To determine the epidemiological characteristics and risk factors for heart failure (HF) among Japanese patients with type 2 diabetes.
Methods
A retrospective cohort analysis, using J-DREAMS database, was conducted from December 2015 to January 2020 with type 2 diabetes. The primary objectives were to describe patient characteristics stratified by HF history at baseline and new HF events during follow-up. The secondary objectives were to clarify the association between HF history or new HF events and clinical characteristics. The association between renal disease stage and HF was also studied.
Results
Among 18,250 adult patients with type 2 diabetes, 3,613 (19.8%) patients had HF history and the mean age was 68.46 years, predominantly male (66.4%) with 13.32 years of mean duration of type 2 diabetes. Patients with HF history had a higher proportion of patients with nephropathy (51.2%) and coronary heart disease (55.6%) than those without HF history. Coronary heart disease (CHD) and deteriorating renal function were strongly associated with both HF history (CHD adjusted odds ratio [OR]: 7.41, 95% confidence interval [CI]: 6.05–9.08; eGFR G5 stage adjusted OR: 6.56, 95% CI: 2.97–14.49) and new HF events (CHD adjusted OR: 1.63, 95% CI: 1.17–2.29; eGFR G4 stage adjusted OR: 3.42, 95% CI: 1.81–6.47).
Conclusions
Comorbidities, especially CHD and deteriorating renal function, were strongly associated with HF history and new HF events among Japanese patients with type 2 diabetes. The study results suggested the importance of early intervention to treat comorbidities and maintain renal function.
{"title":"Epidemiological characteristics and risk factors for heart failure in Japanese patients with type 2 diabetes: A retrospective analysis of the J-DREAMS database","authors":"Mitsuru Ohsugi, Daisuke Nitta, Yusuke Naito, Kohjiro Ueki","doi":"10.1111/jdi.14378","DOIUrl":"10.1111/jdi.14378","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>To determine the epidemiological characteristics and risk factors for heart failure (HF) among Japanese patients with type 2 diabetes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective cohort analysis, using J-DREAMS database, was conducted from December 2015 to January 2020 with type 2 diabetes. The primary objectives were to describe patient characteristics stratified by HF history at baseline and new HF events during follow-up. The secondary objectives were to clarify the association between HF history or new HF events and clinical characteristics. The association between renal disease stage and HF was also studied.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 18,250 adult patients with type 2 diabetes, 3,613 (19.8%) patients had HF history and the mean age was 68.46 years, predominantly male (66.4%) with 13.32 years of mean duration of type 2 diabetes. Patients with HF history had a higher proportion of patients with nephropathy (51.2%) and coronary heart disease (55.6%) than those without HF history. Coronary heart disease (CHD) and deteriorating renal function were strongly associated with both HF history (CHD adjusted odds ratio [OR]: 7.41, 95% confidence interval [CI]: 6.05–9.08; eGFR G5 stage adjusted OR: 6.56, 95% CI: 2.97–14.49) and new HF events (CHD adjusted OR: 1.63, 95% CI: 1.17–2.29; eGFR G4 stage adjusted OR: 3.42, 95% CI: 1.81–6.47).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Comorbidities, especially CHD and deteriorating renal function, were strongly associated with HF history and new HF events among Japanese patients with type 2 diabetes. The study results suggested the importance of early intervention to treat comorbidities and maintain renal function.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"414-425"},"PeriodicalIF":3.1,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14378","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143031776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I read with great interest the article “Rising mortality rates linked to type-2 diabetes and obesity in the United States: An observational analysis from 1999 to 20221.” The study offers valuable insights into a critical public health issue. However, I noticed an apparent discrepancy between the statistical analysis and the graphical representation of the age-adjusted mortality rate (AAMR) trends.
The results section states that the AAMR increased steadily from 1999 to 2017 and then rose steeply. While I understand that the Annual Percentage Change (APC) analysis may have detected a statistical trend starting in 2017, the steep increase is more visually apparent only after 2019, as shown in figure 1. This disconnect between the statistical interpretation and the visual data could potentially confuse readers.
I would appreciate it if the authors could clarify how the APC analysis aligns with the visual trends in the graph. This clarification would ensure a more accurate understanding of the results and help bridge the gap between statistical and visual interpretations.
Thank you for your attention to this matter.
None.
The author declares no conflict of interest.
Approval of the research protocol: N/A.
Informed consent: N/A.
Registry and the registration no. of the study/trial: N/A.
Animal studies: N/A.
