Journal of Diabetes最新文献

{"title":"Diabetes Complications and Comorbidities as Risk Factors for MACE in People With Type 2 Diabetes and Their Development Over Time: A Danish Registry-Based Case–Control Study","authors":"Asger Ahlmann Bech,&nbsp;Mia Daugaard Madsen,&nbsp;Annika Vestergaard Kvist,&nbsp;Peter Vestergaard,&nbsp;Nicklas Højgaard-hessellund Rasmussen","doi":"10.1111/1753-0407.70076","DOIUrl":"https://doi.org/10.1111/1753-0407.70076","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study aimed to investigate the association between cardiovascular risk factors and major adverse cardiovascular events (MACE) in people with type 2 diabetes, while assessing potential changes over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Utilizing data from Danish registries, this study identified people with type 2 diabetes between 2002 and 2021 (<i>n</i> = 372 328) and subdivided them into two 10-year time periods: TP1: 2002–2011 and TP2: 2012–2021, and further categorized into cases and controls. Cases were defined as having suffered a first-time three-point MACE (<i>n</i>_TP1 = 12 713, <i>n</i>_TP2 = 8981) and matched 1:1 with controls on age, sex, and type 2 diabetes duration. Exposures were preselected diabetes complications and comorbidities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Fewer were affected by MACE during TP2 compared to TP1 (<i>p</i> &lt; 0.001). Diabetes complications associated with MACE were nephropathy (OR_TP1 = 1.54, 95% CI 1.30–1.83, OR_TP2 = 1.47, 95% CI 1.20–1.79), neuropathy (OR_TP1 = 2.02, 95% CI 1.84–2.21 OR_TP2 = 1.58, 95% CI 1.44–1.73) and retinopathy (OR_TP1 = 1.10, 95% CI 0.98–1.23, OR_TP2 = 1.38, 95% CI 1.17–1.63). Comorbidities associated with MACE included hypertension (OR_TP1 = 1.30, 95% CI 1.22–1.38 OR_TP2 = 1.31, 95% CI 1.22–1.41), atrial flutter or fibrillation (OR_TP1 = 1.46, 95% CI 1.35–1.58, OR_TP2 = 1.37, 95% CI 1.26–1.50), heart failure (OR_TP1 = 1.53, 95% CI 1.401.67-, OR_TP2 = 1.37, 95% CI 1.23–1.54) and hypercholesterolemia (OR_TP1 = 1.13, 95% CI 1.07–1.20, OR_TP2 = 1.02, 95% CI 0.96–1.10). Hypercholesterolemia (<i>p =</i> 0.038) and neuropathy (<i>p =</i> 0.038) exhibited a significant decrease in association with MACE between the time periods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The prevalence of first-time MACE decreased over time, despite a relatively stable prevalence of type 2 diabetes. Several diabetes-related complications and comorbidities were significantly associated with MACE. The associations of neuropathy and hypercholesterolemia with MACE lessened over time, suggesting potential improvements in risk management or treatment strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698744","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}

{"title":"The Relationship Between Glycated Albumin and Time in Tight Range in Type 2 Diabetes","authors":"Jiaying Ni,&nbsp;Wenshuo Han,&nbsp;Yaxin Wang,&nbsp;Jiamin Yu,&nbsp;Wei Lu,&nbsp;Yufei Wang,&nbsp;Xiaojing Ma,&nbsp;Jingyi Lu,&nbsp;Jian Zhou","doi":"10.1111/1753-0407.70073","DOIUrl":"https://doi.org/10.1111/1753-0407.70073","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Among the new glucose metrics derived from continuous glucose monitoring, the concept of time in tight range (TITR) has gained increasing attention. We aimed to assess the association between TITR and traditional glycemic indicators, such as glycated albumin (GA).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 310 patients with type 2 diabetes on a stable glucose-lowering regimen over the previous 3 months were enrolled. TITR and time in range (TIR) were calculated using continuous glucose monitoring data collected over a minimum of 5 days. Spearman correlation analysis was performed to assess the relationships between traditional glycemic indicators, including GA and HbA1c, with TITR and TIR. Receiver operating characteristic curves were used to evaluate the predictive value of GA for TITR &gt; 50% and TIR &gt; 70%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The median levels of GA and HbA1c were 15.6% (14.0%, 17.3%) and 6.5% (6.1%, 7.1%), respectively. Median TITR and TIR were 70.0% (56.0%, 81.0%) and 91.0% (84.0%, 96.8%), respectively. Spearman correlation analysis showed a moderate negative relationship between GA and both TITR and TIR. The optimal GA cutoff for identifying either TITR &gt; 50% or TIR &gt; 70% was 17.4%. Moreover, combining GA with fasting plasma glucose or 2-h postprandial glucose significantly enhanced the ability to identify TITR &gt; 50%, achieving performance comparable to the combination of HbA1c and plasma glucose.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In patients with type 2 diabetes, a GA cutoff of 17.4% effectively identifies TITR &gt; 50%.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143699033","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}

