Diabetes Research and Clinical Practice
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#1Aihua Wang (Capital Medical University)H-Index: 1
#2Huilin Tang (UF: University of Florida)H-Index: 23
Last. Xin Feng (Capital Medical University)H-Index: 1
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Abstract null null Aims null This network meta-analysis aimed to evaluate the asthma risk associated with dipeptidyl peptidase (DPP)-4 inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), and sodium-glucose co-transporter (SGLT) 2 inhibitors. null null null Methods null Electronic databases were systematically searched up to March 2021 to include placebo-controlled cardiovascular (or cardiorenal) outcome trials that reported the asthma incidents in patients taking DPP-4 inhibitors, ...
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#1Hye-Min ParkH-Index: 3
#2Hye Sun Lee (Yonsei University)H-Index: 34
Last. Jun-Hyuk Lee (Eulji University)H-Index: 1
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Abstract null null Aims null Insulin resistance is an independent risk factor for developing type 2 diabetes. Therefore, this study compared the predictability of the triglyceride–glucose (TyG) index and the homeostatic model assessment of insulin resistance (HOMA-IR) for the prevalence and incidence of type 2 diabetes. null null null Methods null We analyzed data from 9730 adults aged 40–69 years at baseline and 7783 participants without diabetes who were followed up in the Korean Genome and Ep...
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#1Kwang Seob Lee (Yonsei University)
#2John Hoon Rim (Yonsei University)H-Index: 12
Last. Jeong-Ho Kim (Yonsei University)H-Index: 19
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AIMS Obesity is the most common risk factor for type 2 diabetes. However, not all obese individuals develop diabetes. In the era of precision medicine, metabolomics may reveal the fundamental metabolic status of an individual. Our aim was to assess the association of metabolites with incident type 2 diabetes in obese individuals using Korean Genome and Epidemiology Cohort Study. METHODS Using 12 years of metabolomic data from 2,580 individuals, we performed a metabolomic study to define metaboli...
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#1Patricia Dualib (UNIFESP: Federal University of São Paulo)H-Index: 5
#2Juliana Ogassavara (UNIFESP: Federal University of São Paulo)
Last. Bianca de Almeida Pititto (UNIFESP: Federal University of São Paulo)H-Index: 1
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BACKGROUND Gestational Diabetes Mellitus (GDM) is one of the most prevalent complications of pregnancy and can cause adverse maternal and fetal outcomes. The maternal gut microbiota is involved in several metabolic functions, but it is not yet known its role in GDM physiopathology. This study aims to review the role of gut microbiota in pregnancies that evolved with GDM. METHODS Systematic search of the PubMed, Embase, and Scopus databases was performed to identify articles published until 18th ...
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#1Flavio De Maio (UCSC: Catholic University of the Sacred Heart)H-Index: 13
#2Cristian E. Boru (Sapienza University of Rome)H-Index: 10
Last. Maurizio Sanguinetti (UCSC: Catholic University of the Sacred Heart)H-Index: 77
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Introduction null gut microbiota (GM) seems to be involved in the pathophysiology and progression of both metabolic syndrome (MS) and obesity. The aim was to investigate GM's composition in patients with severe obesity, candidates for bariatric/metabolic surgery BMS. null Materials and methods null multicentre, prospective, cohort study, enrolling 84 patients with BMI 40-55kg/m2, divided bymetabolic status (MS) inhealthy(group A), pre-MS (B), or MS (C). null Results null no differences were foun...
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#1Fu-Chih Hsiao (CGU: Chang Gung University)H-Index: 4
#2Chia-Pin Lin (CGU: Chang Gung University)H-Index: 4
Last. Pao-Hsien Chu (CGU: Chang Gung University)H-Index: 20
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Abstract null null Aims null To compare the risk of incident major adverse limb events (MALEs) between patients with type 2 diabetes (T2DM) who initiated glucagon-like peptide-1 receptor agonists (GLP-1 RAs) or sodium-glucose cotransporter-2 Inhibitors (SGLT2Is). null null null Methods null T2DM patients with prescriptions of GLP-1 RAs or SGLT2Is between January 1, 2016 and December 31, 2018 were retrospectively identified from a multi-institutional database. We used inverse probability of treat...
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#1Tran Quang Binh (NIN: National Institute of Nutrition, Hyderabad)H-Index: 8
#2Pham Tran Phuong (NIN: National Institute of Nutrition, Hyderabad)H-Index: 6
Last. Le Danh Tuyen (NIN: National Institute of Nutrition, Hyderabad)H-Index: 1
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AIMS To sought for an easily applicable nomogram for detecting individuals at high risk of undiagnosed type 2 diabetes. METHODS The development cohort included 2542 participants recruited randomly from a rural population in 2011.The glycemic status of subjects was determined using the fasting plasma glucose test and the oral glucose tolerance test. The Bayesian Model Average approach was used to search for a parsimonious model with minimum number of predictor and maximum discriminatory power. Th...
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#1Eric H. M. Tang (Li Ka Shing Faculty of Medicine, University of Hong Kong)H-Index: 4
#2Carlos K. H. Wong (Li Ka Shing Faculty of Medicine, University of Hong Kong)H-Index: 25
Last. Bernard M.Y. Cheung (Li Ka Shing Faculty of Medicine, University of Hong Kong)H-Index: 60
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Abstract null null Aims null To compare cardio-renal outcomes and incurred direct medical costs of patients initiating sodium glucose cotransporter-2 inhibitors (SGLT2i) versus glucagon-like peptide-1 receptor agonists (GLP-1RA). null null null Methods null A population-based cohort of patients with type 2 diabetes was identified from Hong Kong Hospital Authority. Patients who were free from cardiovascular and end-stage renal diseases at baseline, and newly treated with SGLT2i (n = 2,541) or GLP...
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#1Shanpin Fanchiang (Charles R. Drew University of Medicine and Science)
#2Matthew F. Bouchonville (UNM: University of New Mexico)H-Index: 7
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#1Sergio Di Molfetta (University of Bari)H-Index: 4
#2Emanuele Bosi (UniSR: Vita-Salute San Raffaele University)H-Index: 59
Last. Francesco Giorgino (University of Bari)H-Index: 61
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Abstract null null Aims null To investigate the relationship between single therapeutic interventions and indicators of glycemic control in the PRISMA trial, a large study comparing the effects of intensive structured SMBG (ISM) vs. active control (AC) in non-insulin-treated T2D. null null null Methods null Information was collected at four time points, corresponding to months 3, 6, 9, and 12 and visits 2, 3, 4, and 5, respectively. Data on therapeutic interventions, HbA1c levels and the number ...
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Top fields of study
Endocrinology
Type 2 diabetes
Insulin
Diabetes mellitus
Medicine