Diabetes duration and types of diabetes treatment in data-driven clusters of patients with diabetes

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28 2月 2026

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Author : 伤口世界

Diabetes duration and types of diabetes treatment in data-driven clusters of patients with diabetes

This article is excerpted from the 《 Frontiers in Endocrinology》 by Wound World

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伤口世界

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Relationship between body adiposity and glycemic control in children and adolescents with type 1 diabetes
One year after gestational diabetes: metabolic changes and predictors of postpartum dysglycaemia
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Relationship between body adiposity and glycemic control in children and adolescents with type 1 diabetes 2026-05-07 00:00

Claudio Maffeis1 · Ilaria Fierri1 · Elisa Morotti1 · Erika Caiazza1 · Quincy Pedranzini1 · Marco Marigliano1 · Claudia Piona1

Received: 20 October 2025 / Accepted: 6 January 2026 / Published online: 31 January 2026 © The Author(s) 2026

Abstract

Aims To investigate the relationship between body adiposity and glycemic control in children and adolescents with type 1 diabetes (T1D).

Methods This cross-sectional study included 364 children and adolescents aged 6–18 years with T1D. Anthropometric indi-ces [BMI, BMI Z-score, waist-to-height ratio (WHtR)] and body composition [fat mass (FM), FM%, fat mass index (FMI)], assessed using bioelectrical impedance analysis, were obtained. Hemoglobin A1c and glucose sensor metrics, including time in range (TIR), were used to assess glycemic control. Associations between variables were analyzed using Spearman’s correlation. Logistic regression models were run to identify independent predictors of HbA1c<7.0% and TIR>70%, with FMI, WHtR, total daily insulin dose per kg (TDD), treatment modalities, sex, age, diabetes duration, and pubertal stage as independent variables.

Results Adiposity measures (FMI, FM%, and WHtR) were positively associated with HbA1c and negatively with TIR in both sexes. Logistic regression showed that HbA1c<7% and TIR>70% were significantly predicted by FMI [OR(95%CI): 0.822(0.704–0.960), p=0.013, and 0.807(0.681–0.955), p=0.012, respectively] and WHtR(x100) [OR(95%CI): 0.927(0.874– 0.983), p=0.013, and 0.923(0.866–0.985), p=0.015, respectively], independently of TDD, sex, treatment modalities and the other independent variables.

Conclusions Body adiposity negatively impacts glycemic control in children and adolescents with T1D, independent of sex and insulin treatment modalities. Despite technological advances in diabetes care, excess adiposity is emerging as a key modifiable factor associated with poorer glycemic outcomes and, consequently, poorer long-term health in children and adolescents with T1D.

Keywords Type 1 diabetes · Children · Body mass index · Adiposity · HbA1c · TIR

Abbreviations

ADA American Diabetes Association

AID Automated insulin delivery

BMI Body mass index

BP blood pressure

CGM Continuous glucose monitoring

Communicated by Annunziata Lapolla

Marco Marigliano

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1 Section of Pediatric Diabetes and Metabolism, Department of Surgery, Dentistry, Pediatrics, and Gynecology, University and Azienda Ospedaliera Universitaria Integrata of Verona, Piazzale Stefani, 1, Verona 37126, Italy

CVRFs Cardiovascular risk factors

FM Fat mass

FMI Fat mass index

GRI Glycemia risk index

HDL High-density lipoprotein cholesterol

IP Insulin Pump

ISPAD International Society for Pediatric and Adoles

cent Diabetes

LDL Low-density lipoprotein

MDI Multiple daily injection

PwD People with type 1 diabetes

TAR Time above range

TBR Time below range

TDD Total daily dose/kg of body weight

TG Triglycerides (TG)

TIR Time in range

T1D Type 1 diabetes

WC Waist circumference

WHtR Waist-to-height ratio
One year after gestational diabetes: metabolic changes and predictors of postpartum dysglycaemia 2026-05-06 00:00

Alessia Gaglio1 · Yana Pigotskaya1 · Gabriele Rossi2 · Marco Mirani3 · Federico Giacchetti5 · Valeria Grancini1 · Valeria Maggi2 · Giovanna Mantovani1,4 · Irene Cetin2,4 · Emanuela Orsi5 · Veronica Resi1

Received: 21 November 2025 / Accepted: 17 January 2026

© The Author(s) 2026

Abstract

Background Women with previous gestational diabetes mellitus (GDM) are at high risk of developing type 2 diabetes mel-litus (T2DM). Although early postpartum screening is recommended, metabolic changes occurring during the first year remain poorly characterized, and Italian guidelines do not include assessment at this time point.