{"title":"Medical Education in Diabetes Management on the New Horizon: Insights From Metabolic Management Center","authors":"Guang Ning","doi":"10.1111/1753-0407.70075","DOIUrl":"10.1111/1753-0407.70075","url":null,"abstract":"&lt;p&gt;The global diabetes epidemic presents a formidable challenge to healthcare systems, with 529 million cases documented in 2021 and projections estimating a rise to more than 1.31 billion by 2050 [&lt;span&gt;1&lt;/span&gt;]. Low- and middle-income countries bear a disproportionate burden, representing 80% of global diabetes cases [&lt;span&gt;2&lt;/span&gt;]. Notably, China has the largest population living with diabetes worldwide, with over 118 million individuals affected [&lt;span&gt;1&lt;/span&gt;], accompanied by alarmingly low rates of awareness, treatment, and control [&lt;span&gt;3, 4&lt;/span&gt;]. Driven by rapid urbanization, an aging population, significant environmental and lifestyle shifts, and regional and socioeconomic disparities, China faces an urgent imperative to effectively address these challenges.&lt;/p&gt;&lt;p&gt;The National Metabolic Management Center (MMC), launched in 2016, emerged as a response to these challenges. Guided by the principle of “One Center, One Stop, One Standard,” MMC integrates cutting-edge medical equipment, evidence-based protocols and multidisciplinary collaboration to redefine diabetes management [&lt;span&gt;5&lt;/span&gt;]. The MMC establishes a nationwide network of metabolic centers across hospitals and primary healthcare facilities in China to enhance guideline-based diabetes management. This editorial delineates MMC's development journey, emphasizing its innovations in patient care, medical education, artificial intelligence (AI)-driven precision medicine, and global contributions to metabolic health governance.&lt;/p&gt;&lt;p&gt;MMC's operational model revolutionizes traditional fragmented care by consolidating services into a unified center. Guided by the MMC Experts Committee, a series of standard operating procedures (SOPs) and MMC-specific guidelines have been developed to standardize the disease management. At every MMC, patients can receive one-stop care encompassing the complete spectrum of healthcare services from initial registration, diagnostic testing, clinical assessment, therapeutic prescription, to formulation of personalized follow-up strategies [&lt;span&gt;6-8&lt;/span&gt;]. To ensure the nationwide implementation of this model, the MMC has established a four-tiered prevention and control network, comprising the MMC leading center, regional centers, county centers, and community centers. A teleconsultation and referral system for complex cases has been integrated into this network, enabling seamless communication and patient transfers across different levels of MMCs. Furthermore, the MMC leverages a health information platform based on Internet of Things (IoT) and advanced technologies to support continuous and personalized care delivery, effectively bridging the gap between hospital-based and community-based management. Central to the MMC platform are two interconnected systems: the MMC digital medical record system and the online education system.&lt;/p&gt;&lt;p&gt;The digital medical record system integrates comprehensive clinical phenotyping, detailed biochemical profiling,","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143661812","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}

