UNASSIGNED: As the world population recovers from the COVID-19 infection, a series of acute sequelae emerge including new incident diabetes. However, the association between COVID-19 infection and new incident diabetes is not fully understood. We purpose to determine the risk of new incident diabetes after COVID-19 infection.
UNASSIGNED: PubMed, Embase, and Cochrane Library were used as databases to search for cohort studies published from database inception to February 4, 2024. Two reviewers independently conducted the study screening, data extraction, and risk of bias assessment. A random-effects model was adopted to pool the hazard ratio (HR) with corresponding 95% confidence intervals (CI). Subgroup analysis was conducted to explore the potential influencing factors.
UNASSIGNED: A total of 20 cohort studies with over 60 million individuals were included. The pooling analysis illustrates the association between COVID-19 infection and an increased risk of new incident diabetes (HR = 1.46; 95% CI: 1.38-1.55). In subgroup analysis, the risk of type 1 diabetes was HR=1.44 (95% CI: 1.13-1.82), and type 2 diabetes was HR=1.47 (95% CI: 1.36-1.59). A slightly higher risk of diabetes was found in males (HR=1.37; 95% CI: 1.30-1.45) than in females (HR=1.29; 95% CI: 1.22-1.365). The risk of incident diabetes is associated with hospitalization: non-hospitalized patients have an HR of 1.16 (95% CI: 1.07-1.26), normal hospitalized patients have an HR of 2.15 (95% CI: 1.33-3.49), and patients receiving intensive care have the highest HR of 2.88 (95% CI: 1.73-4.79).
UNASSIGNED: COVID-19 infection is associated with an elevated risk of new incident diabetes. Patients ever infected with COVID-19 should be recognized as a high-risk population with diabetes.
UNASSIGNED: https://www.crd.york.ac.uk/prospero, identifier CRD42024522050.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but life-threatening skin lesion triggered by hypersensitive drug reaction. They are characterized by extensive epidermal necrosis and skin exfoliation. Fulminant type 1 diabetes mellitus (FT1DM) is featured by a rapid-onset of hyperglycemia with ketoacidosis due to severely destroyed β-cell function. Fulminant type 1 diabetes mellitus as a sequela of SJS/TEN has rarely been reported.
METHODS: We present a 73-year-old female patient who developed SJS/TEN skin allergic reaction after taking carbamazepine and phenytoin for 35 days. Then, hyperglycemia and diabetic ketoacidosis occurred 20 days after discontinuation of antiepileptic drugs. A very low serum C-peptide level (8.79 pmol/l) and a near-normal glycosylated hemoglobin level met the diagnostic criteria for fulminant T1DM. Intravenous immunoglobulin (IVIG) and insulin were promptly administered, and the patient recovered finally.
CONCLUSIONS: This rare case indicates that monitoring blood glucose is necessary in SJS/TEN drug reaction, and comprehensive therapy with rehydration, insulin, antibiotics, and IVIG may improve the prognosis.

OBJECTIVE: Human recombinant insulin is currently the only therapy for children and adolescents with type 1 diabetes (T1D), although not always efficient for the glycemic control of these individuals. The interrelation between the gut microbiome and the glycemic control of apparently healthy populations, as well as various populations with diabetes, is undeniable. Probiotics are biotherapeutics that deliver active components to various targets, primarily the gastrointestinal tract. This systematic review and meta-analysis examined the effect of the administration of probiotics on the glycemic control of pediatric and adolescent individuals with T1D.
METHODS: Randomized controlled trials employing the administration of probiotics in children and adolescents with T1D (with ≥10 individuals per treatment arm), written in English, providing parameters of glycemic control, such as mean glucose concentrations and glycosylated hemoglobin (HbA1c), were deemed eligible.
RESULTS: The search strategy resulted in six papers with contradictory findings. Ultimately, five studies of acceptable quality, comprising 388 children and adolescents with T1D, were included in the meta-analysis. Employing a random and fixed effects model revealed statistically significant negative effect sizes of probiotics on the glycemic control of those individuals, i.e., higher concentrations of glucose and HbA1c than controls.
CONCLUSIONS: Children and adolescents with T1D who received probiotics demonstrated worse glycemic control than controls after the intervention. Adequately powered studies, with extended follow-up periods, along with monitoring of compliance and employing the proper strains, are required to unravel the mechanisms of action and the relative effects of probiotics, particularly concerning diabetes-related complications and metabolic outcomes.