{"title":"Letter to Editor in response to the article “Rising mortality rates linked to type-2 diabetes and obesity in the United States: An observational analysis from 1999 to 2022”","authors":"Muheem Khan","doi":"10.1111/jdi.14412","DOIUrl":"10.1111/jdi.14412","url":null,"abstract":"<p>Dear Editor,</p><p>I read with great interest the article “Rising mortality rates linked to type-2 diabetes and obesity in the United States: An observational analysis from 1999 to 2022<span><sup>1</sup></span>.” The study offers valuable insights into a critical public health issue. However, I noticed an apparent discrepancy between the statistical analysis and the graphical representation of the age-adjusted mortality rate (AAMR) trends.</p><p>The results section states that the AAMR increased steadily from 1999 to 2017 and then rose steeply. While I understand that the Annual Percentage Change (APC) analysis may have detected a statistical trend starting in 2017, the steep increase is more visually apparent only after 2019, as shown in figure 1. This disconnect between the statistical interpretation and the visual data could potentially confuse readers.</p><p>I would appreciate it if the authors could clarify how the APC analysis aligns with the visual trends in the graph. This clarification would ensure a more accurate understanding of the results and help bridge the gap between statistical and visual interpretations.</p><p>Thank you for your attention to this matter.</p><p>None.</p><p>The author declares no conflict of interest.</p><p>Approval of the research protocol: N/A.</p><p>Informed consent: N/A.</p><p>Registry and the registration no. of the study/trial: N/A.</p><p>Animal studies: N/A.</p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"563"},"PeriodicalIF":3.1,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14412","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fatemeh Rasulpur, Mohammad Barary, Mostafa Javanian, Soheil Ebrahimpour
<p>Dear Editor,</p><p>We read with great interest the article titled “Prognostic Value of Longitudinal HbA1c Variability in Predicting the Development of Diabetic Sensorimotor Polyneuropathy Among Patients with Type 2 Diabetes Mellitus: A Prospective Cohort Observational Study” by Lai <i>et al</i>.<span><sup>1</sup></span> The study identifies average real variability (HbA1c ARV) as the most predictive measure of HbA1c variability for anticipating new cases of diabetic sensorimotor polyneuropathy (DSPN) in patients with type 2 diabetes mellitus. The authors' meticulous investigation of HbA1c variability in the context of DSPN risk adds substantial value to the growing body of literature on glycemic control. However, we believe that addressing the following methodological aspects would enhance the robustness of the findings and provide broader clinical insights.</p><p>While the study convincingly establishes the predictive value of HbA1c ARV, the lack of additional laboratory parameters limits its scope. Biomarkers such as thyroid and liver function tests, vitamin B12, zinc, copper, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and the systemic immune-inflammation index (SII) have been implicated in diabetic complications and could potentially provide further insights into DSPN risk<span><sup>2</sup></span>. The absence of these markers leaves room for residual confounding, especially in a multifactorial condition like DSPN, where inflammation and micronutrient deficiencies play critical roles.</p><p>The article does not detail the concurrent use of other medications, such as lipid-lowering therapies, antihypertensives, and antibiotics, which could significantly influence the development or progression of neuropathy<span><sup>3</sup></span>. For example, statins have been linked to myopathy and neuropathy in specific populations, while the anti-inflammatory properties of some drugs might modulate DSPN risk. A more comprehensive medication profile would strengthen the causal attributions made in this study.</p><p>Comorbidities such as psychological disorders, autoimmune diseases, and thyroid dysfunctions were not adequately accounted for. Each of these conditions has been independently associated with neuropathy<span><sup>4</sup></span>. Their exclusion not only limits the generalizability of the findings but may also lead to overestimation of the role of HbA1c variability.</p><p>Socioeconomic determinants, including urban vs rural residency, educational attainment, and income, were overlooked. Additionally, lifestyle factors such as physical activity levels, alcohol consumption, and dietary habits could significantly modify the risk of DSPN. These factors are particularly relevant in assessing glycemic variability, as they influence both HbA1c levels and overall diabetes management.</p><p>The study does not report on insulin resistance or vitamin D status—both key players in the pathogenesis of neuropathy. Insulin resis
