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

Triglyceride-glucose index-A novel metabolism disorder biomarker as a promising indicator for predicting postoperative 30-day infections in elderly patients undergoing gastrointestinal-related abdominal and pelvic surgery

BACKGROUND

The triglyceride-glucose index, a reliable surrogate biomarker of insulin resistance, has been reported to be associated with cardiovascular events and atherosclerosis. However, few studies have investigated the association of the triglyceride-glucose index with postoperative infections. This study aimed to study the clinical risk values of the preoperative triglyceride-glucose index in postoperative infection complications in elderly patients undergoing gastrointestinal-related abdominal and pelvic surgery.

METHODS

This retrospective cohort study included 3,225 older patients who underwent gastrointestinal-related abdominal and pelvic surgery between 2014 and 2019. The patients were divided into groups of triglyceride-glucose index ≤8.268 and triglyceride-glucose index >8.268 according to the optimal triglyceride-glucose index cut-off value. The outcome of interest was postoperative infections within 30 days after surgery. Primary and subgroup analyses were performed to confirm that preoperative triglyceride-glucose index qualifies as a reliable, independent risk indicator. Propensity score matching analysis was further applied to address covariates' potential residual confounding effect and test the robustness of the results.

RESULTS

In this study, the median age was 71 years (interquartile range, 67, 75 years), the proportion of male patients was 66.3%, and 1,058 (32.8%) were infected within 30 days after surgery. A triglyceride-glucose index >8.268 was associated with an increased risk of postoperative infections in multivariate regression analysis (odds ratio, 1.37; 95% confidence interval, 1.15-1.64; P < .001). The correlation between the triglyceride-glucose index and postoperative infections remained significantly robust (odds ratio, 1.52; 95% confidence interval, 1.21-1.92; P < .001) in the propensity score matching analysis.

CONCLUSIONS

The triglyceride-glucose index elevation determined by the optimal cutoff value of 8.268 was an independent risk factor for developing postoperative infections.

Predictive value of triglyceride glucose index in acute kidney injury in patients with severe traumatic brain injury

Background At present, the relationship between the Triglyceride-glucose index (TyG index) and Acute kidney injury (AKI) in traumatic brain injury patients in the Intensive Care Unit (ICU) is still unclear. Currently, the relationship between TyG index and AKI occurred within 7 days in the ICU is a highly researched and trending topic. Objective In this study, we conducted in-depth exploration of the relationship between the development of AKI in traumatic brain injury (TBI) patients in the ICU and changes in TyG index, as well as its relevance. Methods A cross-sectional study was conducted with a total of 492 individuals enrolled in the Medical Information Mart for Intensive Care IV(MIMIC-IV) database. Multivariate model logistic regression, smoothed curve fitting and forest plots were utilized to confirm the study objectives. The predictive power of the TyG index for outcome indicators was assessed using subject work characteristics (ROC) curves. As well as comparing the Integrated Discriminant Improvement Index and the Net Reclassification Index of the traditional forecasting model with the addition of the TyG index. Results Of all eligible subjects, 55.9% were male and the incidence of AKI was 59.3%. There was a statistically significant difference in the incidence of AKI within 7 days in the ICU between the different TyG index groups. The difference between TyG index and the risk of AKI within 7 days in the ICU remained significant after adjustment for logistic multifactorial modeling (OR = 2.07, 95% CI = 1.41-3.05, P < 0.001). A similar pattern of associations was observed in subgroup analyses (P values for all interactions were greater than 0.05). The addition of TyG index to the traditional risk factor model improved the predictive power of the risk of AKI within 7 days in ICU (P < 0.05). Conclusion The findings of this study demonstrate a strong association between the TyG index and the occurrence of AKI within 7 days in ICU patients. The TyG index can potentially be used as a risk stratification tool for early identification and prevention of AKI. Implementing preventive strategies targeting patients with a high TyG index may help reduce the burden of AKI in the ICU. Further prospective studies are warranted to validate these findings and explore the clinical utility of the TyG index in AKI prevention.

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 role of the prognostic nutritional index in predicting mortality in stroke patients

OBJECTIVE

The aim of this study was to evaluate the role of the prognostic nutritional index in predicting in-hospital mortality among patients with acute ischemic stroke.

METHODS

This retrospective, observational study included patients diagnosed with acute ischemic stroke at the emergency department of the hospital between January 1, 2022, and January 1, 2023. Demographic data, vital parameters, comorbidities, stroke interventions, and laboratory data were collected from electronic medical records. Prognostic nutritional index was calculated using serum albumin levels and a total lymphocyte count. The primary outcome was in-hospital mortality.

