Search

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.

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation. OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008. METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends. RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ± 11 to ± 38% (median ± 17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours. CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ± 11 to ± 38% (median ± 17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

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.

Aims/hypothesis The aim of the study was to describe 20- year incidence trends for childhood type 1 diabetes in 23 EURODIAB centres and compare rates of increase in the first (1989–1998) and second (1999–2008) halves of the period. Methods All registers operate in geographically defined regions and are based on a clinical diagnosis. Completeness of registration is assessed by capture–recapture methodology. Twenty-three centres in 19 countries registered 49,969 new cases of type 1 diabetes in individuals diagnosed before their 15th birthday during the period studied. Results Ascertainment exceeded 90% in most registers. During the 20-year period, all but one register showed statistically significant changes in incidence, with rates universally increasing. When estimated separately for the first and second halves of the period, the median rates of increase were similar: 3.4% per annum and 3.3% per annum, respectively. However, rates of increase differed significantly between the first half and the second half for nine of the 21 registers with adequate coverage of both periods; five registers showed significantly higher rates of increase in the first half, and four significantly higher rates in the second half. Conclusions/interpretation The incidence rate of childhood type 1 diabetes continues to rise across Europe by an average of approximately 3–4% per annum, but the increase is not necessarily uniform, showing periods of less rapid and more rapid increase in incidence in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions is warranted.

Objective: To evaluate glycaemic targets set by diabetes teams, their perception by adolescents and parents, and their influence on metabolic control. Methods: Clinical data and questionnaires were completed by adolescents, parents/carers and diabetes teams in 21 international centres. HbA1c was measured centrally. Results: A total of 2062 adolescents completed questionnaires (age 14.4 +/- 2.3 yr; diabetes duration 6.1 +/- 3.5 yr). Mean HbA 1c = 8.2 +/- 1.4% with significant differences between centres (F = 12.3; p <0.001) range from 7.4 to 9.1%. There was a significant correlation between parent (r = 0.20) and adolescent (r = 0.21) reports of their perceived ideal HbA1c and their actual HbA1c result (p <0.001), and a stronger association between parents' (r = 0.39) and adolescents' (r = 0.4) reports of the HbA1c they would be happy with and their actual HbA1c result. There were significant differences between centres on parent and adolescent reports of ideal and happy with HbA1c (8.1 17.4;p <0.001). A lower target HbA1c and greater consistency between members of teams within centres were associated with lower centre HbA1c (F = 16.0; df = 15; p <0.001). Conclusions: Clear and consistent setting of glycaemic targets by diabetes teams is strongly associated with HbA1c outcome in adolescents. Target setting appears to play a significant role in explaining the differences in metabolic outcomes between centres

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. S ELDI-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

Aims: To assess the importance of family factors in determining metabolic outcomes in adolescents with type1 diabetes across varying international contexts. Methods: Adolescents with type 1 diabetes aged 11-18 years, from 21 paediatric diabetes care centres, across 19 countries, and their parents were invited to participate. Questionnaires were administered recording demographic data, details of insulin regimens, severe hypoglycaemic events and number of episodes of diabetic ketoacidosis. Adolescents completed the parental involvement scale from the Diabetes Quality of Life (DQOLY-SF) and the Diabetes Family Responsibility Questionnaire (DFRQ). Parents completed the DFRQ and a Parental Burden of Diabetes score. A capillary blood sample was drawn from each patient and analyzed centrally for HbA1c. Results: 2062 adolescents completed a questionnaire, with 2036 providing a blood sample. 1994 parents also completed a questionnaire. Family demographic factors that were associated with metabolic outcomes included, parents living together (t=4.1;p

OBJECTIVE: We investigated the association of anti-inflammatory cytokine interleukin (IL)-1 receptor antagonist (IL-1ra), adiponectin, proinflammatory cytokines IL-1 beta, IL-6, and CCL2, and tumor necrosis factor-alpha with beta-cell function, metabolic status, and clinical remission in patients with recent-onset type 1 diabetes. RESEARCH DESIGN AND METHODS: Serum was obtained from 256 newly diagnosed patients (122 males and 134 females, median age 9.6 years). Stimulated C-peptide, blood glucose, and A1C were determined in addition to circulating concentration of cytokines at 1, 6, and 12 months after diagnosis. Analyses were adjusted for sex, age, and BMI percentile. RESULTS: Anti-inflammatory IL-1ra was positively associated with C-peptide after 6 (P = 0.0009) and 12 (P = 0.009) months. The beneficial association of IL-1ra on beta-cell function was complemented by the negative association of IL-1 beta with C-peptide after 1 month (P = 0.009). In contrast, anti-inflammatory adiponectin was elevated in patients with poor metabolic control after 6 and 12 months (P < 0.05) and positively correlated with A1C after 1 month (P = 0.0004). Proinflammatory IL-6 was elevated in patients with good metabolic control after 1 month (P = 0.009) and showed a positive association with blood glucose disposal after 12 months (P = 0.047). CONCLUSIONS: IL-1ra is associated with preserved beta-cell capacity in type 1 diabetes. This novel finding indicates that administration of IL-1ra, successfully improving beta-cell function in type 2 diabetes, may also be a new therapeutic approach in type 1 diabetes. The relation of adiponectin and IL-6 with remission and metabolic status transfers observations from in vitro and animal models into the human situation in vivo.