{"title":"Commentary on “Prognostic value of longitudinal HbA1c variability in predicting the development of diabetic sensorimotor polyneuropathy among patients with type 2 diabetes mellitus: A prospective cohort observational study”","authors":"Fatemeh Rasulpur, Mohammad Barary, Mostafa Javanian, Soheil Ebrahimpour","doi":"10.1111/jdi.14408","DOIUrl":"10.1111/jdi.14408","url":null,"abstract":"<p>Dear Editor,</p><p>We read with great interest the article titled “Prognostic Value of Longitudinal HbA1c Variability in Predicting the Development of Diabetic Sensorimotor Polyneuropathy Among Patients with Type 2 Diabetes Mellitus: A Prospective Cohort Observational Study” by Lai <i>et al</i>.<span><sup>1</sup></span> The study identifies average real variability (HbA1c ARV) as the most predictive measure of HbA1c variability for anticipating new cases of diabetic sensorimotor polyneuropathy (DSPN) in patients with type 2 diabetes mellitus. The authors' meticulous investigation of HbA1c variability in the context of DSPN risk adds substantial value to the growing body of literature on glycemic control. However, we believe that addressing the following methodological aspects would enhance the robustness of the findings and provide broader clinical insights.</p><p>While the study convincingly establishes the predictive value of HbA1c ARV, the lack of additional laboratory parameters limits its scope. Biomarkers such as thyroid and liver function tests, vitamin B12, zinc, copper, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and the systemic immune-inflammation index (SII) have been implicated in diabetic complications and could potentially provide further insights into DSPN risk<span><sup>2</sup></span>. The absence of these markers leaves room for residual confounding, especially in a multifactorial condition like DSPN, where inflammation and micronutrient deficiencies play critical roles.</p><p>The article does not detail the concurrent use of other medications, such as lipid-lowering therapies, antihypertensives, and antibiotics, which could significantly influence the development or progression of neuropathy<span><sup>3</sup></span>. For example, statins have been linked to myopathy and neuropathy in specific populations, while the anti-inflammatory properties of some drugs might modulate DSPN risk. A more comprehensive medication profile would strengthen the causal attributions made in this study.</p><p>Comorbidities such as psychological disorders, autoimmune diseases, and thyroid dysfunctions were not adequately accounted for. Each of these conditions has been independently associated with neuropathy<span><sup>4</sup></span>. Their exclusion not only limits the generalizability of the findings but may also lead to overestimation of the role of HbA1c variability.</p><p>Socioeconomic determinants, including urban vs rural residency, educational attainment, and income, were overlooked. Additionally, lifestyle factors such as physical activity levels, alcohol consumption, and dietary habits could significantly modify the risk of DSPN. These factors are particularly relevant in assessing glycemic variability, as they influence both HbA1c levels and overall diabetes management.</p><p>The study does not report on insulin resistance or vitamin D status—both key players in the pathogenesis of neuropathy. Insulin resis","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"561-562"},"PeriodicalIF":3.1,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142996879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our study aimed to evaluate the effectiveness of a 3-months digital therapy (DTx) intervention in the real world for the management of blood glucose in 3,902 Chinese patients with type 2 diabetes (T2D) in Lingshui, Hainan.
Methods
Adults with T2D who were capable of using DTx application (app) were enrolled. Fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPBG), and body weight before and after the intervention were collected. Participants recorded blood glucose and body weight at least once weekly, and attended diabetes education program with the app during online follow-up once weekly.
Results
A total of, 3,902 patients with T2D were enrolled, including 46.3% of men, with an average age of 64.3 years. After 3-months of DTx, FBG decreased by 0.52 mmol/L (8.05–7.53, P < 0.001) from baseline, 2hPBG decreased by 1.18 mmol/L (11.95–10.77, P < 0.001), and body weight decreased by 1.50 kg (61.18–59.68, P < 0.001). The median number of glucose self-reports for each patient was three (0, 273) times. Defining participants who finished glucose or weight self-report for once within 7 days as the motivated group (n = 1,013), the motivated group showed significant weight loss after DTx intervention (motivated group vs inactive group, −3.01 kg vs −0.36 kg, P < 0.01). No significant difference was found in FBG and 2hPBG between the two groups.
Conclusions
DTx reveals significant efficacy on glucose and weight control in patients with T2D, which can reduce FBG, PBG, and body weight. Better compliance and motivation with DTx and frequent weight monitoring help achieve better weight control.
{"title":"An interventional study of digital therapy on blood glucose and weight management in Chinese patients with type 2 diabetes","authors":"Difei Lu, Wenfeng Jiang, Dongyan Ai, Chaoping Cen, Qianying Ou, Kaining Chen, Junqing Zhang","doi":"10.1111/jdi.14376","DOIUrl":"10.1111/jdi.14376","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Our study aimed to evaluate the effectiveness of a 3-months digital therapy (DTx) intervention in the real world for the management of blood glucose in 3,902 Chinese patients with type 2 diabetes (T2D) in Lingshui, Hainan.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Adults with T2D who were capable of using DTx application (app) were enrolled. Fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPBG), and body weight before and after the intervention were collected. Participants recorded blood glucose and body weight at least once weekly, and attended diabetes education program with the app during online follow-up once weekly.