR, 1.53 [95% CI 1.17-2.07], P = 0.006), 90-day mortality (HR, 1.58 [95% CI 1.17-2.13], P = 0.003), and 1-year mortality (HR, 1.58 [95% CI 1.17-2.13], P = 0.003). Furthermore, the restricted cubic spline (RCS) model indicated a linear relationship between RAR and 1-year mortality.

CONCLUSION

The results suggest that RAR holds potential as a valuable prognostic biomarker in ICU patients with both CHD and DM. Elevated RAR levels were found to be significantly associated with increased mortality during hospitalization, facilitating the identification of individuals at higher risk of adverse outcomes. These findings underscore the importance of incorporating RAR into risk stratification and overall management strategies for ICU patients with coexisting CHD and DM.

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 Levels Positively Associated with Higher Risk of Low Muscle Mass in Patients with Type 2 Diabetes

Aim

Although the interplay of insulin resistance (IR) and low muscle mass is increasingly recognized, it remains unknown whether the triglyceride-glucose (TyG) index, as an indicator of IR, is associated with low muscle mass in patients with type 2 diabetes (T2D). Our study aimed to investigate the association between TyG index and low muscle mass in hospitalized T2D patients.

Methods

This cross-sectional study involved 2687 hospitalized participants with T2D. The TyG index was calculated by fasting plasma glucose (FPG) and triglyceride levels. The outcome variables were defined as appendicular skeletal muscle mass index (ASMI) and low muscle mass. To explore the relationship between TyG index and low muscle mass, we conducted the multivariate linear regression, multivariate logistic regression, and subgroup analysis.

Results

In the fully adjusted multivariate linear regression, there was a negative correlation between TyG index (β=-0.10, 95% CI: -0.14, -0.06) and ASMI. TyG index (OR = 1.34, 95% CI: 1.08, 1.65) had a more significant association with low muscle mass compared to FPG (OR = 1.05, 95% CI: 1.01, 1.09) and glycated hemoglobin A1c (OR = 1.07, 95% CI: 0.99, 1.15). The statistical significance of the trend persisted among the TyG index quartile groups. Subgroup analysis revealed stronger positive associations between TyG index and low muscle mass in females, individuals aged 60 years or older, those with a body mass index of 28kg/m2 or higher, and HbA1c levels of 6.5% or higher, as well as those with hypertension and dyslipidemia.

Conclusion

A higher TyG index level is positively associated with a higher risk of low muscle mass, suggesting that TyG index could be a potential biomarker of low muscle mass in hospitalized T2D patients.

Predictive value of the triglyceride-glucose index for short- and long-term all-cause mortality in patients with critical coronary artery disease: a cohort study from the MIMIC-IV database

BACKGROUND

Triglyceride-glucose (TyG) index is linked to a poor prognosis for cardiovascular condition and is a valid indicator of insulin resistance. This study evaluated the potential predicting usefulness of the TyG index for all-cause mortality, both short- and long-term, for those concerning critical coronary artery disease (CAD).

METHODS

In this study, information from 5452 critically-ill individuals with CAD in intensive care units were gathered from the Medical Information Marketplace in Intensive Care (MIMIC-IV) database. Depending on the TyG index degree, the patients were categorized into three categories. Clinical outcomes included short-term (30-day) and long-term (365-day) all-cause mortality. The corresponding relationships involving the TyG index and clinical outcomes were examined by deploying restricted cubic spline (RCS) regression analysis and Cox proportional risk regression.

RESULTS

An increased TyG index was associated with increased 30-day (Tertile 1: 6.1%, Tertile 2: 7.3%, Tertile 3: 9.2%, P = 0.001) and 365-day (Tertile 1: 15.2%, Tertile 2: 17.0%, Tertile 3: 19.6%, P = 0.002) death rates across all causes. Cox regression with multiple variables indicates that higher TyG indices were linked to higher all-caused mortality hazard ratios throughout the short and long terms, with a larger predictive value for the former. RCS regression analyses suggested that the risk of death was notably and linearly that is associated with TyG index.

