Targets and teamwork: Understanding differences in pediatric diabetes centers treatment outcomes.

OBJECTIVE: The reason for center differences in metabolic control of childhood diabetes is still unknown. We sought to determine to what extent the targets, expectations, and goals that diabetes care professionals have for their patients is a determinant of center differences in metabolic outcomes. RESEARCH DESIGN AND METHODS: Children, under the age of 11 with type 1 diabetes and their parents treated at the study centers participated. Clinical, medical, and demographic data were obtained, along with blood sample for centralized assay. Parents and all members of the diabetes care team completed questionnaires on treatment targets for hemoglobin A1c (HbA1c) and recommended frequency of blood glucose monitoring. RESULTS: Totally 1113 (53% male) children (mean age 8.0 ± 2.1 years) from 18 centers in 17 countries, along with parents and 113 health-care professionals, participated. There were substantial differences in mean HbA1c between centers ranging from 7.3 ± 0.8% (53 mmol/mol ± 8.7) to 8.9 ± 1.1% (74 mmol/mol ± 12.0). Centers with lower mean HbA1c had (1) parents who reported lower targets for their children, (2) health-care professionals that reported lower targets and more frequent testing, and (3) teams with less disagreement about recommended targets. Multiple regression analysis indicated that teams reporting higher HbA1c targets and more target disagreement had parents reporting higher treatment targets. This seemed to partially account for center differences in Hb1Ac. CONCLUSIONS: The diabetes care teams' cohesiveness and perspectives on treatment targets, expectations, and recommendations have an influence on parental targets, contributing to the differences in pediatric diabetes center outcomes.

Hvidoere Smiley Faces: International diabetes quality of life assessment tool for young children.

BACKGROUND: Few diabetes-specific quality of life (QOL) tools are available for young children. OBJECTIVES: To design and evaluate, a new age-specific QOL questionnaire and its associations with treatment regimens and metabolic control. METHODS: Clinical, demographic data and centrally analyzed HbA1c were collected on 1133 children <11 years (girls 48%; mean ± SD age 8.0 ± 2.1 years; diabetes duration ≥1 year) from 18 centers (Europe, Japan, North America and Australia). Children completed the 10-item Smiley Faces QOL questionnaire constructed for the study, and children ≥7 years also completed the KIDSCREEN-10 Index. RESULTS: In total, 1035 children completed the new Smiley Faces questionnaire which was well understood by 993 (70% ≥4 years and 96% ≥5 years, respectively). Internal consistency and reliability were good (Cronbach's α = .73). Inter-item correlation ranged r = 0.047 to 0.451 indicating each item measures separate aspects of children's satisfaction construct. Convergent validity assessed by comparison to the HrQOL KIDSCREEN-10 Index showed moderate correlation coefficient 0.501. Factor analysis revealed 3 factors explaining 51% of the variance. Children reported good QOL with most items positive, mean values between 1 and 2 on a 5-point scale (lower scores indicating greater QOL). Diabetes satisfaction was unrelated to age, diabetes duration, HbA1c, or severe hypoglycemia. Girls were more satisfied than boys. Children on intensive regimens reported better QOL (P < .02). Main dissatisfaction related to insulin injections and blood sugar testing. CONCLUSIONS: The Smiley Faces questionnaire enables QOL assessment in young children and identification of areas of dissatisfaction and other clinically relevant items relating to diabetes management.

Do eating behaviors in the general population account for country variance in glycemic control among adolescents with diabetes: the Hvidoere Study Group and the Health Behaviour in School-Aged Children study.