RESULTS

The study included 176 patients, divided into survivor (93.2%, n=164) and deceased (6.8%, n=12) groups. No significant differences were observed in age, gender, blood pressure, heart rate, or body temperature between the groups. Atrial fibrillation was significantly more common in the deceased group (50%) compared to the survivor group (18.9%) (p=0.011). The median lymphocyte count was significantly higher in the survivor group (1,353 [interquartile range, IQR 984-1,968]/mm³) compared to the deceased group (660 [IQR 462-1,188]/mm³) (p=0.009). The median albumin level was significantly lower in the deceased group (3.31 [IQR 2.67-3.4] g/dL) compared to the survivor group (3.74 [IQR 3.39-4.21] g/dL) (p<0.001). The median prognostic nutritional index was significantly higher in the survivor group (46.05 [IQR 39.1-51.3]) compared to the deceased group (36.7 [IQR 28.7-40.5]) (p<0.001). The area under the receiver operating characteristic for prognostic nutritional index predicting mortality was 0.791 (95%CI 0.723-0.848) (p=0.0002), with a cut-off value of ≤41.92 providing the highest diagnostic accuracy.

CONCLUSIONS

Prognostic nutritional index is a valuable prognostic indicator for in-hospital mortality in acute ischemic stroke patients. Low prognostic nutritional index values are associated with increased mortality risk. Incorporating prognostic nutritional index into clinical practice may aid in the early identification of high-risk patients and the optimization of treatment strategies. Further research is needed to validate these findings and explore the broader clinical applications of prognostic nutritional index.

Non-linear association of triglyceride-glucose index with cardiovascular and all-cause mortality in T2DM patients with diabetic kidney disease: NHANES 2001-2018 retrospective cohort study

BACKGROUND

The triglyceride glucose (TyG) index is a cutting-edge and highly effective marker of insulin resistance, a crucial factor in the development and exacerbation of diabetic kidney disease (DKD). To date, there has been limited research on how the triglyceride-glucose (TyG) index affects the outlook for patients suffering from DKD.

METHODS

In this multicenter retrospective cohort study, the analysis recruited 2,203 DKD patients from the National Health and Nutrition Examination Survey (NHANES) dataset, which covers the US from 2001 to 2018. The research applied a Cox proportional hazards model with multiple variables to investigate the association of the TyG index with mortality outcomes. Restricted cubic splines (RCS) and methods for analyzing threshold effects were employed to identify possible non-linear relationships.

RESULTS

Over nearly 19 years of follow-up, this study captured data on 753 all-cause and 231 cardiovascular disease-specific fatalities. Sophisticated statistical methods, including RCS and smoothing curve adjustments via penalized splines, helped identify distinctive patterns: The baseline TyG index was observed to have a U-shaped pattern related to overall mortality and an L-shape with cardiovascular diseases(CVD) mortality among individuals with DKD. Notably, TyG index below 9.15 for overall mortality and 9.27 for CVD mortality were linked to reduced death rates (HR = 0.65, 95% CI = 0.52-0.82 for all-cause; HR = 0.58, 95% CI = 0.43-0.83 for CVD). On the other hand, TyG index exceeding these benchmarks (greater than 9.15 for all-cause and 9.27 for CVD) correlated with increased all-cause mortality risks (HR = 1.21, 95% CI = 1.02-1.43) and showed a non-significant change in CVD mortality risks (HR = 1.07, 95% CI = 0.83-1.38).

CONCLUSIONS

This study emphasizes the non-linear linkage involving the TyG index and death rates due to CVD and other factors in patients with DKD, demonstrating its effectiveness in estimating potential adverse events within this demographic.

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.

Association of triglyceride-glucose index and delirium in patients with sepsis: a retrospective study

OBJECTIVE

It is well known that glucose and lipid metabolism disorders and insulin resistance are common in sepsis, which affect the occurrence and prognosis of multiple organ dysfunction in septic patients. Previous study reported the predictive value of triglyceride-glucose index (TyG), a clinical indicator for insulin resistance, in postoperative delirium patients. However, it remains unclear whether the TyG index is a novel predictive biomarker for sepsis-associated delirium. The aim of this study is to explore the relationship between TyG index and the risk of delirium in patients with sepsis.

METHODS

Adult septic patients were identified from the MIMIC-IV database and divided into four groups based on the mean value of TyG. The primary outcome was the incidence of delirium. The association between TyG and the risk of developing delirium was evaluated by restricted cubic spline (RCS), multivariate logistic regression and subgroup analysis. Propensity Score Matching (PSM) method was used to balance the baseline data.

RESULTS

A total of 3,331 septic patients were included in the analysis, and further divided into four groups: Q1 (TyG ≤ 8.67), Q2 (8.67 < TyG ≤ 9.08), Q3 (9.08 < TyG ≤ 9.61), and Q4 (TyG > 9.61). The RCS curves demonstrated a non-linear positive relationship between TyG index and the risk of developing delirium, and an optimal cut-of value 9.09 was recommended. After balancing the baseline information by PSM, patients in the TyG > 9.09 group had a significant higher incidence of delirium compared with those in the TyG ≤ 9.09 group. In logistic regression analysis, TyG > 9.09 was significantly associated with lower risk of developing delirium in both original cohort (OR 1.54-1.78, all P < 0.001) and the PSM cohort (OR 1.41-1.48, all P < 0.001). No association was found between the TyG index and mortality (all P > 0.05). In subgroup analysis, our findings were consistent (all OR > 1 in all subgroups).

