Xiaoyu Meng, Haiyang Du, Danpei Li, Yaming Guo, Peiqiong Luo, Limeng Pan, Ranran Kan, Peng Yu, Yuxi Xiang, Beibei Mao, Yi He, Siyi Wang, Wenjun Li, Yan Yang, Xuefeng Yu
Background
Diabetes is a prevalent public health issue worldwide, and the cognitive dysfunction and subsequent dementia caused by it seriously affect the quality of life of patients.
Methods
Recent studies were reviewed to provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for diabetes-related cognitive dysfunction (DACD).
Results
Several risk factors contribute to DACD, including hyperglycemia, hypoglycemia, blood sugar fluctuations, hyperinsulinemia, aging, and others. Among them, modifiable risk factors for DACD include blood glucose control, physical activity, diet, smoking, and hypertension management, while non-modifiable risk factors include age, genetic predisposition, sex, and duration of diabetes. At the present, the pathogenesis of DACD mainly includes insulin resistance, neuroinflammation, vascular disorders, oxidative stress, and neurotransmitter disorders.
Conclusions
In this review, we provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for DACD, providing information from multiple perspectives for its prevention and management.
{"title":"Risk Factors, Pathological Changes, and Potential Treatment of Diabetes-Associated Cognitive Dysfunction","authors":"Xiaoyu Meng, Haiyang Du, Danpei Li, Yaming Guo, Peiqiong Luo, Limeng Pan, Ranran Kan, Peng Yu, Yuxi Xiang, Beibei Mao, Yi He, Siyi Wang, Wenjun Li, Yan Yang, Xuefeng Yu","doi":"10.1111/1753-0407.70089","DOIUrl":"https://doi.org/10.1111/1753-0407.70089","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Diabetes is a prevalent public health issue worldwide, and the cognitive dysfunction and subsequent dementia caused by it seriously affect the quality of life of patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Recent studies were reviewed to provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for diabetes-related cognitive dysfunction (DACD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Several risk factors contribute to DACD, including hyperglycemia, hypoglycemia, blood sugar fluctuations, hyperinsulinemia, aging, and others. Among them, modifiable risk factors for DACD include blood glucose control, physical activity, diet, smoking, and hypertension management, while non-modifiable risk factors include age, genetic predisposition, sex, and duration of diabetes. At the present, the pathogenesis of DACD mainly includes insulin resistance, neuroinflammation, vascular disorders, oxidative stress, and neurotransmitter disorders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In this review, we provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for DACD, providing information from multiple perspectives for its prevention and management.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We appreciate the author's attention to our study [1] and their detailed comments. To address their questions and help the readers better understand this research, we would like to provide the following explanation of our study's process.
A study titled “Altitudes and Hemoglobin A1c Value” conducted by my colleagues was published in 2024 [2]. Their analysis, which included 95 052 individuals across 162 sites in China, revealed a positive correlation between altitude above 2500 m and HbA1c levels, while no such correlation was observed at altitudes below 2500 m. Due to the lack of data on hemoglobin concentrations and red blood cell counts, their study could not provide more in-depth results. Fortunately, our team had some data suitable for further investigation. We selected two cities with altitudes below 2500 m: Kunming (1891 m) and Chengdu (503 m). The hemoglobin concentration in Kunming (mean: 158.73 g/L, SD: 16.36) was higher than in Chengdu (mean: 145.44 g/L, SD: 16.82). There was no difference in HbA1c levels between two groups, with Kunming showing a mean of 5.40 (SD: 0.48) and Chengdu 5.41 (SD: 0.41).
Although hemoglobin levels in the two cities differ, they remain within the normal reference range. Moreover, residents of both cities shared similar lifestyles and socio-economic conditions; we combined the data to analyze the effects of gender and age. We employed the Generalized Additive Model (GAM) for our analysis, as it effectively captures nonlinear relationships and allows us to focus on trends and patterns. Notably, Figure D reveals a significant gender-based difference in the relationship between HbA1c and age. The HbA1c curve for women shows a distinctive turning point around age 45, which prompted our further investigation in Figures C and D. In Figure D, the disparity in HbA1c levels between women above and below the age of 45 is likely influenced by menopause and changes in estrogen levels. Unfortunately, our dataset does not include estrogen-related data, preventing further analyses in this direction. However, a previous study indicated that estrogen therapy in postmenopausal women with type 1 or type 2 diabetes can reduce HbA1c and fasting glucose levels, which supports our findings [3].
We acknowledge that our analysis has limitations regarding the types and scope of the real-world clinical data. Therefore, the findings presented in this article underscore the need for more epidemiological studies with rigorous system design to achieve more reliable conclusions.