Aims To assess the importance of family factors in determining metabolic outcomes in adolescents with Type 1 diabetes in 19 countries. Methods Adolescents with Type 1 diabetes aged 11-18 years, from 21 paediatric diabetes care centres, in 19 countries, and their parents were invited to participate. Questionnaires were administered recording demographic data, details of insulin regimens, severe hypoglycaemic events and number of episodes of diabetic ketoacidosis. Adolescents completed the parental involvement scale from the Diabetes Quality of Life for Youth-Short Form (DQOLY-SF) and the Diabetes Family Responsibility Questionnaire (DFRQ). Parents completed the DFRQ and a Parental Burden of Diabetes score. Glycated haemoglobin (HbA(1c)) was analysed centrally on capillary blood. Results A total of 2062 adolescents completed a questionnaire, with 2036 providing a blood sample; 1994 parents also completed a questionnaire. Family demographic factors that were associated with metabolic outcomes included: parents living together (t = 4.1; P < 0.001), paternal employment status (F = 7.2; d.f. = 3; P < 0.001), parents perceived to be over-involved in diabetes care (r = 0.11; P < 0.001) and adolescent-parent disagreement on responsibility for diabetes care practices (F = 8.46; d.f. = 2; P < 0.001). Although these factors differed between centres, they did not account for centre differences in metabolic outcomes, but were stronger predictors of metabolic control than age, gender or insulin treatment regimen. Conclusions Family factors, particularly dynamic and communication factors such as parental over-involvement and adolescent-parent concordance on responsibility for diabetes care appear be important determinants of metabolic outcomes in adolescents with diabetes. However, family dynamic factors do not account for the substantial differences in metabolic outcomes between centres Udgivelsesdato: 2008/4

OBJECTIVE: We investigated the association of anti-inflammatory cytokine interleukin (IL)-1 receptor antagonist (IL-1ra), adiponectin, proinflammatory cytokines IL-1 beta, IL-6, and CCL2, and tumor necrosis factor-alpha with beta-cell function, metabolic status, and clinical remission in patients with recent-onset type 1 diabetes. RESEARCH DESIGN AND METHODS: Serum was obtained from 256 newly diagnosed patients (122 males and 134 females, median age 9.6 years). Stimulated C-peptide, blood glucose, and A1C were determined in addition to circulating concentration of cytokines at 1, 6, and 12 months after diagnosis. Analyses were adjusted for sex, age, and BMI percentile. RESULTS: Anti-inflammatory IL-1ra was positively associated with C-peptide after 6 (P = 0.0009) and 12 (P = 0.009) months. The beneficial association of IL-1ra on beta-cell function was complemented by the negative association of IL-1 beta with C-peptide after 1 month (P = 0.009). In contrast, anti-inflammatory adiponectin was elevated in patients with poor metabolic control after 6 and 12 months (P < 0.05) and positively correlated with A1C after 1 month (P = 0.0004). Proinflammatory IL-6 was elevated in patients with good metabolic control after 1 month (P = 0.009) and showed a positive association with blood glucose disposal after 12 months (P = 0.047). CONCLUSIONS: IL-1ra is associated with preserved beta-cell capacity in type 1 diabetes. This novel finding indicates that administration of IL-1ra, successfully improving beta-cell function in type 2 diabetes, may also be a new therapeutic approach in type 1 diabetes. The relation of adiponectin and IL-6 with remission and metabolic status transfers observations from in vitro and animal models into the human situation in vivo Udgivelsesdato: 2008/4

Context: Conflicting evidence exists as to whether the Pro12Ala single nucleotide polymorphism of the type 2 diabetes susceptibility gene peroxisome proliferator-activated receptor gamma (PPARG) also confers risk for type 1 diabetes (T1D). Objective: The objective of this study was to investigate the PPARG gene in relation to residual beta-cell function and glycemic control in newly diagnosed T1D. Design: Prospective, non-interventional, 12-month follow-up study, conducted in 18 centers in 15 countries. Patients: Two hundred and fifty-seven children and adolescents (aged < 16 yr) with newly diagnosed T1D. Main outcome measures: Beta-cell function was determined as 90-min meal-stimulated C-peptide (Boost test) 1, 6, and 12 months after diagnosis. Hemoglobin A1c (HbA1c) and daily insulin dose (IU/kg/d) were recorded at 1, 3, 6, 9, and 12 months after diagnosis. Haplotypes within PPARG were estimated by SNPHAP program. Statistical analyses were performed in a repeated measurements model. Results: Five haplotypes within PPARG were generated (h1, 68.4%; h2, 16.3%; h3, 8.3%; h4, 3.5%; and hx, 3.5%). Compared with the most frequent h1 haplotype, the haplotypes h3 and h4 of the PPARG associated with residual beta-cell function during the first year of clinical disease: h3 with a 27% lower C-peptide (p = 0.02) and h4 with a 39% lower C-peptide (p = 0.01). Haplotype h4 also associated with a 0.86% (absolute) higher HbA1c, after adjustment for the insulin dose (p = 0.02). Conclusion: Variation in the PPARG locus may influence disease progression during the first year after the presentation of T1D Udgivelsesdato: 2008/8

Udgivelsesdato: 2007/8