Diabetes research and clinical practice最新文献

{"title":"A prediction model for gestational diabetes mellitus based on steroid hormonal changes in early and mid-down syndrome screening: A multicenter longitudinal study","authors":"Bo Zhu ,&nbsp;Binbin Yin ,&nbsp;Hui Li ,&nbsp;Xuelian Chu ,&nbsp;Zhifeng Mi ,&nbsp;Yanni Sun ,&nbsp;Xiaofen Yuan ,&nbsp;Rongchang Chen ,&nbsp;Zhixin Ma","doi":"10.1016/j.diabres.2024.111865","DOIUrl":"10.1016/j.diabres.2024.111865","url":null,"abstract":"<div><h3>Background</h3><div>Steroid hormones (SH) during pregnancy are associated with the development of gestational diabetes mellitus (GDM). Early and mid-Down syndrome screening is used to assess the risk of Down syndrome in the fetus. It is unclear whether changes in SH during this period can be used as an early predictor of GDM.</div></div><div><h3>Methods</h3><div>This study was a multicenter, longitudinal cohort study. GDM is diagnosed by an oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation. We measured SH levels at early and mid-Down syndrome screening, respectively. Based on the SH changes, logistic regression analysis was used to construct a prediction model for GDM. Finally, evaluated the model’s predictive performance by creating a receiver operating characteristic curve (ROC) and performing external validation.</div></div><div><h3>Results</h3><div>This study enrolled 193 pregnant women (discovery cohort, n = 157; validation cohort, n = 36). SH changes occur dynamically after pregnancy. At early Down syndrome screening, only cortisol (F) (<em>p</em> &lt; 0.05, 95 % CI 4780.95–46083.68) was elevated in GDM. At mid-Down syndrome screening, free testosterone (FT) (<em>p</em> &lt; 0.01, 95 % CI 0.10–0.55) and estradiol (E2) (<em>p</em> &lt; 0.05, 95 % CI 203.55–1784.78) were also significantly elevated. There were significant differences in the rates of change in E2 (Fold change (FC) = 1.3425, <em>p</em> = 0.0072), albumin (ALB) (FC=1.5759, <em>p</em> = 0.0117), and dihydrotestosterone (DHT) (FC=-2.1234, <em>p</em> = 0.0165) between GDM and no-GDM. Stepwise logistic regression analysis resulted in the best predictive model, including six variables (Δweight, ΔF, Δcortisone (E), ΔE2, Δprogesterone (P), ΔDHT). The area under the curve for this model was 0.791, and for the external validation cohort, it was 0.799.</div></div><div><h3>Conclusions</h3><div>A GDM prediction model can be constructed using SH measures during early and mid-Down syndrome screening.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111865"},"PeriodicalIF":6.1,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sleep quality and glucose control in adults with type 1 diabetes during the seasonal daylight saving time shifts","authors":"Silvia Angelino ,&nbsp;Miriam Longo ,&nbsp;Paola Caruso ,&nbsp;Lorenzo Scappaticcio ,&nbsp;Nicole Di Martino ,&nbsp;Concetta Di Lorenzo ,&nbsp;Daniela Forestiere ,&nbsp;Vanda Amoresano Paglionico ,&nbsp;Giuseppe Bellastella ,&nbsp;Maria Ida Maiorino ,&nbsp;Katherine Esposito","doi":"10.1016/j.diabres.2024.111859","DOIUrl":"10.1016/j.diabres.2024.111859","url":null,"abstract":"<div><h3>Aim</h3><p>There is a bidirectional relationship between glucose control and sleep quality and timing in type 1 diabetes (T1D). The aim of the study was to investigate the sleep quality and the glucose metrics in people with T1D at the seasonal clock adjustment.</p></div><div><h3>Methods</h3><p>This observational study retrospectively compared the continuous glucose monitoring (CGM) derived metrics and sleep quality observed before (Time 0) and after (Time 1) transition in autumn and before (Time 2) and after (Time 3) transition in spring. We included adults with T1D, treated with CGM systems, who completed the Pittsburgh Sleep Quality Index questionnaire. The main outcome measure was the change in glucose monitoring indicator (GMI), time in range (TIR), time above range (TAR) and time below range.</p></div><div><h3>Results</h3><p>Sixty-two participants showed no changes in sleep quality at time transitions. GMI values increased during both time transitions and the percentage of TIR decreased from Time 0 to Time 1 and from Time 2 to Time 3. The percentage of level 2 TAR increased during the observation.