{"title":"Comparative Analysis of AI Tools for Disseminating ADA 2025 Diabetes Care Standards: Implications for Cardiovascular Physicians","authors":"Tengfei Zheng","doi":"10.1111/1753-0407.70072","DOIUrl":"https://doi.org/10.1111/1753-0407.70072","url":null,"abstract":"&lt;p&gt;Artificial intelligence (AI) models are increasingly used in clinical practice, including medical education and the dissemination of updated clinical guidelines. In this study, we evaluated four AI tools—ChatGPT-4o, ChatGPT-o1, ChatGPT-o3Mini, and DeepSeek—to assess their ability to summarize the &lt;i&gt;Standards of Care in Diabetes—2025&lt;/i&gt; from the American Diabetes Association (ADA) for cardiovascular physicians in primary care settings [&lt;span&gt;1&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Using a standardized prompt, we compared the AI-generated summaries across 10 key metrics, including accuracy (alignment with ADA 2025 guidelines), completeness (inclusion of core topics such as glycemic targets, blood pressure management, lipid control, and pharmacologic strategies), clarity (readability and conciseness for cardiovascular physicians), clinical relevance (utility for real-world cardiovascular practice), consistency (logical coherence and uniformity in recommendations), evidence support (reference to supporting studies and ADA standards), ethics (neutral and evidence-based recommendations), timeliness (inclusion of the latest ADA updates), actionability (practical guidance for cardiovascular physicians), and fluency (professional language and structure). Each AI tool was rated on a 0–5 scale for each category, yielding a total possible score of 50 points. All summaries were anonymized to remove identifiers. Each model (ChatGPT-4o, ChatGPT-o1, ChatGPT-o3Mini, and DeepSeek) was then tasked with evaluating all four anonymized summaries, including its own output, using the predefined 10 metrics. For each model, the four scores assigned by the evaluators (including self-evaluation) were averaged to calculate the final score per metric.&lt;/p&gt;&lt;p&gt;Our evaluation showed that ChatGPT-o1 performed best (48.3/50), excelling in completeness (5.0), clinical relevance (5.0), and actionability (5.0), with comprehensive coverage of diabetes screening, cardiovascular risk assessment, hypertension/lipid management, and multidisciplinary collaboration (Table 1). However, its evidence support (4.0) required improvement. ChatGPT-4o (45.5/50) demonstrated strengths in clarity (4.8) and structure but had limitations in timeliness (4.5) and evidence support (3.3), as it failed to incorporate 2025 guideline updates and lacked specific research references. The free models, O3Mini (47.3/50) and DeepSeek (47.3/50), performed comparably to paid tools. O3Mini excelled in consistency (5.0) and CKD/heart failure monitoring, while DeepSeek prioritized concise cardiovascular risk management (clarity: 5.0). Both free models, however, scored lower in completeness (O3Mini: 4.8; DeepSeek: 4.5) and evidence support (O3Mini: 4.0; DeepSeek: 3.8), reflecting insufficient integration of 2025 updates and trial data (Table 1).&lt;/p&gt;&lt;p&gt;Among the most critical takeaways for cardiovascular physicians were the importance of individualized glycemic targets, the use of SGLT2 inhibitors and GLP-1 receptor agonists for cardiovascu","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565103","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}

{"title":"Association of Glycaemia Risk Index With Indices of Atherosclerosis: A Cross-Sectional Study","authors":"Keiichi Torimoto,&nbsp;Yosuke Okada,&nbsp;Tomoya Mita,&nbsp;Kenichi Tanaka,&nbsp;Fumiya Sato,&nbsp;Naoto Katakami,&nbsp;Hidenori Yoshii,&nbsp;Keiko Nishida,&nbsp;Yoshiya Tanaka,&nbsp;Ryota Ishii,&nbsp;Masahiko Gosho,&nbsp;Iichiro Shimomura,&nbsp;Hirotaka Watada","doi":"10.1111/1753-0407.70065","DOIUrl":"https://doi.org/10.1111/1753-0407.70065","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>This study determined the association of the glycaemia risk index (GRI), a novel comprehensive metric derived from continuous glucose monitoring (CGM), and atherosclerosis in patients with type 2 diabetes (T2DM).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We evaluated the relationship between GRI and intima-media thickness (IMT), gray-scale median (GSM), tissue characteristics of the carotid artery wall, and brachial-ankle pulse wave velocity (baPWV), using baseline data from a multicenter prospective cohort study of 1000 Japanese patients with T2DM free of cardiovascular disease (CVD).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The study subjects were 999 patients (age: 64.6 ± 9.6 years, mean ± SD, 60.9% males, body mass index: 24.6 ± 3.9 kg/m², HbA1c 7.1% ± 0.8%, TIR 78.9% ± 18.6%) with T2DM (duration of 12.9 ± 8.5 years). A higher GRI was associated with a longer duration of diabetes, a higher HbA1c level, a mean glucose level, and baPWV, and lower mean GSM. No association was noted between GRI and mean IMT. 