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
Ontology highlight
ABSTRACT:
SUBMITTER: Wang H
PROVIDER: S-EPMC11340174 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundThe triglyceride-glucose (TyG) index was significantly associated with insulin resistance (IR). Several studies have validated the effect of TyG index on cerebrovascular disease. However, the value of TyG index in patients with severe stroke requiring ICU admission remains unclear. The aim of this study was to investigate the association between the TyG index and clinical prognosis of critically ill patients with ischemic stroke (IS).MethodsThis study identified patients with severe IS requiring ICU admission from the Medical Information Mart for Intensive Care (MIMIC-IV) database, and divided them into quartiles based on TyG index level. The outcomes included in-hospital mortality and ICU mortality. The association between the TyG index and clinical outcomes in critically ill patients with IS was elucidated using Cox proportional hazards regression analysis and restricted cubic splines.ResultsA total of 733 patients (55.8% male) were enrolled. The hospital mortality and intensive care unit (ICU) mortality reached 19.0% and 14.9%, respectively. Multivariate Cox proportional hazards analysis showed that the elevated TyG index was significantly related to all-cause death. After confounders adjusting, patients with an elevated TyG index had a significant association with hospital mortality (adjusted hazard ratio, 1.371; 95% confidence interval, 1.053-1.784; P = 0.013) and ICU mortality (adjusted hazard ratio, 1.653; 95% confidence interval, 1.244-2.197; P = 0.001). Restricted cubic splines revealed that a progressively increasing risk of all-cause mortality was related to an elevated TyG index.ConclusionThe TyG index has a significant association with hospital and ICU all-cause death in critically ill patients with IS. This finding demonstrates that the TyG index might be useful in identifying patients with IS at high risk of all-cause death.
| S-EPMC10262584 | biostudies-literature
Project description:BackgroundResearch 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).MethodsThis 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.ResultsDuring 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).ConclusionFor 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.
| S-EPMC11580213 | biostudies-literature
Project description:BackgroundHemorrhagic stroke (HS), including non-traumatic intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH), constitutes a substantial proportion of cerebrovascular incidents, accounting for around 30% of stroke cases. The triglyceride-glucose index (TyG-i) represents a precise insulin resistance (IR) indicator, a crucial metabolic disturbance. Existing literature has demonstrated an association between TyG-i and all-cause mortality (ACM) among individuals suffering from ischemic stroke (IS). Yet, the TyG-i prognostic implications for severe HS patients necessitating intensive care unit (ICU) admission are not clearly understood. Considering the notably elevated mortality and morbidity associated with HS relative to IS, investigating this association is warranted. Our primary aim was to investigate TyG-i and ACM association among critically ill HS patients within an ICU context.MethodsHerein, patients with severe HS were identified by accessing the Medical Information Mart for Intensive Care-IV (MIMIC-IV, version 2.2) database, using the International Classification of Diseases (ICD)-9/10 as diagnostic guidelines. Subsequently, we stratified the subjects into quartiles, relying on their TyG-i scores. Moreover, we measured mortality at ICU, in-hospital, 30 days, 90 days, and 1 year as the outcomes. Cox proportional hazards regression analysis and restricted cubic splines (RCS) were deployed for elucidating the relation between the TyG-i and ACM while utilizing the Kaplan-Meier (K-M) method to estimate survival curves. The findings' robustness was assessed by conducting subgroup analysis and interaction tests employing likelihood ratio tests.ResultsThe analysis included 1475 patients, with a male predominance of 54.4%. Observed mortality rates in the ICU, hospital, 30 days, 90 days, and 1 year were 7.3%, 10.9%, 13.8%, 19.7%, and 27.3%, respectively. Multivariate Cox regression analysis results manifested that heightened TyG-i was significantly related to ACM at 30 days (adjusted hazard ratio [aHR]: 1.32; 95% confidence interval [CI]: 1.05-1.67; P = 0.020), 90 days (aHR: 1.27; 95% CI: 1.04-1.55; P = 0.019), and 1 year (aHR: 1.22; 95% CI: 1.03-1.44; P = 0.023). The results of RCS analysis demonstrated a progressive elevation in ACM risk with rising TyG-i levels. Interaction tests found no significant effect modification in this relationship.ConclusionIn summary, TyG-i exhibits a significant correlation with ACM among patients enduring critical illness due to HS. This correlation underscores the probable utility of TyG-i as a prognostic tool for stratifying HS patients according to their risk of mortality. Applying TyG-i in clinical settings could enhance therapeutic decision-making and the management of disease trajectories. Additionally, this investigation augments existing research on the linkage between the TyG-i and IS, elucidating the TyG-i's role in predicting mortality across diverse stroke categories.
