Unmasking Fracture Risk in Type 2 Diabetes: The Association of Longitudinal Glycemic Hemoglobin Level and Medications

Relationship between diabetes treatment status and occupational accidents

AIMS

To evaluate the relationship between diabetes treatment status and occupational accidents.

METHODS

A cross-sectional study was conducted using an online questionnaire survey completed in March 2022 among workers aged 20 years or older. The questionnaire included questions about diabetes treatment status and occupational accidents. The association between the treatment status of diabetes and occupational accidents was examined using a logistic regression analysis.

RESULTS

The study included 25,756 participants with no diabetes, 1,364 participants receiving diabetes treatment, 177 participants who had interrupted diabetes treatment, and 396 participants who needed diabetes treatment but had not seen a doctor. Compared with those with diabetes treatment, the odds ratio of occupational accidents among participants without diabetes was 0.40 (95% CI: 0.32-0.49), the odds ratio among participants with interrupted diabetes treatment was 4.15 (95% CI: 2.86-6.01), and the odds ratio among participants who needed diabetes treatment but had not seen a doctor was 1.25 (95% CI: 0.89-1.77).

CONCLUSIONS

This study showed that diabetes treatment status was related to occupational accidents, and it may be important for workers with diabetes to be supported to balance their diabetes management and their work commitments.

Exploring the Interplay between Vitamin D, Insulin Resistance, Obesity and Skeletal Health

Vitamin D (ViD), plays an important role in calcium absorption and bone mineralization, is associated with bone mineral density. Severe deficiency in ViD has long been linked to conditions such as rickets in children and osteomalacia in adults, revealing its substantial role in skeletal health. Additionally, investigations show an existing interconnection between ViD and insulin resistance (Ins-R), especially in patients with type 2 diabetes mellitus (T2DM). Obesity, in conjunction with Ins-R, may augment the risk of osteoporosis and deterioration of skeletal health. This review aims to examine recent studies on the interplay between ViD, Ins-R, obesity, and their impact on skeletal health, to offer insights into potential therapeutic strategies. Cochrane Library, Google Scholar, and Pubmed were searched to investigate relevant studies until December 2023. Current research demonstrates ViD's impact on pancreatic β-cell function, systemic inflammation, and insulin action regulation. Our findings highlight an intricate association between ViD, Ins-R, obesity, and skeletal health, providing a perspective for the prevention and/or treatment of skeletal disorders in patients with obesity, Ins-R, and T2DM.

Deep learning-based long-term risk evaluation of incident type 2 diabetes using electrocardiogram in a non-diabetic population: a retrospective, multicentre study

Background

Diabetes is a major public health concern. We aimed to evaluate the long-term risk of incident type 2 diabetes in a non-diabetic population using a deep learning model (DLM) detecting prevalent type 2 diabetes using electrocardiogram (ECG).

Methods

In this retrospective study, participants who underwent health checkups at two tertiary hospitals in Seoul, South Korea, between Jan 1, 2001 and Dec 31, 2022 were included. Type 2 diabetes was defined as glucose ≥126 mg/dL or glycated haemoglobin (HbA1c) ≥ 6.5%. For survival analysis on incident type 2 diabetes, we introduced an additional variable, diabetic ECG, which is determined by the DLM trained on ECG and corresponding prevalent diabetes. It was assumed that non-diabetic individuals with diabetic ECG had a higher risk of incident type 2 diabetes than those with non-diabetic ECG. The one-dimensional ResNet-based model was adopted for the DLM, and the Guided Grad-CAM was used to localise important regions of ECG. We divided the non-diabetic group into the diabetic ECG group (false positive) and the non-diabetic ECG (true negative) group according to the DLM decision, and performed a Cox proportional hazard model, considering the occurrence of type 2 diabetes more than six months after the visit.

Findings

190,581 individuals were included in the study with a median follow-up period of 11.84 years. The areas under the receiver operating characteristic curve for prevalent type 2 diabetes detection were 0.816 (0.807-0.825) and 0.762 (0.754-0.770) for the internal and external validations, respectively. The model primarily focused on the QRS duration and, occasionally, P or T waves. The diabetic ECG group exhibited an increased risk of incident type 2 diabetes compared with the non-diabetic ECG group, with hazard ratios of 2.15 (1.82-2.53) and 1.92 (1.74-2.11) for internal and external validation, respectively.

Interpretation

In the non-diabetic group, those whose ECG was classified as diabetes by the DLM were at a higher risk of incident type 2 diabetes than those whose ECG was not. Additional clinical research on the relationship between the phenotype of ECG and diabetes to support the results and further investigation with tracked data and various ECG recording systems are suggested for future works.

Funding

National Research Foundation of Korea.

Meta-Analysis on the Association Between DPP-4 Inhibitors and Bone Mineral Density and Osteoporosis

Background Type 2 Diabetes Mellitus (T2DM) frequently coexists with osteoporosis and reduced bone mineral density (BMD). Dipeptidyl peptidase-4 inhibitors (DPP-4i), a class of antihyperglycemic agents, are commonly employed in T2DM treatment. However, the influence of DPP-4i on bone health remains unclear and debated. This meta-analysis is conducted to explore the relationship between the use of DPP-4i and changes in BMD, as well as the prevalence of osteoporosis among T2DM patients. Methods We conducted a comprehensive search in PubMed, Embase, and Cochrane Library and Web of Science databases for relevant studies published up until June 2023. Studies included in the meta-analysis were those investigating T2DM patients under DPP-4i treatment, and examining the effects on BMD and osteoporosis. Random-effects models and fixed-effect models were utilized to compute the pooled effects. Heterogeneity among the included studies was evaluated using I² statistics. Results This meta-analysis incorporated a total of 10 studies, encompassing a combined population of 214,541 individuals. The results from this meta-analysis indicated an increase in BMD following DPP-4i usage (SMD 0.15, 95 % confidence interval 0.03-0.26). Additionally, the risk of osteoporosis was significantly reduced (OR 0.90, 95 % confidence interval 0.86-0.94) with very low heterogeneity, recorded at 0 % and 53.0 % respectively. No publication bias was detected in the funnel plot, and sensitivity analyses affirmed the stability of the study's conclusions. Conclusion Our results offer valuable insights into the positive impact of DPP-4i on bone health in T2DM patients, contributing to informed clinical decision-making. These findings may inform the development of more comprehensive T2DM management strategies that account for bone health.

