Pediatric Diabetes最新文献

Aims: To assess associations of psychosocial factors with medication adherence in young adults with youth-onset type 2 diabetes in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY2) cohort.

Methods: Participants (mean age 26 years) completed validated psychosocial measures. Adherence to oral hypoglycemia agents (OHAs) was assessed with 3-monthly unannounced phone pill counts; insulin adherence by self-report. Logistic and linear regressions identified factors associated with "low-adherence" (<80% of pills/insulin) controlling for confounders.

Results: Of 212 participants taking OHAs (67% female, 39% Hispanic, 36% non-Hispanic Black), 69.8% were low-adherent. After adjustment, beliefs that medicines are necessary was associated with lower odds of low-adherence (p = 0.040, dichotomous). Less self-management support (p = 0.008), no healthcare coverage (p = 0.001), ≥1 (p = 0.008)/≥2 (p = 0.045) need insecurities were associated with higher odds of low-adherence. Factors associated with lower % adherence (continuous) were beliefs that medicines are harmful (p < 0.001)/overused (p = 0.007)/less necessary (p = 0.022), low self-management support (p = 0.003), food insecurity (p = 0.036), no healthcare coverage (p < 0.001), ≥1 (p = 0.003)/≥2 (p = 0.018) need insecurities. Of 192 taking insulin (69% female, 36% Hispanic, 41% non-Hispanic Black, 16% non-Hispanic white), 37.0% were low-adherent. Beliefs that medicines are overused (p = 0.009), that diabetes is not serious (p = 0.010), low diabetes self-efficacy (p = 0.035), high distress (p = 0.027), low self-management support (p = 0.001), food insecurity (p = 0.020), ≥1 (p = 0.011)/≥2 (p = 0.015) insecurities increased odds of insulin low-adherence.

Conclusions: Poor medication adherence, common in young adults with youth-onset type 2 diabetes, is associated with interfering beliefs, diabetes distress and social factors. We must address these factors to develop tailored interventions for this vulnerable group.

Objective: Limited information is available regarding youth-onset diabetes in Mali. We investigated demographic, clinical, biochemical, and genetic features in new diabetes cases in children and adolescents.

Research design and methods: The study was conducted at Hôpital du Mali in Bamako. A total of 132 recently-diagnosed cases <21 years were enrolled. Demographic characteristics, clinical information, biochemical parameters (blood glucose, HbA1c, C-peptide, glutamic acid decarboxylase-65 (GAD-65) and islet antigen-2 (IA2) autoantibodies) were assessed. DNA was genotyped for HLA-DRB1 using high-resolution genotyping technology.

Results: A total of 130 cases were clinically diagnosed as type 1 diabetes (T1D), one with type 2 diabetes (T2D), and one with secondary diabetes. A total of 66 (50.8%) T1D cases were males and 64 (49.2%) females, with a mean age at diagnosis of 13.8 ± 4.4 years (range 0.8-20.7 years) peak onset of 15 years. 58 (44.6%) presented in diabetic ketoacidosis; with 28 (21.5%) IA2 positive, 76 (58.5%) GAD-65 positive, and 15 (11.5%) positive for both autoantibodies. HLA was also genotyped in 195 controls without diabetes. HLA-DRB1 genotyping of controls and 98 T1D cases revealed that DRB1*03:01, DRB1*04:05, and DRB1*09:01 alleles were predisposing for T1D (odds ratios [ORs]: 2.82, 14.76, and 3.48, p-values: 9.68E-5, 2.26E-10, and 8.36E-4, respectively), while DRB1*15:03 was protective (OR = 0.27; p-value = 1.73E-3). No significant differences were observed between T1D cases with and without GAD-65 and IA2 autoantibodies. Interestingly, mean C-peptide was 3.6 ± 2.7 ng/ml (1.2 ± 0.9 nmol/L) in T1D cases at diagnosis.

Conclusions: C-peptide values were higher than expected in those diagnosed as T1D and autoantibody rates lower than in European populations. It is quite possible that some cases have an atypical form of T1D, ketosis-prone T2D, or youth-onset T2D. This study will help guide assessment and individual management of Malian diabetes cases, potentially enabling healthier outcomes.

Optimizing postprandial blood glucose (PPG) levels after mixed meals that contain high fat and protein remains a challenge in the treatment of type 1 diabetes. This study evaluated the efficacy of different algorithms used for dosing insulin based on counting units of high fat and high protein (HFHP) meals with the current conventional method of counting carbohydrates alone to control PPG excursions. The MEDLINE, EMBASE, and Cochrane electronic databases were searched, with the analysis restricted to randomized control trials (RCTs). The primary outcome was the PPG (mean and standard deviation) at 240 min. The pooled final estimate was the mean difference (MD) of the PPGs at 240 min using random effect models to account for heterogeneity. In total, 15 studies were identified and included in the systemic review, of which 12 were RCTs, and three studies were non-randomized trials. The pooled MD of the PPG at 240 min was in favor of additional insulin doses in HFHP meals compared to the carbohydrate counting alone. The statistically significant results favored the combined bolus (30:70) that split over 2 h in insulin pump therapy with pooled MD of the PPG, 240 min of -24.65; 95% CI: -36.59, -8.41; and heterogeneity, 0%. Other statistically significant results favored the additional insulin added to insulin to carb ratio (ICR) of meal bolus (25-60% ICR) in multiple daily injections therapy with the pooled MD of PPG at 240 min, -21.71; 95% CI: -38.45, -4.73; and heterogeneity, 18%. Insulin treatment based on fat and protein content, in addition to carbohydrate counting, is more effective than the carbohydrate counting method alone; however, further research is warranted to determine the best equation for fat and protein counting, particularly in people with multiple daily injections.

Objective: Both diabetes and obesity can affect the brain, yet their impact is not well characterized in children with type 2 (T2) diabetes and obesity. This pilot study aims to explore differences in brain function and cognition in adolescents with T2 diabetes and obesity and nondiabetic controls with obesity and lean controls.

Research design and methods: Participants were 12-17 years old (5 T2 diabetes with obesity [mean HgbA1C 10.9%], 6 nondiabetic controls with obesity and 10 lean controls). Functional MRI (FMRI) during hyperglycemic/euglycemic clamps was performed in the T2 diabetes group.

Results: When children with obesity, with and without diabetes, were grouped (mean BMI 98.8%), cognitive scores were lower than lean controls (BMI 58.4%) on verbal, full scale, and performance IQ, visual-spatial and executive function tests. Lower scores correlated with adiposity and insulin resistance but not HgbA1C. No significant brain activation differences during task based and resting state FMRI were noted between children with obesity (with or without diabetes) and lean controls, but a notable effect size for the visual-spatial working memory task and resting state was observed.

Conclusions: In conclusion, our pilot study suggests that obesity, insulin resistance, and dysglycemia may contribute to relatively poorer cognitive function in adolescents with T2 diabetes and obesity. Further studies with larger sample size are needed to assess if cognitive decline in children with obesity, with and without T2 diabetes, can be prevented or reversed.

Objective: Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study.

Research design and methods: A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age.

Results: It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001).

Conclusion: In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.