Impact of Type 1 Diabetes Mellitus on Bone Health in Children

Adaptation and validation of an artificial intelligence based digital radiogrammetry tool for assessing bone health of indian children and youth with type-1 diabetes

BACKGROUND AND OBJECTIVES

BoneXpert (BX) is an artificial intelligence software used primarily for bone age assessment. Besides, it can also be used to screen for bone health using the digital radiogrammetry tool called bone health index (BHI) for which normative reference values available are calculated from healthy European children. Due to ethnic difference in bone geometry, in a previous study, we generated reference curves based on healthy Indian children. The objectives of this study were: 1) To assess and compare bone health of Indian children with Type 1 diabetes (T1D) using both European and Indian BHI SDS reference data and 2) To identify determinants of poor bone health in Indian children and youth with T1D by using BHI tool (based on BHI-SDS Indian reference data) of BX.

METHOD

The BHI was assessed retrospectively in 1159 subjects with T1D using digitalised left-hand x-rays and SDS were computed using European and Indian data. The demographic, anthropometric, clinical, biochemistry, dual x-ray absorptiometry (DXA) data and peripheral quantitative computed tomography (pQCT) data collection were performed using standard protocols and were extracted from hospital records.

RESULTS

The BHI correlated well with DXA and pQCT parameters in subjects with T1D. BHI-SDS calculated using Indian reference data had better correlation with height and DXA parameters. 8.6% study participants had low (less than -2) BHI-SDS (Indian), with height SDS having significant effect. Subjects with low BHI-SDS were older, shorter and had higher duration of diabetes. They also had lower IGF1 and vitamin D concentrations, bone mineral density, and trabecular density. Female gender, increased duration of illness, poor glycaemic control, and vitamin D deficiency/insufficiency were significant predictors of poor BHI-SDS.

CONCLUSION

Our study highlights the utility of digital radiogrammetry AI tool to screen for bone health of children with T1D and demonstrates and highlights the necessity of interpretation using ethnicity specific normative data.

Trabecular bone score in type 1 diabetes: a meta-analysis of cross-sectional studies

BACKGROUND

Bone fragility is a recognized complication of type 1 diabetes (T1D). Thus, lower trabecular bone score (TBS) measurements in T1D patients can be predicted. However, the results of current studies on TBS in patients with T1D are inconsistent. In this context, the present study aimed to test the hypothesis that T1D is associated with lower TBS through a meta-analysis.

METHODS

An electronic search of the literature was conducted using PubMed, Embase and Web of science databases to identify studies related to TBS and T1D, supplemented by an additional manual check of the reference list of relevant original and review articles. All data was analyzed using a random effects model. Results were compared using standardized mean differences (SMD) and 95% confidence intervals (CI). P ≤ 0.05 was considered statistically significant. Review Manager 5.4 software and Stata 17.0 software were used for statistical analysis.

RESULTS

Seven cross-sectional studies involving 848 participants were included. TBS was lower in T1D patients than in healthy controls on random effects analysis, with no heterogeneity (SMD =  - 0.39, 95% CI [- 0.53, - 0.24], P < 0.001; I2 = 0%). In addition, by subgroup analysis, T1D patients were strongly associated with reduced TBS in different regions and age groups, and the results were independent of covariate adjustment.

CONCLUSION

This study showed that TBS was lower in patients with T1D than in healthy individuals with normal blood glucose levels, suggesting that TBS may be a useful measure to assess fracture risk in T1D.