There is no safe and effective prevention for insulin-dependent diabetes (IDDM) mellitus, which makes it highly dependent on its treatment. This systematic review with meta-analyses of randomized clinical trials investigated the overall effects of dietary supplements of vitamins, minerals, trace elements, and non-essential compounds with antioxidant properties, fatty acids, and amino acids in IDDM. Searches of MEDLINE, Embase, CENTRAL, LILACS, The Grey Literature Report, and ClinicaTrials.gov, and citations from previous reviews were used to identify reports published through July 2023. The Risk of Bias 2 (RoB2) tool was used to analyze the risk of bias and GRADE was used to assess the quality of the results. Fifty-eight studies (n=3,044) were included in qualitative analyses and seventeen (n=723) in meta-analyses. Qualitative analyses showed few positive effects on some metabolic function markers, such as endothelial and renal function and lipid profile. Meta-analyses showed a positive effect of omega-3 on glycated hemoglobin (HbA1c) (RMD=-0.33; 95%CI: -0.53, -0.12, P=0.002; I2=0%; GRADE: low quality; 4 studies) and of vitamin D on fasting C-peptide (FCP) (RMD=0.05; 95%CI: 0.01, 0.9, P=0.023; I2=0%; GRADE: very low quality; 4 studies). Most studies showed bias concern or high risk of bias. A recommendation for dietary supplementation in IDDM cannot be made because of the few positive results within different interventions and markers, the serious risk of bias in the included studies, and the low quality of evidence from meta-analyses. The positive result of vitamin D on FCP is preliminary, requiring further investigation.

OBJECTIVE: The evidence about the acceptability and effectiveness of innovative paediatric models of care for Type 1 diabetes is limited. To address this gap, we synthesised literature on implemented models of care, model components, outcomes, and determinants of implementation and sustainability.
METHODS: A systematic review was conducted and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Database searches of Medline, CINAHL, EMBASE and Scopus were conducted. Empirical studies focused on Type 1 diabetes paediatric models of care, published from 2010 to 2022 in English were included.
RESULTS: Nineteen extant studies reported on models and their associations with health and psychosocial outcomes, patient engagement with healthcare, and healthcare costs. Thirteen studies described multidisciplinary teamwork, education and capacity building that supported self-care. Four studies involved shared decision making between providers and patients, and two discussed outreach support where technology was an enabler. Fourteen studies reported improvements in health outcomes (e.g. glycaemic control), mostly for models that included multidisciplinary teams, education, and capacity building (11 studies), outreach support or shared care (3 studies). Four studies reported improvements in quality of life, three reported increased satisfaction for patients and carers and, and one reported improved communication. Four of five studies describing shared care and decision-making reported improvements in quality of life, support and motivation. Outreach models reported no negative outcomes, however, accessing some models was limited by technological and cost barriers. Eight studies reported on model sustainability, but only half reported implementation determinants; none reported applying a theoretical framework to guide their research.
CONCLUSIONS: Some health and psychosocial benefits were associated with newer models. To address knowledge gaps about implementation determinants and model sustainability, longitudinal studies are needed to inform future adoption of innovative models of care for children with Type 1 diabetes.

