Diabetes/Metabolism Research and Reviews最新文献

{"title":"Use of an Advanced Hybrid Closed Loop System During Marathon Running: Case Examples and Clinical Implications","authors":"María T. Onetto,&nbsp;Denise Montt-Blanchard,&nbsp;Cari Berget,&nbsp;Kristel Strodhoff,&nbsp;Bruno Grassi","doi":"10.1002/dmrr.70034","DOIUrl":"https://doi.org/10.1002/dmrr.70034","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and aims</h3>\u0000 \u0000 <p>Maintaining glucose levels in the target range during aerobic training and athletic competition is especially difficult. The use of Automated Insulin Delivery (AID) technology is increasing, but exercise continues to be a challenge for persons with type 1 diabetes (T1D). In this case report series, we present 3 cases (C1, C2 and C3) of persons with T1D who used the MiniMed 780G during marathon races. We describe the strategies they used before, during and after the race to manage their glycaemia as well as the results of these strategies on their glycaemic control during the race.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The Medtronic CareLink platform was employed to remotely access insulin pump settings and glycaemic outcomes. Race parameters were obtained from sport watches. Supplemental data were obtained through interviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Carelink data for Cases 1, 2, and 3 before the race were downloaded: Time in range (TIR) 70–180 mg/dL 89%, 76%, 82%; time above range (TAR) &gt; 180 mg/dL, 9%, 20%, 16%; time below range (TBR) &lt; 70 mg/dL, 1%, 4%, 1%, respectively. The breakfast insulin reduction percentages were −25%, 0%, and 0% for C1, C2, and C3, respectively. In all three cases, insulin dose reduction was applied to the pre-race snack at percentages of −50%, −100% and −83%. The consumption of carbohydrates during the race was 0.39 g/kg/hour, 0.42 g/kg/hour, and 0.5 g/kg/hour, respectively. The total amount of carbohydrates consumed was 101 g, 120 g, and 115 g, respectively. Throughout the race, a temporary target was used for all cases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These cases provide insights for healthcare professionals who assist athletes with T1D using AID systems during prolonged physical activities. Highlighting the significance of specialised education, planning, and personalised approaches.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 3","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dmrr.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513808","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":"Temporal Trends in the Burden of Diabetes and Its Risk Factors Across the Western Pacific Region Between 1990 and 2044: A Systematic Analysis of the Global Burden of Disease Study 2019","authors":"Xinwei Liu,&nbsp;Bing Wu,&nbsp;Yongqiang Lai,&nbsp;Xiyu Zhang,&nbsp;Hongyu Li,&nbsp;Fangqi Qu,&nbsp;Chenxi Zhang,&nbsp;Yulu Tian,&nbsp;Xuelian Fu,&nbsp;Jida Li,&nbsp;Huiqi Yang,&nbsp;Rui Chen,&nbsp;Baoguo Shi,&nbsp;Yanan Ma,&nbsp;Jia Meng,&nbsp;Ye Li","doi":"10.1002/dmrr.70036","DOIUrl":"https://doi.org/10.1002/dmrr.70036","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>We aimed to assess changes in the burden of diabetes in the Western Pacific region (WPR) between 1990 and 2019, project future trends for 2020–2044, and identify the factors influencing these trends.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>Data from the Global Burden of Disease Study 2019 were used to calculate the age-standardised incidence rate (ASIR), age-standardised death rate (ASDR) and age-standardised disability-adjusted life years (DALYs) rate for diabetes in the region. The Nordpred model was used to predict diabetes-related ASIR and ASDR trends over the next 25 years, and an age-period-cohort (APC) model analysed the effects of age, period and cohort. We examined the associations of ASIR, ASDR and age-standardised DALYs rate per 100,000 population with the socio-demographic index (SDI).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We observed an increasing trend in the incidence. Mortality increased in the lower-middle income group and decreased slowly in the high- and upper-middle income groups. High body mass index significantly affected diabetes, with an increasing influence over time, whereas that of tobacco showed a decreasing trend. The incidence of diabetes showed a trend towards occurring at a younger age, in a manner consistent with the economic development trend. Diabetes incidence and mortality showed the opposite trend in the high-income group, with an increase in SDI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The burden of diabetes is increasing in the WPR, in association with urbanisation and unhealthy lifestyles. Targeting the risk factors that affect all stages of the disease and managing them through multi-agency collaboration may improve the quality of life in patients living with the condition.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 2","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dmrr.