</p></div><div><h3>Conclusions</h3><p>At similar level of sleep quality, adults with T1D underwent the worsening of most of CGM-derived glucose control metrics during the transition time.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111859"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168822724007691/pdfft?md5=634c9dc676c402fca942e09956120407&pid=1-s2.0-S0168822724007691-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetes distress profiles and health outcomes of individuals with type 2 diabetes and overweight/obesity: A cluster analysis","authors":"Yiyun Zhang ,&nbsp;Dan Zhang ,&nbsp;Tianxue Long,&nbsp;Yi Wu,&nbsp;Jing Huang,&nbsp;Yating Zhang,&nbsp;Mingzi Li","doi":"10.1016/j.diabres.2024.111863","DOIUrl":"10.1016/j.diabres.2024.111863","url":null,"abstract":"<div><h3>Aims</h3><p>To determine the prevalence and patterns of diabetes distress, and evaluate the differences in health outcomes between profiles.</p></div><div><h3>Methods</h3><p>This cross-sectional study included 330 adults with T2DM and overweight/obesity. The participants completed questionnaires on diabetes distress, sleep quality, self-efficacy, depression, anxiety and positive and negative affect. A cluster analysis was performed to identify different patterns of diabetes distress and one-way ANOVA was used to investigate the differences in physical and psychological outcomes between profiles.</p></div><div><h3>Results</h3><p>30.6% of patients were identified as moderately to highly distressed, with the regimen-related distress found to be the most prominent. The Cluster analysis revealed four distinct clusters: (1) “comprehensively exhausted profile”; (2) “strained profile”; (3) “high internal anguish profile”; (4) “unperturbed profile”. The measures of fasting blood glucose (FBG), glycated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, sleep quality, depression, anxiety, positive and negative affect and self-efficacy differ between clusters.</p></div><div><h3>Conclusions</h3><p>This study identified important differences that existed in patterns of diabetes distress among people with T2DM and overweight/obesity, and this variation can be utilized to tailor intervention strategies to the particular needs of different subgroups within individuals with T2DM.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111863"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetes mellitus is associated with low exercise capacity and impaired peripheral vasodilation in patients with heart failure − a propensity score-matched study","authors":"Miroslava Valentova ,&nbsp;Mirela Vatic ,&nbsp;Tania Garfias-Veitl ,&nbsp;Anja Sandek ,&nbsp;Tarek Bekfani ,&nbsp;Ewa A. Jankowska ,&nbsp;John G.F. Cleland ,&nbsp;Andrew L. Clark ,&nbsp;Mitja Lainscak ,&nbsp;Ali Ahmed ,&nbsp;Nadja Jauert ,&nbsp;Gerd Hasenfuss ,&nbsp;Stefan D. Anker ,&nbsp;Wolfram Doehner ,&nbsp;Stephan von Haehling","doi":"10.1016/j.diabres.2024.111864","DOIUrl":"10.1016/j.diabres.2024.111864","url":null,"abstract":"<div><h3>Aims</h3><div>Diabetes mellitus (DM) and heart failure (HF) share vascular, skeletal and metabolic abnormalities that can reduce exercise capacity. We investigated whether exercise capacity differ in patients with type 2 DM compared to those without DM with HF of similar severity.</div></div><div><h3>Methods and results</h3><div>The Studies Investigating Co-morbidities Aggravating HF (SICA-HF) prospectively enrolled 615 patients with chronic HF, 259 (42.1 %) of whom had DM. We assembled a propensity score-matched cohort of 231 pairs of patients with HF with or without DM who were balanced on age, sex and variables reflecting HF severity. Patients with DM had lower median peak VO₂ (15.7 [13.0–19.1] <em>vs.</em> 17.3 [14.1–21.0] ml/min/kg; p = 0.005). Forearm blood flow reserve (per 1 ml/min/100 ml increase) was associated with lower exercise capacity (peak VO2 ≤ 16.6 ml/min/kg) in patients with DM (OR, 0.92; 95 % CI, (0.85–0.98; p = 0.014), but not in those without DM (OR, 0.98; 95 % CI, 0.93–1.02). A similar heterogeneity was also observed for HDL cholesterol.</div></div><div><h3>Conclusions</h3><div>Diabetes is associated with a reduced exercise capacity in patients with HF. Most predictors of lower exercise capacity in HF are similar regardless of DM except impaired vascular function and lower HDL cholesterol which predict lower exercise capacity only in those with DM.