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of, 3,902 patients with T2D were enrolled, including 46.3% of men, with an average age of 64.3 years. After 3-months of DTx, FBG decreased by 0.52 mmol/L (8.05–7.53, <i>P</i> < 0.001) from baseline, 2hPBG decreased by 1.18 mmol/L (11.95–10.77, <i>P</i> < 0.001), and body weight decreased by 1.50 kg (61.18–59.68, <i>P</i> < 0.001). The median number of glucose self-reports for each patient was three (0, 273) times. Defining participants who finished glucose or weight self-report for once within 7 days as the motivated group (<i>n</i> = 1,013), the motivated group showed significant weight loss after DTx intervention (motivated group vs inactive group, −3.01 kg vs −0.36 kg, <i>P</i> < 0.01). No significant difference was found in FBG and 2hPBG between the two groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>DTx reveals significant efficacy on glucose and weight control in patients with T2D, which can reduce FBG, PBG, and body weight. Better compliance and motivation with DTx and frequent weight monitoring help achieve better weight control.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"475-480"},"PeriodicalIF":3.1,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142996875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Currently, there are no effective pharmacological treatments for diabetic neuropathy. It is widely recognized that a comprehensive therapeutic approach should include both the management of risk factors and the implementation of strict, early blood glucose control.</p><p>The European Diabetes (EURODIAB) Prospective Study identified several independent risk factors for diabetic neuropathy. Tesfaye <i>et al</i>.<span><sup>1</sup></span> examined modifiable risk factors contributing to the development of diabetic neuropathy in 1,172 patients with type 1 diabetes mellitus, in EURODIAB Prospective Complications Study. Their analysis demonstrated that the total incidence of neuropathy was closely linked to glycosylated hemoglobin levels and the duration of diabetes. After adjustment for these factors, the study found that elevated total and low-density lipoprotein (LDL) cholesterol levels, higher triglycerides, increased body mass index (BMI), elevated von Willebrand factor, greater urinary albumin excretion, hypertension, and smoking were all significantly associated with the risk of neuropathy. These findings suggest that rigorous management of risk factors, including hypertension, dyslipidemia, obesity, and smoking, may be vital for the effective treatment of diabetic neuropathy.</p><p>Conversely, increasing evidence supports a link between the degree of obesity and the risk of developing diabetic neuropathy in type 2 diabetes, with components of metabolic syndrome also recognized as significant risk factors for diabetic neuropathy<span><sup>2</sup></span>. Christensen <i>et al</i>.<span><sup>3</sup></span> examined the relationship between metabolic and lifestyle factors and the onset of possible diabetic neuropathy and neuropathic pain in patients with early-stage type 2 diabetes. Their study revealed that central obesity, measured by waist circumference, waist-to-hip ratio, and waist-to-height ratio, was strongly associated with diabetic neuropathy. Additionally, other key metabolic factors, including hypertriglyceridemia, decreased high-density lipoprotein (HDL) cholesterol, high-sensitivity C-reactive protein (hs-CRP), C-peptide, and HbA1c, were linked to diabetic neuropathy. Antihypertensive medication use, smoking, and physical inactivity were also found to be associated with diabetic neuropathy, while smoking, excessive alcohol consumption, and a failure to increase physical activity following a diabetes diagnosis were related to neuropathic pain. The study concluded that potential diabetic neuropathy is correlated with metabolic syndrome factors, insulin resistance, inflammation, and modifiable lifestyle behaviors in early-stage type 2 diabetes. Therefore, addressing metabolic and lifestyle risk factors is essential for the effective management of diabetic neuropathy.</p><p>Patients newly diagnosed with type 2 diabetes mellitus can be stratified into three distinct pathophysiological categories based on the homeostasis model assessment-2
{"title":"High HOMA2-B: A novel risk factor for diabetic peripheral neuropathy beyond metabolic syndrome components in type 2 diabetes","authors":"Koichi Kato","doi":"10.1111/jdi.14403","DOIUrl":"10.1111/jdi.14403","url":null,"abstract":"<p>Currently, there are no effective pharmacological treatments for diabetic neuropathy. It is widely recognized that a comprehensive therapeutic approach should include both the management of risk factors and the implementation of strict, early blood glucose control.</p><p>The European Diabetes (EURODIAB) Prospective Study identified several independent risk factors for diabetic neuropathy. Tesfaye <i>et al</i>.<span><sup>1</sup></span> examined modifiable risk factors contributing to the development of diabetic neuropathy in 1,172 patients with type 1 diabetes mellitus, in EURODIAB Prospective Complications Study. Their analysis demonstrated that the total incidence of neuropathy was closely linked to glycosylated hemoglobin levels and the duration of diabetes. After adjustment for these factors, the study found that elevated total and low-density lipoprotein (LDL) cholesterol levels, higher triglycerides, increased body mass index (BMI), elevated von Willebrand factor, greater urinary albumin excretion, hypertension, and smoking were all significantly associated with the risk of neuropathy. These findings suggest that rigorous management of risk factors, including hypertension, dyslipidemia, obesity, and smoking, may be vital for the effective treatment of diabetic neuropathy.</p><p>Conversely, increasing evidence supports a link between the degree of obesity and the risk of developing diabetic neuropathy in type 2 diabetes, with components of metabolic syndrome also recognized as significant risk factors for diabetic neuropathy<span><sup>2</sup></span>. Christensen <i>et al</i>.