CONCLUSION

Our study demonstrated an independent association between TyG index and increased risk of delirium in septic patients, indicating that TyG index can serve as a biomarker for delirium in sepsis.

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 related indices and mortality among individuals with non-alcoholic fatty liver disease or metabolic dysfunction-associated steatotic liver disease

BACKGROUND

The prognostic value of triglyceride-glucose (TyG) related indices in non-alcoholic fatty liver disease (NAFLD) or metabolic dysfunction-associated steatotic liver disease (MASLD) is still unclear. This study aimed to determine the associations between TyG-related indices and long-term mortality in this population.

METHODS

The data came from the National Health and Nutrition Examination Survey (NHANES III) and National Death Index (NDI). Baseline TyG, TyG combining with body mass index (TyG-BMI), and TyG combining with waist circumference (TyG-WC) indices were calculated, and mortality status was determined through 31 December 2019. Multivariate Cox and restricted cubic spline (RCS) regression models were performed to evaluate the relationship between TyG-related indices and long-term mortality among participants with NAFLD/MASLD. In addition, we examined the association between TyG-related indices and all-cause mortality within subgroups defined by age, sex, race/ethnicity, and fibrosis-4 index (FIB-4).

RESULTS

There were 10,390 participants with completed ultrasonography and laboratory data included in this study. NAFLD was diagnosed in 3672/10,390 (35.3%) participants, while MASLD in 3556/10,390 (34.2%) amongst the overall population. The multivariate Cox regression analyses showed high levels of TyG-related indices, particularly in TyG-BMI and TyG-WC indices were significantly associated with the all-cause mortality, cardiovascular mortality, and diabetes mortality in either NAFLD or MASLD. The RCS curves showed a nonlinear trend between three TyG-related indices with all-cause mortality in either NAFLD or MASLD. Subgroup analyses showed that TyG-BMI and TyG-WC indices were more suitable for predicting all-cause mortality in patients without advanced fibrosis.

CONCLUSION

Our study highlights the clinical value of TyG-related indices in predicting the survival of the NAFLD/MASLD population. TyG-BMI and TyG-WC indices would be the surrogate biomarkers for the follow-up of the population without advanced fibrosis.

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.

Association between atherogenic index of plasma and new-onset stroke in individuals with different glucose metabolism status: insights from CHARLS

BACKGROUND

Circulating atherogenic index of plasma (AIP) levels has been proposed as a novel biomarker for dyslipidemia and as a predictor of insulin resistance (IR) risk. However, the association between AIP and the incidence of new-onset stroke, particularly in individuals with varying glucose metabolism status, remains ambiguous.

METHODS

A total of 8727 participants aged 45 years or older without a history of stroke from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. The AIP was calculated using the formula log [Triglyceride (mg/dL) / High-density lipoprotein cholesterol (mg/dL)]. Participants were divided into four groups based on their baseline AIP levels: Q1 (AIP ≤ 0.122), Q2 (0.122 < AIP ≤ 0.329), Q3 (0.329 < AIP ≤ 0.562), and Q4 (AIP > 0.562). The primary endpoint was the occurrence of new-onset stroke events. The Kaplan-Meier curves, multivariate Cox proportional hazard models, and Restricted cubic spline analysis were applied to explore the association between baseline AIP levels and the risk of developing a stroke among individuals with varying glycemic metabolic states.

RESULTS

During an average follow-up of 8.72 years, 734 participants (8.4%) had a first stroke event. The risk for stroke increased with each increasing quartile of baseline AIP levels. Kaplan-Meier curve analysis revealed a significant difference in stroke occurrence among the AIP groups in all participants, as well as in those with prediabetes mellitus (Pre-DM) and diabetes mellitus (DM) (all P values < 0.05). After adjusting for potential confounders, the risk of stroke was significantly higher in the Q2, Q3, and Q4 groups than in the Q1 group in all participants. The respective hazard ratios (95% confidence interval) for stroke in the Q2, Q3, and Q4 groups were 1.34 (1.05-1.71), 1.52 (1.19-1.93), and 1.84 (1.45-2.34). Furthermore, high levels of AIP were found to be linked to an increased risk of stroke in both pre-diabetic and diabetic participants across all three Cox models. However, this association was not observed in participants with normal glucose regulation (NGR) (p > 0.05). Restricted cubic spline analysis also demonstrated that higher baseline AIP levels were associated with higher hazard ratios for stroke in all participants and those with glucose metabolism disorders.

CONCLUSIONS

An increase in baseline AIP levels was significantly associated with the risk of stroke in middle-aged and elderly individuals, and exhibited distinct characteristics depending on the individual's glucose metabolism status.

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

Background

Insulin resistance (IR) is closely related to the development of cardiovascular diseases. Triglyceride-glucose-body mass index (TyG-BMI) has been proven to be a reliable surrogate of IR, but the relationship between TyG-BMI and acute myocardial infarction (AMI) is unknown. The present study aims to determine the effects of TyG-BMI on the clinical prognosis of critically ill patients with AMI.

