Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database
Abstract Background This 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. Methods This was a retrospective observational cohort study and data were obtained from the Medical Information M...
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Published in | Cardiovascular diabetology Vol. 22; no. 1; pp. 1 - 307 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
BioMed Central
08.11.2023
BMC |
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Abstract | Abstract
Background
This 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.
Methods
This 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.
Results
1,257 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.
Conclusion
Our 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. |
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AbstractList | Abstract
Background
This 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.
Methods
This 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.
Results
1,257 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.
Conclusion
Our 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. 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. Abstract Background This 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. Methods This 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. Results 1,257 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. Conclusion Our 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. |
ArticleNumber | 307 |
Author | Zheng, Rui Lou, Chen Xu, Honglei Shi, Yiyi Pan, Jingye Qian, Songzan |
Author_xml | – sequence: 1 givenname: Rui surname: Zheng fullname: Zheng, Rui – sequence: 2 givenname: Songzan surname: Qian fullname: Qian, Songzan – sequence: 3 givenname: Yiyi surname: Shi fullname: Shi, Yiyi – sequence: 4 givenname: Chen surname: Lou fullname: Lou, Chen – sequence: 5 givenname: Honglei surname: Xu fullname: Xu, Honglei – sequence: 6 givenname: Jingye surname: Pan fullname: Pan, Jingye |
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CitedBy_id | crossref_primary_10_1186_s12933_024_02253_8 crossref_primary_10_1186_s12933_024_02215_0 crossref_primary_10_1016_j_heliyon_2024_e26570 crossref_primary_10_1186_s12933_023_02113_x crossref_primary_10_3389_fimmu_2024_1378730 |
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Snippet | Abstract
Background
This study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in... BackgroundThis study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in critically ill... BACKGROUNDThis study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in critically ill... Abstract Background This study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in... |
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SubjectTerms | Algorithms Binomial distribution Body mass index Cardiac arrhythmia Cardiovascular disease Chronic obstructive pulmonary disease Creatinine Disease prevention Feature selection Gender Glucose Hemoglobin Hospitals In-hospital mortality Insulin resistance Kidneys Learning algorithms Machine learning MIMIC-IV database Mortality Neutrophils Patients Regression analysis Sensitivity analysis Sepsis Software Standard scores Structured Query Language-SQL Triglyceride-glucose index Triglycerides Variables |
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Title | Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database |
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