Diabetes mellitus (DM) encompasses metabolic disorders marked by persistent hyperglycemia and compromised metabolism of carbohydrates, lipids, and proteins due to deficiencies in insulin secretion, action, or both (1). Projections from the International Diabetes Federation anticipate a rise to 578 million adults with diabetes by 2030 and 700 million by 2045 (2, 3). Notably, over 90% of global diabetes cases fall under type 2 diabetes mellitus (T2D) (4), which, rather than manifesting in isolation, manifests as a component of a multifaceted metabolic‐cardiovascular syndrome (5). Epidemiological investigations have firmly established a significant correlation between heart failure and DM (6–8). Specifically, T2D acts as a cardiovascular risk factor, elevating the likelihood of heart failure and intensifying morbidity and mortality risks in affected individuals (9). Heart failure surpasses myocardial infarction or stroke as the most prevalent cardiovascular complication of diabetes (10). Previous studies suggest that individuals with T2D represent a distinct population with heightened cardiovascular risk, necessitating tailored prevention programs (11). Therefore, assessing the progression in patients with both heart failure and T2D is imperative for optimizing personalized treatment strategies.

The Triglyceride-Glucose (TyG) index, derived from fasting triglyceride and fasting blood glucose, emerges as a novel surrogate measure for insulin resistance, exhibiting superior diagnostic and predictive capabilities for diabetes compared to blood glucose alone (12, 13). Several studies associate the TyG index with atherosclerosis, metabolic syndrome, and T2D (14–16), while others explore its relevance in heart failure and severe illnesses (17). Recognizing the shared pathophysiological mechanisms between diabetes and heart failure underscores the significance of managing their synergistic effects (9, 10). Nevertheless, the linkage between the TyG index and the length of hospital stay (LHS) in patients with both T2D and heart failure (HF) remains unexplored.

Previous research underscores the importance of LHS as an indicator for assessing postoperative functional recovery, correlating with postoperative complications and resource utilization (18, 19). This study endeavors to examine the association between the TyG index and the risk of in-hospital events and LHS in patients with combined T2D and HF admitted to the intensive care unit (ICU). This exploration may assist in identifying high-risk patients, warranting closer monitoring or early intervention.

In this retrospective observational cohort study, we present the inaugural investigation into the association between the TyG index and the duration of hospitalization in critically ill patients with coexisting HF and T2D within a United States (US) cohort. Following meticulous adjustment for numerous potential confounding variables, our analysis reveals a positive correlation between the TyG index and the LHS. Employing smooth curve fitting techniques reinforces the identification of a linear relationship between the TyG index and LHS. The robustness of these findings is underscored by stratified and sensitivity analyses.

The TyG index, serving as a novel surrogate marker for insulin resistance, has been extensively utilized in predicting the risk and severity of various diseases (31). Numerous clinical investigations on the association between the TyG index and patient outcomes across diverse diseases have been conducted. Meta-analysis shows that the TyG index as a valuable marker to assess the risk of HF incidence (32), ischemic stroke (33), coronary artery disease (34), cardiovascular diseases and mortality in the general population (35)and atrial fibrillation (36). A study focusing on the general American population demonstrated that an elevated TyG index signifies more severe insulin resistance, displaying a non-linear association with LHS due to all-cause and cardiovascular diseases (37). In the context of chronic kidney disease (CKD), another study found a non-linear relationship between the TyG index and CKD, with a higher TyG index correlating with an increased risk of CKD (38). In the stroke population, a study identified the TyG index as a potential predictor for hospital and intensive care unit (ICU) mortality in critically ill stroke patients (39) Significantly, prior research on the TyG index and its connection to diabetes or HF has primarily focused on individual diseases. A Chinese study revealed an elevated risk of incident T2D with increasing TyG index among rural Chinese individuals, suggesting its potential as an important indicator for identifying individuals at high risk of T2D (40). Another study found that patients with a discordantly high TyG index faced a significantly greater risk of cardiovascular events irrespective of diabetes status (41). Furthermore, an independent association between an elevated TyG index and poor prognosis in patients with acute decompensated HF was identified (17). HF, a prevalent and severe cardiovascular consequence of DM, has garnered substantial global attention (4). Approximately 40% of HF patients are affected by DM, resulting in a two- to five-fold elevation in the risk of HF compared to normoglycemic individuals (42). Previous investigations emphasize the unfavorable clinical prognosis for diabetic patients with HF, displaying higher mortality rates than their normoglycemic counterparts (43–45). Despite the well-established association between diabetes and HF, there is limited data supporting the relationship between the TyG index and the LHS in patients with both HF and T2D. Through multivariate regression analysis and subgroup examinations, our study establishes the independent relevance of the TyG index to the LHS in patients with concurrent T2D and HF. Considering the TyG index as a straightforward method for evaluating insulin resistance, our findings affirm that insulin resistance is independently associated with the LHS.