Methods

The data of AMI patients were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All patients were divided into four groups according to the TyG-BMI quartile. Outcomes were defined as 30-, 90-, 180-, and 365-day all-cause mortality. Kaplan-Meier (K-M) curve was used to compare survival rate between groups. Meanwhile, Cox regression analysis and restricted cubic splines (RCS) were used to explore the relationship between TyG-BMI index and outcome events.

Results

A total of 1,188 critically ill patients with AMI were included in this study. They were divided into four groups according to TyG-BMI quartiles, there were significant differences in 90-, 180-, and 365-day all-cause mortality while there was no difference in 30-day all-cause mortality. Interestingly, with the increase of TyG-BMI, the 90-, 180-, and 365-day survival rate increased first and then gradually decreased, but the survival rate after decreasing was still higher than that in the group with the lowest TyG-BMI. U-shaped relationships between TyG-BMI index and 90-, 180-, and 365-day all-cause mortality were identified using RCS curve and the inflection point was 311.1, 316.5, and 320.1, respectively, whereas the TyG-BMI index was not non-linearly associated with 30-day all-cause mortality. The results of Cox proportional hazard regression analysis are consistent with those of RCS analysis.

Conclusion

U-shaped relationships are existed between the TyG-BMI index and 90-, 180-, and 365-day all-cause mortality in critically ill patients with AMI, but not 30-day all-cause mortality. The TyG-BMI index can be used as an effective index for early prevention of critically ill patients with AMI.

Association of the TyG index with prognosis in surgical intensive care patients: data from the MIMIC-IV

BACKGROUND

The triglyceride-glucose (TyG) index, a tool for assessing insulin resistance, is increasingly recognized for its ability to predict cardiovascular and metabolic risks. However, its relationship with trauma and surgical patient prognosis is understudied. This study investigated the correlation between the TyG index and mortality risk in surgical/trauma ICU patients to identify high-risk individuals and improve prognostic strategies.

METHODS

This study identified patients requiring trauma/surgical ICU admission from the Medical Information Mart for Intensive Care (MIMIC-IV) database, and divided them into tertiles based on the TyG index. The outcomes included 28-day mortality and 180-day mortality for short-term and long-term prognosis. The associations between the TyG index and clinical outcomes in patients were elucidated using Cox proportional hazards regression analysis and RCS models.

RESULTS

A total of 2103 patients were enrolled. The 28-day mortality and 180-day mortality rates reached 18% and 24%, respectively. Multivariate Cox proportional hazards analysis revealed that an elevated TyG index was significantly related to 28-day and 180-day mortality after covariates adjusting. An elevated TyG index was significantly associated with 28-day mortality (adjusted hazard ratio, 1.19; 95% confidence interval 1.04-1.37) and 180-day mortality (adjusted hazard ratio, 1.24; 95% confidence interval 1.11-1.39). RCS models revealed that a progressively increasing risk of mortality was related to an elevated TyG index. According to our subgroup analysis, an elevated TyG index is associated with increased risk of 28-day and 180-day mortality in critically ill patients younger than 60 years old, as well as those with concomitant stroke or cardiovascular diseases. Additionally, in nondiabetic patients, an elevated TyG index is associated with 180-day mortality.

CONCLUSION

An increasing risk of mortality was related to an elevated TyG index. In critically ill patients younger than 60 years old, as well as those with concomitant stroke or cardiovascular diseases, an elevated TyG index is associated with adverse short-term and long-term outcomes. Furthermore, in non-diabetic patients, an elevated TyG index is associated with adverse long-term prognosis.

Prognostic value of the systemic immune-inflammation index in critically ill elderly patients with hip fracture: evidence from MIMIC (2008-2019)

Background

The systemic immune-inflammation index (SII) showed an extensive link between immunological dysfunction and the activation of systemic inflammation. Several studies have confirmed the application of SII to orthopedic diseases. However, the significance of SII in critically ill elderly individuals with hip fracture who require intensive care unit (ICU) admission is not yet known. This study centered on exploring the relationship between SII and clinical outcomes among critically ill elderly hip fracture individuals.

Methods

The study centered around elderly patients experiencing severe illness following hip fractures and requiring admission to the ICU. These patients from the MIMIC-IV database formed the basis of this study's cohort. We stratified them into quartiles according to their SII levels. The results involved the mortality at 30 days and 1 year post-admission. Then we employ Cox proportional hazards regression analysis as well as restricted cubic splines to explore the association between the SII and clinical results in critically ill elderly patients with hip fracture.

Results

The study encompassed 991 participants, among whom 63.98% identified as females. Notably, the mortality rates attributed to any cause within 30 days and 1 year after hospitalization stood at 19.68 and 33.40%, respectively. The multivariate Cox proportional hazards model disclosed a significant correlation between an elevated SII and all-cause mortality. Following adjustments for confounding variables, individuals with a high SII showed a notable correlation with 30-day mortality [adjusted hazard ratio (HR), 1.065; 95% confidence interval (CI), 1.044-1.087; p < 0.001] and 1-year mortality (adjusted HR, 1.051; 95% CI, 1.029-1.074; p < 0.001). Furthermore, the analysis of restricted cubic splines demonstrated a progressive increase in the risk of all-cause death as the SII value rose.