| S-EPMC10949583 | biostudies-literature
Project description:BackgroundThe TyG-BMI index, which is a reliable indicator of insulin resistance (IR), has been found to have a significant correlation with the occurrence of cardiovascular events. However, there still lacks study on the TyG-BMI index and prognosis in patients with atrial fibrillation (AF). The objective of the present study was to evaluate the relationship between TyG-BMI index at admission to ICU and all-cause mortality in critically ill patients with AF.MethodsThe patient's data were extracted from Medical Information Mart for Intensive Care IV(MIMIC-IV) database. All patients were divided into four groups according to TyG-BMI index. Outcomes include primary and secondary endpoints, with the primary endpoint being the 30-day and 365-day all-cause mortality and the secondary endpoint being the 90-day and 180-day all-cause mortality. TyG-BMI index was quartile and Kaplan-Meier curve was used to compare the outcome of each group. Cox proportional-hazards regression model and restricted cubic splines (RCS) were conducted to assess the relationship between TyG-BMI index and outcomes.ResultsOut of a total of 2509 participants, the average age was 73.26 ± 11.87 years, with 1555 (62.0%) being males. Patients with lower level of TyG-BMI had higher risk of 30-day, 90-day, 180-day and 365-day all-cause mortality, according to the Kaplan-Meier curves (log-rank P < 0.001). In addition, cox proportional-hazards regression analysis revealed that the risk of 30-day, 90-day, 180-day and 365-day all-cause mortality was significantly higher in the lowest quartile of TyG-BMI. Meanwhile, the RCS analysis indicated that L-typed relationships between TyG-BMI index and all-cause mortality, with inflection points at 223.60 for 30-day and 255.02 for 365-day all-cause mortality, respectively. Compared to patients with TyG-BMI levels below the inflection points, those with higher levels had a 1.8% lower risk for 30-day all-cause mortality (hazard ratio [HR] 0.982, 95% confidence interval [CI] 0.9676-0.988) and 1.1% lower risk for 365-day all-cause mortality (HR 0.989, 95% CI 0.986-0.991).ConclusionIn critically ill patients with AF, a lower TyG-BMI level is significantly associated with a higher risk of 30-day, 90-day, 180-day and 365-day all-cause mortality. TyG-BMI index could be used as a valid indicator for grading and treating patients with AF in the ICU.
| S-EPMC10859027 | biostudies-literature
Project description:BackgroundThis study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in critically ill patients with sepsis.MethodsThis was a retrospective observational cohort study and data were obtained from the Medical Information Mart for Intensive Care-IV (MIMIC IV2.2) database. The participants were grouped into three groups according to the TyG index tertiles. The primary outcome was in-hospital all-cause mortality. Multivariable logistics proportional regression analysis and restricted cubic spline regression was used to evaluate the association between the TyG index and in-hospital mortality in patients with sepsis. In sensitivity analysis, the feature importance of the TyG index was initially determined using machine learning algorithms and subgroup analysis based on different subgroups was also performed.Results1,257 patients (56.88% men) were included in the study. The in-hospital, 28-day and intensive care unit (ICU) mortality were 21.40%, 26.17%, and 15.43% respectively. Multivariate logistics regression analysis showed that the TyG index was independently associated with an elevated risk of in-hospital mortality (OR 1.440 [95% CI 1.106-1.875]; P = 0.00673), 28-day mortality (OR 1.391; [95% CI 1.52-1.678]; P = 0.01414) and ICU mortality (OR 1.597; [95% CI 1.188-2.147]; P = 0.00266). The restricted cubic spline regression model revealed that the risks of in-hospital, 28-day, and ICU mortality increased linearly with increasing TyG index. Sensitivity analysis indicate that the effect size and direction in different subgroups are consistent, the results is stability. Additionally, the machine learning results suggest that TyG index is an important feature for the outcomes of sepsis.ConclusionOur study indicates that a high TyG index is associated with an increased in-hospital mortality in critically ill sepsis patients. Larger prospective studies are required to confirm these findings.