BACKGROUND: Continuous glucose monitoring (CGM) devices allow for 24-h real-time measurement of interstitial glucose levels and have changed the interaction between people with diabetes and their health care providers. The large amount of data generated by CGM can be analyzed and evaluated using a set of standardized parameters, collectively named glucometrics. This review aims to provide a summary of the existing evidence on the use of glucometrics data and its impact on clinical practice based on published studies involving adults and children with type 1 diabetes (T1D) in Spain.
METHODS: The PubMed and MEDES (Spanish Medical literature) databases were searched covering the years 2018-2022 and including clinical and observational studies, consensus guidelines, and meta-analyses on CGM and glucometrics conducted in Spain.
RESULTS: A total of 16 observational studies were found on the use of CGM in Spain, which have shown that cases of severe hypoglycemia in children with T1D were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Real-world data from Spain shows that CGM is associated with improved glycemic markers (increased time in range, reduced time below and above range, and glycemic variability), and that there is a relationship between glycemic variability and hypoglycemia. Also, CGM and analysis of glucometrics proved highly useful during the COVID-19 pandemic. New glucometrics, such as the glycemic risk index, or new mathematical approaches to the analysis of CGM-derived glucose data, such as \"glucodensities,\" could help patients to achieve better glycemic control in the future.
CONCLUSIONS: By using glucometrics in clinical practice, clinicians can better assess glycemic control and a patient\'s individual response to treatment.
Continuous glucose monitoring (CGM) devices are used to monitor glucose levels in real time over 24 h. This has changed the way people with diabetes and their health care providers interact. These devices produce a large amount of data that can be analyzed and evaluated using standardized parameters called glucometrics, which include the time a patient’s glucose is in range, below range, and above range, and how much it varies over 24 h. Clinicians can use these data to better assess glycemic control and a patient\'s individual response to treatment. In this article, we summarize evidence from published studies involving adults and children with type 1 diabetes in Spain to look at how the use of these data has affected clinical practice. Studies have shown that cases of severe low blood glucose in children with diabetes were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Data from clinical practice in Spain show that CGM is associated with improved blood glucose markers. Many studies analyzed these data during the COVID-19 pandemic and showed that CGM and analysis of glucometrics were highly useful during this time. New glucometrics and approaches to the analysis of data from CGM could help patients achieve better blood glucose control.

Pancreas transplant (PTx) is the only treatment that establishes normal glucose levels for patients diagnosed with diabetes types 1 and 2. The paper aims to review and analyze graft survival, patient survival, and the impact on diabetic complications. We describe that the graft survival was 82-98% at 1 year, 90% at 5 years, and 75-54% at 10 years for simultaneous pancreas-kidney recipient; 71% pancreas after kidney (PAK), and 62% PTx alone at 1 year. Patient survival: At 1 year for recipients was 96.9% simultaneous pancreas-kidney transplantation (SPK); for PAK transplantation recipients, 96.3%; and for PTx alone recipients, 98.3%. In general, the pancreas transplantation improves and reverses diabetic complications. Finally, the pancreatic transplant is a morbid procedure and emerges as a significant alternative in diabetes management, directly competing with conventional insulin therapies. Results so far suggest that the most effective transplant model is the SPK. While more patients could benefit from this procedure, surgical complications and the need for immunosuppression pose significant challenges.
El trasplante de páncreas es el único tratamiento que estabiliza los niveles normales de glucosa en los pacientes diagnosticados con diabetes tipo 1 o tipo 2. En esta revisión se analizan la supervivencia del injerto, la supervivencia del paciente y el impacto en las complicaciones diabéticas. Se describe la supervivencia del injerto: 82-98% al año para los receptores de trasplante simultáneo de páncreas y riñón, 71% para trasplante páncreas después de riñón y 62% para trasplante de páncreas solitario al año. Supervivencia de los pacientes a 1 año: 96.9% para los receptores de trasplante simultáneo de páncreas y riñón, 96.3% para los receptores de trasplante de páncreas después de riñón y 98.3% para los receptores de páncreas solitario. En general, el trasplante de páncreas mejora y revierte las complicaciones diabéticas. Finalmente, el trasplante de páncreas, un procedimiento mórbido, surge como una alternativa significativa en el manejo de la diabetes, compitiendo directamente con las terapias convencionales de insulina. Hasta ahora, los resultados indican que el modelo de trasplante más efectivo es el simultáneo de páncreas y riñón. Aunque más pacientes podrían beneficiarse de este procedimiento, las complicaciones quirúrgicas y la necesidad de inmunosupresión plantean desafíos significativos.

BACKGROUND: Type 1 Diabetes (T1D) affects over 9 million worldwide and necessitates meticulous self-management for blood glucose (BG) control. Utilizing BG prediction technology allows for increased BG control and a reduction in the diabetes burden caused by self-management requirements. This paper reviews BG prediction models in T1D, which include nutritional components.
METHODS: A systematic search, utilizing the PRISMA guidelines, identified articles focusing on BG prediction algorithms for T1D that incorporate nutritional variables. Eligible studies were screened and analyzed for model type, inclusion of additional aspects in the model, prediction horizon, patient population, inputs, and accuracy.
RESULTS: The study categorizes 138 blood glucose prediction models into data-driven (54%), physiological (14%), and hybrid (33%) types. Prediction horizons of ≤30 min are used in 36% of models, 31-60 min in 34%, 61-90 min in 11%, 91-120 min in 10%, and >120 min in 9%. Neural networks are the most used data-driven technique (47%), and simple carbohydrate intake is commonly included in models (data-driven: 72%, physiological: 52%, hybrid: 67%). Real or free-living data are predominantly used (83%).
CONCLUSIONS: The primary goal of blood glucose prediction in T1D is to enable informed decisions and maintain safe BG levels, considering the impact of all nutrients for meal planning and clinical relevance.