BACKGROUND: The Hvidoere Study Group (HSG) has demonstrated major differences in glycemic control between pediatric diabetes centers which remain largely unexplained. This study investigates whether these differences are partly attributable to healthy eating norms in the background population. METHODS: The study involved adolescents from 18 countries from (i) the Health Behaviour in School-Aged Children study (HBSC) and (ii) the HSG. There were 94 387 participants from representative HBSC samples of 11-, 13- and 15-yr-olds and 1483 11- to 15-yr-old adolescents with diabetes from the HSG. The frequency of intake of fruit, vegetables, sweets, sugary soft drinks, and daily breakfast was compared between the two groups. The glycemic control of the adolescents in the HSG cohort was determined by measuring glycated hemoglobin (HbA1c). RESULTS: Across countries in the HSBC survey, there was substantial variation in prevalence of healthy eating behavior and even greater variation between adolescents from the HSG centers. In all countries more adolescents with diabetes reported healthy eating behavior compared to national norms. In individuals healthy eating behavior had a significant effect on the individual level HbA1c. There was no significant correlation between the frequencies of these healthy eating behaviors at (i) the national level and (ii) diabetes center level and the center mean HbA1c. CONCLUSIONS: Although individual healthy eating behavior is associated with better glycemic control at the individual level, such eating behavior does not explain the center differences in HbA1c. Similarly, the reported healthy eating norm of the background populations does not explain the variation in glycemic control among centers.

Metabolic outcomes in young children with type 1 diabetes differ between treatment centers: the Hvidoere Study in Young Children 2009.

OBJECTIVE: To investigate whether center differences in glycemic control are present in prepubertal children <11 yr with type 1 diabetes mellitus. RESEARCH DESIGN AND METHODS: This cross-sectional study involved 18 pediatric centers worldwide. All children, <11 y with a diabetes duration ≥12 months were invited to participate. Case Record Forms included information on clinical characteristics, insulin regimens, diabetic ketoacidosis (DKA), severe hypoglycemia, language difficulties, and comorbidities. Hemoglobin A1c (HbA1c) was measured centrally by liquid chromatography (DCCT aligned, range: 4.4-6.3%; IFFC: 25-45 mmol/mol). RESULTS: A total of 1133 children participated (mean age: 8.0 ± 2.1 y; females: 47.5%, mean diabetes duration: 3.8 ± 2.1 y). HbA1c (overall mean: 8.0 ± 1.0%; range: 7.3-8.9%) and severe hypoglycemia frequency (mean 21.7 events per 100 patient-years), but not DKA, differed significantly between centers (p < 0.001 resp. p = 0.179). Language difficulties showed a negative relationship with HbA1c (8.3 ± 1.2% vs. 8.0 ± 1.0%; p = 0.036). Frequency of blood glucose monitoring demonstrated a significant but weak association with HbA1c (r = -0.17; p < 0.0001). Although significant different HbA1c levels were obtained with diverse insulin regimens (range: 7.3-8.5%; p < 0.001), center differences remained after adjusting for insulin regimen (p < 0.001). Differences between insulin regimens were no longer significant after adjusting for center effect (p = 0.199). CONCLUSIONS: Center differences in metabolic outcomes are present in children <11 yr, irrespective of diabetes duration, age, or gender. The incidence of severe hypoglycemia is lower than in adolescents despite achieving better glycemic control. Insulin regimens show a significant relationship with HbA1c but do not explain center differences. Each center's effectiveness in using specific treatment strategies remains the key factor for outcome.

Disease progression and search for monogenic diabetes among children with new onset type 1 diabetes negative for ICA, GAD- and IA-2 Antibodies.