{"title":"Response to Commentary on “A Population-Based Correlation Analysis Between Hemoglobin A1c and Hemoglobin Levels”","authors":"Tingyu Zhang, Bin Cui","doi":"10.1111/1753-0407.70086","DOIUrl":"https://doi.org/10.1111/1753-0407.70086","url":null,"abstract":"<p>We appreciate the author's attention to our study [<span>1</span>] and their detailed comments. To address their questions and help the readers better understand this research, we would like to provide the following explanation of our study's process.</p><p>A study titled “Altitudes and Hemoglobin A1c Value” conducted by my colleagues was published in 2024 [<span>2</span>]. Their analysis, which included 95 052 individuals across 162 sites in China, revealed a positive correlation between altitude above 2500 m and HbA1c levels, while no such correlation was observed at altitudes below 2500 m. Due to the lack of data on hemoglobin concentrations and red blood cell counts, their study could not provide more in-depth results. Fortunately, our team had some data suitable for further investigation. We selected two cities with altitudes below 2500 m: Kunming (1891 m) and Chengdu (503 m). The hemoglobin concentration in Kunming (mean: 158.73 g/L, SD: 16.36) was higher than in Chengdu (mean: 145.44 g/L, SD: 16.82). There was no difference in HbA1c levels between two groups, with Kunming showing a mean of 5.40 (SD: 0.48) and Chengdu 5.41 (SD: 0.41).</p><p>Although hemoglobin levels in the two cities differ, they remain within the normal reference range. Moreover, residents of both cities shared similar lifestyles and socio-economic conditions; we combined the data to analyze the effects of gender and age. We employed the Generalized Additive Model (GAM) for our analysis, as it effectively captures nonlinear relationships and allows us to focus on trends and patterns. Notably, Figure D reveals a significant gender-based difference in the relationship between HbA1c and age. The HbA1c curve for women shows a distinctive turning point around age 45, which prompted our further investigation in Figures C and D. In Figure D, the disparity in HbA1c levels between women above and below the age of 45 is likely influenced by menopause and changes in estrogen levels. Unfortunately, our dataset does not include estrogen-related data, preventing further analyses in this direction. However, a previous study indicated that estrogen therapy in postmenopausal women with type 1 or type 2 diabetes can reduce HbA1c and fasting glucose levels, which supports our findings [<span>3</span>].</p><p>We acknowledge that our analysis has limitations regarding the types and scope of the real-world clinical data. Therefore, the findings presented in this article underscore the need for more epidemiological studies with rigorous system design to achieve more reliable conclusions.</p><p>T.Z. and B.C. drafted and revised the manuscript.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>We read with interest the study by Zhang et al. [<span>1</span>], which explored the gender- and age-specific associations between hemoglobin A1c (HbA1c) and hemoglobin levels in a large Chinese cohort. While the authors provide valuable insights into the potential role of estrogen in modulating HbA1c, several methodological and interpretative limitations warrant discussion to strengthen the validity and generalizability of their conclusions.</p><p>The study's reliance on health examination data from Southwest China raises concerns about external validity. Regional variations in genetic, dietary, and socioeconomic factors may influence hemoglobin and HbA1c dynamics, limiting extrapolation to global populations. Furthermore, while the authors adjusted for basic covariates (e.g., age, gender), critical confounders such as iron status, inflammation markers (e.g., C-reactive protein), and nutritional deficiencies—known to affect both hemoglobin and HbA1c—were omitted. For instance, iron deficiency anemia disproportionately impacts women and could confound the observed correlations [<span>2</span>].</p><p>The use of a binary age cutoff (≤ 45 vs. > 45 years) to approximate menopausal status is problematic. Menopause timing varies widely across individuals and ethnicities, with a significant proportion of women experiencing it after 45. Without direct assessment of hormonal levels (e.g., estradiol, FSH) or menstrual history, the assumption that age alone accurately reflects estrogen status risks misclassification bias. This may obscure nuanced relationships, particularly in perimenopausal populations.</p><p>Although generalized additive models (GAMs) effectively capture non-linear trends, the absence of model diagnostics (e.g., residual plots, goodness-of-fit metrics) undermines confidence in their robustness. Additionally, the reported Pearson's correlation coefficients (figure 1) appear incongruent with the non-linear splines, suggesting potential overfitting. A sensitivity analysis comparing GAMs with simpler linear models adjusted for spline terms would clarify whether the observed associations are artifacts of modeling complexity.</p><p>The hypothesis linking estrogen decline to elevated HbA1c in postmenopausal women, while plausible, remains speculative. The study lacks direct measurements of estrogen or markers of insulin resistance (e.g., HOMA-IR), relying instead on indirect epidemiological inferences. Longitudinal data or subgroup analyses stratified by hormone replacement therapy (HRT) use could strengthen causal inference. Notably, HRT's glucose-lowering effects in diabetic women—a finding that aligns with the authors' hypothesis but was not leveraged in this cross-sectional design [<span>3</span>].</p><p>The gender-specific reference intervals (RIs) for hemoglobin, though aligned with WHO criteria, may not account for altitude-related variations in hemoglobin, prevalent in Southwest China's highland populations. This oversight could s
