Bone Health Index and bone turnover in pediatric patients with type 1 diabetes mellitus and poor metabolic control.

BACKGROUND: There is a need for a non-invasive, affordable, and reliable method for bone health screening in pediatric patients at risk. OBJECTIVE: To assess Bone Health Index (BHI) in pediatric patients with type 1 diabetes (T1D) and its relation to bone metabolism, age at onset, duration, control, and insulin dose. SUBJECTS AND METHODS: Left-hand radiographs were obtained from 65 patients with T1D, mean age 11.23 ± 3.89 years, mean disease duration 5.23 ± 3.76 years and mean glycosylated hemoglobin (HbA1c)-83 mmol/mol (9.7%). Blood and 24 hours urine samples were collected for bone and mineral metabolism assessment. BoneXpert was used to determine BHI, Bone Health Index standard deviation score (BHI SDS), and bone age. RESULTS: Mean BHI SDS was -1.15 ± 1.19 (n = 54). In 20.37% (n = 11) BHI SDS was < -2SD with mean value -2.82 ± 0. 69, P < .001. These patients had lower levels of beta cross laps (0.77 ± 0.33 ng/mL vs 1.17 ± 0.47 ng/mL), osteocalcin (47.20 ± 14.07 ng/mL vs 75.91 ± 32.08 ng/mL), serum magnesium (0.79 ± 0.05 mmol/L vs 0.83 ± 0.06 mmol/L) and phosphorus (1.48 ± 0.29 mmol/L vs 1.71 ± 0.28 mmol/L) but higher ionized calcium (1.29 ± 0.04 mmol/L vs 1.26 ± 0.05 mmol/L), P < .05, compared to patients with BHI SDS in the normal range. We found a positive correlation between BHI SDS and age at manifestation (r = 0.307, P = 0.024) and a negative one with disease duration (r = -0.284, P = .038). No correlations were found with HbA1c, insulin dose, height, weight, BMI. CONCLUSIONS: To the best of our knowledge, this is the first study to assess bone health in pediatric patients with T1D using BHI. We found significantly decreased cortical bone density and bone turnover in 20.37%. Earlier age at onset and diabetes duration may have a negative impact on cortical bone density in patients with poor control. Longitudinal studies are needed to follow changes or to assess future interventions.

Possibilities and challenges of a large international benchmarking in pediatric diabetology-The SWEET experience.

AIM: Despite the existence of evidence-based guidelines for the care of children with diabetes, widespread gaps in knowledge, attitude, and practice remain. The purpose of this paper is to present a review of benchmarking practices and results of this process within SWEET, moreover focusing on current challenges and future directions. METHODS: Biannually, members electronically transfer de-identified clinic data for 37 parameters to the SWEET database. Each center receives benchmarking and data validation reports. RESULTS: In 2015, 48 centers have contributed data for 20 165 unique patients (51.6% male). After exclusion for missing data 19 131 patients remain for further analysis. The median age is 14.2 years, with a median diabetes duration 4.8 years; 96.0% of patients have type 1, 1.1% type 2, and 2.9% other diabetes types. Data completeness has increased over time. In 2015, median HbA1c of all patients' (diabetes type 1) medians was 7.8% (61.7 mmol/mol) with 39.1%, 41.4%, and 19.4% of patients having HbA1c < 7.5% (58 mmol/mol), 7.5%-9% (58-75 mmol/mol) and >9% (75 mmol/mol), respectively. Although HbA1c has been stable over time [7.7%-7.8% (60.7-61.7 mmol/mol)], there remains wide variation between centers. Fourteen centers achieve a median HbA1c <7.5% (58 mmol/mol). CONCLUSIONS: Our vision is that the participation in SWEET is encouraging members to deliver increasingly accurate and complete data. Dissemination of results and prospective projects serve as further motivation to improve data reporting. Comparing processes and outcomes will help members identify weaknesses and introduce innovative solutions, resulting in improved and more uniform care for patients with diabetes.