BACKGROUND: Protein influences acute postprandial glucose and insulin responses, but the effects of dose, protein type, and health status are unknown.
OBJECTIVE: We aimed to determine the acute effect of adding protein to carbohydrate on postprandial responses and identify effect modifiers.
METHODS: We searched MEDLINE, EMBASE, and Cochrane databases through 30 July, 2023 for acute, crossover trials comparing acute postprandial responses elicited by carbohydrate-containing test meals with and without added protein in adults without diabetes or with type 2 (T2DM) or type 1 (T1DM) diabetes mellitus. Group data were pooled separately using generic inverse variance with random-effects models and expressed as the ratio of means with 95% confidence interval. Risk of bias and certainty of evidence (Grading of Recommendations Assessment, Development, and Evaluation) were assessed.
RESULTS: In 154 trial comparisons of animal, dairy, and plant proteins (without diabetes, n = 22, 67, 32, respectively; T2DM, n = 14, 16, 3, respectively), each gram protein per gram available carbohydrate (g/g) reduced the glucose area under the curve (AUC) less in adults with T2DM than in those without diabetes (-10% compared with -50%, P < 0.05) but increased the insulin AUC similarly (+76% compared with +56%). In subjects without diabetes, each g/g of dairy and plant protein reduced glucose AUC by 52% and 55%, respectively, and increased the insulin AUC by 64% and 45%, respectively (all P < 0.05). Animal proteins significantly reduced the glucose AUC by 31% and increased the insulin AUC by 37% (pooled effects) but without a significant dose-response. In adults with T2DM, animal protein reduced the glucose AUC by 13% and increased the insulin AUC by 105%, with no significant dose-response. Dairy protein reduced the glucose AUC by 18% (no dose-response), but each g/g increased the insulin AUC by 34% (P < 0.05). In adults with T1DM, protein increased the glucose AUC by 40% (P < 0.05, n = 5). Data source (reported AUC compared with calculated AUC) and study methodology quality significantly modified some outcomes and contributed to high between-study heterogeneity.
CONCLUSIONS: In people without diabetes, adding dairy or plant protein to a carbohydrate-containing meal elicits physiologically significant reductions in glucose AUC and increases insulin AUC. Animal protein may slightly reduce the glucose AUC and may increase the insulin AUC. In people with T2DM, protein may not have such large and consistent effects. Further research is needed to determine if the effects of protein differ by health status and protein source. This study was registered at PROSPERO as CRD42022322090.

Diabetes mellitus (DM) poses a significant challenge to global health, with its prevalence projected to rise dramatically by 2045. This narrative review explores the bidirectional relationship between periodontitis (PD) and type 1 diabetes mellitus (T1DM), focusing on cellular and molecular mechanisms derived from the interplay between oral microbiota and the host immune response. A comprehensive search of studies published between 2008 and 2023 was conducted to elucidate the association between these two diseases. Preclinical and clinical evidence suggests a bidirectional relationship, with individuals with T1DM exhibiting heightened susceptibility to periodontitis, and vice versa. The review includes recent findings from human clinical studies, revealing variations in oral microbiota composition in T1DM patients, including increases in certain pathogenic species such as Porphyromonas gingivalis, Prevotella intermedia, and Aggregatibacter actinomycetemcomitans, along with shifts in microbial diversity and abundance. Molecular mechanisms underlying this association involve oxidative stress and dysregulated host immune responses, mediated by inflammatory cytokines such as IL-6, IL-8, and MMPs. Furthermore, disruptions in bone turnover markers, such as RANKL and OPG, contribute to periodontal complications in T1DM patients. While preventive measures to manage periodontal complications in T1DM patients may improve overall health outcomes, further research is needed to understand the intricate interactions between oral microbiota, host response, periodontal disease, and systemic health in this population.