{"title":"Commentary on “A Population-Based Correlation Analysis Between Hemoglobin A1c and Hemoglobin Levels”","authors":"Youyuan Hu, Tinghua Zhang","doi":"10.1111/1753-0407.70087","DOIUrl":"https://doi.org/10.1111/1753-0407.70087","url":null,"abstract":"<p>We read with interest the study by Zhang et al. [<span>1</span>], which explored the gender- and age-specific associations between hemoglobin A1c (HbA1c) and hemoglobin levels in a large Chinese cohort. While the authors provide valuable insights into the potential role of estrogen in modulating HbA1c, several methodological and interpretative limitations warrant discussion to strengthen the validity and generalizability of their conclusions.</p><p>The study's reliance on health examination data from Southwest China raises concerns about external validity. Regional variations in genetic, dietary, and socioeconomic factors may influence hemoglobin and HbA1c dynamics, limiting extrapolation to global populations. Furthermore, while the authors adjusted for basic covariates (e.g., age, gender), critical confounders such as iron status, inflammation markers (e.g., C-reactive protein), and nutritional deficiencies—known to affect both hemoglobin and HbA1c—were omitted. For instance, iron deficiency anemia disproportionately impacts women and could confound the observed correlations [<span>2</span>].</p><p>The use of a binary age cutoff (≤ 45 vs. > 45 years) to approximate menopausal status is problematic. Menopause timing varies widely across individuals and ethnicities, with a significant proportion of women experiencing it after 45. Without direct assessment of hormonal levels (e.g., estradiol, FSH) or menstrual history, the assumption that age alone accurately reflects estrogen status risks misclassification bias. This may obscure nuanced relationships, particularly in perimenopausal populations.</p><p>Although generalized additive models (GAMs) effectively capture non-linear trends, the absence of model diagnostics (e.g., residual plots, goodness-of-fit metrics) undermines confidence in their robustness. Additionally, the reported Pearson's correlation coefficients (figure 1) appear incongruent with the non-linear splines, suggesting potential overfitting. A sensitivity analysis comparing GAMs with simpler linear models adjusted for spline terms would clarify whether the observed associations are artifacts of modeling complexity.</p><p>The hypothesis linking estrogen decline to elevated HbA1c in postmenopausal women, while plausible, remains speculative. The study lacks direct measurements of estrogen or markers of insulin resistance (e.g., HOMA-IR), relying instead on indirect epidemiological inferences. Longitudinal data or subgroup analyses stratified by hormone replacement therapy (HRT) use could strengthen causal inference. Notably, HRT's glucose-lowering effects in diabetic women—a finding that aligns with the authors' hypothesis but was not leveraged in this cross-sectional design [<span>3</span>].</p><p>The gender-specific reference intervals (RIs) for hemoglobin, though aligned with WHO criteria, may not account for altitude-related variations in hemoglobin, prevalent in Southwest China's highland populations. This oversight could s","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arunkumar Krishnan, Carolin V. Schneider, Diptasree Mukherjee, Tinsay A. Woreta, Saleh A. Alqahtani
Context
The management of metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM) presents a significant clinical challenge, with a focus on preventing progression to liver and renal complications.
Objective
To evaluate the liver and renal outcomes among new users of sodium-glucose cotransporter 2 inhibitors (SGLT2i) versus glucagon-like peptide-1 receptor agonists (GLP-1RA), dipeptidyl peptidase-4 inhibitors (DPP4i) and other anti-diabetic medications in patients with MASLD and T2DM.
Design
Retrospective cohort study.
Setting
Electronic health records.
Participants
A total number of 88 306 patients with MASLD and T2DM were included in a propensity score-matched analysis comparing the effects of anti-diabetic drugs.
Intervention
Patients were categorized into groups based on their initiation of anti-diabetic medications.
Main Outcome Measures
The primary outcomes were the incidence of cirrhosis, hepatic decompensations, and hepatocellular carcinoma. Secondary outcomes were a progression of chronic kidney disease (CKD), severity of CKD stages, and the need for hemodialysis.
Results
In the SGLT2i versus DPP4i, a reduced risk of cirrhosis was observed in the SGLT2i (HR: 0.97), along with fewer hepatic decompensations (HR: 0.84) and a lower incidence of HCC (HR: 0.50). CKD progression, particularly to stages 4–5, was significantly lower in the SGLT2i (HR: 0.53), as was hemodialysis (HR: 0.38). However, SGLT2i exhibited a slightly lower risk of CKD progression (HR: 0.77) and a reduced need for hemodialysis (HR: 0.71) compared to the GLP-1RA, while there was no difference in hepatic outcomes between the GLP-1RA and SGLT2i.
