Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Background Patients with chronic heart failure (CHF) and type 2 diabetes mellitus (DM) are prone to insulin resistance and malnutrition, both of which are significant prognostic factors for CHF. However, the combined effect of the triglyceride–glucose index (TyG index) and prognostic nutritional index (PNI) on the mortality risk in patients with CHF and type 2 DM has not yet been studied. Methods We enrolled 3,315 patients with CHF and type 2 DM. We used a multivariate Cox regression model to assess hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality risk based on TyG index and PNI levels. Furthermore, we constructed a novel index, the insulin resistance–nutritional index (IRNI), defined as TyG index/Ln (PNI), and evaluated its prognostic significance. Results During follow-up, 1,214 deaths occurred. Participants with a high TyG index and non-high PNI had a significantly higher mortality risk compared to those with a non-high TyG index and high PNI, with an adjusted HR of 1.91 (95% CI, 1.57–2.32). The multivariate Cox regression analysis revealed HRs for all-cause and cardiovascular deaths of 1.93 (95% CI, 1.66–2.26; P < 0.001) and 2.50 (95% CI, 2.05–3.06; P < 0.001), respectively, when comparing the highest and lowest IRNI tertiles. IRNI’s predictive power was stronger in groups with higher adapted Diabetes Complications Severity Index scores ( P for interaction < 0.05). Additionally, adding IRNI to the baseline risk model significantly improved predictive performance, showing a greater effect compared to the TyG index or PNI. Conclusion IRNI, a novel and composite index reflecting insulin resistance and nutritional status, emerges as a potentially valuable prognostic marker for patients with CHF and type 2 DM.
Background Patients with chronic heart failure (CHF) and type 2 diabetes mellitus (DM) are prone to insulin resistance and malnutrition, both of which are significant prognostic factors for CHF. However, the combined effect of the triglyceride–glucose index (TyG index) and prognostic nutritional index (PNI) on the mortality risk in patients with CHF and type 2 DM has not yet been studied. Methods We enrolled 3,315 patients with CHF and type 2 DM. We used a multivariate Cox regression model to assess hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality risk based on TyG index and PNI levels. Furthermore, we constructed a novel index, the insulin resistance–nutritional index (IRNI), defined as TyG index/Ln (PNI), and evaluated its prognostic significance. Results During follow-up, 1,214 deaths occurred. Participants with a high TyG index and non-high PNI had a significantly higher mortality risk compared to those with a non-high TyG index and high PNI, with an adjusted HR of 1.91 (95% CI, 1.57–2.32). The multivariate Cox regression analysis revealed HRs for all-cause and cardiovascular deaths of 1.93 (95% CI, 1.66–2.26; P < 0.001) and 2.50 (95% CI, 2.05–3.06; P < 0.001), respectively, when comparing the highest and lowest IRNI tertiles. IRNI’s predictive power was stronger in groups with higher adapted Diabetes Complications Severity Index scores ( P for interaction < 0.05). Additionally, adding IRNI to the baseline risk model significantly improved predictive performance, showing a greater effect compared to the TyG index or PNI. Conclusion IRNI, a novel and composite index reflecting insulin resistance and nutritional status, emerges as a potentially valuable prognostic marker for patients with CHF and type 2 DM.
Obesity represents a major health crisis in the United States, significantly increasing risks for chronic diseases and generating substantial economic costs. While bariatric surgery and pharmacological interventions such as GLP-1 receptor agonists have been proven effective in achieving substantial weight loss and improving comorbid conditions, they also raise concerns about the unintended loss of fat-free mass, particularly muscle. This loss of muscle mass compromises physical functionality, quality of life, and long-term metabolic health, particularly in individuals with sarcopenic obesity or those at risk of frailty. To sustain strength, mobility, and metabolic function during weight loss interventions, the preservation of muscle mass is essential. However, current weight-loss strategies often fail to adequately address the need to maintain fat-free mass. This review explores the physiological mechanisms governing muscle mass, the impact of obesity and rapid weight loss on muscle protein turnover, and nutritional and age-based strategies that may help protect muscle during intentional weight reduction. By focusing on these critical countermeasures, this review aims to inform future clinical practice and research initiatives with the long-term goal of achieving effective weight loss through reduction in fat tissue while preserving skeletal muscle mass, enhancing health outcomes, and long-term functionality in patients undergoing significant weight reduction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.