Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Zhang S

PROVIDER: S-EPMC11302829 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Publications

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

Zhang Sen S Fan Tianhua T Wang Li L Chen Nan N Ma Liansheng L

BMC infectious diseases 20240805 1

<h4>Introduction</h4>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.<h4>Methods</h4>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 Deacones ...[more]

PMID: 39103750

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Project description:BackgroundWe determined utilizing a sepsis participant cohort whether there is a significant association between TyG-BMI (triglyceride glucose body mass index) and mortality rates at any stage.MethodsHerein, a historical cohort investigation approach was adopted, using information provided by the Medical Information Mart for Intensive Care-IV (MIMIC-IV). We categorized the included individuals in accordance with their TyG-BMI data quartiles, and the primary outcomes were mortality during the hospital stay and death rate due to any reason at postadmission day 28, 90, and 365. To evaluate TyG-BMI mortality's relationship with sepsis-induced mortality risk, we employed restricted cubic spline regression (RCS) and Cox regression models. Additionally, we confirmed TyG-BMI's significant predictive value for mortality via machine learning methods. Furthermore, we performed subgroup analyses to investigate possible differences among various patient groups.ResultsThe cohort included 4759 individuals, aged 63.9 ± 15.0 years, involving 2885 males (60.6%). The rates of death that took place during hospital stay and at 28, 90 and 365 days postadmission were respectively 19.60%, 24.70%, 28.80%, and 35.20%. As reflected by Cox models, TyG-BMI was negatively associated with mortality risk at various intervals: in-hospital [hazard ratio (HR) 0.47 (0.39-0.56), P = 0.003], 28 days postadmission [HR 0.42 (0.35-0.49), P < 0.001], 90 days postadmission [HR 0.41 (0.35-0.48), P < 0.001], and 365 days postadmission [HR 0.41 (0.35-0.47), P < 0.001]. Additionally, the relationship between TyG-BMI and death rates was L-shaped, as reflected by the RCS, with a TyG-BMI of 249 being the turning point.ConclusionsAmong sepsis patients in critical care, TyG-BMI is negatively correlated with mortality possibility at various intervals: during hospital stay and 28 days, 90 days, and one year postadmission. TyG-BMI is a beneficial parameter for categorizing risk levels among sepsis patients and for predicting their mortality risk within one year.

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.

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.

Project description:BackgroundPrevious 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.MethodsA 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.ResultsThe 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.ConclusionsOur 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.

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.

Project description:BackgroundThe triglyceride-glucose (TyG) index, proven a reliable and simple surrogate of insulin resistance, has shown potential associations with cardiovascular outcomes and renal diseases. This research delved into the utility of the TyG index in predicting the risk of acute kidney injury (AKI) in patients with coronary artery disease (CAD), an area not extensively covered in existing literature.MethodsA cohort of patients with CAD was recruited from the Medical Information Mart for Intensive Care-IV database, and categorized into quartiles based on their TyG index. The primary outcome was AKI incidence, and the secondary outcome was renal replacement therapy (RRT). Scatterplot histograms, cox proportional hazards models, Kaplan-Meier survival curves, and restricted cubic splines were employed to investigate the association between the TyG index and the risk of AKI in patients with CAD.ResultsA total of 1,501 patients were enrolled in this study, predominantly male (61.56%), with a median age of 69.80 years. The AKI incidence was 67.22% among all patients, with the AKI stages increased with higher TyG levels (P for trend <0.001). The Kaplan-Meier survival analyses demonstrated statistically significant differences in AKI incidence and RRT application throughout the entire cohort, stratified by the TyG index quartiles (p < 0.001). Additionally, the restricted cubic spline analysis revealed a non-linear association between the TyG index and the risk of AKI (P for non-linear =0.637). Both multivariate Cox proportional hazards analyses (HR 1.62; 95% CI 1.15-2.27; p = 0.005) and multivariate logistic regression analyses (OR 2.16; 95% CI 1.18-3.94; p = 0.012) showed that the elevated TyG index was significantly related to AKI incidence. The association between TyG index and the risk of AKI is more significant in patients without diabetes (HR 1.27; 95% CI 1.14-1.42; p < 0.001), compared to patients with diabetes (P for interaction =0.013).ConclusionsIn summary, the TyG index emerged as a reliable predictor for the occurrence of AKI in CAD patients during ICU stay. Furthermore, it is also anticipated to serve as a valuable indicator for non-diabetic patients in predicting the incidence of AKI.

Dataset Information

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

Introduction

Methods

Results

Conclusion

Publications

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

Similar Datasets

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