Aim To evaluate glycaemic and metabolic changes one year after delivery in women with previous GDM and identify clini-cal and lifestyle predictors of postpartum glucose impairment.

Methods A cohort of 134 women with prior GDM was assessed at 6–12 weeks (T0) and one year postpartum (T1). Anthro-pometric, biochemical, nutritional, lifestyle, and quality-of-life parameters were collected. Dietary habits were evaluated using a 3-day food diary and the PREDIMED questionnaire; physical activity was assessed using the International Physical Activity Questionnaire (IPAQ). Logistic regression models were used to identify predictors of altered OGTT at T1.

Results At baseline, 32.9% of women showed altered OGTT; this increased to 38.8% at one year, while T2DM prevalence rose from 2.2 to 5.2%. Insulin therapy during pregnancy was the only independent predictor of dysglycaemia at T1 (OR 3.5, 95% CI 1.28–9.50, p=0.015). Women with altered OGTT reported lower SF-36 scores in the domains “role limitations due to physical health” (p=0.016) and “health change” (p=0.030). Breastfeeding was associated with more favourable glucose outcomes (p=0.009).

Conclusions One-year follow-up after GDM reveals early metabolic and psychosocial differences not detectable in the early postpartum period. Insulin therapy during pregnancy strongly predicts glucose impairment, highlighting the need for extended postpartum surveillance and targeted lifestyle interventions.

Keywords Gestational diabetes · Postpartum follow-up · Impaired glucose tolerance · Lifestyle · Breastfeeding

Communicated by Annunziata Lapolla.

Alessia Gaglio

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1 Endocrinology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milan, Italy

2 Obstetric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

3 Endocrinology, Diabetology and Andrology Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy

4 Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy

5 Diabetology and Nutritional Unit, Department of Specialist Medicine, ASST Santi Paolo e Carlo, Milan, Italy
Metabolic challenges in rheumatoid arthritis: a translational overview from pathogenesis to patient care 2026-04-30 00:00

Sara Ferrigno1 · Eneida Çela1 · Mauro Fatica1,2 · Benedetta Monosi1 · Arianna D’Antonio1 · Paola Conigliaro1 · Marina Cardellini3,4 · Susanna Longo3,4 · Massimo Federici3,4 · Maria Sole Chimenti1

Received: 20 February 2026 / Accepted: 26 March 2026 © The Author(s) 2026

Abstract

Rheumatoid arthritis (RA) is an inflammatory disease characterized by a higher burden of cardiovascular and metabolic diseases than in the general population. Altered lipid and glucose metabolic pathways are widely observed, primarily due to chronic inflammation. However, metabolic dysfunction may also affect RA pathogenesis, further enhancing immune cell activation and joint damage. Glucose and lipid alterations observed in RA help define the comorbidity burden of this disease, significantly affecting disease activity and prognosis. The aim of the present review is to describe the role of metabolic dysfunctions in RA and to examine how disease activity and treatments can influence these conditions. We also summarized the main management strategies based on current literature and developed a cardiometabolic monitoring algorithm across different clinical settings to support daily patient care of these patients.

Keywords Rheumatoid arthritis · Glucose metabolism · Lipid metabolism · Atherogenesis · Inflammation · Immune-metabolism · Cardiovascular risk

Sara Ferrigno and Eneida Çela contributed equally to this manuscript

Communicated by Salvatore Corrao, M.D

Sara Ferrigno

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1 Rheumatology, Allergology and Clinical Immunology, Department of Systems Medicine, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy

2 Academic Rheumatology Unit, Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, Via Giovanni Paolo II, C/da Tappino, Campobasso 86100, Italy

3 Department of Systems Medicine, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy

4 Center for Atherosclerosis, Policlinico Tor Vergata, Viale Oxford 81, Rome 00133, Italy

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主任医师、教授、博导，南方医科大学第三附属医院（广东省骨科医院）院长

Diabetes duration and types of diabetes treatment in data-driven clusters of patients with diabetes

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Diabetes duration and types of diabetes treatment in data-driven clusters of patients with diabetes

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