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111864"},"PeriodicalIF":6.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computed tomography-based body composition indicative of diabetes after hypertriglyceridemic acute pancreatitis","authors":"Yingbao Huang ,&nbsp;Yi Zhu ,&nbsp;Weizhi Xia ,&nbsp;Huanhuan Xie ,&nbsp;Huajun Yu ,&nbsp;Lifang Chen ,&nbsp;Liuzhi Shi ,&nbsp;Risheng Yu","doi":"10.1016/j.diabres.2024.111862","DOIUrl":"10.1016/j.diabres.2024.111862","url":null,"abstract":"<div><h3>Background</h3><p>Post‑acute pancreatitis prediabetes/diabetes mellitus (PPDM‑A) is one of the common sequelae of acute pancreatitis (AP). The aim of our study was to build a machine learning (ML)-based prediction model for PPDM-A in hypertriglyceridemic acute pancreatitis (HTGP).</p></div><div><h3>Methods</h3><p>We retrospectively enrolled 165 patients for our study. Demographic and laboratory data and body composition were collected. Multivariate logistic regression was applied to select features for ML. Support vector machine (SVM), linear discriminant analysis (LDA), and logistic regression (LR) were used to develop prediction models for PPDM-A.</p></div><div><h3>Results</h3><p>65 patients were diagnosed with PPDM-A, and 100 patients were diagnosed with non-PPDM-A. Of the 84 body composition-related parameters, 15 were significant in discriminating between the PPDM-A and non-PPDM-A groups. Using clinical indicators and body composition parameters to develop ML models, we found that the SVM model presented the best predictive ability, obtaining the best AUC=0.796 in the training cohort, and the LDA and LR model showing an AUC of 0.783 and 0.745, respectively.</p></div><div><h3>Conclusions</h3><p>The association between body composition and PPDM-A provides insight into the potential pathogenesis of PPDM-A. Our model is feasible for reliably predicting PPDM-A in the early stages of AP and enables early intervention in patients with potential PPDM-A.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111862"},"PeriodicalIF":6.1,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical activity and sedentary behaviour in relation to body composition, estimated insulin sensitivity and arterial stiffness in adults with type 1 diabetes","authors":"Simon Helleputte ,&nbsp;Jan Stautemas ,&nbsp;Marieke De Craemer ,&nbsp;Lotte Bogaert ,&nbsp;Tine De Backer ,&nbsp;Patrick Calders ,&nbsp;Bruno Lapauw","doi":"10.1016/j.diabres.2024.111860","DOIUrl":"10.1016/j.diabres.2024.111860","url":null,"abstract":"<div><h3>Aims</h3><p>To examine the association of daily PA levels and sedentary behaviour with body composition, estimated insulin sensitivity, and arterial stiffness in adults with type 1 diabetes (T1D).</p></div><div><h3>Methods</h3><p>Cross-sectional study in adults with T1D (n = 54). PA levels (daily steps, and time in moderate-to-vigorous intensity PA (MVPA)) and sedentary behaviour were measured using accelerometry for 7 days (<em>McRoberts® DynaPort MoveMonitor</em>). Cardiopulmonary exercise test for VO_2max. Anthropometrics were collected, and body composition (total and % of fat mass (FM_tot, FM_%), total and % of lean mass (LM_tot, LM_%), and estimated visceral adipose tissue (VAT)) volume was assessed with dual energy X-ray-absorptiometry (DXA). Estimates of insulin sensitivity were determined (estimated glucose disposal rate (eGDR) and total daily insulin dose). Arterial stiffness was assessed with carotid-femoral pulse wave velocity (cf-PWV (m/s); <em>SphygmoCor®</em>).</p></div><div><h3>Results</h3><p>Lower 10-years HbA1_c associated moderately with all PA measures. Favourable moderate associations were also found between PA measures and BMI, waist, VAT but not FM and LM. PA measures were favourably associated with a lower total daily insulin dose and higher eGDR. All PA parameters associated moderately with cf-PWV however not independent from traditional risk factors. VO_2max was inversely associated with cf-PWV independent of age, T1D duration and 24-hour mean blood pressure.</p></div><div><h3>Conclusions</h3><p>Higher levels of PA, lower sedentary behaviour and greater exercise capacity are favourably associated with long-term glycaemic control, body composition, insulin dosage, estimated insulin sensitivity and arterial stiffness in adults with T1D. Therefore, regular PA and limiting sedentary time should be encouraged to improve metabolic and cardiovascular health in this population. Future longitudinal studies should explore mutual interactions and synergistic effects of PA on these outcomes.