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Background: Glucose management indicator (GMI) is a useful metric for the clinical management of diabetic patients using continuous glucose monitoring (CGM). In adults, a marked discordance between HbA1c and GMI has been reported. To date, no studies have evaluated this discordance in children/adolescents with type 1 diabetes (T1D)., Methods: HbA1c and real-life CGM data of the 12 weeks preceding HbA1c measurement were collected from 805 children/adolescents. The absolute difference between HbA1c and GMI was calculated for both the 12-week and 4-week periods preceding HbA1c measurement and the proportion of discordant patients was defined according to specific thresholds in the entire study population and in subjects stratified by type of CGM, insulin therapy, gender, age and puberty. Regression analyses were performed with HbA1c-GMI discordance as dependent variable and patients' characteristics as independent ones. A new GMI equation for children and adolescent was derived from the linear regression analysis between mean glucose and HbA1c., Results: HbA1c-GMI discordance calculated on the 12-week period was <0.1, ≥0.5 and ≥1.0 in 24.8, 33.9 and 9.2% of the subjects, respectively. No significant differences in the proportion of discordant patients were found comparing patients stratified by type of CGM, insulin therapy, gender, age and puberty. GMI-HbA1c discordance was not significantly explained by age, gender, BMI, type of CGM, insulin therapy, hemoglobin, anemia and autoimmune diseases (R 2  = 0.012, p = 0.409). HbA1c-GMI discordance calculated on the 4-week period was comparable. GMI (%) equation derived for this cohort was: 3.74 + 0.022x (mean glucose in mg/dl)., Conclusions: GMI could be meaningfully discordant respect to HbA1c in more than a third of children/adolescents with T1D. This discrepancy should be taken into careful consideration when the two indices are directly compared in daily clinical practice., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), responsible for the coronavirus disease COVID-19, was first identified in Wuhan, China in December 2019. Diabetes, as well as other cardiovascular comorbidities, has been recognized as a major risk factor for outcomes and mortality in adults with COVID-19, particularly in the elderly with type 2 diabetes. Based on these conclusions, COVID-19 data on adults have been generalized to youth with diabetes. Nevertheless, experience from pediatric diabetes practices in China (Wuhan), Italy, Spain (Catalonia), and the United States (San Francisco Bay Area) consistently report only a single severe case of COVID-19 in a 20-year-old female youth with type 1 diabetes (T1D) that was hospitalized for bilateral pneumonia and was subsequently discharged without complications. In Italy, information on COVID-19 in all children with diabetes is collected on a weekly basis and those with positive swab test or infection-related symptoms reported to a dedicated national registry. Of a total of 15 500 children tested, 11 subjects with T1D (age 8-17y) tested positive for COVID-19; 6/11 were asymptomatic and the rest presented with mild symptoms. In the rest of locations, youths with T1D diagnosed with COVID-19 were based on clinical suspicion and a confirmatory PCR test (Wuhan:0; Catalonia-HSJD:3; California-Stanford:2). All of them were asymptomatic or had a mild course. We suggest that COVID-19 data from adults should not be generalized to children, adolescents, and youth with diabetes as their outcomes and prognosis seem to be similar to their non-diabetic-peers and consistently milder than adults with diabetes., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: No studies have assessed if 2-week of continuous glucose monitoring (CGM) data provide good estimation of long-term glycemic control and glucose variability (GV) in pediatric patients with type 1 diabetes (T1D) as in adults., Methods: Six hundred fifty-four T1D pediatric patients were enrolled and 12-weeks of CGM data, before HbA1c measurement, were collected. Metrics of glycemic control and GV in incremental sampling periods were calculated. The agreement between metrics calculated in the sampling periods and the full 12-week period was assessed with correlation analysis (R 2 ), median relative absolute difference (RAD) or absolute difference in the entire study populations and subjects stratified by age, pubertal status, insulin therapy (MDI,CSII), type of CGM (intermittently scanned [isCGM], real-time [rtCGM]), and HbA1c level., Results: Correlations with metrics of the full 12-week period improved by extending the sampling periods. R 2 values close to 0.90 using 4-week period were significantly higher than 2-week period, particularly for coefficient of variation, mean glucose SD, percentage of time below the range <70 mg/dL. A significant difference was found comparing the median RAD of 2- and 4-week, especially for mean glucose and coefficient of variation. Similar results were obtained analyzing subjects according to age and pubertal status, whereas in patients with HbA1c ≤7%, using rtCGM and CSII significant correlations were found for 2-week period., Conclusions: In T1D pediatric subjects, 4-week CGM data better reflects long-term glycemic control and GV in MDI and isCGM users. The 2-week period may be acceptably accurate in CSII and rtCGM users, especially in those with good glycometabolic control., (© 2020 John Wiley & Sons A/S . Published by John Wiley & Sons Ltd.)

