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Diabetes Mellitus and Oral Health
Diabetes Mellitus and Oral Health: An Interprofessional Approach is a practical tool for dentists and dental hygienists providing oral health care to patients with diabetes mellitus. Firmly grounded in the latest evidence, the book addresses medical considerations, dental considerations, and case scenarios from clinical practice in three easily accessible sections. The first section on medical considerations reviews the definition of diabetes and discusses underlying pathologic mechanisms, classification, diagnosis, and medical complications of the disease. It also promotes the comprehensive management of patients with diabetes in the dental office, with a thorough discussion of lifestyle changes and medications used to treat diabetes. The second section on dental considerations provides guidance on how treat patients with diabetes. Oral complications will be covered in detail, with a focus on management and treatment strategies that can be used in the dental office. The third section includes multiple case studies illustrating common complications and how-to instruction on appropriate patient management. Ideal for all members of the dental team, Diabetes Mellitus and Oral Health is an essential tool for providing optimal clinical care to patients with diabetes.
eBook
Traveling with sugar : chronicles of a global epidemic
\"Traveling with Sugar reframes the rising diabetes epidemic as part of a five-hundred-year-old global history of sweetness and power. Amid eerie injuries, changing bodies, amputated limbs, and untimely deaths, many people across the Caribbean and Central America simply call the affliction \"sugar\"--Or, as some in Garifuna Belize say, \"traveling with sugar.\" A decade in the making, this book reveals a series of crâonicas--a word meaning both slow-moving story and slow-moving disease. It profiles the careful work of those \"still fighting it,\" as they grapple with unequal material infrastructures and unsettling dilemmas. Guiding us into the surprising landscapes of global diabetes, these individuals speak back to science and policy misrecognitions that have prematurely cast their lost limbs and deaths as normal. Facing a new incarnation of blood sugar, they practice their arts of maintenance and repair, illuminating ongoing struggles to survive and remake larger systems of food, land, technology, and medicine\"--Provided by publisher.
Book
Obstetric and perinatal outcomes in pregnancies complicated by diabetes, and control pregnancies, in Kronoberg, Sweden
Background
Diabetes during pregnancy is an increasingly common metabolic disorder, associated with significantly increased risks for both mother and child. Aim of this study was to compare maternal and perinatal outcomes in women with pregestational (PDM) type 1 (T1DM), type 2 diabetes (T2DM), gestational diabetes mellitus (GDM) and compare these to pregnancies not complicated with diabetes. This study also evaluated a specifically organized care-model mostly involving specialist diabetes nurses.
Methods
Retrospective population-based records review 2009–2012. Rates of maternal (preeclampsia, pre-term delivery, cesarean section (CS)) and fetal outcomes (large for gestational age (LGA), macrosomia, congenital malformations/intrauterine death) were assessed and potential predisposing or contributing factors as maternal age, ethnicity, obesity, weight gain, parity, HbA1c levels, insulin types and doses.
Results
Among 280 pregnancies 48 were PDM, 97 GDM and 135 without diabetes. Within the group with diabetes, early-pregnancy BMI was higher (
p
= 0.0001), pregnancy weight gain lower (11.1 ± 6.7 kg vs 13.1 ± 7.1 kg,
p
= 0.005), more delivered preterm (
p
= 0.0001), by CS (
p
= 0.05), and had more LGA neonates (
p
= 0.06) than the group without diabetes. Among pregnancies with diabetes, GDM mothers gained less weight (9.9 kg vs 13.5 kg) (
p
= 0.006), and rates of CS (
p
= 0.03), preterm deliveries (
p
= 0.001) and LGA (
p
= 0.0001) were not increased compared to PDM; More T1DM infants were LGA, 60% vs. 27% in T2DM. In pregnancies with diabetes obesity, excessive weight gain and multiparity were associated with increased risk of LGA neonates, and mother’s type of diabetes and gestational week were associated with higher rates of CS.
Conclusion
Weight gain during pregnancy was lower in pregnancies with diabetes and prevalence of LGA, CS and preterm deliveries in GDM was not elevated, also for T2DM, except increased prevalence of LGA in T1DM that warrants increased clinical attention, indicating that this model of antenatal diabetes care may have contributed to improved maternal and fetal outcomes.