Conclusion

Among critically ill elderly patients with hip fracture, the SII exhibits a non-linear association that positively correlates with both 30-day and 1-year all-cause mortality rates. The revelation indicates that the SII may play a vital role in identifying patients with hip fractures who face an escalated risk of mortality due to any cause.

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.

Long-term survival in stroke patients: insights into triglyceride-glucose body mass index from ICU data

BACKGROUND

The Triglyceride Glucose-Body Mass Index (TyG-BMI) has been established as a robust indicator of insulin resistance (IR), reflecting metabolic health across various populations. In general, lower TyG-BMI values are often associated with better metabolic health outcomes and a reduced risk of adverse health events in non-critically ill populations. Previous studies have highlighted a significant negative association between TyG-BMI and all-cause mortality (ACM) among critically ill atrial fibrillation patients. Given the high prevalence and severe outcomes associated with stroke, understanding how TyG-BMI at the time of ICU admission correlates with ACM in critically ill stroke patients becomes imperative. This study aims to assess the correlation between TyG-BMI and ACM in this specific patient cohort, exploring how traditional associations between TyG-BMI and metabolic health may differ in the context of acute, life-threatening illness.

METHODS

Patient data were retrieved by accessing the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database, categorizing patients into three groups on the basis of TyG-BMI tertiles. The study evaluated both primary and secondary outcomes: the primary outcomes included the 90-day, 180-day, and 1-year ACM, while secondary outcomes encompassed ICU, in-hospital, and 30-day ACM. Our study employed the Kaplan-Meier (K-M) curve method for outcome comparison across the groups while utilizing multivariate Cox proportional-hazards regression models and restricted cubic splines (RCS) to explore TyG-BMI association with these outcomes. Additionally, interaction and subgroup analyses were performed, focusing on different mortality time points.

RESULTS

Among a cohort of 1707 individuals diagnosed with stroke, the average age was 68 years (interquartile range [IQR]: 58-78 years), with 946 (55.42%) of the participants being male. The analysis of K-M curves suggested that patients having a lower TyG-BMI level faced a heightened risk of long-term ACM, whereas the short-term ACM exhibited no statistically significant differences across the three TyG-BMI groups. Furthermore, Cox proportional-hazards regression analysis validated a statistically significant increased risk of long-term ACM among patients belonging to the lowest TyG-BMI tertile. Additionally, RCS analysis results demonstrated L-shaped correlations between the TyG-BMI index and both short- and long-term ACM. These findings underscore the TyG-BMI predictive value for long-term mortality in stroke patients, highlighting a nuanced relationship that varies over different time frames. The results revealed no interactions between TyG-BMI and the stratified variables, with the exception of age.

CONCLUSION

In our study, lower TyG-BMI levels in critically ill stroke patients are significantly related to a higher risk of long-term ACM within the context of the United States. This finding suggests the potential of TyG-BMI as a marker for stratifying long-term risk in this patient population. However, it's crucial to note that this association was not observed for short-term ACM, indicating that the utility of TyG-BMI may be more pronounced in long-term outcome prediction. Additionally, our conclusion that TyG-BMI could serve as a reliable indicator for managing and stratifying stroke patients over the long term is preliminary. To confirm our findings and assess the universal applicability of TyG-BMI as a prognostic tool, it is crucial to conduct rigorously designed research across various populations.

Triglyceride-glucose index predicts sepsis-associated acute kidney injury and length of stay in sepsis: A MIMIC-IV cohort study

Background

Inflammation and stress response may be related to the occurrence of sepsis-associated acute kidney injury (SA-AKI) in patients with sepsis.Insulin resistance (IR) is closely related to the stress response, inflammatory response, immune response and severity of critical diseases. We assume that the triglyceride-glucose (TyG) index, an alternative indicator for IR, is associated with the occurrence of SA-AKI in patients with sepsis.

Methods

Data were obtained from The Medical Information Mart for Intensive Care-IV(MIMIC-IV) database in this retrospective cohort study. Univariate and multivariate logistic regression analysis and multivariate restricted cubic spline(RCS) regression were conducted to evaluate the association between TyG index and SA-AKI, length of stay (LOS). Subgroup and sensitivity analyses were performed to verify the robustness of the results.

Results

The study ultimately included data from 1426 patients with sepsis, predominantly of white ethnicity (59.2%) and male sex (56.4%), with an SA-AKI incidence rate of 78.5%. A significant linear association was observed between the TyG index and SA-AKI (OR, 1.40; 95% confidence interval(CI) [1.14-1.73]). Additionally, the TyG index demonstrated a significant correlation with the length of stay (LOS) in both the hospital (β, 1.79; 95% CI [0.80-2.77]) and the intensive care unit (ICU) (β, 1.30; 95% CI [0.80-1.79]). Subgroup and sensitivity analyses confirmed the robustness of these associations.

Conclusion

This study revealed a strong association between the TyG index and both SA-AKI and length of stay in patients with sepsis. These findings suggest that the TyG index is a potential predictor of SA-AKI and the length of hospitalization in sepsis cases, broadening its application in this context. However, further research is required to confirm whether interventions targeting the TyG index can genuinely enhance the clinical outcomes of patients with sepsis.