{"title":"Adverse Liver and Renal Outcomes After Initiating SGLT-2i and GLP-1RA Therapy Among Patients With Diabetes and MASLD","authors":"Arunkumar Krishnan, Carolin V. Schneider, Diptasree Mukherjee, Tinsay A. Woreta, Saleh A. Alqahtani","doi":"10.1111/1753-0407.70069","DOIUrl":"https://doi.org/10.1111/1753-0407.70069","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Context</h3>\u0000 \u0000 <p>The management of metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM) presents a significant clinical challenge, with a focus on preventing progression to liver and renal complications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To evaluate the liver and renal outcomes among new users of sodium-glucose cotransporter 2 inhibitors (SGLT2i) versus glucagon-like peptide-1 receptor agonists (GLP-1RA), dipeptidyl peptidase-4 inhibitors (DPP4i) and other anti-diabetic medications in patients with MASLD and T2DM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Retrospective cohort study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting</h3>\u0000 \u0000 <p>Electronic health records.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Participants</h3>\u0000 \u0000 <p>A total number of 88 306 patients with MASLD and T2DM were included in a propensity score-matched analysis comparing the effects of anti-diabetic drugs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Intervention</h3>\u0000 \u0000 <p>Patients were categorized into groups based on their initiation of anti-diabetic medications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main Outcome Measures</h3>\u0000 \u0000 <p>The primary outcomes were the incidence of cirrhosis, hepatic decompensations, and hepatocellular carcinoma. Secondary outcomes were a progression of chronic kidney disease (CKD), severity of CKD stages, and the need for hemodialysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In the SGLT2i versus DPP4i, a reduced risk of cirrhosis was observed in the SGLT2i (HR: 0.97), along with fewer hepatic decompensations (HR: 0.84) and a lower incidence of HCC (HR: 0.50). CKD progression, particularly to stages 4–5, was significantly lower in the SGLT2i (HR: 0.53), as was hemodialysis (HR: 0.38). However, SGLT2i exhibited a slightly lower risk of CKD progression (HR: 0.77) and a reduced need for hemodialysis (HR: 0.71) compared to the GLP-1RA, while there was no difference in hepatic outcomes between the GLP-1RA and SGLT2i.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>SGLT2 inhibitors in patients with MASLD and T2DM ","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gangjiao Zhu, Xiong Ding, Hui Zhou, Janis M. Nolde, Thomas Beaney, Dan Wu, Yulong Lan, Yan Tian, Ruolin Zhang, Bolu Yang, Shuohua Chen, Bifeng Yuan, Shouling Wu, Lijing L. Yan
Background
This aimed to quantify the association between dual trajectory patterns combining seven central adiposity (CA) indices and fasting plasma glucose (FPG) with cardiovascular disease (CVD) risk in adults, and to compare their predictive performance.
Methods
The Kailuan Study, a prospective study initiated in June 2006, included 39 772 adults without pre-existing CVD as of 2010. Dual trajectories of seven CA indices combined with FPG were recorded from 2006 to 2010 to predict CVD risk from 2010 to 2021. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD.
Results
During a median follow-up of 11.0 years, 2715 incident CVD events were recorded. Four distinct patterns of CA indices (waist circumference, waist-to-height ratio, abdominal volume index, body roundness index) and three distinct patterns of other CA indices (waist-to-hip ratio, conicity index, A body shape index) combined with FPG were identified. Compared with the lowest-risk group, the highest-risk group exhibited a significantly higher CVD risk (adjusted HRs [95% CIs]: 2.41 [2.02–2.86], 2.57 [2.18–3.05], 2.25 [1.92–2.63], 2.35 [2.01–2.73], 2.08 [1.74–2.49], 1.97 [1.72–2.26], 1.81 [1.58–2.07], respectively). Overall, the predictive capabilities were generally similar, with the combination of waist circumference and FPG showing a slightly better predictive performance compared with other patterns.
Conclusions
Distinct patterns of dual trajectories involving seven CA indices combined with FPG were associated with CVD risk. The results suggest that the combination of waist circumference and FPG may have greater clinical significance in predicting CVD risk.
{"title":"Predictive Capability of Dual Trajectories of Central Adiposity Indices Combined With Glucose for Cardiovascular Diseases","authors":"Gangjiao Zhu, Xiong Ding, Hui Zhou, Janis M. Nolde, Thomas Beaney, Dan Wu, Yulong Lan, Yan Tian, Ruolin Zhang, Bolu Yang, Shuohua Chen, Bifeng Yuan, Shouling Wu, Lijing L. Yan","doi":"10.1111/1753-0407.70081","DOIUrl":"https://doi.org/10.1111/1753-0407.70081","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>This aimed to quantify the association between dual trajectory patterns combining seven central adiposity (CA) indices and fasting plasma glucose (FPG) with cardiovascular disease (CVD) risk in adults, and to compare their predictive performance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The Kailuan Study, a prospective study initiated in June 2006, included 39 772 adults without pre-existing CVD as of 2010. Dual trajectories of seven CA indices combined with FPG were recorded from 2006 to 2010 to predict CVD risk from 2010 to 2021. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>During a median follow-up of 11.0 years, 2715 incident CVD events were recorded. Four distinct patterns of CA indices (waist circumference, waist-to-height ratio, abdominal volume index, body roundness index) and three distinct patterns of other CA indices (waist-to-hip ratio, conicity index, A body shape index) combined with FPG were identified. Compared with the lowest-risk group, the highest-risk group exhibited a significantly higher CVD risk (adjusted HRs [95% CIs]: 2.41 [2.02–2.86], 2.57 [2.18–3.05], 2.25 [1.92–2.63], 2.35 [2.01–2.73], 2.08 [1.74–2.49], 1.97 [1.72–2.26], 1.81 [1.58–2.07], respectively). Overall, the predictive capabilities were generally similar, with the combination of waist circumference and FPG showing a slightly better predictive performance compared with other patterns.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Distinct patterns of dual trajectories involving seven CA indices combined with FPG were associated with CVD risk. The results suggest that the combination of waist circumference and FPG may have greater clinical significance in predicting CVD risk.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143871639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Torimoto, Y. Okada, T. Mita, et al., “Association of Glycaemia Risk Index With Indices of Atherosclerosis: A Cross-Sectional Study,” Journal of Diabetes 17, no. 3 (2025): e70065, https://doi.org/10.1111/1753-0407.70065.