CONCLUSIONS

The TyG index is a reliable predictor of all-cause mortality at different stages in critically ill CAD patients, with a higher predictive ability for short-term mortality. Early intervention in patients with elevated TyG index may improve their survival outcomes. Future research should delve into understanding its pathophysiological mechanisms and develop intervention strategies based on the TyG index, providing new insights and strategies to enhance the outlook for critically ill CAD patients.

Oxidative stress mediates the association between triglyceride-glucose index and risk of cardiovascular and all-cause mortality in metabolic syndrome: evidence from a prospective cohort study

BACKGROUND

The aim of this study was to investigate the relationship between triglyceride-glucose (TyG) index and cardiovascular disease (CVD) and all-cause mortality in adults with metabolic syndrome (MeS) and explore the mediating role of oxidative stress.

METHODS

This study included 6131 adults with MeS from the National Health and Nutrition Examination Survey (NHANES). The relationships between TyG index and mortality were elucidated using multivariate Cox proportional hazards models, restricted cubic splines (RCS) Fine-Gray competing risk model. In addition, mediation analysis was used to test the indirect effect of oxidative stress indicators.

RESULTS

Over a median 106-month follow-up, a total of 357 CVD and 1292 all-cause deaths were recorded. After multivariate adjustment, there was a J-type relationship between TyG index and CVD and all-cause mortality, with optimal inflection point of 9.13 and 8.92. After the threshold point, TyG index was positively associated with CVD (HR: 4.21, 95%CI: 1.82, 9.78) and all-cause mortality(HR: 2.93, 95%CI: 2.05, 4.18). Even using non-cardiovascular mortality as a competitive risk, the Fine-Gray model also illustrated that the cumulative CVD mortality incidence was higher in MeS with TyG index >9.13 (Fine-Gray P< 0.01). Mediation analysis revealed that biomarkers of oxidative stress, including gamma-glutamyl transferase and uric acid, collectively mediated 10.53% of the association between the TyG index and CVD mortality, and 8.44% of the association with all-cause mortality (P < 0.05).

CONCLUSION

In the cohort study, TyG index was found to have a J-shaped association with CVD mortality and all-cause mortality in MeS population and oxidative stress may play a key mediating role in this relationship.

Association between the triglyceride-glucose index and mortality in critically ill patients: A meta-analysis

BACKGROUND

To further identify the association of the triglyceride-glucose (TyG) index with the risk of mortality among critically ill patients admitted to the intensive care unit (ICU).

METHODS

The PubMed, Web of Science, and EMBASE databases were searched for relevant studies up to February 2, 2024. The primary outcomes were in-hospital mortality and ICU mortality. The secondary outcomes were 30-day mortality, 90-day mortality, and 1-year mortality. The hazard ratios (HRs) with 95% confidence intervals (CIs) were combined to evaluate the associations between the TyG index and the above endpoints. All the statistical analyses were performed with STATA 15.0 software.

RESULTS

Ten studies involving 22,694 patients were included. The pooled results demonstrated that an elevated TyG index indicated an increased risk of in-hospital mortality (HR = 1.76, 95% CI: 1.41-2.18, P < .001), ICU mortality (HR = 1.52, 95% CI: 1.33-1.74, P < .001), 30-day mortality (HR = 1.50, 95% CI: 1.02-2.19, P = .037), 90-day mortality (HR = 1.42, 95% CI: 1.01-2.00, P = .043), and 1-year mortality (HR = 1.19, 95% CI: 1.11-1.28, P < .001). Subgroup analysis for in-hospital mortality and ICU mortality based on sex, age, body mass index and hypertension showed similar results. However, subgroup analysis stratified by diabetes mellitus (DM) revealed that the associations of the TyG index with in-hospital mortality (HR = 2.21, 95% CI: 1.30-3.78, P = .004) and ICU mortality (HR = 1.93, 95% CI: 0.95-3.94, P = .070) were observed only among patients without DM.