Associations of triglyceride-glucose (TyG) index with chest pain incidence and mortality among the U.S. population

BACKGROUND

The triglyceride and glucose (TyG) index, a simple surrogate marker of insulin resistance, is related to cardiovascular disease. However, there is a lack of evidence for the relationship between the TyG index and chest pain. This study aimed to investigate the association of the TyG index with chest pain and to evaluate the relationship between the TyG index and all-cause mortality in participants with or without chest pain.

METHODS

The present study utilized data from the 2001-2012 National Health and Nutrition Examination Survey (NHANES), employing a combination of cross-sectional and cohort study designs. The association between the TyG index and chest pain was investigated using weighted logistic regression models. Weighted Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause mortality. Restricted cubic spline analysis was used to explore linear or nonlinear relationships between the TyG index and chest pain or all-cause mortality.

RESULTS

The findings revealed a positive correlation between the TyG index and chest pain, even after adjusting for potential confounding factors (quartile 4 versus quartile 1, odds ratio [OR] 1.42, 95% confidence interval [CI] 1.14-1.77, P = 0.002). During a mean follow-up time of 139 months, a total of 2286 individuals (27.43%) experienced mortality. Weighted multivariate Cox regression models indicated that for each one-unit increase in the TyG index, the adjusted hazard ratio (HR) for mortality was 1.14 (95% CI = 0.94-1.37) for participants with chest pain and 1.25 (95% CI = 1.09-1.43) for those without chest pain. Furthermore, restricted cubic spline analysis revealed a linear relationship between the TyG index and chest pain (P for nonlinearity = 0.902), whereas a nonlinear relationship was shown between the TyG index and all-cause mortality among populations regardless of chest pain (all P for nonlinearity < 0.01).

CONCLUSION

The TyG index was positively linked to a higher incidence of chest pain. Moreover, the TyG index was associated with all-cause mortality not only in participants with chest pain but also in those without chest pain.

Triglyceride-glucose index: a novel evaluation tool for all-cause mortality in critically ill hemorrhagic stroke patients-a retrospective analysis of the MIMIC-IV database

BACKGROUND

Hemorrhagic 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.

METHODS

Herein, 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.

RESULTS

The 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.

CONCLUSION

In 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.

Association between triglyceride-glucose index and intracranial/extracranial atherosclerotic stenosis: findings from a retrospective study

OBJECTIVE

The association of the triglyceride-glucose (TyG) index with intracranial atherosclerotic stenosis (ICAS) and extracranial atherosclerotic stenosis (ECAS) is unclear. This study aimed to investigate the relationship of TyG index with the distribution and severity of ICAS and ECAS.

METHOD

Patients who underwent digital subtraction angiography (DSA) for evaluating ICAS/ECAS in Zhongnan Hospital of Wuhan University from January 2017 to October 2021 were retrospectively enrolled in our study. Clinical characteristics, DSA data, blood routine, lipid profile and fasting glucose were recorded. The association of TyG index and ICAS/ECAS status were investigated in four aspects: location and distribution of stenosis, stenosis severity and whether stenosis is symptomatic. Logistic regression models were used to evaluate the association. Restricted cubic splines were constructed to model the non-linear relationship between the TyG index and different arterial stenosis status.

RESULTS

Among 1129 included patients, the median age was 62 (IQR 55-68) years, and 71.3% were male. The median TyG index was 8.81 (8.40, 9.21). Elevated TyG index was significantly associated with ICAS, combined ICAS/ECAS, anterior circulation stenosis, posterior circulation stenosis, combined anterior/posterior circulation stenosis, severe stenosis, both asymptomatic and symptomatic stenosis. This association was maintained after adjusting for age, sex, smoking, drinking, medical history of hypertension and stroke, platelet, total cholesterol, high-density lipoprotein, and low-density lipoprotein. Multivariable-adjusted spline regression models showed that a progressively increasing risk of arterial stenosis was related to an elevated TyG index.

CONCLUSION

Elevated TyG index was associated with ICAS/ECAS. TyG index might be a useful indicator of ICAS and severe stenosis.

The prediction of in-hospital mortality in elderly patients with sepsis-associated acute kidney injury utilizing machine learning models

Background

Sepsis-associated acute kidney injury (SA-AKI) is a severe complication associated with poorer prognosis and increased mortality, particularly in elderly patients. Currently, there is a lack of accurate mortality risk prediction models for these patients in clinic.

Objectives

This study aimed to develop and validate machine learning models for predicting in-hospital mortality risk in elderly patients with SA-AKI.

Methods

Machine learning models were developed and validated using the public, high-quality Medical Information Mart for Intensive Care (MIMIC)-IV critically ill database. The recursive feature elimination (RFE) algorithm was employed for key feature selection. Eleven predictive models were compared, with the best one selected for further validation. Shapley Additive Explanations (SHAP) values were used for visualization and interpretation, making the machine learning models clinically interpretable.