<span><sup>3</sup></span> examined the relationship between metabolic and lifestyle factors and the onset of possible diabetic neuropathy and neuropathic pain in patients with early-stage type 2 diabetes. Their study revealed that central obesity, measured by waist circumference, waist-to-hip ratio, and waist-to-height ratio, was strongly associated with diabetic neuropathy. Additionally, other key metabolic factors, including hypertriglyceridemia, decreased high-density lipoprotein (HDL) cholesterol, high-sensitivity C-reactive protein (hs-CRP), C-peptide, and HbA1c, were linked to diabetic neuropathy. Antihypertensive medication use, smoking, and physical inactivity were also found to be associated with diabetic neuropathy, while smoking, excessive alcohol consumption, and a failure to increase physical activity following a diabetes diagnosis were related to neuropathic pain. The study concluded that potential diabetic neuropathy is correlated with metabolic syndrome factors, insulin resistance, inflammation, and modifiable lifestyle behaviors in early-stage type 2 diabetes. Therefore, addressing metabolic and lifestyle risk factors is essential for the effective management of diabetic neuropathy.</p><p>Patients newly diagnosed with type 2 diabetes mellitus can be stratified into three distinct pathophysiological categories based on the homeostasis model assessment-2","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"389-391"},"PeriodicalIF":3.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14403","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142996883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Low-density lipoprotein cholesterol (LDL-C) is known to be a causal substance of atherosclerosis, but its usefulness as a predictive biomarker for atherosclerotic cardiovascular disease (ASCVD) is limited. In patients with type 2 diabetes (T2D), LDL-C concentrations do not markedly increase, while triglycerides (TG) concentrations are usually elevated. Although TG is associated with ASCVD risk, they do not play a direct role in the formation of atheromatous plaques. TG changes the risk of ASCVD in a way that is dependent on LDL-C, and TG is the primary factor in reducing LDL particle size. Small dense (sd)LDL, a potent atherogenic LDL subfraction, best explains the “Atherogenic Duo” of TG and LDL-C. Although hypertriglyceridemia is associated with small-sized LDL, patients with severe hypertriglyceridemia and low LDL-C rarely develop ASCVD. This suggests that quantifying sdLDL is more clinically relevant than measuring LDL size. We developed a full-automated direct sdLDL-C assay, and it was proven that sdLDL-C is a better predictor of ASCVD than LDL-C. The sdLDL-C level is specifically elevated in patients with metabolic syndrome and T2D who have insulin resistance. Due to its clear link to metabolic dysfunction, sdLDL-C could be named “metabolic LDL-C.” Insulin resistance/hyperinsulinemia promotes TG production in the liver, causing steatosis and overproduction of VLDL1, a precursor of sdLDL. sdLDL-C is closely associated with steatotic liver disease and chronic kidney disease, which are common complications in T2D. This review focuses on T2D and discusses the clinical significance of sdLDL-C including its composition, pathophysiology, measurements, association with ASCVD, and treatments.
{"title":"Clinical significance of small dense low-density lipoprotein cholesterol measurement in type 2 diabetes","authors":"Tsutomu Hirano","doi":"10.1111/jdi.14398","DOIUrl":"10.1111/jdi.14398","url":null,"abstract":"<p>Low-density lipoprotein cholesterol (LDL-C) is known to be a causal substance of atherosclerosis, but its usefulness as a predictive biomarker for atherosclerotic cardiovascular disease (ASCVD) is limited. In patients with type 2 diabetes (T2D), LDL-C concentrations do not markedly increase, while triglycerides (TG) concentrations are usually elevated. Although TG is associated with ASCVD risk, they do not play a direct role in the formation of atheromatous plaques. TG changes the risk of ASCVD in a way that is dependent on LDL-C, and TG is the primary factor in reducing LDL particle size. Small dense (sd)LDL, a potent atherogenic LDL subfraction, best explains the “Atherogenic Duo” of TG and LDL-C. Although hypertriglyceridemia is associated with small-sized LDL, patients with severe hypertriglyceridemia and low LDL-C rarely develop ASCVD. This suggests that quantifying sdLDL is more clinically relevant than measuring LDL size. We developed a full-automated direct sdLDL-C assay, and it was proven that sdLDL-C is a better predictor of ASCVD than LDL-C. The sdLDL-C level is specifically elevated in patients with metabolic syndrome and T2D who have insulin resistance. Due to its clear link to metabolic dysfunction, sdLDL-C could be named “metabolic LDL-C.” Insulin resistance/hyperinsulinemia promotes TG production in the liver, causing steatosis and overproduction of VLDL1, a precursor of sdLDL. sdLDL-C is closely associated with steatotic liver disease and chronic kidney disease, which are common complications in T2D. This review focuses on T2D and discusses the clinical significance of sdLDL-C including its composition, pathophysiology, measurements, association with ASCVD, and treatments.</p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"370-383"},"PeriodicalIF":3.1,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14398","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142941763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several studies have reported the potential association between smoking and diabetic nephropathy. However, the studies of non-significant association results were against the association between smoking and diabetic nephropathy. Therefore, the relationship between smoking and diabetic nephropathy was still debated and controversial.