CONCLUSION

The TyG index was significantly associated with mortality among critically ill patients without DM, and an elevated TyG index predicted an increased risk of mortality.

Impact of the triglyceride-glucose index on 28-day mortality in non-diabetic critically Ill patients with sepsis: a retrospective cohort analysis

INTRODUCTION

Sepsis is a life-threatening condition that poses a globally high mortality rate. Identifying risk factors is crucial. Insulin resistance and the TYG index, associated with metabolic disorders, may play a role. This study explores their correlation with mortality in non-diabetic septic patients.

METHODS

This retrospective cohort study used data from the MIMIC-IV (version 2.1) database, which includes over 50,000 ICU admissions from 2008 to 2019 at Beth Israel Deaconess Medical Center in Boston. We included adult patients with sepsis who were admitted to the intensive care unit in the study. The primary outcome was to evaluate the ability of TYG to predict death at 28-day of hospital admission in patients with sepsis.

RESULTS

The study included 2213 patients with sepsis, among whom 549 (24.8%) died within 28 days of hospital admission. We observed a non-linear association between TYG and the risk of mortality. Compared to the reference group (lower TYG subgroup), the 28-day mortality increased in the higher TYG subgroup, with a fully adjusted hazard ratio of 2.68 (95% CI: 2.14 to 3.36). The area under the curve (AUC) for TYG was 67.7%, higher than for triglycerides alone (AUC = 64.1%), blood glucose (AUC = 62.4%), and GCS (AUC = 63.6%), and comparable to SOFA (AUC = 69.3%). The final subgroup analysis showed no significant interaction between TYG and each subgroup except for the COPD subgroup (interaction P-values: 0.076-0.548).

CONCLUSION

In our study, TYG can be used as an independent predictor for all-cause mortality due to sepsis within 28 days of hospitalization.

An overview of the application and potential mechanism on the triglyceride glucose index with multi-vessel coronary disease

Multi-vessel coronary disease (MVCD) is a severe form of coronary artery disease (CAD) that significantly increases the risk of acute coronary syndrome (ACS) and heart attacks. The triglyceride glucose (TyG) index is a reliable and convenient marker for insulin resistance (IR). Recent studies have demonstrated its predictive value for CAD in patients with MVCD. This review aims to explore the application of the TyG index in managing MVCD and its underlying pathogenesis to enhance risk stratification and improve therapeutic decision-making.

Value of the triglyceride-glucose index and related parameters in heart failure patients

The triglyceride-glucose (TyG) index, proven to be a crucial insulin resistance biomarker (better than the Homeostasis Model Assessment for Insulin Resistance), is simple and non-invasive. Recently, indisputable evidence has shown that the TyG index is strongly associated with cardiovascular disease [CVD, including atherosclerosis, heart failure (HF), and hypertension] prognosis and mortality. Nevertheless, the value of the TyG index in HF patients treated with sodium-glucose cotransporter 2 inhibitors (SGLT2is) has not been systematically evaluated. Therefore, in this review, we summarized the value of the TyG index and its related parameters as markers of CVD, especially HF. Furthermore, we addressed the use of SGLT2is and GLP-1 receptor antagonists in HF patients. Finally, we summarized the mechanism of the "obesity paradox."

Association between triglyceride-glucose index and sarcopenia in patients with chronic inflammatory airway disease

Objective

This research sought to explore the association between the triglyceride-glucose (TyG) index and the risk of sarcopenia in patients with chronic inflammatory airway disease (CIAD).