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111860"},"PeriodicalIF":6.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of ideal cardiovascular health and history of gestational diabetes mellitus in NHANES 2007–2018","authors":"Rabail Sadiq ,&nbsp;Eric K. Broni ,&nbsp;Lisa D. Levine ,&nbsp;Ravi Retnakaran ,&nbsp;Justin B. Echouffo-Tcheugui","doi":"10.1016/j.diabres.2024.111857","DOIUrl":"10.1016/j.diabres.2024.111857","url":null,"abstract":"<div><h3>Background</h3><p>Population-based studies of ideal cardiovascular health (CVH) and gestational diabetes mellitus (GDM) are scarce.</p></div><div><h3>Methods</h3><p>We conducted a cross-sectional analysis of 2007–2018 National Health Examination and Nutrition Survey women aged ≥ 20 years, who had data on Life’s Simple 7 (LS7) metrics and self-reported GDM history. Each LS7 metric was assigned a score of 0 (non-ideal) and 1(ideal) and summed to obtain total ideal CVH scores (0–7). We used logistic regression models to assess associations between LS7 ideal CVH scores (0–7) and GDM history, accounting for socio-demographic factors.</p></div><div><h3>Results</h3><p>Among 9199 women (mean age: 46 years, 8 % with a GDM history), there was a progressive decrease in the odds of past GDM history across increasing ideal CVH scores. Compared to females with 0–1 ideal CVH scores, females with ideal CVH scores of 3, 4 and 5–7 had an associated 39 % lower [odds ratio: 0.61 (95 % CI: 0.41–0.90)], 50 % lower [0.50 (0.33–0.76)] and 66 % lower [0.34 (0.20–0.56)] odds of past GDM history, respectively. There were notable racial/ethnic and citizenship/nativity differences in these associations.</p></div><div><h3>Conclusions</h3><p>Women with higher ideal CVH scores had lower odds of GDM history. Our findings underscore the importance of optimizing cardiometabolic health among women with GDM history.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111857"},"PeriodicalIF":6.1,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142272010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of microRNAs in diabetic foot ulcers: Mechanisms and possible interventions","authors":"Lin Wang,&nbsp;Cong Wang,&nbsp;Caiyan Huang,&nbsp;Zhongyu Zhou,&nbsp;Ruihong Yang,&nbsp;Ying Huang,&nbsp;Zhuangsen Chen,&nbsp;Yanrong Zhang,&nbsp;Shanshan Wang,&nbsp;Kun Feng","doi":"10.1016/j.diabres.2024.111858","DOIUrl":"10.1016/j.diabres.2024.111858","url":null,"abstract":"<div><p>Diabetic foot ulcer (DFU) is a common and serious complication among diabetic patients, and its incidence and difficulty in treatment have placed large burdens on patient health and quality of life. Diabetic foot tissue typically exhibits chronic wounds, ulcers, or necrosis that are difficult to heal, are prone to infection, and, in severe cases, may even lead to amputation. Recent studies have shown that microRNAs (miRNAs) play key roles in the development and healing of DFUs. miRNAs are a class of short noncoding RNA molecules that regulate gene expression to affect cellular functions and physiological processes. miRNAs may be involved in the development of DFUs by regulating cell growth, proliferation, differentiation and apoptosis. miRNAs can also participate in the healing and recovery of DFUs by regulating key steps, such as inflammation, angiogenesis, cell migration and proliferation, tissue repair and matrix remodeling. Therefore, altering the pathological processes of diabetic foot by modulating the expression of miRNAs could improve the recovery and treatment outcomes of patients. This review provides new insights and perspectives for the treatment of DFUs by summarizing the roles of miRNAs in the development and healing of DFUs and the mechanisms.