BACKGROUND: To investigate disease progression the first 12 months after diagnosis in children with type 1 diabetes negative (AAB negative) for pancreatic autoantibodies [islet cell autoantibodies(ICA), glutamic acid decarboxylase antibodies (GADA) and insulinoma-associated antigen-2 antibodies (IA-2A)]. Furthermore the study aimed at determining whether mutations in KCNJ11, ABCC8, HNF1A, HNF4A or INS are common in AAB negative diabetes. MATERIALS AND METHODS: In 261 newly diagnosed children with type 1 diabetes, we measured residual ß-cell function, ICA, GADA, and IA-2A at 1, 6 and 12 months after diagnosis. The genes KCNJ11, ABCC8, HNF1A, HNF4A and INS were sequenced in subjects AAB negative at diagnosis. We expressed recombinant K-ATP channels in Xenopus oocytes to analyse the functional effects of an ABCC8 mutation. RESULTS: Twenty-four patients (9.1%) tested AAB negative after one month. Patients, who were AAB-negative throughout the 12-month period, had higher residual ß-cell function (P = 0.002), lower blood glucose (P = 0.004), received less insulin (P = 0.05) and had lower HbA1c (P = 0.02) 12 months after diagnosis. One patient had a heterozygous mutation leading to the substitution of arginine at residue 1530 of SUR1 (ABCC8) by cysteine. Functional analyses of recombinant K-ATP channels showed that R1530C markedly reduced the sensitivity of the K-ATP channel to inhibition by MgATP. Morover, the channel was highly sensitive to sulphonylureas. However, there was no effect of sulfonylurea treatment after four weeks on 1.0-1.2 mg/kg/24 h glibenclamide. CONCLUSION: GAD, IA-2A, and ICA negative children with new onset type 1 diabetes have slower disease progression as assessed by residual beta-cell function and improved glycemic control 12 months after diagnosis. One out of 24 had a mutation in ABCC8, suggesting that screening of ABCC8 should be considered in patients with AAB negative type 1 diabetes.

Multinational study in children and adolescents with newly diagnosed type 1 diabetes: association of age, ketoacidosis, HLA status, and autoantibodies on residual beta-cell function and glycemic control 12 months after diagnosis.

OBJECTIVE: To identify predictors of residual beta-cell function and glycemic control during the first 12 months after the diagnosis of type 1 diabetes (T1D). SUBJECTS AND METHODS: Clinical information and blood samples were collected from 275 children. HbA1c, antibodies, HLA typing and mixed meal-stimulated C-peptide levels 1, 6, and 12 months after diagnosis were analyzed centrally. RESULTS: Mean age at diagnosis was 9.1 yr. DKA with standard bicarbonate <15 mmol/L was associated with significantly poorer residual beta-cell function 1 (p = 0.004) and 12 months (p = 0.0003) after diagnosis. At 12 months, the decline in stimulated C-peptide levels compared with the levels at 1 month was 69% in the youngest age group and 50% in patients 10 yr and above (p < 0.001). Stimulated C-peptide at 12 months was predicted by younger age (p < 0.02) and bicarbonate levels at diagnosis (p = 0.005), and by stimulated C-peptide (p < 0.0001), postmeal blood glucose (p = 0.0004), insulin antibodies (IA; p = 0.02) and glutamic acid decarboxylase antibodies (GADA; p = 0.0004) at 1 month. HbA1c at 12 months was predicted by HbA1c at diagnosis (p < 0.0001), GADA at 1 month (p = 0.01), and non-white Caucasian ethnicity (p = 0.002). CONCLUSIONS: Younger age, ketoacidosis at diagnosis, and IA and GADA 1 month after diagnosis were the strongest explanatory factors for residual beta-cell function at 12 months. Glycemic control at 12 months was influenced predominantly by ethnicity, HbA1c at diagnosis, and GADA at 1 month.

New definition for the partial remission period in children and adolescents with type 1 diabetes.