In Results of the “ABSTRACT” section, the text “GRI was significantly associated with mean GSM (regression coefficient, β = −0.1277; 95% confidence interval: CI: −0.2165 to −0.0390, p = 0.005) and baPWV (regression coefficient, β = −3.1568; 95% CI: 1.5058 to 4.8079, p < 0.001) after adjustment for various cardiovascular risk factors.” was incorrect. This should have read: “GRI was significantly associated with mean GSM (regression coefficient, β = −0.1392; 95% confidence interval: CI: −0.2323 to −0.0460, p = 0.003) and baPWV (regression coefficient, β = 3.1692; 95% CI: 1.4085 to 4.9299, p < 0.001) after adjustment for various cardiovascular risk factors.”
We apologize for this error.
K. Torimoto， Y. Okada， T. Mita等，“血糖风险指数与动脉粥样硬化指数的相关性：一项横断面研究”，《糖尿病杂志》第17期。3 (2025): e70065, https://doi.org/10.1111/1753-0407.70065.In“ABSTRACT”部分的结果显示，文本“GRI与平均GSM显著相关(回归系数，β = - 0.1277；95%置信区间：CI: - 0.2165 ~ - 0.0390, p = 0.005)和baPWV(回归系数，β = - 3.1568；校正各种心血管危险因素后，95% CI: 1.5058 ~ 4.8079, p < 0.001)。是不正确的。这应该是：“GRI与平均GSM显著相关(回归系数，β = - 0.1392；95%置信区间：CI:−0.2323 ~−0.0460,p = 0.003)和baPWV(回归系数，β = 3.1692；在调整各种心血管危险因素后，95% CI: 1.4085至4.9299,p < 0.001)。我们为这个错误道歉。
{"title":"Correction to “Association of Glycaemia Risk Index With Indices of Atherosclerosis: A Cross-Sectional Study”","authors":"","doi":"10.1111/1753-0407.70092","DOIUrl":"https://doi.org/10.1111/1753-0407.70092","url":null,"abstract":"<p>K. Torimoto, Y. Okada, T. Mita, et al., “Association of Glycaemia Risk Index With Indices of Atherosclerosis: A Cross-Sectional Study,” <i>Journal of Diabetes</i> 17, no. 3 (2025): e70065, https://doi.org/10.1111/1753-0407.70065.</p><p>In Results of the “ABSTRACT” section, the text “GRI was significantly associated with mean GSM (regression coefficient, <i>β</i> = −0.1277; 95% confidence interval: CI: −0.2165 to −0.0390, <i>p</i> = 0.005) and baPWV (regression coefficient, <i>β</i> = −3.1568; 95% CI: 1.5058 to 4.8079, <i>p</i> < 0.001) after adjustment for various cardiovascular risk factors.” was incorrect. This should have read: “GRI was significantly associated with mean GSM (regression coefficient, <i>β</i> = −0.1392; 95% confidence interval: CI: −0.2323 to −0.0460, <i>p</i> = 0.003) and baPWV (regression coefficient, <i>β</i> = 3.1692; 95% CI: 1.4085 to 4.9299, <i>p</i> < 0.001) after adjustment for various cardiovascular risk factors.”</p><p>We apologize for this error.</p>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143871825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Circulating Gremlin 2 (Grem2) has recently been linked to human obesity, but its role in type 2 diabetes (T2D) remains unclear. This study aims to explore the association of circulating Grem2 with β-cell function.
Methods
A post hoc analysis was conducted using data from three clinical trials, in which all participants underwent the oral glucose tolerance test (OGTT). Circulating Grem2 levels were measured at 0, 1, and 2 h during the OGTT. In Trial 1, Grem2 levels were compared between participants with T2D (n = 59) and without T2D (n = 119). We further examined changes in Grem2 levels in response to oral antidiabetic drugs in participants with T2D in Trial 2 (n = 67) and calorie restriction in participants with prediabetes in Trial 3 (n = 231). The relationship between Grem2 levels and β-cell function was analyzed across all trials.
Results
Fasting and 1-h Grem2 levels were lower in participants with T2D compared with those without T2D (728 ± 25 vs. 649 ± 31 pg/mL, p = 0.020; 631 ± 26 vs. 537 ± 31 pg/mL, p = 0.007). Fasting Grem2 levels were restored after antidiabetic treatment (550 ± 12 vs. 575 ± 12 pg/mL, p = 0.019), and 1-h Grem2 levels increased following calorie restriction (1118 ± 89 vs. 1144 ± 90 vs. 1253 ± 89 pg/mL, p for trend = 0.002). The 1-h Grem2 levels were positively associated with β-cell function assessed by the oral disposition index and HOMA-β.