| S-EPMC10634031 | biostudies-literature
Project description:BackgroundAcute kidney injury (AKI) is a common complication that affects the outcomes of patients undergoing percutaneous coronary intervention (PCI). The triglyceride-glucose (TyG) index, a metric computed from fasting blood triglyceride and glucose levels, is closely associated with poor PCI outcomes. This study examined the association between the TyG index and incidence of AKI in patients undergoing PCI.MethodsClinical information was obtained from the Medical Information Mart for Intensive Care IV database, which contains clinical data on 70,000 patients admitted to the intensive care unit at Beth Israel Deaconess Medical Center from 2008 to 2019. In total, 435 patients who underwent PCI were enrolled in this retrospective study, and they were categorized according to their AKI status, TyG quartiles, and diabetes mellitus (DM) history to analyze their baseline characteristics. The association of the TyG index with the risk of AKI was assessed using restricted cubic spline regression and logistic regression models. Subgroup analyses were also performed in patients with and without DM.ResultsCompared with the non-AKI population, patients with AKI who underwent PCI had a higher mean TyG index (p = 0.004). The restricted cubic spline regression model revealed a linear correlation between the TyG index and AKI risk (p for nonlinear = 0.123) in patients undergoing PCI. A high TyG index was a risk factor for AKI in non-DM subgroup, as well as in patients with BMI < 28 (odds ratio [OR] = 1.77; p = 0.050) and those with no history of diabetes (OR = 1.83; p = 0.047) or COPD (OR = 1.56; p = 0.030).ConclusionsThis study highlighted the role of the TyG index as a predictive biomarker for AKI in patients without DM undergoing PCI, providing clinicians with a tool for identifying high-risk individuals for early intervention.
| S-EPMC11874802 | biostudies-literature
Project description:BackgroundSepsis is a serious consequence of acute pancreatitis (AP) that requires immediate detection and treatment. Triglyceride-glucose (TyG) index demonstrated predictive ability for a number of diseases. In an effort to enhance clinical care and early warning systems, this study examined the association between the TyG index and sepsis risk with the aim of improving clinical care and early warning systems.MethodsPatients who were first admitted and satisfied the diagnostic criteria for acute pancreatitis (ICD-9: 5770; ICD-10: K85) were chosen from the MIMIC-IV database, excluding those lacking essential demographic or laboratory data. Using the Sepsis-3.0 criteria. Depending on whether they had sepsis or not, patients were divided into sepsis group and non-sepsis group. Utilizing the formula ln[(triglycerides mg/dl) × (glucose mg/dl)/2], the TyG index was calculated. The Boruta algorithm and Xgboost model were used for feature selection in order to pinpoint the important variables affecting results. Logistic regression with univariate and multivariate factors were used to assess the association between the TyG index and the start of sepsis after admission.ResultsTwenty-eight thousand AP patients were screened in all, among which 661 patients were ultimately included in the study. Of these, 228 patients (34.5%) developed sepsis. The TyG index was shown to have a significant correlation (OR = 1.891, 95% CI: 1.408-2.555) with sepsis, and an increased risk of sepsis was observed with an increase in the TyG index (all P values for trend < 0.001). Subgroup analysis showed that among patients of various ages, sexes, and with hypertension and diabetes, there was a positive association between the TyG index and the probability of sepsis (all P values for trend < 0.05). The combination of the TyG index with clinical indicators had an area under the curve (AUC) of 0.828 (0.794-0.862), which was significantly greater than that of the TyG index alone (0.657 [0.613-0.701]), with a statistically significant difference (Z= -7.362, P < 0.001).ConclusionIn patients who have AP, the TyG index is substantially linked to a higher risk of sepsis, and when combined with clinical markers, its predictive power for sepsis is enhanced. The findings imply that the TyG index might be a helpful detection for determining which AP patients are at a higher risk of developing sepsis.
| S-EPMC11817547 | biostudies-literature
Project description:Although accumulating researches were done for investigating the relationship between triglyceride-glucose index (TyG index) and different diseases, none of the researches have been made in sepsis yet. In this study, we aimed to explore the relationship between TyG index and clinical outcomes in sepsis based on a large critical care public database. Sepsis patients in Medical Information Mart for Intensive Care IV (MIMIC-IV) Database were included. The exposure was TyG index, which was calculated by the equation: ln (TG (mg/dL) × FBG (mg/dL)/2). The outcomes were in-hospital mortality and 1-year mortality. The relationship between TyG index and outcomes was performed by Cox regression analysis. Smooth fitting curves were constructed by using generalized additive model. Kaplan-Meier analyses for cumulative hazard of 1-year mortality in different groups were done. 1103 sepsis patients were included with a median TyG index of 9.78. The mortalities of in-hospital and 1-year were 37.53% (n = 414) and 42.25% (n = 466), respectively. After adjusting confounders, there was a significantly negative relationship between TyG index and mortalities of in-hospital and 1-year. With the per unit increment in TyG index, the risk of in-hospital and 1-year mortality both decreased by 21% (HR = 0.79, 95% CI: 0.66-0.94, p = 0.0086 and HR = 0.79, 95% CI: 0.66-0.94, p = 0.0080, respectively). A negative relationship between TyG index and clinical outcomes in sepsis was found.