Journal Article
Plasma branched chain/aromatic amino acids, enriched Mediterranean diet and risk of type 2 diabetes: case-cohort study within the PREDIMED Trial
Aims/hypothesisBranched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) are associated with type 2 diabetes. However, repeated measurements of BCAA/AAA and their interactions with dietary interventions have not been evaluated. We investigated the associations between baseline and changes at 1 year in BCAA/AAA with type 2 diabetes in the context of a Mediterranean diet (MedDiet) trial.MethodsWe included 251 participants with incident type 2 diabetes and a random sample of 694 participants (641 participants without type 2 diabetes and 53 overlapping cases) in a case-cohort study nested within the PREvención con DIeta MEDiterránea (PREDIMED) trial. Participants were randomised to a MedDiet+extra-virgin olive oil (n = 273), a MedDiet+nuts (n = 324) or a control diet (n = 295). We used LC-MS/MS to measure plasma levels of amino acids. Type 2 diabetes was a pre-specified secondary outcome of the PREDIMED trial.ResultsElevated plasma levels of individual BCAAs/AAAs were associated with higher type 2 diabetes risk after a median follow-up of 3.8 years: multivariable HR for the highest vs lowest quartile ranged from 1.32 for phenylalanine ([95% CI 0.90, 1.92], p for trend = 0.015) to 3.29 for leucine ([95% CI 2.03, 5.34], p for trend<0.001). Increases in BCAA score at 1 year were associated with higher type 2 diabetes risk in the control group with HR per SD = 1.61 (95% CI 1.02, 2.54), but not in the MedDiet groups (p for interaction <0.001). The MedDiet+extra-virgin olive oil significantly reduced BCAA levels after 1 year of intervention (p = 0.005 vs the control group).Conclusions/interpretationOur results support that higher baseline BCAAs and their increases at 1 year were associated with higher type 2 diabetes risk. A Mediterranean diet rich in extra-virgin olive oil significantly reduced the levels of BCAA and attenuated the positive association between plasma BCAA levels and type 2 diabetes incidence.Clinical trial number: SRCTN35739639 (www.controlled-trials.com)
Journal Article
Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study
Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values can further optimize such devices. In this study, we used machine learning to train models in predicting future glucose levels based on prior CGM and accelerometry data.
We used data from The Maastricht Study, an observational population-based cohort that comprises individuals with normal glucose metabolism, prediabetes, or type 2 diabetes. We included individuals who underwent >48h of CGM (n = 851), most of whom (n = 540) simultaneously wore an accelerometer to assess physical activity. A random subset of individuals was used to train models in predicting glucose levels at 15- and 60-minute intervals based on either CGM data or both CGM and accelerometer data. In the remaining individuals, model performance was evaluated with root-mean-square error (RMSE), Spearman's correlation coefficient (rho) and surveillance error grid. For a proof-of-concept translation, CGM-based prediction models were optimized and validated with the use of data from individuals with type 1 diabetes (OhioT1DM Dataset, n = 6).
Models trained with CGM data were able to accurately predict glucose values at 15 (RMSE: 0.19mmol/L; rho: 0.96) and 60 minutes (RMSE: 0.59mmol/L, rho: 0.72). Model performance was comparable in individuals with type 2 diabetes. Incorporation of accelerometer data only slightly improved prediction. The error grid results indicated that model predictions were clinically safe (15 min: >99%, 60 min >98%). Our prediction models translated well to individuals with type 1 diabetes, which is reflected by high accuracy (RMSEs for 15 and 60 minutes of 0.43 and 1.73 mmol/L, respectively) and clinical safety (15 min: >99%, 60 min: >91%).
Machine learning-based models are able to accurately and safely predict glucose values at 15- and 60-minute intervals based on CGM data only. Future research should further optimize the models for implementation in closed-loop insulin delivery systems.
Journal Article
Exposure to antibiotics and risk of latent autoimmune diabetes in adults and type 2 diabetes: results from a Swedish case–control study (ESTRID) and the Norwegian HUNT study
Aims/hypothesis
Some studies find an increased risk of type 1 diabetes in children exposed to antibiotics. We investigated if exposure to antibiotics increases the risk of latent autoimmune diabetes in adults (LADA) and type 2 diabetes.
Methods
We used data from a Swedish case–control study (Epidemiological Study of Risk Factors for LADA and Type 2 Diabetes [ESTRID]: LADA,
n
=597; type 2 diabetes,
n
=2065; control participants matched on participation time,
n
=2386) and a case–control study nested within the Norwegian Trøndelag Health Study (HUNT) (
n
=82/1279/2050). Anatomical Therapeutic Chemical (ATC) codes indicating antibiotic dispensations were retrieved from the Swedish National Prescribed Drug Register and Norwegian Prescription Database. Multivariable adjusted ORs with 95% CIs were estimated by conditional logistic regression and pooled using fixed-effects inverse-variance weighting.
