{"title":"糖尿病对败血症性心肌病的影响。","authors":"Weiwei Lai, Li Liu, Shuhang Wang, Qing Tang, Yancun Liu, Yanfen Chai","doi":"10.1016/j.diabres.2025.112001","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>This study investigated the association between diabetes and Sepsis-induced cardiomyopathy (SIC), focusing on how changes in inflammatory response and cardiac function influence SIC prognosis. The aim is to provide clinicians with more accurate treatment and management strategies, ultimately enhancing patient outcomes and quality of life.</div></div><div><h3>Methods</h3><div>This retrospective cohort study analyzed 258 Sepsis-induced cardiomyopathy (SIC) patients, stratified by diabetes status and HbA1C levels. Data were collected from electronic medical records. Statistical tests included the Kolmogorov-Smirnov, <em>t</em>-test, Mann-Whitney U, Kruskal-Wallis, chi-square, and Spearman correlation. Univariate and multivariate logistic regression assessed diabetes’ impact on SIC severity. Model fit was evaluated with the Hosmer–Lemeshow and negative log-likelihood ratio tests. A nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Subgroup and interaction analyses were performed (P < 0.05).</div></div><div><h3>Results</h3><div>Diabetes worsened inflammation and immune responses in SIC, significantly affecting markers like LVEF, TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA scores (P < 0.05). Grouping by HbA1C levels revealed no significant differences in LVEF (P = 0.078), Alb (P = 0.105), or L/A (P = 0.211), but differences were found for TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA (P < 0.05). HbA1C strongly correlated with CRP (rs = 0.8664). BNP (OR 1.001) and HbA1C (OR 1.302) were significant risk factors for SIC, with the nomogram showing good predictive performance (AUC 0.693). No significant interaction between HbA1C and BNP on SIC severity was observed (P = 0.791).</div></div><div><h3>Conclusion</h3><div>Diabetes exacerbates inflammatory and immune responses in Sepsis-induced cardiomyopathy patients, leading to worsened cardiac function.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"220 ","pages":"Article 112001"},"PeriodicalIF":6.1000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of diabetes on Sepsis-induced cardiomyopathy\",\"authors\":\"Weiwei Lai, Li Liu, Shuhang Wang, Qing Tang, Yancun Liu, Yanfen Chai\",\"doi\":\"10.1016/j.diabres.2025.112001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>This study investigated the association between diabetes and Sepsis-induced cardiomyopathy (SIC), focusing on how changes in inflammatory response and cardiac function influence SIC prognosis. The aim is to provide clinicians with more accurate treatment and management strategies, ultimately enhancing patient outcomes and quality of life.</div></div><div><h3>Methods</h3><div>This retrospective cohort study analyzed 258 Sepsis-induced cardiomyopathy (SIC) patients, stratified by diabetes status and HbA1C levels. Data were collected from electronic medical records. Statistical tests included the Kolmogorov-Smirnov, <em>t</em>-test, Mann-Whitney U, Kruskal-Wallis, chi-square, and Spearman correlation. Univariate and multivariate logistic regression assessed diabetes’ impact on SIC severity. Model fit was evaluated with the Hosmer–Lemeshow and negative log-likelihood ratio tests. A nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Subgroup and interaction analyses were performed (P < 0.05).</div></div><div><h3>Results</h3><div>Diabetes worsened inflammation and immune responses in SIC, significantly affecting markers like LVEF, TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA scores (P < 0.05). Grouping by HbA1C levels revealed no significant differences in LVEF (P = 0.078), Alb (P = 0.105), or L/A (P = 0.211), but differences were found for TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA (P < 0.05). HbA1C strongly correlated with CRP (rs = 0.8664). BNP (OR 1.001) and HbA1C (OR 1.302) were significant risk factors for SIC, with the nomogram showing good predictive performance (AUC 0.693). No significant interaction between HbA1C and BNP on SIC severity was observed (P = 0.791).</div></div><div><h3>Conclusion</h3><div>Diabetes exacerbates inflammatory and immune responses in Sepsis-induced cardiomyopathy patients, leading to worsened cardiac function.</div></div>\",\"PeriodicalId\":11249,\"journal\":{\"name\":\"Diabetes research and clinical practice\",\"volume\":\"220 \",\"pages\":\"Article 112001\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes research and clinical practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168822725000154\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes research and clinical practice","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168822725000154","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
The impact of diabetes on Sepsis-induced cardiomyopathy
Purpose
This study investigated the association between diabetes and Sepsis-induced cardiomyopathy (SIC), focusing on how changes in inflammatory response and cardiac function influence SIC prognosis. The aim is to provide clinicians with more accurate treatment and management strategies, ultimately enhancing patient outcomes and quality of life.
Methods
This retrospective cohort study analyzed 258 Sepsis-induced cardiomyopathy (SIC) patients, stratified by diabetes status and HbA1C levels. Data were collected from electronic medical records. Statistical tests included the Kolmogorov-Smirnov, t-test, Mann-Whitney U, Kruskal-Wallis, chi-square, and Spearman correlation. Univariate and multivariate logistic regression assessed diabetes’ impact on SIC severity. Model fit was evaluated with the Hosmer–Lemeshow and negative log-likelihood ratio tests. A nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Subgroup and interaction analyses were performed (P < 0.05).
Results
Diabetes worsened inflammation and immune responses in SIC, significantly affecting markers like LVEF, TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA scores (P < 0.05). Grouping by HbA1C levels revealed no significant differences in LVEF (P = 0.078), Alb (P = 0.105), or L/A (P = 0.211), but differences were found for TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA (P < 0.05). HbA1C strongly correlated with CRP (rs = 0.8664). BNP (OR 1.001) and HbA1C (OR 1.302) were significant risk factors for SIC, with the nomogram showing good predictive performance (AUC 0.693). No significant interaction between HbA1C and BNP on SIC severity was observed (P = 0.791).
Conclusion
Diabetes exacerbates inflammatory and immune responses in Sepsis-induced cardiomyopathy patients, leading to worsened cardiac function.
期刊介绍:
Diabetes Research and Clinical Practice is an international journal for health-care providers and clinically oriented researchers that publishes high-quality original research articles and expert reviews in diabetes and related areas. The role of the journal is to provide a venue for dissemination of knowledge and discussion of topics related to diabetes clinical research and patient care. Topics of focus include translational science, genetics, immunology, nutrition, psychosocial research, epidemiology, prevention, socio-economic research, complications, new treatments, technologies and therapy.