OBJECTIVE To find a simple definition of partial remission in type 1 diabetes that reflects both residual beta-cell function and efficacy of insulin treatment. RESEARCH DESIGN AND METHODS A total of 275 patients aged <16 years were followed from onset of type 1 diabetes. After 1, 6, and 12 months, stimulated C-peptide during a challenge was used as a measure of residual beta-cell function. RESULTS By multiple regression analysis, a negative association between stimulated C-peptide and A1C (regression coefficient -0.21, P < 0.001) and insulin dose (-0.94, P < 0.001) was shown. These results suggested the definition of an insulin dose-adjusted A1C (IDAA1C) as A1C (percent) + [4 x insulin dose (units per kilogram per 24 h)]. A calculated IDAA1C < or =9 corresponding to a predicted stimulated C-peptide >300 pmol/l was used to define partial remission. The IDAA1C < or =9 had a significantly higher agreement (P < 0.001) with residual beta-cell function than use of a definition of A1C < or =7.5%. Between 6 and 12 months after diagnosis, for IDAA1C < or =9 only 1 patient entered partial remission and 61 patients ended partial remission, for A1C < or =7.5% 15 patients entered partial remission and 53 ended, for a definition of insulin dose < or =0.5 units . kg(-1) . 24 h(-1) 5 patients entered partial remission and 66 ended, and for stimulated C-peptide (>300 pmol/l) 9 patients entered partial remission and 49 ended. IDAA1C at 6 months has good predictive power for stimulated C-peptide concentrations after both 6 and 12 months. CONCLUSIONS A new definition of partial remission is proposed, including both glycemic control and insulin dose. It reflects residual beta-cell function and has better stability compared with the conventional definitions.

Evaluation of a type 1 diabetes serum cohort by SELDI-TOF MS protein profiling.

Proteomics analysis of serum from patients with type 1 diabetes (T1D) may lead to novel biomarkers for prediction of disease and for patient monitoring. However, the serum proteome is highly sensitive to sample processing and before proteomics biomarker research serum cohorts should preferably be examined for potential bias between sample groups. SELDI-TOF MS protein profiling was used for preliminary evaluation of a biological-bank with 766 serum samples from 270 patients with T1D, collected at 18 different paediatric centers representing 15 countries in Europe and Japan over 2 years (2000-2002). Samples collected 1 (n = 270), 6 (n = 248), and 12 (n = 248) months after T1D diagnosis were grouped across centers and compared. The serum protein profiles varied with collection site and day of analysis; however, markers of sample processing were not systematically different between samples collected at different times after diagnosis. Three members of the apolipoprotein family increased with time in patient serum collected 1, 6, and 12 months after diagnosis (ANOVA, p<0.001). These results support the use of this serum cohort for further proteomic studies and illustrate the potential of high-throughput MALDI/SELDI-TOF MS protein profiling for evaluation of serum cohorts before proteomics biomarker research.

Continuing stability of center differences in pediatric diabetes care: do advances in diabetes treatment improve outcome? The Hvidoere Study Group on Childhood Diabetes.

OBJECTIVE: To reevaluate the persistence and stability of previously observed differences between pediatric diabetes centers and to investigate the influence of demography, language communication problems, and changes in insulin regimens on metabolic outcome, hypoglycemia, and ketoacidosis. RESEARCH DESIGN AND METHODS: This was an observational cross-sectional international study in 21 centers, with clinical data obtained from all participants and A1C levels assayed in one central laboratory. All individuals with diabetes aged 11-18 years (49.4% female), with duration of diabetes of at least 1 year, were invited to participate. Fourteen of the centers participated in previous Hvidoere Studies, allowing direct comparison of glycemic control across centers between 1998 and 2005. RESULTS: Mean A1C was 8.2 +/- 1.4%, with substantial variation between centers (mean A1C range 7.4-9.2%; P < 0.001). There were no significant differences between centers in rates of severe hypoglycemia or diabetic ketoacidosis. Language difficulties had a significant negative impact on metabolic outcome (A1C 8.5 +/- 2.0% vs. 8.2 +/- 1.4% for those with language difficulties vs. those without, respectively; P < 0.05). After adjustement for significant confounders of age, sex, duration of diabetes, insulin regimen, insulin dose, BMI, and language difficulties, the center differences persisted, and the effect size for center was not reduced. Relative center ranking since 1998 has remained stable, with no significant change in A1C. CONCLUSIONS: Despite many changes in diabetes management, major differences in metabolic outcome between 21 international pediatric diabetes centers persist. Different application between centers in the implementation of insulin treatment appears to be of more importance and needs further exploration.