Results

There were 16,154 patients with SA-AKI in the MIMIC-IV database, and 8426 SA-AKI patients were included in this study (median age: 77.0 years; female: 45%). 7728 patients excluded based on these criteria. They were randomly divided into a training cohort (5,934, 70%) and a validation cohort (2,492, 30%). Nine key features were selected by the RFE algorithm. The CatBoost model achieved the best performance, with an AUC of 0.844 in the training cohort and 0.804 in the validation cohort. SHAP values revealed that AKI stage, PaO2, and lactate were the top three most important features contributing to the CatBoost model.

Conclusion

We developed a model capable of predicting the risk of in-hospital mortality in elderly patients with SA-AKI.

The association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with atrial fibrillation: a retrospective study from MIMIC-IV database

BACKGROUND

The 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.

METHODS

The 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.

RESULTS

Out 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).

CONCLUSION

In 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.

The triglyceride-glucose index: a novel predictor of stroke and all-cause mortality in liver transplantation recipients

BACKGROUND

The triglyceride-glucose (TyG) index, identified as a reliable indicator of insulin resistance (IR), was reported to be associated with stroke recurrence and morbidity in the general population and critically ill patients. However, the relationship in liver transplantation (LT) recipients remains unknown. This study aimed to investigate the correlation between the TyG index and post-LT stroke along with all-cause mortality and further assess the influence of IR on the LT recipients' prognosis.

METHODS

The retrospective cohort study enrolled 959 patients who underwent LT at a university-based medical centre between January 2015 and January 2021. The participants were divided into three groups according to their TyG index tertiles. The primary outcome was post-LT stroke. Multivariate logistic regression, COX proportional hazards regression, and restricted cubic spline RCS were used to examine the association between the TyG index and outcomes in LT recipients.

RESULTS

With a median TyG index of 8.23 (7.78-8.72), 780 (87.18% males) patients were eventually included. The incidence of post-LT stroke was 5.38%, and the in-hospital, 1-year, and 3-year mortality rates were 5.54%, 13.21%, and 15.77%, respectively. Multivariate regression analysis showed an independent association between the TyG index and an increased risk of post-LT stroke [adjusted odds ratio (aOR), 3.398 (95% confidence interval [CI]: 1.371-8.426) P = 0. 008], in-hospital mortality [adjusted hazard ratio (aHR), 2.326 (95% CI: 1.089-4.931) P = 0.025], 1-year mortality [aHR, 1.668 (95% CI: 1.024-2.717) P = 0.039], and 3-year mortality [aHR, 1.837 (95% CI: 1.445-2.950) P = 0.012]. Additional RCS analysis also suggested a linear increase in the risk of postoperative stroke with elevated TyG index (P for nonlinearity = 0.480).

CONCLUSIONS

The TyG index may be a valuable and reliable indicator for assessing stroke risk and all-cause mortality in patients undergoing LT, suggesting its potential relevance in improving risk stratification during the peri-LT period.

Designing machine learning for big data: A study to identify factors that increase the risk of ischemic stroke and prognosis in hypertensive patients

Background

Ischemic stroke (IS) accounts large amount of stroke incidence. The aim of this study was to discover the risk and prognostic factors that affecting the occurrence of IS in hypertensive patients.

Method

Study data were obtained from the Medical Information Mart for Intensive Care (MIMIC)-IV database. To avoid biased factors selection process, several approaches were studied including logistic regression, elastic net regression, random forest, correlation analysis, and multifactor logistic regression methods. And seven different machine-learning methods are used to construct predictive models. The performance of the developed models was evaluated using AUC (Area Under the Curve), prediction accuracy, precision, recall, F1 score, PPV (Positive Predictive Value) and NPV (Negative Predictive Value). Interaction analysis was conducted to explore potential relationships between influential factors.

Results

The study included 92,514 hypertensive patients, of which 1746 hypertensive patients experienced IS. The Gradient Boosted Decision Tree (GBDT) model outperformed the other prediction model terms of prediction accuracy and AUC values in both ischemic and prognosis cases. By using the SHapley Additive exPlanations (SHAP), we found that a range of factors and corresponding interactions between factors are important risk factors for IS and its prognosis in hypertensive patients.

Conclusion

The study identified factors that increase the risk of IS and poor prognosis in hypertensive patients, which may provide guidance for clinical diagnosis and treatment.

Association of triglyceride glucose index with all-cause and cardiovascular mortality in the general population

OBJECTIVE

The Triglyceride-glucose (TyG) index, a novel indicator of insulin resistance, has been associated with mortality from coronary artery diseases, ischemic stroke, and heart failure. In recent years, much emphasis has been placed on the relationship between the TyG index and mortality in the general population. However, the impact of age on the association between TyG and all-cause and cardiovascular mortality remains controversial. This study investigated the link between the TyG index and all-cause and cardiovascular mortality, emphasizing differences between older and non-older populations.