Methods
Prospective cohort studies were included in the current meta-analysis. The tobacco smoking (current smokers or former smokers) and non-smoking groups in the enrolled studies were compared for the hazard ratio (HR) of diabetic nephropathy. Fifteen studies with 221,821 subjects were included in this meta-analysis. Subgroup analysis of the type 1 diabetes and type 2 diabetes groups was also performed individually to investigate the effects of different types of diabetes on the relationship between smoking and diabetic nephropathy.
Results
Current smoking was significantly associated with a greater log HR of diabetic nephropathy [1.44 (1.22–1.70), Z = 4.39]. In addition, former smoking was significantly associated with diabetic nephropathy [log HR = 1.04 (1.03–1.05), Z = 8.02]. The individual subgroup analysis of type 1 diabetes and type 2 diabetes subjects showed that smoking might be both significantly associated with greater log HRs of diabetic nephropathy.
Discussion
Current and former smoking might be the risk factors for diabetic nephropathy in the current meta-analytic results. The phenomenon of such significant associations were discovered in type 1 and 2 diabetes.
{"title":"Smoking and diabetic nephropathy: An updated systematic review and meta-analysis","authors":"Haihui Zhu, Liang Li, Songchun Liu, Jing Li","doi":"10.1111/jdi.14385","DOIUrl":"10.1111/jdi.14385","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>Several studies have reported the potential association between smoking and diabetic nephropathy. However, the studies of non-significant association results were against the association between smoking and diabetic nephropathy. Therefore, the relationship between smoking and diabetic nephropathy was still debated and controversial.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Prospective cohort studies were included in the current meta-analysis. The tobacco smoking (current smokers or former smokers) and non-smoking groups in the enrolled studies were compared for the hazard ratio (HR) of diabetic nephropathy. Fifteen studies with 221,821 subjects were included in this meta-analysis. Subgroup analysis of the type 1 diabetes and type 2 diabetes groups was also performed individually to investigate the effects of different types of diabetes on the relationship between smoking and diabetic nephropathy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Current smoking was significantly associated with a greater log HR of diabetic nephropathy [1.44 (1.22–1.70), <i>Z</i> = 4.39]. In addition, former smoking was significantly associated with diabetic nephropathy [log HR = 1.04 (1.03–1.05), <i>Z</i> = 8.02]. The individual subgroup analysis of type 1 diabetes and type 2 diabetes subjects showed that smoking might be both significantly associated with greater log HRs of diabetic nephropathy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Current and former smoking might be the risk factors for diabetic nephropathy in the current meta-analytic results. The phenomenon of such significant associations were discovered in type 1 and 2 diabetes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"442-450"},"PeriodicalIF":3.1,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14385","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Li Jiang, Jie Jian, Xulin Sai, Hongda Yu, Wanxian Liang, Xiai Wu
Objective
To explore and validate the association between the oxidative balance and prevalence of diabetic kidney disease (DKD) and mortality in patients with diabetes.
Study design
A large and representative sample from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2016 was analyzed to study the potential association between Oxidative Balance Score (OBS) and prognosis of DKD in adult diabetic patients. Weighted multivariate logistic regression analysis was conducted to examine the relationship between OBS and DKD risk. Subgroup analysis, sensitivity analysis, and mediation effect analysis were conducted to explore the effect of the covariates and assess the robustness of the findings. Mendelian randomization (MR) was employed to evaluate the correlated relationship between mitochondrial reactive oxygen species (ROS) levels and DKD at the genetic level.
Result
The highest OBS quartile showed the most significant negative correlation with DKD compared to the lowest OBS quartile (OR = 0.62, 95% CI 0.41–0.92, P = 0.017). Higher OBS was associated with a reduced risk of DKD (OR = 0.96; 95% CI = 0.93, 0.98; P < 0.001) and mortality (P = 0.021 by log-rank) in diabetic patients. This association remained robust even after excluding individual OBS components. Subgroup analysis revealed the interaction of metabolic syndrome on OBS was significant. Mediation analyses revealed that OBS's effect on DKD was independent of blood uric acid and cholesterol. Restricted cubic spline (RCS) analysis indicated a typical L-shaped relationship between OBS and DKD risk. The physical activity was identified as the core variable predicting DKD risk by two machine learning algorithms. MR showed a potential correlated relationship between ROS and microalbuminuria in DKD.
Conclusions
The high level of oxidative balance score was negatively correlated with the risk of DKD and mortality in diabetic patients.