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466114","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":"Inpatient Dietary Behaviour Score (IDBS) Predicts the Risk of Hypoglycemia in Type 2 Diabetes Mellitus (T2DM) Patients","authors":"Zhiping Liu,&nbsp;Jiangqiong Chen,&nbsp;Qing Liang,&nbsp;Wenjin Luo,&nbsp;Qingfeng Cheng,&nbsp;Qifu Li,&nbsp;Mei Mei,&nbsp;Liping Zan","doi":"10.1002/dmrr.70035","DOIUrl":"https://doi.org/10.1002/dmrr.70035","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>The aim of this study was to develop the inpatient dietary behaviour score (IDBS) and validate its predictive performance in assessing the risk of hypoglycemia in patients with type 2 diabetes mellitus (T2DM).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The study included patients with T2DM admitted to the Endocrinology Department of the First Affiliated Hospital of Chongqing Medical University between 1 March 2021 and 1 March 2023. Patients were categorised into hypoglycemia and non-hypoglycemia groups using a paired approach, with hypoglycemia defined as any point-of-care glucose test results ≤ 3.9 mmol/L. Clinical data were collected, and the IDBS was calculated using a self-designed scale with 11 variables. Subsequently, measures for predicting hypoglycemia risk in hospitalised T2DM patients were formulated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 1478 patients were included in the survey, with 739 patients in each of the hypoglycemic and non-hypoglycemic groups after pairing. Baseline differences were observed in education, marital status, job status, DM duration, glycosylated haemoglobin A1c (HbA1c), body mass index (BMI), hypoglycemia history, diabetic peripheral artery disease (DM-PAD), diabetic foot (DF), diabetic kidney disease (DKD), and diabetic retinopathy (DR) between the hypoglycemic and non-hypoglycemic groups. Significant correlations were found between the updated and baseline changes in the IDBS. The predictive efficacy was highest in DKD patients (OR = 1.82, 95% CI: 1.69–1.97, <i>P</i> = 6.75E-53). In multivariate analyses, only BMI, DM duration, diabetic foot and marriage response were included in the regression model. The area under the curve (AUC) and mean squared error (MSE) of the IDBS were 0.77 and 0.00039, respectively. A linear relationship existed between the IDBS and OR values, indicating that the risk of hypoglycemia increased with higher scores.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>IDBS demonstrated a robust predictive effect on hypoglycemia. The variable data were easily obtainable, and the evaluation and calculation methods were straightforward. This scoring system could serve as a valuable reference for hypoglycemia prevention and screening of hospitalised diabetic patients at high risk of hypoglycemia.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 2","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dmrr.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404391","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 GLP-1 Receptor Agonists With Risk of Suicidal Ideation and Behaviour: A Systematic Review and Meta-Analysis","authors":"Ganesh Bushi,&nbsp;Mahalaqua Nazli Khatib,&nbsp;Shivam Rohilla,&nbsp;Mahendra Pratap Singh,&nbsp;Nidhi Uniyal,&nbsp;Suhas Ballal,&nbsp;Pooja Bansal,&nbsp;Kiran Bhopte,&nbsp;Manika Gupta,&nbsp;Abhay M. Gaidhane,&nbsp;Balvir S. Tomar,&nbsp;Ayash Ashraf,&nbsp;M. Ravi Kumar,&nbsp;Ashish Singh Chauhan,&nbsp;Sanjit Sah,&nbsp;Hashem Abu Serhan,&nbsp;Muhammed Shabil","doi":"10.1002/dmrr.70037","DOIUrl":"https://doi.org/10.1002/dmrr.70037","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background and Objective</h3>\u0000 \u0000 <p>Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely used to treat type 2 diabetes and obesity, providing metabolic and cardiovascular benefits. However, concerns have emerged about potential neuropsychiatric side effects, including suicidal ideation and behaviour, prompting investigations by regulatory bodies such as the FDA and EMA. This systematic review and meta-analysis aimed to assess the association between GLP-1RA use and the risk of suicidal ideation or behaviour.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A systematic literature search was conducted in PubMed, Embase, and Web of Science through September 2024, adhering to PRISMA guidelines. Observational cohort and case-control studies reporting suicidal ideation or behaviour in adults using GLP-1RAs were included. The Modified Newcastle-Ottawa Scale assessed risk of bias, and random-effect models calculated risk ratios (RR) with 95% confidence intervals (CIs). Heterogeneity was assessed using the I² statistic.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 126 studies, 11 were included from multiple countries with diverse designs. The meta-analysis of four studies showed no statistically significant difference in suicidal outcomes between GLP-1RA users and users of other anti-hyperglycaemic drugs (RR: 0.568, 95% CI: 0.077–4.205). Substantial heterogeneity was observed (I² = 98%). Pharmacovigilance studies indicated no disproportionate increase in suicidality, while some observational studies suggested a lower risk.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This review found no significant link between GLP-1RA use and increased suicidal ideation or behaviour. However, the high heterogeneity and reliance on pharmacovigilance data suggest caution. Clinicians should monitor patients, particularly those with psychiatric conditions, and further research is needed to assess long-term neuropsychiatric safety.