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> &lt; 0.001) after adjustment for various cardiovascular risk factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>GRI is a potentially useful predictor of atherosclerosis in patients with T2DM. Our findings suggest that GRI, a marker of the risk of hypoglycaemia and hyperglycaemia, may serve as a clinically useful tool for the assessment of the risk of CVD in patients with T2DM, independent of the classical cardiovascular risk factors.</p>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565102","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}

{"title":"Sex Differences in the Efficacy of Glucagon-Like Peptide-1 Receptor Agonists for Weight Reduction: A Systematic Review and Meta-Analysis","authors":"Yucheng Yang,&nbsp;Liyun He,&nbsp;Shumeng Han,&nbsp;Na Yang,&nbsp;Yiwen Liu,&nbsp;Xuechen Wang,&nbsp;Ziyi Li,&nbsp;Fan Ping,&nbsp;Lingling Xu,&nbsp;Wei Li,&nbsp;Huabing Zhang,&nbsp;Yuxiu Li","doi":"10.1111/1753-0407.70063","DOIUrl":"https://doi.org/10.1111/1753-0407.70063","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>To verify sex differences of GLP-1RAs for weight reduction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We searched RCTs reporting weight change by sex from PubMed, Web of Science, Embase, Cochrane Library, and ClinicalTrials registries. Meta-regression was performed to evaluate the association between weight reduction and sex differences. Subgroup analyses were stratified by individual GLP-1RA medications, dose, treatment duration, indication, type of control, background treatment, and baseline weight. The study protocol was registered (CRD42023480167).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Fourteen studies covering dulaglutide, exenatide, liraglutide, semaglutide, and retatrutide were included in this study. The meta-analysis showed that females lost more weight than males (MD 1.04 kg [95% CIs 0.70–1.38]; MD 1.69% [95% CI 0.78–2.61]). The pooled results of GLP-1RAs indicated similar results (MD 0.88 kg [95% CIs 0.67–1.09]). Meta-regression illustrated that substantial weight reduction was significantly relevant to greater gender differences (<i>β</i> = −0.19 [95% CIs −0.29 to −0.09]). Subgroup analysis demonstrated that indications for weight reduction increased the gender difference in weight reduction (MD 4.21 kg [95% CIs 1.75–6.67]). Background treatment, dose, duration of treatment, baseline weight, and type of control had no subgroup differences in the sex difference in weight reduction of GLP-1RAs. Dulaglutide (MD 0.88 kg [95% CIs 0.63–1.12]) and semaglutide (MD 1.04 kg [95% CIs 0.45–1.63]) showed statistically significant differences in weight reduction between males and females. No gender difference was observed in the exenatide subgroup analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Females lost more weight than males when treated with GLP-1RAs for weight reduction. The sex difference in weight reduction became more pronounced as the degree of weight reduction increased. Indications for obesity could magnify this sex difference.</p>\u0000 \u0000 <div>\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554460","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}

{"title":"Response to Commentary on “Pedal Medial Arterial Calcification in Diabetic Foot Ulcers: A Significant Risk Factor of Amputation and Mortality”","authors":"Lihong Chen,&nbsp;Dawei Chen,&nbsp;Hongping Gong,&nbsp;Chun Wang,&nbsp;Yun Gao,&nbsp;Yan Li,&nbsp;Weiwei Tang,&nbsp;Panpan Zha,&nbsp;Xingwu Ran","doi":"10.1111/1753-0407.70070","DOIUrl":"https://doi.org/10.1111/1753-0407.70070","url":null,"abstract":"&lt;p&gt;We appreciate the authors for their insightful commentary and for recognizing our manuscript [&lt;span&gt;1&lt;/span&gt;] as a valuable contribution that provides crucial insights into the relationship between pedal MAC, the risk of amputation, and mortality in patients with diabetic foot ulcers (DFUs).&lt;/p&gt;&lt;p&gt;We concur that a more sophisticated classification system, such as SINBAD or WIfI systems, could enhance the comprehension of the severity and risk associated with DFUs and improve communication among healthcare professionals. However, considering its simplicity and practicality, the Wagner wound classification system remains internationally recognized and widely utilized.