Association between the Triglyceride Glucose Index and All-Cause Mortality in Critically Ill Patients with Acute Kidney Injury
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PROVIDER: S-EPMC10843181 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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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.
| S-EPMC11843639 | biostudies-literature
Project description:BackgroundTriglyceride-glucose (TyG) index as a reliable surrogate of insulin resistance (IR) has been shown to be related to adverse clinical outcomes in patients with acute coronary syndrome, heart failure, ischemic stroke and so on. However, the relationship between TyG index and all-cause mortality in intensive care unit (ICU) patients remains unknown. The purpose of this study was to investigate the correlation between TyG index and all-cause mortality to evaluate the impact of IR on the prognosis of this population.MethodsThis was a retrospective observational study that included 3026 patients who had an initial triglyceride and glucose data on the first day of ICU admission, and all data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. These patients were grouped into quartiles (Q1-Q4) according to TyG index. The Kaplan-Meier analysis was used to compare all-cause mortality among the above four groups. Cox proportional hazards analyses were performed to examine the association between TyG index and all-cause mortality.ResultsDuring 10.46 years of follow-up, 1148 (37.9%) patients died, of which 350 (11.6%) occurred during the hospital stay and 258 (8.5%) occurred during the ICU stay. Kaplan-Meier analysis showed that the risk of all-cause mortality was significantly higher in patients with higher TyG index (log-rank P = 0.021). Multivariable Cox proportional hazards analyses showed that the TyG index was an independent risk predictor of ICU death (HR: 1.72, 95% CI 1.18-2.52, P = 0.005) and hospital death (HR: 2.19, 95% CI 1.59-3.03, P < 0.001), and each 1-unit increased in the TyG index, a 1.19-fold increase in the risk of death during the hospital stay.ConclusionsTyG index is strongly related to the all-cause mortality increasing in critically ill patients. This finding indicates that the TyG index might be useful in identifying people at high risk of ICU death and hospital death.
| S-EPMC9270811 | biostudies-literature
Project description:BackgroundTo 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).MethodsThe 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.ResultsTen 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.ConclusionThe TyG index was significantly associated with mortality among critically ill patients without DM, and an elevated TyG index predicted an increased risk of mortality.
| S-EPMC11332756 | biostudies-literature
Project description:BackgroundThe 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.MethodsWe 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.ResultsA 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).ConclusionTyG index is positively associated with different clinical outcomes of critically ill AUD patients.
| S-EPMC11483960 | biostudies-literature
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.
| S-EPMC11660890 | biostudies-literature
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.
| S-EPMC11210025 | biostudies-literature
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:BackgroundTo assess whether acute kidney injury (AKI) is independently associated with hospital mortality in ICU patients with sepsis, and estimate the excess AKI-related mortality attributable to AKI.MethodsWe analyzed adult patients from two distinct retrospective critically ill cohorts: (1) Medical Information Mart for Intensive Care IV (MIMIC IV; n = 15,610) cohort and (2) Wenzhou (n = 1,341) cohort. AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We applied multivariate logistic and linear regression models to assess the hospital and ICU mortality, hospital length-of-stay (LOS), and ICU LOS. The excess attributable mortality for AKI in ICU patients with sepsis was further evaluated.ResultsAKI occurred in 5,225 subjects in the MIMIC IV cohort (33.5%) and 494 in the Wenzhou cohort (36.8%). Each stage of AKI was an independent risk factor for hospital mortality in multivariate logistic regression after adjusting for baseline illness severity. The excess attributable mortality for AKI was 58.6% (95% CI [46.8%-70.3%]) in MIMIC IV and 44.6% (95% CI [12.7%-76.4%]) in Wenzhou. Additionally, AKI was independently associated with increased ICU mortality, hospital LOS, and ICU LOS.ConclusionAcute kidney injury is an independent risk factor for hospital and ICU mortality, as well as hospital and ICU LOS in critically ill patients with sepsis. Thus, AKI is associated with excess attributable mortality.