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 2","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/dmrr.70037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397156","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":"Review of Associations of Diabetes and Insulin Resistance With Brain Health in Three Harmonised Cohort Studies of Ageing and Dementia","authors":"Roshni Biswas,&nbsp;Ana W. Capuano,&nbsp;Rupal I. Mehta,&nbsp;Lisa L. Barnes,&nbsp;David A. Bennett,&nbsp;Zoe Arvanitakis","doi":"10.1002/dmrr.70032","DOIUrl":"10.1002/dmrr.70032","url":null,"abstract":"<p>Diabetes increases the risk of dementia, and insulin resistance (IR) has emerged as a potential unifying feature. Here, we review published findings over the past 2 decades on the relation of diabetes and IR to brain health, including those related to cognition and neuropathology, in the Religious Orders Study, the Rush Memory and Aging Project, and the Minority Aging Research Study (ROS/MAP/MARS), three harmonised cohort studies of ageing and dementia at the Rush Alzheimer's Disease Center (RADC). A wide range of participant data, including information on medical conditions such as diabetes and neuropsychological tests, as well as other clinical and laboratory-based data collected annually. Neuropathology data are collected in participants who agree to autopsy at death. Recent studies have measured additional peripheral and brain IR data, including multi-omics. This review summarises findings from the RADC cohort studies that investigate the relation of diabetes and IR in older adults to cognition, neuropathology, omics in dementia, and other brain health measures. Examining the risk of clinically diagnosed dementia in older adults, our study found a 65% increased risk of Alzheimer's disease (AD) dementia in individuals with diabetes compared with those without. Regarding cognitive function, we have consistently observed associations of diabetes, as well as both peripheral and brain IR, with worse and declining performance in global cognition and specific cognitive domains, particularly semantic memory and perceptual speed. Studies utilising neuropathological data showed associations of diabetes and peripheral IR with brain infarcts, while brain IR measures, notably alpha serine/threonine-protein kinase1 (AKT1), were associated with both brain infarcts and AD pathology. Multi-omics studies suggested shared causal genes and pathways between diabetes and dementia. Recent epigenetic studies have revealed associations between IR and AD risk, along with distinct 5-hydroxymethylcytosine signatures in diabetes-associated AD. Furthermore, our studies have utilised other available data to investigate the impact of diabetes on neurological outcomes other than cognition and reported worsening of parkinsonian-like signs in diabetes. Recent studies have also explored risk factors for diabetes and have reported associations between lower literacy and decision-making abilities with elevated haemoglobin A1C levels, a peripheral IR measure. Overall, our findings, as summarised in this review, illustrate a range of mechanistic and other insights into the complex relationship of diabetes and IR with brain health. These findings may have important implications for future research on the ageing brain, including the prevention of cognitive decline and dementia in persons at risk for or with diabetes.</p>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143053996","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 Burden of Diabetes in the Southeastern Coastal Region of China From 1990 to 2019 and Projections for 2030: A Systematic Analysis of the 2019 Global Burden of Disease Study","authors":"Yating Ding,&nbsp;Xiuli Cai,&nbsp;Yangjiang Ou,&nbsp;Dong Liang,&nbsp;Qing Guan,&nbsp;Wenling Zhong,&nbsp;Xiuquan Lin","doi":"10.1002/dmrr.70031","DOIUrl":"10.1002/dmrr.70031","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study examined the diabetes burden in Fujian Province, China, from 1990 to 2019, comparing it with China and global levels to inform policymakers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>We used data from GBD 2019 to analyse diabetes prevalence, death, and disability-adjusted life-years (DALYs). We assessed the average annual percentage change (AAPC) and estimated the impact of 17 risk factors. An age-period-cohort model evaluated age, period, and cohort effects on diabetes metrics. Bayesian models forecasted prevalence and DALYs for 2020–2030, with frontier analysis linking DALYs to per capita GDP.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In 2019, Fujian Province had approximately 2,359,179 diabetes cases with a prevalence rate of 4423.82 (95% UI 4004.12–4864.55) per 100,000 and an age-standardised DALYs of 475.00 (375.63–589.49) per 100,000, both lower than China and global averages. From 1990 to 2019, Fujian Province's age-standardised mortality rate remained higher than the China average, but the gap narrowed compared with 1990. Elderly males showed a pronounced increase in mortality. The period effect indicated a turning point during 2005–2009. DALYs increased among men and decreased among women over cohorts. By 2030, the DALYs rate is projected to decrease by 6.59%. Frontier analysis showed that compared with the same economic level, the effective difference in diabetes disease burden in Fujian Province was small, but there was room for improvement.