Background: Age-specific preventive interventions by exploiting age-appropriate means are needed to effectively support adolescents with type 1 diabetes in facing illness and developmental-related difficulties. The provision of social support through a content analysis of messages posted on online conversations was examined., Methods: Participants and moderators' messages posted to an Italian online chat group for adolescents with type 1 diabetes were content analyzed using a social support behavior coding system., Results: Of 250 adolescents approached (aged 12-18), 161 (64.4%) agreed to participate. Seventeen thousand twenty-five individual posts (10 735 written by participants, 6290 by moderators) from 37 chat sessions were examined. Topics concerned management of the disease, diabetes-related problems, nutrition, and the emotional impact of diabetes. Social support was found in 30.64% of the messages (N = 5215). The frequency of supporting messages posted by participants was significantly higher than those written by moderators (X 2 = 20.025, P < .0001). Participants most frequently offered emotional (79.97%) and information support (16.21%), while moderators presented information (52.89%) and emotional support (34.56%)., Conclusions: How posting messages in an online group provides an opportunity for adolescents with type 1 diabetes to support each other and help health professionals to learn about the experiences of young individuals is discussed., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: To identify the role of the family's socio-economic and clinical characteristics on metabolic control in children and adolescents with type 1 diabetes., Methods: In this cross-sectional, multicentre study, 768 subjects with type 1 diabetes under 18 years of age were consecutively recruited from January 2008 to February 2009. Target condition was considered for HbA 1c values <7.5% (<58 mmol/mol). A multiple correspondence analysis (MCA) was performed to analyze the association between the socio-economic and clinical characteristics of the participants. A logistic regression analysis was performed to identify factors associated with the subjects metabolic control. In both analyses, the family's socio-economic status was represented, measured by the Hollingshead Four-Factor Index of Social Status (SES) or by parental years of education., Results: A total of 28.1% of subjects reached target HbA1c values. The MCA identified a strong association between at-target condition and several factors: high levels of SES or high levels of parental education, the use of the carbohydrate counting system, the use of insulin pumps, the use of the insulin delivery system over a short period of time, a normal body mass index. The logistic regression analysis showed that SES and the mother's years of education were significantly associated with the target condition [odds ratio (OR): 1.01, 95% confidence interval (CI): 1.01-1.03, p = 0.029; OR: 1.05, 95% CI: 1.01-1.10, p = 0.027, respectively)., Conclusions: Personal, clinical, and family characteristics were found to be associated with HbA 1c target. Their identification can be crucial in addressing strategies to optimize metabolic control and improve diabetes management., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Cataract represents one of the most frequent eye complications in type 1 and type 2 patients; contrarily, acute cataract in young diabetic patients occurs very rarely. The aim of this study was to describe six cases of acute cataract in adolescents at the onset of type 1 diabetes. Eight hundred and twenty-six patients with type 1 diabetes were retrospectively studied. A multivariate analysis was applied to verify the weight of the following laboratory findings taken on admission (independent variables): glycemia, glycated hemoglobin (HbA1c), pH, base excess (BE),and on the occurrence of cataract (dependent variable). Six patients (0.7%) presented with acute lens opacities. Cataract development was significantly correlated with HbA1c and glycemia. The relative risk increases about twice for each percentage point from 12.8 to 14.1% of HbA1c; glycemic blood levels represent a moderate risk factor for cataractogenesis. Ketoacidosis and BE were not significantly correlated., (© 2011 John Wiley & Sons A/S.)

Background: Insulin deficiency with glucagon excess leads to the release of ketone bodies (KBs) by the liver and excretion in the urine. So far, only KB monitoring in urine has been used during assessment of children with diabetes. Currently used nitroprusside strips for urine KB detection react only with acetoacetate (AcAc) and not with the most prevalent KB moiety - 3beta-hydroxybutyrate (3HB) - that is in equilibrium with AcAc (up to 10:1 ratio)., Aim: To verify the significance of 3HB in the blood compared to that of AcAc in the urine in recently diagnosed type 1 diabetic subjects independent of the presence of diabetic ketoacidosis (DKA)., Methods: A total of 118 consecutive newly diagnosed subjects with type 1 diabetes from different centers in Italy underwent intensive insulin therapy and hydration when necessary (38/118 = 32% with DKA). Hourly urine and capillary blood samples were used to monitor KBs until metabolic control was achieved., Results: Although DKA was present in 32% of patients, blood 3HB was significantly increased (3.56 +/- 1.7 mmol/L) in 83% of the patients and correlated with blood glucose (r = 0.39; p < 0.01) according to a bimodal model. The strongest association was found between 3HB and venous pH (r =-0.56; p < 0.0001). Time required for blood 3HB normalization depended strongly on the starting blood KB values (r = 0.44; p < 0.0001) and was significantly lower than that required for disappearance of KB from urine (17.4 +/- 13.6 h, range 1-69 h vs. 19.7 +/- 17.8 h, range 1-120 h; p = 0.004). However, urine KBs disappeared before blood 3HB normalization in 23% of the patients., Conclusions: Blood 3HB evaluation is a better indicator of metabolic control compared to urine KB detection and is useful to predict the time required for blood KB clearing. Further studies are needed to assess its use in the early detection and management of DKA.