Methods

Data were obtained from the National Health and Nutrition Examination Survey 2011-2018. Grouping was performed using TyG index tertiles and multiple logistic regression was employed to assess the correlation between TyG levels and the risk of sarcopenia. The Receiver Operating Characteristic (ROC) curve analysis was conducted to determine the prognostic value of the TyG index for sarcopenia. Linear regression analysis was utilized to elucidate the direct relationship between TyG index and sarcopenia. Additionally, the curve between the TyG and sarcopenia indices was examined using a generalized additive model.

Results

The study included 981 individuals diagnosed with CIAD. After adjusting for potential confounders, a significant positive correlation was observed between TyG and sarcopenia (OR = 1.70, 95 % CI: 1.20-2.39, P = 0.002). Trend analysis using the chi-square test revealed an increase in sarcopenia prevalence concomitant with higher TyG levels (P < 0.05). Furthermore, linear regression analysis revealed a notable inverse linear association between the TyG and sarcopenia indices (β = -0.03; 95 % CI: -0.07-0.01; P = 0.020). The ROC curves corroborated the robust predictive capacity of TyG for sarcopenia among patients with CIAD, with an AUC of 0.685 (95 % CI: 0.636-0.735, P < 0.001).

Conclusion

Our research indicates a positive association between TyG and sarcopenia in CIAD patients. The TyG index may serve as a reliable marker for predicting sarcopenia risk in CIAD patients.

Association between the triglyceride glucose index and the risk of acute kidney injury in critically ill patients with hypertension: analysis of the MIMIC-IV database

Background

The triglyceride glucose (TyG) index, a metric computed from the levels of fasting triglyceride (TG) and fasting plasma glucose (FPG), has emerged as a simple surrogate measure for insulin resistance (IR) in recent years. In multiple critical care scenarios, such as contrast-induced acute kidney injury (AKI) and cardiorenal syndrome, a high TyG index levels shows a notable correlation with AKI incidence. However, its predictive value for AKI in critically ill hypertensive patients remains uncertain.

Methods

Participants were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and divided into quartiles based on the TyG index. The primary focus of the study was to investigate the risk of acute kidney injury (AKI), with in-hospital mortality as a secondary endpoint, assessed among all study subjects as well as specifically among AKI patients. The use of renal replacement therapy (RRT), indicative of AKI progression, was also considered a secondary endpoint reflecting renal outcomes. To explore the correlation between the TyG index and AKI risk in critically ill hypertensive patients, the study employed a restricted cubic splines model and Cox proportional hazards (CPH) models. Additionally, Kaplan-Meier survival analysis was utilized to assess differences in primary and secondary outcomes across groups categorized by their TyG index. Analyses were conducted to ensure the consistency of the predictive capability of TyG index across various subgroups.

Results

Our study included 4,418 participants, with 57% being male patients. AKI occurred in 56.1% of cases. Through the CPH analysis, we identified a significant association between the TyG index and AKI occurrence in critically ill hypertensive patients. With the help of a restricted cubic splines model, we observed a direct relationship between an elevated TyG index and an increased AKI. Subgroup examinations consistently proved the predictive value of the TyG index across categories. Furthermore, Kaplan-Meier survival analysis revealed notable differences in RRT among AKI patients.

Conclusion

The findings underscore the importance of the TyG index as a reliable predictor for the occurrence of AKI and adverse renal outcomes among hypertensive patients in critical ill states. Nevertheless, validating causality mandates extensive prospective investigations.

Association between Triglyceride-Glucose Index and risk of all-cause and cardiovascular mortality in adults with prior cardiovascular disease: a cohort study using data from the US National Health and Nutrition Examination Survey, 2007-2018

OBJECTIVE

The association between the Triglyceride-Glucose (TyG) Index and mortality rates in patients with cardiovascular disease (CVD) remains unclear. This study investigates the association between the TyG index and the incidence of all-cause and CVD-specific mortality among individuals with a history of CVD.

DESIGN

Population-based cohort study.

SETTING

Data were sourced from the US National Health and Nutrition Examination Survey (2007-2018) and linked mortality data, with follow-up continuing until 31 December 2019.