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>From 1990 to 2019, Fujian Province's age-standardised diabetes prevalence slightly increased, while mortality and DALYs declined. Significant gender and age disparities existed, highlighting the need for targeted strategies for elderly males. Fujian Province's success in diabetes management can provide a model for other regions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Postpartum Metabolic Heterogeneity Among Women Who Progressed to Type 2 Diabetes After Gestational Diabetes: A Prospective Cohort","authors":"Saifur R. Khan,&nbsp;Julie A. D. Van,&nbsp;Zhang Xiangyu,&nbsp;Stacey E. Alexeeff,&nbsp;Babak Razani,&nbsp;Michael B. Wheeler,&nbsp;Erica P. Gunderson","doi":"10.1002/dmrr.70027","DOIUrl":"10.1002/dmrr.70027","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Gestational diabetes mellitus (GDM) poses a significant risk for developing type 2 diabetes mellitus (T2D) and exhibits heterogeneity. However, understanding the link between different types of post-GDM individuals without diabetes and their progression to T2D is crucial to advance personalised medicine approaches.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>We employed a discovery-based unsupervised machine learning clustering method to generate clustering models for analysing metabolomics, clinical, and biochemical datasets. For this analysis, we selected 225 women who later developed T2D during the 12-year follow-up period from the cohort of 1010 women who returned to a non-diabetic state at 6–9 weeks (study baseline) after a GDM pregnancy based on 2-h 75 g research OGTTs. The optimal model was selected by assessing Bayesian Information Criterion values, class separation performance, and the potential for clinically distinguishable clusters, accounting for participant prenatal and early postpartum characteristics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The selected model comprises three clusters: pancreatic beta cell dysfunction (cluster-β: median HOMA-B 161.3 and median HOMA-IR 3.8), insulin-resistance (cluster-IR: median HOMA-B 630.5 and median HOMA-IR 16.8), and a mixed cluster (cluster-mixed: median HOMA-B 307.2 and median HOMA-IR 8.6). These clusters are distinguishable based on postpartum blood test parameters such as glucose tolerance, HOMA indices, and fasting lipid profiles including triglycerides, leptin, HDL-c, and adiponectin, as well as participant age and BMI. Metabolomic analysis identified unique molecular signatures for each cluster. However, the time to T2D onset was not statistically significant among the three clusters (<i>p</i> = 0.22).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study enhances our understanding of the heterogeneity of early postpartum metabolic profiles that characterise the future onset of T2D diabetes in a diverse cohort of women with GDM, revealing insights into distinct mechanisms and personalised intervention strategies for the prevention of T2D.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985128","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":"Chinese Visceral Adiposity Index Trajectory and Stroke in Prediabetes and Diabetes: A Prospective Cohort Study","authors":"Qitong Liu,&nbsp;Ming Sun,&nbsp;Yang Liu,&nbsp;Wenqi Xu,&nbsp;Huancong Zheng,&nbsp;Ning Ning,&nbsp;Rong Huang,&nbsp;Jin Zhou,&nbsp;Jinang Shao,&nbsp;Wenhui Zhou,&nbsp;Shuohua Chen,&nbsp;Shouling Wu,&nbsp;Yanan Ma","doi":"10.1002/dmrr.70025","DOIUrl":"10.1002/dmrr.70025","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Stroke is a common diabetic complication, by which the Chinese visceral adiposity index (CVAI) is confirmed as a better predictor of visceral fat. However, the relationship between CVAI change and the stroke risk among patients with diabetes and prediabetes remains unclear. Therefore, we aimed to examine the association of CVAI trajectory with the risk of stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>This prospective cohort study included 11,339 patients with prediabetes and diabetes from the Kailuan study. These participants had complete repeated metabolic and body measurements that formed the continuous CVAI records. The stroke cases were identified by medical records. Latent mixture modelling was conducted to fit four groups of CVAI trajectories. Cox proportional hazard regression models were used to examine the associations between CVAI trajectories and the risk of stroke and its subtypes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Four distinct CVAI trajectories were identified: the low-stable, moderate low-stable, moderate high-stable, and high-increasing groups. Compared with low-stable CVAI, moderate high-stable (HR: 1.50, 95%CI: 1.10–2.04) and high-increasing CVAI (HR: 2.15, 95%CI: 1.49–3.10) were positively associated with the risk of stroke. Similarly, moderate high-stable (HR: 1.70, 95%CI: 1.21–2.39) and high-increasing CVAI trajectory groups (HR: 2.53, 95%CI: 1.71–3.73) had an increased risk of ischaemic stroke compared with the low-stable