目的：探讨并验证糖尿病患者氧化平衡与糖尿病肾病（DKD）患病率及死亡率之间的关系。研究设计：分析2013 - 2016年全国健康与营养调查（NHANES）中具有代表性的大样本，研究成人糖尿病患者氧化平衡评分（OBS）与DKD预后之间的潜在关联。采用加权多因素logistic回归分析检验OBS与DKD风险之间的关系。通过亚组分析、敏感性分析和中介效应分析来探讨协变量的影响并评估研究结果的稳健性。采用孟德尔随机化（Mendelian randomization， MR）在遗传水平上评估线粒体活性氧（reactive oxygen species， ROS）水平与DKD之间的相关关系。结果：与最低OBS四分位数相比，最高OBS四分位数与DKD呈最显著的负相关（OR = 0.62, 95% CI 0.41-0.92, P = 0.017）。较高的OBS与DKD风险降低相关(OR = 0.96；95% ci = 0.93, 0.98；结论：高水平的氧化平衡评分与糖尿病患者DKD风险和死亡率呈负相关。
{"title":"Oxidative balance is associated with diabetic kidney disease and mortality in adults with diabetes mellitus: Insights from NHANES database and Mendelian randomization","authors":"Li Jiang, Jie Jian, Xulin Sai, Hongda Yu, Wanxian Liang, Xiai Wu","doi":"10.1111/jdi.14390","DOIUrl":"10.1111/jdi.14390","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To explore and validate the association between the oxidative balance and prevalence of diabetic kidney disease (DKD) and mortality in patients with diabetes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study design</h3>\u0000 \u0000 <p>A large and representative sample from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2016 was analyzed to study the potential association between Oxidative Balance Score (OBS) and prognosis of DKD in adult diabetic patients. Weighted multivariate logistic regression analysis was conducted to examine the relationship between OBS and DKD risk. Subgroup analysis, sensitivity analysis, and mediation effect analysis were conducted to explore the effect of the covariates and assess the robustness of the findings. Mendelian randomization (MR) was employed to evaluate the correlated relationship between mitochondrial reactive oxygen species (ROS) levels and DKD at the genetic level.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Result</h3>\u0000 \u0000 <p>The highest OBS quartile showed the most significant negative correlation with DKD compared to the lowest OBS quartile (OR = 0.62, 95% CI 0.41–0.92, <i>P</i> = 0.017). Higher OBS was associated with a reduced risk of DKD (OR = 0.96; 95% CI = 0.93, 0.98; <i>P</i> < 0.001) and mortality (<i>P</i> = 0.021 by log-rank) in diabetic patients. This association remained robust even after excluding individual OBS components. Subgroup analysis revealed the interaction of metabolic syndrome on OBS was significant. Mediation analyses revealed that OBS's effect on DKD was independent of blood uric acid and cholesterol. Restricted cubic spline (RCS) analysis indicated a typical L-shaped relationship between OBS and DKD risk. The physical activity was identified as the core variable predicting DKD risk by two machine learning algorithms. MR showed a potential correlated relationship between ROS and microalbuminuria in DKD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The high level of oxidative balance score was negatively correlated with the risk of DKD and mortality in diabetic patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"451-462"},"PeriodicalIF":3.1,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14390","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This review highlights the significance of the Japan Diabetes Complications Study (JDCS), one of the earliest large-scale studies of people with type 2 diabetes outside Europe and the United States, in understanding type 2 diabetes mellitus among East Asian populations, particularly in Japan. Historically, large-scale clinical studies on type 2 diabetes mellitus have predominantly focused on Western populations, despite East Asians comprising the largest proportion of diabetic patients globally. The JDCS, which was initiated in 1996, enrolled 2,033 Japanese type 2 diabetes mellitus patients. It aimed to evaluate the effects of intensive lifestyle interventions on diabetic complications. The study demonstrated that lifestyle-focused interventions significantly reduced the risk of stroke and other complications compared to conventional treatment. Key findings of its sub-analyses include the unique characteristics of Japanese patients with type 2 diabetes mellitus, such as their lower body mass index (BMI) compared to Western counterparts and a stronger association between even modest BMI increases and beta cell dysfunction. Additionally, the JDCS provided insights into the risk factors for nephropathy, retinopathy, and macrovascular complications, emphasizing the importance of controlling blood pressure, glycemia, and lifestyle factors. The study also explored the impact of diet, exercise, and mental health on diabetic outcomes, revealing the protective effects of physical activity and a balanced diet, while highlighting the risks associated with high salt intake and depression. A risk prediction model tailored to Japanese patients was also developed. Overall, this study made a significant contribution to the evidence-based management of type 2 diabetes mellitus in East Asia.
