You Zhou, Yingli Xie, Jingjing Dong, Kunlun He, Hebin Che
{"title":"胰岛素抵抗-营养指数:慢性心力衰竭和 2 型糖尿病患者死亡率风险的简单指数和潜在预测指标。","authors":"You Zhou, Yingli Xie, Jingjing Dong, Kunlun He, Hebin Che","doi":"10.2147/DMSO.S490585","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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; <i>P</i> < 0.001) and 2.50 (95% CI, 2.05-3.06; <i>P</i> < 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 (<i>P</i> 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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":11116,"journal":{"name":"Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11550712/pdf/","citationCount":"0","resultStr":"{\"title\":\"Insulin Resistance-Nutritional Index: A Simple Index and Potential Predictor of Mortality Risk in Patients with Chronic Heart Failure and Type 2 Diabetes.\",\"authors\":\"You Zhou, Yingli Xie, Jingjing Dong, Kunlun He, Hebin Che\",\"doi\":\"10.2147/DMSO.S490585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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; <i>P</i> < 0.001) and 2.50 (95% CI, 2.05-3.06; <i>P</i> < 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 (<i>P</i> 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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":11116,\"journal\":{\"name\":\"Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11550712/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/DMSO.S490585\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/DMSO.S490585","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Insulin Resistance-Nutritional Index: A Simple Index and Potential Predictor of Mortality Risk in Patients with Chronic Heart Failure and Type 2 Diabetes.
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.
期刊介绍:
An international, peer-reviewed, open access, online journal. The journal is committed to the rapid publication of the latest laboratory and clinical findings in the fields of diabetes, metabolic syndrome and obesity research. Original research, review, case reports, hypothesis formation, expert opinion and commentaries are all considered for publication.