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111858"},"PeriodicalIF":6.1,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016882272400768X/pdfft?md5=146c9c12e1c1ed205fa3ee8019082cae&pid=1-s2.0-S016882272400768X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142244245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early life socioeconomic inequalities and type 2 diabetes incidence: Longitudinal analyses in the Maastricht study","authors":"Rachelle Meisters ,&nbsp;Annemarie Koster ,&nbsp;Jeroen Albers ,&nbsp;Bengisu Sezer ,&nbsp;Marleen M.J. van Greevenbroek ,&nbsp;Bastiaan E. de Galan ,&nbsp;Hans Bosma","doi":"10.1016/j.diabres.2024.111855","DOIUrl":"10.1016/j.diabres.2024.111855","url":null,"abstract":"<div><h3>Aim</h3><p>Type 2 diabetes (T2D) is a common chronic disease that disproportionally affects groups with a low socioeconomic position (SEP). This study aimed to examine associations between childhood SEP and incident T2D, independent of adult SEP.</p></div><div><h3>Methods</h3><p>Longitudinal data from The Maastricht Study were used (N=6,727, 55.2 % female, mean (SD) age 58.7(8.7) years). Childhood SEP was determined by asking for the highest completed educational level for the father and mother and childhood income inadequacy. Adult SEP was determined by highest completed educational level, equivalent household income, and occupational position. Incident T2D was self-reported yearly (up to 12 years of follow-up). Associations were studied with Cox regression analyses.</p></div><div><h3>Results</h3><p>In participants without T2D at baseline, 3.7% reported incident T2D over 8.2 (median) years of follow-up. Incident T2D was most common in people with low childhood and adult SEP and lowest in those with high childhood and adult SEP (1.7 vs. 7.5 per 1,000 person years). The association between childhood SEP and incident T2D was mainly explained by adult SEP, except for childhood income inadequacy which was independently associated with incident T2D.</p></div><div><h3>Conclusion</h3><p>Socioeconomic inequalities in childhood and adulthood are risk factors for incident T2D. More attention is needed to reduce childhood poverty and improve adult SEP to reduce the T2D risk.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111855"},"PeriodicalIF":6.1,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168822724007654/pdfft?md5=1276e53380f91467ff70c2873815fa9d&pid=1-s2.0-S0168822724007654-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pathophysiological characteristics of subjects with intermediate hyperglycemia and type 2 diabetes identified by 1-hour plasma glucose during an oral glucose tolerance test","authors":"Chiara M.A. Cefalo ,&nbsp;Alessia Riccio ,&nbsp;Teresa Vanessa Fiorentino ,&nbsp;Elena Succurro ,&nbsp;Gaia Chiara Mannino ,&nbsp;Maria Perticone ,&nbsp;Angela Sciacqua ,&nbsp;Francesco Andreozzi ,&nbsp;Giorgio Sesti","doi":"10.1016/j.diabres.2024.111856","DOIUrl":"10.1016/j.diabres.2024.111856","url":null,"abstract":"<div><h3>Aims</h3><p>The International Diabetes Federation (IDF) has recently recommended determination of 1-hour plasma glucose (1-hPG) during an oral glucose tolerance test (OGTT) to diagnose intermediate hyperglycemia (IH) and type 2 diabetes (T2DM). Herein, we investigated the cardiometabolic characteristics of individuals with IH and T2DM according to IDF criteria<strong>.</strong></p></div><div><h3>Methods</h3><p>We studied 3086 individuals stratified on the basis of fasting, 1-hPG and 2-hPG in four groups: 1) normal glucose tolerance (NGT), 2) isolated impaired fasting glucose (iIFG,), 3) IH (fasting glucose &lt; 126 mg/dL, 1-hPG 155–208 mg/dL, and/or 2-hPG 140–199 mg/dL, and 4) newly diagnosed T2DM (fasting glucose, 1-hPG and/or 2-hPG≥126 mg/dL, 209 mg/dL and 200 mg/dL, respectively).</p></div><div><h3>Results</h3><p>Individuals with IH and T2DM exhibited higher adiposity, blood pressure, uric acid, a worse lipid and inflammatory profile and a progressive reduction in Matsuda index of insulin sensitivity, insulinogenic index, and disposition index as compared to the NGT group. Moreover, individuals with IH and T2DM exhibited lower Matsuda, insulinogenic, and disposition indexes as compared to the iIFG group.</p></div><div><h3>Conclusions</h3><p>1-h PG-based criteria for diagnosis of IH and diabetes identify individuals having an unfavorable cardiometabolic risk profile with a progressive reduction in insulin sensitivity associated with impaired β cell function.</p></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"217 ","pages":"Article 111856"},"PeriodicalIF":6.1,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142244246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}