Conclusion
Reduced circulating Grem2 levels are associated with impaired β-cell function in T2D, and could be restored through antidiabetic interventions.
循环Gremlin 2 （Grem2）最近与人类肥胖有关，但其在2型糖尿病（T2D）中的作用尚不清楚。本研究旨在探讨循环Grem2与β细胞功能的关系。方法采用三个临床试验的数据进行事后分析，所有参与者都进行了口服葡萄糖耐量试验（OGTT）。在OGTT期间的0、1和2小时测量循环Grem2水平。在试验1中，比较了T2D患者（n = 59）和非T2D患者（n = 119）之间的Grem2水平。我们进一步研究了试验2中T2D患者口服降糖药后Grem2水平的变化（n = 67）和试验3中糖尿病前期患者卡路里限制后Grem2水平的变化（n = 231）。在所有试验中分析Grem2水平与β细胞功能之间的关系。结果T2D患者的空腹和1 h Grem2水平低于无T2D患者(728±25∶649±31 pg/mL, p = 0.020；631±26比537±31 pg/mL， p = 0.007)。抗糖尿病治疗后，空腹Grem2水平恢复（550±12比575±12 pg/mL， p = 0.019），卡路里限制后1小时Grem2水平升高（1118±89比1144±90比1253±89 pg/mL， p趋势= 0.002）。通过口腔处置指数和HOMA-β评估，1 h Grem2水平与β细胞功能呈正相关。结论t2dm患者外周血Grem2水平降低与β细胞功能受损有关，可通过抗糖尿病干预恢复。试验注册：ClinicalTrials.gov: NCT01959984, NCT01758471, NCT03856762
{"title":"Association Between Circulating Gremlin 2 and β-Cell Function Among Participants With Prediabetes and Type 2 Diabetes","authors":"Mengshan Ni, Yanru Chen, Weiqiong Gu, Yifei Zhang, Min Xu, Yanyun Gu, Yufei Chen, Yinmeng Zhu, Xiao Wang, Yaogan Luo, Yu Xu, Xu Lin, Yi Arial Zeng, Ruixin Liu, Jiqiu Wang","doi":"10.1111/1753-0407.70090","DOIUrl":"https://doi.org/10.1111/1753-0407.70090","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>Circulating Gremlin 2 (Grem2) has recently been linked to human obesity, but its role in type 2 diabetes (T2D) remains unclear. This study aims to explore the association of circulating Grem2 with β-cell function.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A post hoc analysis was conducted using data from three clinical trials, in which all participants underwent the oral glucose tolerance test (OGTT). Circulating Grem2 levels were measured at 0, 1, and 2 h during the OGTT. In Trial 1, Grem2 levels were compared between participants with T2D (<i>n</i> = 59) and without T2D (<i>n</i> = 119). We further examined changes in Grem2 levels in response to oral antidiabetic drugs in participants with T2D in Trial 2 (<i>n</i> = 67) and calorie restriction in participants with prediabetes in Trial 3 (<i>n</i> = 231). The relationship between Grem2 levels and β-cell function was analyzed across all trials.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Fasting and 1-h Grem2 levels were lower in participants with T2D compared with those without T2D (728 ± 25 vs. 649 ± 31 pg/mL, <i>p</i> = 0.020; 631 ± 26 vs. 537 ± 31 pg/mL, <i>p</i> = 0.007). Fasting Grem2 levels were restored after antidiabetic treatment (550 ± 12 vs. 575 ± 12 pg/mL, <i>p</i> = 0.019), and 1-h Grem2 levels increased following calorie restriction (1118 ± 89 vs. 1144 ± 90 vs. 1253 ± 89 pg/mL, <i>p</i> for trend = 0.002). The 1-h Grem2 levels were positively associated with β-cell function assessed by the oral disposition index and HOMA-β.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Reduced circulating Grem2 levels are associated with impaired β-cell function in T2D, and could be restored through antidiabetic interventions.</p>\u0000 \u0000 <p><b>Trial Registration:</b> ClinicalTrials.gov: NCT01959984, NCT01758471, NCT03856762</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70090","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diabetes osteoporosis is a debilitating condition that significantly impacts human health. However, it is often underdiagnosed and not addressed in a timely or appropriate manner.
Methods
Recent studies were reviewed to explore the roles of energy metabolism, sarcopeina, low-grade inflammation and gut microbiota in the development of diabetes osteoporosis.
Results
Osteoporosis in diabetic patients differs from primary osteoporosis. Novel biomarkers and risk factors that are biologically, physiologically, and pathologically linked to the development of diabetes osteoporosis are emerging, necessitating a shift in strategies for diagnosis, risk stratification, and prevention of diabetes osteoporosis.
Conclusions
There is an urgent need to approach this disorder from a fresh perspective, initiating a range of basic research and clinical investigations.