&lt;/p&gt;&lt;p&gt;Regarding laboratory markers, inflammatory biomarkers including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammatory response index (SIRI) exhibit significant variability. Specifically, in patients with diabetic foot infections, these inflammatory markers are markedly elevated. Consequently, they serve as indicators of acute infection but are not suitable for assessing long-term prognosis, such as amputation risk or mortality. Additionally, laboratory markers such as magnesium, zinc, and vitamin B12 are not routinely evaluated in clinical practice. Further research could explore the potential associations between these markers and the prognosis of DFUs.&lt;/p&gt;&lt;p&gt;Because of the longitudinal nature of the study design, participants were followed up over an extended period. The hypoglycemic medications prescribed may have varied over time, making it challenging to incorporate both the medications and their dosages into the analysis. Regarding infections and antibiotics, diabetic foot infection is indeed a recognized risk factor for amputation and short-term mortality. However, based on our previous meta-analysis, the primary long-term causes of mortality include cardiovascular diseases, infections (such as sepsis, respiratory infections, and foot infections), and cancers [&lt;span&gt;2&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;We acknowledge that patients with DFUs may concurrently suffer from autoimmune disorders, psychiatric conditions, and malignancies. These comorbidities elevate the risk of amputation and adverse outcomes [&lt;span&gt;3&lt;/span&gt;]. However, in this study, we excluded individuals with these comorbidities prior to analysis.&lt;/p&gt;&lt;p&gt;With respect to socioeconomic status and educational attainment, it is well-established that a lower socioeconomic status constitutes a substantial risk factor for amputation among patients with diabetes and peripheral artery disease [&lt;span&gt;4&lt;/span&gt;]. Socioeconomic status, social capital, and medical challenges significantly impede the effective management and prevention of DFUs [&lt;span&gt;5&lt;/span&gt;]. Enhanced government intervention is imperative to ensure equitable access to health resources. Additionally, a history of ulceration and prior amputations is a critical risk f","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554589","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}

{"title":"Commentary on “Pedal Medial Arterial Calcification in Diabetic Foot Ulcers: A Significant Risk Factor of Amputation and Mortality”","authors":"Mostafa Javanian,&nbsp;Mohammad Barary,&nbsp;Ali Alizadeh Khatir,&nbsp;Majid Khalilizad,&nbsp;Soheil Ebrahimpour","doi":"10.1111/1753-0407.70071","DOIUrl":"https://doi.org/10.1111/1753-0407.70071","url":null,"abstract":"&lt;p&gt;We were glad to read the article entitled “Pedal Medial Arterial Calcification in Diabetic Foot Ulcers: A Significant Risk Factor of Amputation and Mortality,” published in your prestigious journal [&lt;span&gt;1&lt;/span&gt;]. This sheds light on the yet less known association, made clear by the authors, between pedal, medial arterial calcification (MAC) and its strong relationship with amputation and mortality in diabetic foot ulcer (DFU) patients. Not only is pedal MAC a new significant predictor of amputation, but it is also a predictor of amputation independent of peripheral artery disease (PAD). However, we believe that filling in some methodological missing parts could attune the study hypothesis and strengthen the conclusions of the study.&lt;/p&gt;&lt;p&gt;First and foremost, one of the strengths of the study is the use of a widely recognized classification system for grading DFUs, the Wagner classification system. However, I think the study could have benefited from the inclusion of a more comprehensive ulcer scoring system, which takes into account several factors such as ulcer location, size, depth, ischemia, and neuropathy, such as the SINBAD ulcer classification [&lt;span&gt;2&lt;/span&gt;]. This would offer a more comprehensive understanding of severity and risk, particularly for those patients with more complex presentations.