PARTICIPANTS

The study population comprised 3422 individuals aged 20 years or older with a documented history of CVD.

OUTCOME MEASURES

We examined the association between the TyG index and the risk of all-cause and cardiovascular mortality.

RESULTS

Over a median follow-up of 5.79 years, 1030 deaths occurred, including 339 due to CVD. Cox regression analysis, adjusted for multiple confounders, showed that individuals in the highest TyG index quartile, compared with those in the lowest, had HRs of 0.76 (95% CI: 0.60 to 0.96) for all-cause mortality and 0.58 (95% CI: 0.39 to 0.89) for CVD mortality. There was a significant inverse relationship between higher TyG index levels and lower mortality risks. For each unit increase in the TyG index, the adjusted HRs for all-cause and CVD mortality decreased by 18% (HR 0.82; 95% CI: 0.71 to 0.94) and 27% (HR 0.73; 95% CI: 0.57 to 0.92), respectively.

CONCLUSIONS

TyG index values are negatively associated with all-cause and CVD mortality risks among individuals with previous CVD. Further interventional studies are needed to clarify the impact of TyG levels on cardiovascular health.

U-shaped association between triglyceride-glucose index and all-cause mortality among critically ill pediatrics: a population-based retrospective cohort study

BACKGROUND

Previous studies have shown that an elevated triglyceride-glucose (TyG) index was associated with all-cause mortality in both general adult individuals and critically ill adult patients. However, the relationship between the TyG index and clinical prognosis in pediatric patients admitted to the intensive care unit (ICU) remains unknown. We aimed to investigate the association of the TyG index with in-hospital all-cause mortality in critically ill pediatric patients.

METHODS

A total of 5706 patients in the Pediatric Intensive Care database were enrolled in this study. The primary outcome was 30-day in-hospital all-cause mortality, and secondary outcome was 30-day in-ICU all-cause mortality. The restricted cubic spline (RCS) curves and two-piecewise multivariate Cox hazard regression models were performed to explore the relationship between the TyG index and outcomes.

RESULTS

The median age of the study population was 20.5 [interquartile range (IQR): 4.8, 63.0] months, and 3269 (57.3%) of the patients were male. The mean TyG index level was 8.6 ± 0.7. A total of 244 (4.3%) patients died within 30 days of hospitalization during a median follow-up of 11 [7, 18] days, and 236 (4.1%) patients died in ICU within 30 days of hospitalization during a median follow-up of 6 [3, 11] days. The RCS curves indicated a U-shape association between the TyG index and 30-day in-hospital and in-ICU all-cause mortality (both P values for non-linear < 0.001). The risk of 30-day in-hospital all-cause mortality was negatively correlated with the TyG index until it bottoms out at 8.6 (adjusted hazard ratio [HR], 0.72, 95% confidence interval [CI] 0.55-0.93). However, when the TyG index was higher than 8.6, the risk of primary outcome increased significantly (adjusted HR, 1.51, 95% CI 1.16-1.96]). For 30-day in-ICU all-cause mortality, we also found a similar relationship (TyG < 8.6: adjusted HR, 0.75, 95% CI 0.57-0.98; TyG ≥ 8.6: adjusted HR, 1.42, 95% CI 1.08-1.85). Those results were consistent in subgroups and various sensitivity analysis.

CONCLUSIONS

Our study showed that the association between the TyG index and 30-day in-hospital and in-ICU all-cause mortality was nonlinear U-shaped, with a cutoff point at the TyG index of 8.6 in critically ill pediatric patients. Our findings suggest that the TyG index may be a novel and important factor for the short-term clinical prognosis in pediatric patients.