{"title":"New Evidence, Creative Insights, and Strategic Solutions: Advancing the Understanding and Practice of Diabetes Osteoporosis","authors":"Bei Tao, Ximei Shen, Guangfei Li, Xiyu Wu, Yuying Yang, Chunxiang Sheng, Yun Zhang, Ling Wang, Zhiyun Zhao, Qi Song, Dewen Yan, Sunjie Yan, Youjia Xu, Huijuan Yuan, Houde Zhou, Jianmin Liu","doi":"10.1111/1753-0407.70091","DOIUrl":"https://doi.org/10.1111/1753-0407.70091","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Diabetes osteoporosis is a debilitating condition that significantly impacts human health. However, it is often underdiagnosed and not addressed in a timely or appropriate manner.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Recent studies were reviewed to explore the roles of energy metabolism, sarcopeina, low-grade inflammation and gut microbiota in the development of diabetes osteoporosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Osteoporosis in diabetic patients differs from primary osteoporosis. Novel biomarkers and risk factors that are biologically, physiologically, and pathologically linked to the development of diabetes osteoporosis are emerging, necessitating a shift in strategies for diagnosis, risk stratification, and prevention of diabetes osteoporosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>There is an urgent need to approach this disorder from a fresh perspective, initiating a range of basic research and clinical investigations.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yifei Wang, Shiya Gu, Zhixuan Xie, Zhiyong Xu, Wenfang He, Yexiang Chen, Juan Jin, Qiang He
Background
This study analyzes the trends in the burden of chronic kidney disease due to type 2 diabetes (CKD-T2D) in China from 1990 to 2021, evaluates variations in risk factors, and projects the disease burden through 2036.
Method
Estimates of prevalence, incidence, mortality, and disability-adjusted life years (DALYs) for CKD-T2D were retrieved along with their 95% uncertainty intervals (UIs). Age-period-cohort analysis was used to assess burden trends from 1990 to 2021, identify risk factor population attributable fractions (PAFs), and project the burden through 2036.
Results
In 2021, there were 20 911 520 CKD-T2D cases in China, with an age-standardized prevalence rate (ASPR) of 1053.92 per 100 000, an incidence rate (ASIR) of 23.07, an age-standardized mortality rate (ASMR) of 5.72, and an age-standardized DALY rate (ASDR) of 122.15. Although the overall burden showed a slow decline from 1990 to 2021, incidence continued to rise. The 2021 data revealed a marked age effect, with the burden rising with age. Period effects also contributed to an increased risk, with metabolic risk factors such as high fasting plasma glucose and BMI contributing the most. Projections suggest a decline in mortality and DALYs by 2036, while incidence will keep increasing.
Conclusion
Despite declines in ASMR and ASDR, CKD-T2D incidence and cases continue to rise, especially among males and the elderly. This increasing burden is driven by aging and metabolic risk factors. Early screening, education, and risk management are essential for addressing CKD-T2D in China.
{"title":"Trends and Disparities in the Burden of Chronic Kidney Disease due to Type 2 Diabetes in China From 1990 to 2021: A Population-Based Study","authors":"Yifei Wang, Shiya Gu, Zhixuan Xie, Zhiyong Xu, Wenfang He, Yexiang Chen, Juan Jin, Qiang He","doi":"10.1111/1753-0407.70084","DOIUrl":"https://doi.org/10.1111/1753-0407.70084","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>This study analyzes the trends in the burden of chronic kidney disease due to type 2 diabetes (CKD-T2D) in China from 1990 to 2021, evaluates variations in risk factors, and projects the disease burden through 2036.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Estimates of prevalence, incidence, mortality, and disability-adjusted life years (DALYs) for CKD-T2D were retrieved along with their 95% uncertainty intervals (UIs). Age-period-cohort analysis was used to assess burden trends from 1990 to 2021, identify risk factor population attributable fractions (PAFs), and project the burden through 2036.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In 2021, there were 20 911 520 CKD-T2D cases in China, with an age-standardized prevalence rate (ASPR) of 1053.92 per 100 000, an incidence rate (ASIR) of 23.07, an age-standardized mortality rate (ASMR) of 5.72, and an age-standardized DALY rate (ASDR) of 122.15. Although the overall burden showed a slow decline from 1990 to 2021, incidence continued to rise. The 2021 data revealed a marked age effect, with the burden rising with age. Period effects also contributed to an increased risk, with metabolic risk factors such as high fasting plasma glucose and BMI contributing the most. Projections suggest a decline in mortality and DALYs by 2036, while incidence will keep increasing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Despite declines in ASMR and ASDR, CKD-T2D incidence and cases continue to rise, especially among males and the elderly. This increasing burden is driven by aging and metabolic risk factors. Early screening, education, and risk management are essential for addressing CKD-T2D in China.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Globally, diabetic retinopathy (DR) is estimated to have affected 103 persons in 2020, with projections of 130 and 161 million in 2030 and 2045, respectively. The respective prevalences of vision-threatening DR, are 29, 36, and 45 million persons in 2020, 2030, and 2045, and of clinically significant diabetic macular edema (DME), 19, 24, and 29 million persons [<span>1</span>]. Glucagon-like peptide-1 Receptor Activators (GLP-1RA) have become more widely used in the treatment of type 2 diabetes (T2D), with analysis of the TriNetX dataset showing that the prevalence of GLP-1RA use in the US increased from 6.4% in 2018 to 14.9% in 2022 among T2D with ASCVD [<span>2</span>]. 