&lt;/p&gt;&lt;p&gt;Another point of consideration is to investigate further the role of additional laboratory markers in supplementing our understanding of the clinical outcomes of the patient population. For instance, biomarkers including magnesium, zinc, vitamin B12, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and the systemic inflammatory response index (SIRI) could provide a higher level of precision into the underlying mechanisms and may better orient the clinical risk assessment [&lt;span&gt;3, 4&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;The study also fails to thoroughly examine the drugs given to the patients, especially antidiabetic medicines and antibiotics. These treatments can greatly affect how well we heal and whether we have complications like amputation. A detailed breakdown of these medications and their dosages would further shed light on their potential impact on the study's findings.&lt;/p&gt;&lt;p&gt;Further research may also be strengthened by including additional potential comorbid conditions, including autoimmune disorders, psychiatric disorders, and cancers. It is well established that these factors have significant effects on the course of DFUs and the risk of amputation and mortality. This would give a better representation of the patient population and could potentially increase the predictive power of the model.&lt;/p&gt;&lt;p&gt;A deeper dive into demographic information like socioeconomic status, education level, alcohol use, and the patient's history of ulcers or amputation would also improve the study. Previous research has shown how much these variables affect health outcomes, how the","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554590","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}

{"title":"Response to “Comment on Prevalence and Influencing Factors of Malnutrition in Diabetic Patients: A Systematic Review and Meta-Analysis”","authors":"Tong Zhang,&nbsp;Yuxia Ma,&nbsp;Lin Han","doi":"10.1111/1753-0407.70066","DOIUrl":"https://doi.org/10.1111/1753-0407.70066","url":null,"abstract":"&lt;p&gt;We thank the authors for their insightful comments and for recognizing that our manuscript provides valuable contributions to the field of clinical nutrition [&lt;span&gt;1&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Firstly, we acknowledge that meta-regression can provide additional insights into heterogeneity, but its feasibility and reliability in our study were constrained by the inconsistent and limited reporting of key covariates, such as sample characteristics, across the included studies, and current meta-analysis studies on single-group rates are all highly heterogeneous [&lt;span&gt;2, 3&lt;/span&gt;]. Additionally, even meta-regression analysis cannot completely resolve heterogeneity, which is inherent to meta-analysis investigating prevalence rates. Heterogeneity is now widely recognized and accepted as a standard challenge in such studies and is one of the issues to be addressed by future methodologists [&lt;span&gt;4&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Secondly, using Egger's test and funnel plots to assess publication bias are widely adopted methods, and while tools such as Doi plots and the LFK index may provide alternative methods for detecting publication bias, these methods have not been universally used in meta-analyses. We acknowledge that prediction intervals (PIs) can convey the range of effects expected in future studies, but calculating and interpreting PIs relies on normality assumptions, which may be difficult to guarantee. Importantly, retaining our original analysis methods does not alter the conclusions of this paper, which is why we opted to maintain them.&lt;/p&gt;&lt;p&gt;Thirdly, regarding malnutrition assessment tools, we note that a meta-analysis of 83 studies identified more than 30 nutritional assessment tools, none of which are universally applicable or specifically developed for diabetic patients [&lt;span&gt;5&lt;/span&gt;]. We recognize that pooling results from diverse tools introduces significant heterogeneity, but limiting analysis to stratified results would constrain the exploration of factors influencing malnutrition in diabetic patients. To address this, we performed subgroup analysis based on assessment tools. Furthermore, we also advocate for the development of a standardized malnutrition assessment tool tailored for diabetic patients to enhance consistency and comparability across studies.