| S-EPMC8958971 | biostudies-literature
Project description:Background and objectivesAcute kidney injury (AKI) requiring dialysis is associated with high mortality. Most prognostic tools used to describe case complexity and to project patient outcome lack predictive accuracy when applied in patients with AKI. In this study, we developed an AKI-specific predictive model for 60-day mortality and compared the model to the performance of two generic (Sequential Organ Failure Assessment [SOFA] and Acute Physiology and Chronic Health Evaluation II [APACHE II]) scores, and a disease specific (Cleveland Clinic [CCF]) score.Design, setting, participants, & measurementsData from 1122 subjects enrolled in the Veterans Affairs/National Institutes of Health Acute Renal Failure Trial Network study; a multicenter randomized trial of intensive versus less intensive renal support in critically ill patients with AKI conducted between November 2003 and July 2007 at 27 VA- and university-affiliated centers.ResultsThe 60-day mortality was 53%. Twenty-one independent predictors of 60-day mortality were identified. The logistic regression model exhibited good discrimination, with an area under the receiver operating characteristic (ROC) curve of 0.85 (0.83 to 0.88), and a derived integer risk score yielded a value of 0.80 (0.77 to 0.83). Existing scoring systems, including APACHE II, SOFA, and CCF, when applied to our cohort, showed relatively poor discrimination, reflected by areas under the ROC curve of 0.68 (0.64 to 0.71), 0.69 (0.66 to 0.73), and 0.65 (0.62 to 0.69), respectively.ConclusionsOur new risk model outperformed existing generic and disease-specific scoring systems in predicting 60-day mortality in critically ill patients with AKI. The current model requires external validation before it can be applied to other patient populations.
| S-EPMC3359007 | biostudies-literature
Project description:BackgroundThe triglyceride glucose-body mass index (TyG-BMI) has been established as a convenient and reliable marker for assessing insulin resistance (IR) and has been shown to be significantly correlated with stroke. However, only a few studies have been conducted in this field, with conflicting conclusions.MethodsThis study based on the eICU database, investigated the association between TyG-BMI and 28-day mortality in critically ill ischemic stroke (IS) patients. Multivariate Cox regression models were employed to analyze the impacts of the TyG-BMI on 28-day hospital and ICU mortality. Restricted cubic splines (RCS) were applied to explore the nonlinear relationship between the TyG-BMI and 28-day mortality. K‒M curves were utilized for outcome comparisons among different TyG-BMI groups. Additionally, interaction and subgroup analyses were performed to validate the robustness of the results.ResultsA total of 1,362 critically ill patients with IS were enrolled, with a mean age of 68.41 ± 14.16 years; 47.50% were male. Multivariate Cox regression analysis revealed that, the high TyG-BMI group had significantly higher 28-day hospital mortality(HR = 1.734, P = 0.032) and ICU mortality (HR = 2.337, p = 0.048). RCS analysis showed a nonlinear positive correlation between the TyG-BMI and 28-day hospital mortality. Below the inflection point of the TyG-BMI = 380.37, each increase of 1 standard deviation (SD) (approximately 25.5 units) in the TyG-BMI was associated with a 37.3% increase in 28-day hospital mortality (HR = 1.373, P = 0.015), and above 380.376, each 1-SD increase in the TyG-BMI resulted in an 87.9% decrease in 28-day hospital mortality (HR = 0.121, P = 0.057). The log-likelihood ratio test P value = 0.004. For 28-day ICU mortality, the TyG-BMI exhibited a significant positive linear correlation in RCS.ConclusionsElevated TyG-BMI is significantly associated with an increased risk of short-term all-cause mortality in patients with critically ill IS in the United States. This result provides compelling evidence to address the existing discrepancies in this research domain, indicating that the TyG-BMI could serve as a straightforward and efficient biomarker for identifying critically ill IS patients at high risk of mortality.
| S-EPMC11869470 | biostudies-literature