Results
We observed no increased risk of LADA with exposure to antibiotics up to 1 year (OR
pooled
1.15, 95% CI 0.93, 1.41) or 1–5 years (OR
pooled
0.98, 95% CI 0.80, 1.20) prior to diagnosis/matching for one or more vs no dispensation of any type of antibiotic. An increased risk was observed for one or more vs no dispensations of narrow-spectrum antibiotics, but not broad-spectrum antibiotics, 6–10 years prior to LADA diagnosis (OR
pooled
1.39, 95% CI 1.01, 1.91), which was driven by the Swedish data. There was little evidence of an increased risk of type 2 diabetes associated with antibiotic exposure 1–10 years prior to diagnosis.
Conclusions/interpretation
We found no evidence that exposure to broad-spectrum antibiotics up to 10 years prior to diagnosis increases the risk of LADA. There was some indication of increased LADA risk with exposure to narrow-spectrum antibiotics, which warrants further investigation.
Graphical Abstract
Journal Article
Glucagon-like peptide 1 in health and disease
In healthy individuals, the incretin hormone glucagon-like peptide 1 (GLP1) potentiates insulin release and suppresses glucagon secretion in response to the ingestion of nutrients. GLP1 also delays gastric emptying and increases satiety. In patients with type 2 diabetes mellitus (T2DM), supraphysiological doses of GLP1 normalize the endogenous insulin response during a hyperglycaemic clamp. Owing to the short plasma half-life of native GLP1, several GLP1 receptor agonists (GLP1RAs) with longer half-lives have been developed for the treatment of T2DM. These compounds vary in chemical structure, pharmacokinetics and size, which results in different clinical effects on hyperglycaemia and body weight loss; these variations might also explain the difference in cardiovascular effect observed in large-scale cardiovascular outcome trials, in which certain GLP1RAs were shown to have a positive effect on cardiovascular outcomes. Owing to their metabolic effects, GLP1RAs are also considered for the treatment of several other lifestyle-induced conditions, such as obesity, prediabetes and liver disease. This Review provides insights into the physiology of GLP1 and its involvement in the pathophysiology of T2DM and an overview of the currently available and emerging GLP1RAs. Furthermore, we review the results from the currently available large-scale cardiovascular outcome trials and the use of GLP1RAs for other indications.
Journal Article
Comprehensive evaluation of diabetes subtypes in a European cohort reveals stronger differences of lifestyle, education and psychosocial parameters compared to metabolic or inflammatory factors
Background
The traditional binary classification of diabetes into Type 1 and Type 2 fails to capture the heterogeneity among diabetes patients. This study aims to identify and characterize diabetes subtypes within the German FoCus cohort, using the ANDIS cohort's classification framework, and to explore subtype-specific variations in metabolic markers, gut microbiota, lifestyle, social factors, and comorbidities.
Methods
We utilized data from 416 participants (208 with diabetes and 208 matched metabolically healthy controls) from the German FoCus cohort. Participants were classified into five subtypes: severe autoimmune diabetes (SAID)-like, severe insulin-deficient diabetes (SIDD)-like, severe insulin-resistant diabetes (SIRD)-like, mild obesity-related diabetes (MOD)-like, and mild age-related diabetes (MARD)-like. Comprehensive characterization included anthropometric measurements, dietary and physical activity questionnaires, blood biomarker analysis, and gut microbiota profiling.
Results
The subtype distribution in the FoCus cohort accounted to SAID-like: 2.84%, SIDD-like: 30.81%, SIRD-like: 32.23%, MOD-like: 17.54%, MARD-like: 16.59%. Of interest, inflammatory markers (C-reactive protein (CRP) and Interleukin-6 (IL-6)) and glucagon-like peptide-1 (GLP-1) levels were similarly elevated across all subtypes compared to controls, indicating common aspects in Type 2 diabetes molecular pathology despite different clinical phenotypes. While the gut microbiota and dietary patterns only showed minor differences, smoking status, sleep duration, physical activity and psychological aspects varied significantly between the subtypes. In addition, we observed a lower educational status especially for SIDD-like and SIRD-like groups, which should be considered in establishing future diabetes-related patient education programs. In respect to the development of cardio-metabolic comorbidities, we observe not only significant differences in the presence of the diseases but also for their age-of onset, highlighting the need for early preventive intervention strategies.
Conclusions
The study validates the ANDIS classification framework's applicability not only at the time point of manifestation but also in cohorts with pre-existing diabetes. While we did not find major differences regarding the classical metabolic, microbial and nutritional parameters, we identified several significant associations with lifestyle factors. Our findings underscore the importance of personalized, subtype-specific therapies not solely focusing on anthropometric and laboratory markers but comprehensively addressing the patient’s own personality and situation of life.
Journal Article