| S-EPMC11358033 | biostudies-literature
Project description:Triglyceride-glucose (TyG) index has emerged as a novel biomarker for detecting insulin resistance (IR) and has been proven to be associated with various diseases. However, its correlation with the prognosis of severe sepsis remains unraveled. This retrospective cohort study utilized patient records from the Medical Information Mart for Intensive Care (MIMIC-IV, version 2.2) to examine the outcomes of patients with sepsis. The primary outcomes were hospital mortality and intensive care unit (ICU) mortality. The correlation between the TyG index and outcomes was evaluated through the Kaplan-Meier method, the Log-rank test, and univariate and multivariate Cox regression analyses. Additionally, restricted cubic spline (RCS) regression analysis was employed to delve into the nonlinear relationship between baseline TyG index and outcomes, with trend significance assessed through quartile levels. Subgroup analyses were conducted to evaluate the consistency of the TyG index's prognostic value across various influencing factors. The study included 1,742 patients with sepsis requiring intensive care. The in-hospital mortality rate was 19.75% (344/1,742), and the ICU mortality rate was 14.75% (257/1,742). Cox regression analysis revealed that, in comparison to the first quartile (Q1), patients in the fourth quartile (Q4) had a 63% higher risk of in-hospital mortality (HR 1.63 [95% CI 1.22 to 2.18], P < 0.01) and a 79% higher risk of ICU mortality (HR 1.79 [95% CI 1.28 to 2.51], P < 0.001). Model 3 showed that ICU mortality risks for Q4, Q3, and Q2 were 240%, 75%, and 33% higher, respectively (HR 3.40 [95% CI 2.24 to 5.16], P < 0.001; HR 1.75 [95% CI 1.16 to 2.63], P = 0.007; HR 1.33 [95% CI 1.20 to 1.53], P < 0.001). RCS regression analysis identified a nonlinear association between the TyG index and mortality (overall P < 0.001; P for nonlinearity < 0.001, with an inflection point at 8.9). Subgroup analysis showed that the effect size and direction were consistent across different subgroups, suggesting the stability of the results. This study demonstrates that a higher TyG index is significantly associated with increased in-hospital and ICU mortality risk in critically ill sepsis patients, with evidence of non-linear correlation. Therefore, the TyG index helps identify the mortality prognosis of sepsis patients in the ICU.
| S-EPMC11473526 | biostudies-literature
Project description:BackgroundThe kidney is one of the most vulnerable organs in sepsis patients, which mainly manifests as sepsis-associated acute kidney injury (SA-AKI). The case fatality rate of SA-AKI is high, and thus, predicting the risk of SA-AKI-related death is hugely significant. Anion gap (AG) is an important indicator in critical illness patients. The present study aimed to analyze the predictive value of the AG for the short-term prognosis of SA-AKI patients.MethodsSA-AKI patient data from the Medical Information Mart for Intensive Care (MIMIC-IV) database were collected retrospectively. Hospitalized septic patients who meet the inclusion criteria were included in the final analysis. All laboratory test parameters only included the data generated within the first 24 hours after the patient entered the intensive care unit (ICU) and the extreme value. Univariate and multivariate logistic regression analyses were performed to analyze the risk factors related to the death of SA-AKI patients within 28 days during hospitalization in the ICU.ResultsA total of 3,684 SA-AKI patients were included, including 3,305 patients with low AG (<18 mmol/L) and 379 patients with high AG (≥18 mmol/L). Among these patients, 497 cases (13.5%) died during hospitalization, including 376 cases (11.4%) in the low AG group and 121 cases (31.9%) in the high AG group. Multivariate logistic regression analysis showed that elevated AG increased the risk of death in SA-AKI patients within 28 days during hospitalization in the ICU (odds ratio =1.2, 95% confidence interval: 1.2-1.3). Further analysis showed that the risk of death of SA-AKI patients within 28 days during hospitalization in the ICU was increased when AG ≥14 mmol/L. The relationship between AG level and the risk of death of SA-AKI patients during hospitalization was S-shaped.ConclusionsIn clinical practice, AG levels can serve as a valuable predictor of the death risk of SA-AKI patients during hospitalization.
| S-EPMC9843358 | biostudies-literature