{"title":"Japan Diabetes Complications Study: Revisiting one of the first large-scale clinical studies in East Asians with diabetes","authors":"Hirohito Sone, Chika Horikawa, Sachiko Tanaka-Mizuno, Ryo Kawasaki, Kazuya Fujihara, Tatsumi Moriya, Atsushi Araki, Shiro Tanaka, Yasuo Akanuma","doi":"10.1111/jdi.14394","DOIUrl":"10.1111/jdi.14394","url":null,"abstract":"<p>This review highlights the significance of the Japan Diabetes Complications Study (JDCS), one of the earliest large-scale studies of people with type 2 diabetes outside Europe and the United States, in understanding type 2 diabetes mellitus among East Asian populations, particularly in Japan. Historically, large-scale clinical studies on type 2 diabetes mellitus have predominantly focused on Western populations, despite East Asians comprising the largest proportion of diabetic patients globally. The JDCS, which was initiated in 1996, enrolled 2,033 Japanese type 2 diabetes mellitus patients. It aimed to evaluate the effects of intensive lifestyle interventions on diabetic complications. The study demonstrated that lifestyle-focused interventions significantly reduced the risk of stroke and other complications compared to conventional treatment. Key findings of its sub-analyses include the unique characteristics of Japanese patients with type 2 diabetes mellitus, such as their lower body mass index (BMI) compared to Western counterparts and a stronger association between even modest BMI increases and beta cell dysfunction. Additionally, the JDCS provided insights into the risk factors for nephropathy, retinopathy, and macrovascular complications, emphasizing the importance of controlling blood pressure, glycemia, and lifestyle factors. The study also explored the impact of diet, exercise, and mental health on diabetic outcomes, revealing the protective effects of physical activity and a balanced diet, while highlighting the risks associated with high salt intake and depression. A risk prediction model tailored to Japanese patients was also developed. Overall, this study made a significant contribution to the evidence-based management of type 2 diabetes mellitus in East Asia.</p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"360-369"},"PeriodicalIF":3.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhengyi Long, Jingyun Du, Jie Hu, Yang Xiao, Can Hou
Background
The relationship between the systemic immune–inflammatory index (SII) and the prognosis of cardiovascular disease (CVD) patients with diabetes or prediabetes remains uncertain. This study investigated the association between baseline SII and all-cause and cardiovascular mortality in American adults with CVD and diabetes or prediabetes.
Methods
Our survey included 4,060 adults with cardiovascular disease and diabetes or prediabetes from the National Health and Nutrition Examination Survey (1998–2020). Using restricted cubic splines (RCS) based on Cox regression models and a two-piecewise Cox proportional hazards model for both sides of the inflection point, we elucidated the nonlinear relationship between baseline SII and mortality. Mediation analysis was used to explore the indirect impact of SII on mortality through eGFR.
Results
In the median 129 months of follow-up, 620 people died from cardiovascular causes and 1,800 from all causes. In the CVD population with diabetes or prediabetes, SII showed a U-shaped relationship with all-cause mortality. The association between SII and CVD mortality was nonlinear and J-shaped. Stratified and interaction analysis confirmed the stability of the core results. Notably, eGFR partially mediated the association between SII and both all-cause and cardiovascular mortality by 9.4% and 6.9%, respectively.
Conclusions
SII revealed a U-shaped relationship with all-cause mortality (inflection point: lnSII = 6) and a J-shaped association with CVD mortality (inflection point: lnSII = 5.73) in CVD patients with diabetes or prediabetes among American patients. Thus, assessing the SII index may offer valuable insights into risk assessment and prognosis in patients with CVD who are diabetic or prediabetic.
{"title":"The prognostic value of the systemic immunity–inflammation index for cardiovascular and all-cause mortality in cardiovascular disease patients with diabetes or prediabetes","authors":"Zhengyi Long, Jingyun Du, Jie Hu, Yang Xiao, Can Hou","doi":"10.1111/jdi.14383","DOIUrl":"10.1111/jdi.14383","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The relationship between the systemic immune–inflammatory index (SII) and the prognosis of cardiovascular disease (CVD) patients with diabetes or prediabetes remains uncertain. This study investigated the association between baseline SII and all-cause and cardiovascular mortality in American adults with CVD and diabetes or prediabetes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Our survey included 4,060 adults with cardiovascular disease and diabetes or prediabetes from the National Health and Nutrition Examination Survey (1998–2020). Using restricted cubic splines (RCS) based on Cox regression models and a two-piecewise Cox proportional hazards model for both sides of the inflection point, we elucidated the nonlinear relationship between baseline SII and mortality. Mediation analysis was used to explore the indirect impact of SII on mortality through eGFR.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In the median 129 months of follow-up, 620 people died from cardiovascular causes and 1,800 from all causes. In the CVD population with diabetes or prediabetes, SII showed a U-shaped relationship with all-cause mortality. The association between SII and CVD mortality was nonlinear and J-shaped. Stratified and interaction analysis confirmed the stability of the core results. Notably, eGFR partially mediated the association between SII and both all-cause and cardiovascular mortality by 9.4% and 6.9%, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>SII revealed a U-shaped relationship with all-cause mortality (inflection point: lnSII = 6) and a J-shaped association with CVD mortality (inflection point: lnSII = 5.73) in CVD patients with diabetes or prediabetes among American patients. Thus, assessing the SII index may offer valuable insights into risk assessment and prognosis in patients with CVD who are diabetic or prediabetic.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 3","pages":"510-520"},"PeriodicalIF":3.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14383","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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