Triglyceride-glucose index predicts all-cause mortality, but not cardiovascular mortality, in rural Northeast Chinese patients with metabolic syndrome: a community-based retrospective cohort study

BACKGROUND

Metabolic syndrome (MetS) includes a group of metabolic irregularities, including insulin resistance (IR), atherogenic dyslipidemia, central obesity, and hypertension. Consistent evidence supports IR and ongoing low-grade inflammation as the main contributors to MetS pathogenesis. However, the association between the triglyceride-glucose (TyG) index and mortality in people with MetS remains uncertain. The objective of this study was to examine the correlation between the baseline TyG index and all-cause and cardiovascular (CV) mortality in rural Northeast Chinese individuals with MetS.

METHODS

For the Northeast China Rural Cardiovascular Health Study, 3918 participants (mean age, 55 ± 10; 62.4% women) with MetS at baseline were enrolled in 2012-2013 and followed up from 2015 to 2017. The TyG index was calculated using the equation TyG index = ln [fasting TG (mg/dL) × fasting glucose (mg/dL)/2] and subdivided into tertiles [Q1(< 8.92); Q2 (8.92-9.36); Q3 (≥ 9.36)]. Multivariate Cox proportional hazards models were developed to examine the correlations between mortality and the baseline TyG index.

RESULTS

During a median of 4.66 years of follow-up, 196 (5.0%) all-cause deaths and 108 (2.8%) CV disease-related deaths occurred. The incidence of all-cause mortality was significantly different among TyG index tertiles of the overall population (P = 0.045). Kaplan-Meier analysis demonstrated a significantly increased risk of all-cause mortality in rural Chinese patients with a higher TyG index (log-rank P < 0.05). After adjusting for possible confounders, Cox proportional hazard analysis revealed that the TyG index could effectively predict all-cause mortality (HR for the third vs. first tertile of TyG was 1.441 [95% confidence interval, 1.009-2.059]), but not CV mortality, in rural Chinese patients with MetS.

CONCLUSIONS

The TyG index is an effective predictor of all-cause mortality in rural Chinese patients with MetS. This indicates that the TyG index may be useful for identifying rural Chinese individuals with MetS at a high risk of death.

Triglyceride-glucose index as a potential predictor for in-hospital mortality in critically ill patients with intracerebral hemorrhage: a multicenter, case-control study

BACKGROUND

The correlation between the triglyceride-glucose index (TyG) and the prognosis of ischemic stroke has been well established. This study aims to assess the influence of the TyG index on the clinical outcomes of critically ill individuals suffering from intracerebral hemorrhage (ICH).

METHODS

Patients diagnosed with ICH were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD). Various statistical methods, including restricted cubic spline (RCS) regression, multivariable logistic regression, subgroup analysis, and sensitivity analysis, were employed to examine the relationship between the TyG index and the primary outcomes of ICH.

RESULTS

A total of 791 patients from MIMIC-IV and 1,113 ones from eICU-CRD were analyzed. In MIMIC-IV, the in-hospital and ICU mortality rates were 14% and 10%, respectively, while in eICU-CRD, they were 16% and 8%. Results of the RCS regression revealed a consistent linear relationship between the TyG index and the risk of in-hospital and ICU mortality across the entire study population of both databases. Logistic regression analysis revealed a significant positive association between the TyG index and the likelihood of in-hospital and ICU death among ICH patients in both databases. Subgroup and sensitivity analysis further revealed an interaction between patients' age and the TyG index in relation to in-hospital and ICU mortality among ICH patients. Notably, for patients over 60 years old, the association between the TyG index and the risk of in-hospital and ICU mortality was more pronounced compared to the overall study population in both MIMIC-IV and eICU-CRD databases, suggesting a synergistic effect between old age (over 60 years) and the TyG index on the in-hospital and ICU mortality of patients with ICH.

CONCLUSIONS

This study established a positive correlation between the TyG index and the risk of in-hospital and ICU mortality in patients over 60 years who diagnosed with ICH, suggesting that the TyG index holds promise as an indicator for risk stratification in this patient population.

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.