&lt;/p&gt;&lt;p&gt;Finally, we agree that the analysis of some influencing factors, such as smoking, education level, and diabetic foot infection, was limited by small sample sizes. Future studies should focus more on the impact of these factors on the nutritional status of diabetic patients. Additionally, future analysis should aim to incorporate confounding variables, including socioeconomic status, dietary patterns, and psychological factors, to provide a more comprehensive understanding of malnutrition risk.&lt;/p&gt;&lt;p&gt;In conclusion, we thank the authors for their comments on the manuscript and for providing valuable insights. We hope these clarifications address the issues raised and further illuminate our analytica","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143530089","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}

{"title":"Comment on: “Prevalence and Influencing Factors of Malnutrition in Diabetic Patients: A Systematic Review and Meta-Analysis”","authors":"Shubham Kumar,&nbsp;Nosaibah Razaqi,&nbsp;Rachana Mehta,&nbsp;Ranjana Sah","doi":"10.1111/1753-0407.70067","DOIUrl":"https://doi.org/10.1111/1753-0407.70067","url":null,"abstract":"&lt;p&gt;We read with great interest the recent article by Zhang et al., titled “Prevalence and influencing factors of malnutrition in diabetic patients: A systematic review and meta-analysis” [&lt;span&gt;1&lt;/span&gt;]. The study provides valuable insights into an important area of clinical nutrition. The authors should be commended for their effort in consolidating data on malnutrition in diabetic patients and highlighting its associated risk factors. However, upon a detailed review of the article, several methodological issues and potential areas for improvement were identified, which could enhance the reliability and clinical applicability of their findings.&lt;/p&gt;&lt;p&gt;One significant limitation lies in the presence of substantial heterogeneity across the included studies, as evidenced by high &lt;i&gt;I&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; values (&gt; 90%). The heterogeneity raises concerns regarding the comparability of pooled prevalence estimates for malnutrition and at-risk malnutrition, which the authors reported as 33% and 44%, respectively. Although the authors performed subgroup analyses by measurement tools, region, and diabetes complications, these analyses did not fully address the underlying causes of variability. The authors could have considered using meta-regression analysis to explore potential sources of heterogeneity, such as differences in study design, sample characteristics, and diagnostic criteria [&lt;span&gt;2&lt;/span&gt;]. This statistical approach would have provided a deeper understanding of the heterogeneity and potentially improved the robustness of their conclusions.&lt;/p&gt;&lt;p&gt;Additionally, the authors relied on confidence intervals (CIs) to present pooled estimates but did not include prediction intervals (PIs). While CIs describe the precision of the pooled effect size, PIs would have conveyed the range of effects expected in future studies. The use of PIs is especially critical in the presence of high heterogeneity, as it offers a clearer picture of the variability across different settings and populations [&lt;span&gt;3&lt;/span&gt;]. The inclusion of PIs alongside CIs would have strengthened the interpretation of the meta-analysis results, particularly for clinical decision-making.&lt;/p&gt;&lt;p&gt;Another important methodological concern involves the assessment of publication bias. The authors used Egger's test and visual inspection of funnel plots to evaluate publication bias. While these methods are widely used, they may not be optimal for meta-analyses involving proportions, where asymmetry in funnel plots can arise from true heterogeneity rather than bias. The authors might have instead employed more appropriate approaches, such as the Doi plot and LFK index, which are specifically designed to assess publication bias in proportion meta-analyses [&lt;span&gt;4&lt;/span&gt;]. These methods offer greater reliability in detecting bias in prevalence studies and could have provided additional assurance regarding the integrity of the findings.&lt;/p&gt;&lt;p&gt;The use of diverse diagnostic tools, such as the Mini Nu","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"17 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143530367","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}