12% of US adults say they have taken a GLP-1 agonist, and 6% say they are taking this currently; the prevalence of such use is 43% among people with diabetes, 25% among those who have been told of heart disease, and 22% among those who have been told by a doctor about being overweight or obese [<span>3</span>].</p><p>We generally would anticipate excellent glycemic treatment to be associated with improved outcomes of most diabetes complications. Indeed, a meta-analysis of 11 randomized controlled trials (RCT) involving 51 469 patients with T2D showed a 15% reduction in DR risk [<span>4</span>]. The GLP-1RA are among the most effective agents used in T2D treatment, having at least as great a glycemic effect as basal insulin [<span>5</span>], with weight loss rather than weight gain and with a lower likelihood of hypoglycemia. A caveat is the recognized potential that with rapid improvement of poorly controlled diabetes conditions similar to the microvascular complications of diabetes can occur. Acute painful peripheral diabetic neuropathy is one such syndrome [<span>6</span>]. Another such condition was seen in the analysis of the initial outcome of the Diabetes Complications and Control Trial (DCCT) of type 1 diabetes, in which early worsening of DR was observed at the 6- and 12-month DCCT visits in 13.1% of 711 patients assigned to intensive treatment and in 7.6% of 728 patients assigned to conventional treatment, particularly in those with higher baseline HbA1c and in those with a greater 6-month reduction in HbA1c [<span>7</span>].</p><p>The effect of GLP-1RA on DR is less clear. Using the TriNetX global research network to assess the development of DR and DME in ~2 million individuals with type 2 diabetes taking insulin, one study using propensity score matching suggested that those receiving GLP-1RA had a 31% increased risk of DR, without significant change in the risk of DME, compared with those receiving neither sodium-glucose co-transporter 2 inhibitors (SGLT2i) nor GLP-1RA, while compared with those receiving SGLT2i, those receiving GLP-1RA had a 20% higher risk of DR and a 13% higher risk of DME [<span>8</span>]. However, another study using TriNetX among 9.9 million patients with T2D, over a 2-year period of observation, found that DME was 23% and 17% less likely w
{"title":"Semaglutide and the Retina","authors":"Zachary T. Bloomgarden","doi":"10.1111/1753-0407.70085","DOIUrl":"https://doi.org/10.1111/1753-0407.70085","url":null,"abstract":"<p>Globally, diabetic retinopathy (DR) is estimated to have affected 103 persons in 2020, with projections of 130 and 161 million in 2030 and 2045, respectively. The respective prevalences of vision-threatening DR, are 29, 36, and 45 million persons in 2020, 2030, and 2045, and of clinically significant diabetic macular edema (DME), 19, 24, and 29 million persons [<span>1</span>]. Glucagon-like peptide-1 Receptor Activators (GLP-1RA) have become more widely used in the treatment of type 2 diabetes (T2D), with analysis of the TriNetX dataset showing that the prevalence of GLP-1RA use in the US increased from 6.4% in 2018 to 14.9% in 2022 among T2D with ASCVD [<span>2</span>]. 12% of US adults say they have taken a GLP-1 agonist, and 6% say they are taking this currently; the prevalence of such use is 43% among people with diabetes, 25% among those who have been told of heart disease, and 22% among those who have been told by a doctor about being overweight or obese [<span>3</span>].</p><p>We generally would anticipate excellent glycemic treatment to be associated with improved outcomes of most diabetes complications. Indeed, a meta-analysis of 11 randomized controlled trials (RCT) involving 51 469 patients with T2D showed a 15% reduction in DR risk [<span>4</span>]. The GLP-1RA are among the most effective agents used in T2D treatment, having at least as great a glycemic effect as basal insulin [<span>5</span>], with weight loss rather than weight gain and with a lower likelihood of hypoglycemia. A caveat is the recognized potential that with rapid improvement of poorly controlled diabetes conditions similar to the microvascular complications of diabetes can occur. Acute painful peripheral diabetic neuropathy is one such syndrome [<span>6</span>]. Another such condition was seen in the analysis of the initial outcome of the Diabetes Complications and Control Trial (DCCT) of type 1 diabetes, in which early worsening of DR was observed at the 6- and 12-month DCCT visits in 13.1% of 711 patients assigned to intensive treatment and in 7.6% of 728 patients assigned to conventional treatment, particularly in those with higher baseline HbA1c and in those with a greater 6-month reduction in HbA1c [<span>7</span>].</p><p>The effect of GLP-1RA on DR is less clear. Using the TriNetX global research network to assess the development of DR and DME in ~2 million individuals with type 2 diabetes taking insulin, one study using propensity score matching suggested that those receiving GLP-1RA had a 31% increased risk of DR, without significant change in the risk of DME, compared with those receiving neither sodium-glucose co-transporter 2 inhibitors (SGLT2i) nor GLP-1RA, while compared with those receiving SGLT2i, those receiving GLP-1RA had a 20% higher risk of DR and a 13% higher risk of DME [<span>8</span>]. However, another study using TriNetX among 9.9 million patients with T2D, over a 2-year period of observation, found that DME was 23% and 17% less likely w","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 4","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号