METHODS

Data from the National Health and Nutrition Examination Survey (2009-2018), encompassing 20,194 participants, were analyzed. The baseline TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Multivariate Cox proportional hazards regression models with restricted cubic splines and trend tests were employed to explore the association between the TyG index and all-cause and cardiovascular mortality, with emphasis on age-specific analysis. Subgroup analysis was conducted to examine whether the TyG index's association with mortality varied across different subgroups. Additionally, receiver operating characteristic curves were used to compare the predictive ability of the TyG index with the homeostasis model assessment of insulin resistance (HOMA-IR) for all-cause and cardiovascular mortality.

RESULTS

Over a median follow-up period of 105 months, all-cause mortality accounted for 13.345% of cases, and cardiovascular mortality accounted for 3.387%. Kaplan-Meier curves showed a significant increase in all-cause and cardiovascular mortality with higher TyG index values (both P for log-rank test < 0.001). However, during Cox proportional hazards regression analysis, no linear trend was observed between the TyG index and all-cause or cardiovascular mortality after adjusting for confounding factors (all-cause mortality: P for trend = 0.424; cardiovascular mortality: P for trend = 0.481). Restricted cubic splines revealed a non-linear association between the baseline TyG index and all-cause and cardiovascular mortality in the overall population (all-cause mortality: Non-linear P = 0.003; cardiovascular mortality: Non-linear P = 0.034). The effect of the TyG index was consistent across most subgroups in terms of all-cause and cardiovascular mortality, with no significant interaction with randomized factors (all-cause mortality: P for interaction = 0.077-0.940, cardiovascular mortality: P for interaction = 0.173-0.987), except for the age subgroup (all-cause mortality: P for interaction < 0.001, cardiovascular mortality: P for interaction < 0.001). Further age-specific analysis revealed that the association between the TyG index and all-cause and cardiovascular mortality remained significant in patients aged < 65 but not in those aged ≥ 65. Interestingly, a non-linear association was observed between the TyG index and all-cause mortality in individuals aged < 65 (Non-linear P = 0.011), while a linear relationship was observed with cardiovascular mortality, showing an upward trend (Non-linear P = 0.742, P for trend = 0.010). Further stratification according to age yielded similar results only in patients aged 45-64 (all-cause mortality: Non-linear P = 0.001 and cardiovascular mortality: Non-linear P = 0.902, P for trend = 0.015). Compared to HOMA-IR, the TyG index demonstrated superior predictive performance for all-cause and cardiovascular mortality (all-cause mortality: 0.620 vs. 0.524, P < 0.001; cardiovascular mortality: 0.623 vs. 0.537, P < 0.001).

CONCLUSIONS

This study established a significant association between the TyG index and all-cause and cardiovascular mortality in the general population, particularly among individuals aged < 65. Notably, a non-linear association with all-cause mortality was observed in those aged < 65, while a linear relationship with cardiovascular mortality was found.

Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database

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.

Triglyceride-glucose index is associated with the occurrence and prognosis of cardiac arrest: a multicenter retrospective observational study

BACKGROUND

Triglyceride-glucose (TyG) index is an efficient indicator of insulin resistance and is proven to be a valuable marker in several cardiovascular diseases. However, the relationship between TyG index and cardiac arrest (CA) remains unclear. The present study aimed to investigate the association of the TyG index with the occurrence and clinical outcomes of CA.

METHODS

In this retrospective, multicenter, observational study, critically ill patients, including patients post-CA, were identified from the eICU Collaborative Research Database and evaluated. The TyG index for each patient was calculated using values of triglycerides and glucose recorded within 24 h of intensive care unit (ICU) admission. In-hospital mortality and ICU mortality were the primary clinical outcomes. Logistic regression, restricted cubic spline (RCS), and correlation analyses were performed to explore the relationship between the TyG index and clinical outcomes. Propensity score matching (PSM), overlap weighting (OW), and inverse probability of treatment weighting (IPTW) were adopted to balance the baseline characteristics of patients and minimize selection bias to confirm the robustness of the results. Subgroup analysis based on different modifiers was also performed.

RESULTS

Overall, 24,689 critically ill patients, including 1021 patients post-CA, were enrolled. The TyG index was significantly higher in patients post-CA than in those without CA (9.20 (8.72-9.69) vs. 8.89 (8.45-9.41)), and the TyG index had a moderate discrimination ability to identify patients with CA from the overall population (area under the curve = 0.625). Multivariate logistic regression indicated that the TyG index was an independent risk factor for in-hospital mortality (OR = 1.28, 95% CI: 1.03-1.58) and ICU mortality (OR = 1.27, 95% CI: 1.02-1.58) in patients post-CA. RCS curves revealed that an increased TyG index was linearly related to higher risks of in-hospital and ICU mortality (P for nonlinear: 0.225 and 0.271, respectively). Even after adjusting by PSM, IPTW, and OW, the TyG index remained a risk factor for in-hospital mortality and ICU mortality in patients experiencing CA, which was independent of age, BMI, sex, etc. Correlation analyses revealed that TyG index was negatively correlated with the neurological status of patients post-CA.

CONCLUSION

Elevated TyG index is significantly associated with the occurrence of CA and higher mortality risk in patients post-CA. Our findings extend the landscape of TyG index in cardiovascular diseases, which requires further prospective cohort study.