This study utilized smooth curve fitting and restricted cubic spline analysis to evaluate the linear relationship between the TyG index and the duration of hospitalization in patients with concomitant HF and diabetes, diverging from previous investigations. Subsequent subgroup analyses were conducted to ensure the consistency of the primary findings. The observed association demonstrated a linear pattern, indicating that higher TyG index values are correlated with an increased LHS. These findings carry significant implications for clinical practice and patient care. In our investigation, elevated TyG levels were associated with prolonged in-hospital stays among patients with both T2D and HF within a specific range. This suggests that TyG may serve as a valuable tool for risk stratification and management in this high-risk patient population. Addressing the heightened risk associated with high TyG levels requires a comprehensive approach to risk management. These results underscore the importance of considering the TyG index in clinical practice due to its simplicity, reliability, and convenience, setting it apart from other commonly used methods for disease assessment (46). Researchers have increasingly explored the TyG index, identifying it as a reproducible, reliable, cost-effective, and valid surrogate marker of insulin resistance (IR) (47). Previous studies have demonstrated that the TyG index is highly sensitive (96.5%) and specific (85.0%) for detecting IR compared to the hyperinsulinemic–euglycemic clamp technique (48). Moreover, the TyG index has shown superior performance to Homeostatic model assessment insulin resistance index (HOMA-IR) (49), making it widely applicable in clinical practice, given the availability of glucose and triglyceride tests in all clinical laboratories. Additionally, there may be differences between early onset T2D and late onset T2D, which requires further discussion. One study reviewed the health consequences of early-onset T2DM and compared the results with those of late-onset T2DM, based on matched cohorts in the UK Biobank and reveal that early-onset T2D is more challenging in terms of glycemic control, with a higher risk of severe complications (50). The TyG index may provide an earlier clinical evaluation and provide strategies for future diabetes intervention. Furthermore, from the perspective of medical conditions and promotion, other insulin resistance markers such as HOMA-IR need more structural resources, and access to healthcare. The TyG index can be used as substitute for other tests in clinical settings where these tests are not feasible, and it has been demonstrated that the TyG index has high sensitivity and specificity compared with HOMA-IR and Clamp (48, 51). The TyG index can be easily calculated by TG and FPG without additional cost and has a better performance for the prediction of IR.

Several potential mechanisms elucidate the correlation between the TyG index and LHS. The association with adverse hospitalization duration may be attributed to insulin resistance reducing glucose bioavailability, favoring a shift to fatty acid metabolism, thereby increasing myocardial oxygen consumption and compromising myocardial compensatory capacity (52, 53). Additionally, glycolipid metabolism disorder can induce reactive oxygen species, mitochondrial dysfunction, endoplasmic reticulum stress, impaired cardiac calcium signaling, systemic low-grade inflammation, and inappropriate activation of the renin–angiotensin system, exacerbating heart failure progression (54–56). Furthermore, glycosylation end product deposition may increase diastolic left ventricular stiffness and inactivate nitric oxide, a protective factor for vascular endothelium (57). Lastly, a vicious cycle between congestive heart failure and insulin resistance may intensify cardiac function deterioration (58).

Our study boasts several notable strengths. Firstly, it pioneers the examination of the TyG index’s role in patients with both T2D and HF in the Intensive Care Unit (ICU). Emphasizing the necessity of a comprehensive risk management approach for this patient cohort, our study positions the TyG index as a valuable tool in assessing the LHS. Additionally, we employ restricted cubic splines to explore nonlinear relationships between the TyG index and outcomes. To address potential confounding variables, logistic regression analysis, incorporating multiple models, and subgroup analyses with appropriate categorizations were conducted.

Despite these strengths, our study has acknowledged limitations. Primarily, being a single-center retrospective study limits the definitive establishment of causality. We recommend future validation through multicenter prospective studies. Furthermore, drug use may affect the patient’s condition, but due to database limitations, it may not provide sufficient information on drug use. We plan to investigate the usage of patients more in future research on self-built databases. The baseline-only availability of data impedes the assessment of TyG level changes during the follow-up period, though initial levels likely accurately reflect the TyG index at hospitalization commencement. Then, due to the sample size, there may not be statistically significant differences in some subgroups. However, the overall effect value meets the requirements, and we will explore it in a larger sample size population in the future. Lastly, our findings should not be indiscriminately extrapolated to other countries or ICU facilities, given the study’s confinement to the United States and a single ICU institution. Nevertheless, the considerable sample size enhances the credibility and representativeness of our findings.

Our study establishes the TyG index as a significant predictor of prognosis in critically ill patients with both HF and T2D, showing an approximately linear relationship with the LHS. In this high-risk group, TyG emerges as a valuable tool for risk categorization and management. To augment validity and coherence, future research should adopt prospective, randomized, controlled study designs to confirm these results and elucidate the mechanisms linking TyG to the LHS in HF and T2D patients.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The establishment of this database was approved by the Massachusetts Institute of Technology (Cambridge, MA, USA) and Beth Israel Deaconess Medical Center (Boston, MA, USA), and informed consents were exempted due to all patients’ data were anonymized before the data were obtained. We also complied with all relevant ethical regulations regarding the use of the data in our study. All reports adhered to the guidelines for Strengthening the Reporting of Observational Studies in Epidemiology and the Declaration of Helsinki.

KZ: Conceptualization, Writing – original draft. YH: Conceptualization, Writing – original draft. YG: Writing – review & editing, Data curation. FG: Conceptualization, Writing – original draft. TC: Conceptualization, Writing – original draft. ZG: Conceptualization, Investigation, Writing – original draft. ZY: Investigation, Software, Writing – original draft. GM: Conceptualization, Investigation, Writing – original draft. YFG: Conceptualization, Investigation, Writing – original draft. RH: Conceptualization, Investigation, Writing – review & editing. MH: Conceptualization, Investigation, Writing – original draft, Writing – review & editing.