CVAI group. However, a significant association was not found between CVAI trajectory and risk of haemorrhage stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A long-term elevated CVAI is associated with a higher risk of stroke, especially ischaemic stroke. This finding suggests the health benefits of low CVAI levels and the importance of regular surveillance among patients with prediabetes and diabetes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Omics in Untangling the Effect of Lifestyle Factors in Pregnancy and Gestational Diabetes: A Systematic Review","authors":"Kai Liu,&nbsp;Georgia S. Clarke,&nbsp;Jessica A. Grieger","doi":"10.1002/dmrr.70026","DOIUrl":"10.1002/dmrr.70026","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>To synthesise the evidence from clinical trials and observational studies using omics techniques to investigate the impact of diet and lifestyle factors on metabolite profile in pregnancy, and in the prevention and management of gestational diabetes mellitus (GDM).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>A systematic literature search was performed using PubMed, Ovid, CINAHL, and Web of Science databases in October 2023 and updated in September 2024. Inclusion criteria were randomised controlled trials (RCT) or non-RCTs in pregnant women with or without GDM, that measured diet and lifestyle factors, and which applied post-transcriptional omics approaches. Risk of bias was assessed using the ROBINS-I for non-RCTs and ROB-2 tool for RCTs. The results of all studies are narratively synthesised.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 6293 studies identified, eight observational studies and three RCTs comprising 2639 pregnant women were included. Three studies reported on changes in diet-related metabolic phenotypes during pregnancy; however, the impact of certain foods on the metabolome and risk for GDM was less clear. Compared with women without GDM, women with GDM had a worse deterioration in metabolites, including saturated fatty acids, branched chain amino acids and purine degradation metabolites. There is limited evidence that conventional dietary treatment for GDM may modify the metabolome in women with GDM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Metabolome profiles in pregnancy may be altered by certain dietary choices; however, it is inconclusive whether improved diet related metabolite profiles have a beneficial impact in the prevention or management of GDM. High quality studies with larger sample sizes are needed to better understand the role that maternal nutrition plays in modulating the maternal metabolome, not only for a healthy pregnancy but also for the prevention and management of GDM.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11725626/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972955","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 Rise of Type 2 Diabetes in Children and Adolescents: An Emerging Pandemic","authors":"Shiwali Goyal,&nbsp;Vanita Vanita","doi":"10.1002/dmrr.70029","DOIUrl":"10.1002/dmrr.70029","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This review explores the increasing prevalence of Type 2 Diabetes Mellitus (T2DM) in children and adolescents, focusing on its etiology, risk factors, complications, and the importance of early detection and management. It also highlights the need for a multidisciplinary, family-centered approach in managing T2DM in pediatric populations, with an emphasis on nutrition, exercise, and lifestyle interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>A literature review was conducted using PubMed, Google Scholar, and Scopus to incorporate studies from 2015 to 2024 on T2DM in youths/adolescents/children, focusing on epidemiology, risk factors, and prevention strategies. Studies on Type 1 Diabetes Mellitus (T1DM) or adult populations were excluded.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>T2DM is a complex metabolic disorder with various societal, behavioral, environmental, and genetic risk factors. It accounts for one in three new childhood diabetes cases, with rising incidence among American Indian/Alaska Native, Black, and Hispanic/Latino children. The increase in T2DM incidence correlates with growing childhood obesity rates. Early onset significantly raises the risk of complications like retinopathy, nephropathy, neuropathy, cardiovascular diseases, nonalcoholic fatty liver disease, and obstructive sleep apnea. Early detection, screening, and treatment can prevent or delay these complications. A family-centered, multidisciplinary approach is essential for effective management, including lifestyle and behavioral support.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>T2DM in children is a growing health concern with severe implications. Early detection and management, including nutrition and exercise counseling, are critical in reducing long-term complications. A multidisciplinary approach is vital for improving outcomes and minimizing morbidity and mortality.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11335,"journal":{"name":"Diabetes/Metabolism Research and Reviews","volume":"41 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142915707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}