4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A simple fragility fracture risk score for type 2 diabetes patients: a derivation, validation, comparison, and risk stratification study

OBJECTIVES

The aims of this study were to develop and validate 2 simple scores for stratification of the risks of (1) any fragility (AF) and (2) major osteoporotic fracture (MOF) in type 2 diabetes (T2D) patients; we also compared the performance of these scores with that of the Fracture Risk Assessment Tool (FRAX) and its adjustments.

DESIGN AND METHODS

In this longitudinal cohort study, 1855 patients with T2D were enrolled from January 2015 to August 2019. Cox proportional hazard regression was used to model the 5-year risk of AF and MOF. These scores were internally validated using a bootstrap resampling method of 1000.

RESULTS

During a median follow-up of 5 years, 119 (6.42%) cases of AF and 92 (4.96%) cases of MOFs were identified. Both the concordance index (C-index) and calibration plots indicated improved identification performance using the newly established scores. Furthermore, these scores also showed improved outcomes regarding the decision curve analysis (DCA) and area under the curve (AUC) compared to the widely used FRAX and its derivatives. More importantly, these scores successfully separated T2D patients into risk groups according to significant differences in fracture incidence.

CONCLUSIONS

These novel scores enable simple and reliable fracture risk stratification in T2D patients. Future work is needed to validate these findings in external cohort(s).

Advanced glycation and glycoxidation end products in bone

Hyperglycemia and oxidative stress, enhanced in diabetes and aging, result in excessive accumulation of advanced glycation and glycoxidation end products (AGEs/AGOEs) in bone. AGEs/AGOES are considered to be "the missing link" in explaining increased skeletal fragility with diabetes, aging, and osteoporosis where increased fracture risk cannot be solely explained by bone mass and/or fall incidences. AGEs/AGOEs disrupt bone turnover and deteriorate bone quality through alterations of organic matrix (collagen and non-collagenous proteins), mineral, and water content. AGEs and AGOEs are also associated with bone fragility in other conditions such as Alzheimer's disease, circadian rhythm disruption, and cancer. This review explains how AGEs and AGOEs accumulate in bone and impact bone quality and bone fracture, and how AGES/AGOEs are being targeted in preclinical and clinical investigations for inhibition or removal, and for prediction and management of diabetic, osteoporotic and insufficiency fractures.

Effects of Incretin Therapy on Skeletal Health in Type 2 Diabetes-A Systematic Review

Diabetes poses a significant risk to bone health, with Type 1 diabetes (T1D) having a more detrimental impact than Type 2 diabetes (T2D). The group of hormones known as incretins, which includes gastric inhibitory peptide (GIP) and glucagon-like peptide 1 (GLP-1), play a role in regulating bowel function and insulin secretion during feeding. GLP-1 receptor agonists (GLP-1 RAs) are emerging as the primary treatment choice in T2D, particularly when atherosclerotic cardiovascular disease is present. Dipeptidyl peptidase 4 inhibitors (DPP-4is), although less potent than GLP-1 RAs, can also be used. Additionally, GLP-1 RAs, either alone or in combination with GIP, may be employed to address overweight and obesity. Since feeding influences bone turnover, a relationship has been established between incretins and bone health. To explore this relationship, we conducted a systematic literature review following the PRISMA guidelines. While some studies on cells and animals have suggested positive effects of incretins on bone cells, turnover, and bone density, human studies have yielded either no or limited and conflicting results regarding their impact on bone mineral density (BMD) and fracture risk. The effect on fracture risk may vary depending on the choice of comparison drug and the duration of follow-up, which was often limited in several studies. Nevertheless, GLP-1 RAs may hold promise for people with T2D who have multiple fracture risk factors and poor metabolic control. Furthermore, a potential new area of interest is the use of GLP-1 RAs in fracture prevention among overweight and obese people. Based on this systematic review, existing evidence remains insufficient to support a positive or a superior effect on bone health to reduce fracture risk in people with T2D. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

The impact of fasting plasma glucose variability on osteoporotic fractures

Purpose

To investigate the impact of FPG variability on osteoporotic fractures in the entire community population.

Methods

All participants were from the Kailuan Study. Participants completed three consecutive surveys from 2006-2007, 2008-2009, and 2010-2011. We excluded individuals with an osteoporotic fracture in or prior to the index year and those without complete FPG records at the first 3 examinations. All participants were followed from the date of the 3rd examination to the first occurrence of an endpoint event or December 31, 2021. According to the SD of FPG levels, the included subjects were divided into three groups. A Cox proportional hazards model was performed to further analyze the effect of different FPG-SD groups on the risk of osteoporotic fractures.

Results

Ultimately, the study population included 57295 participants. During a median follow-up time of 11.00 years, we documented 772 new osteoporotic fracture cases. When evaluating the FPG-SD level as a categorical variable, the HRs for osteoporotic fractures were 1.07 (95% CI: 0.89-1.29) for T2 and 1.32 (95% CI: 1.10-1.60) for T3 when compared with T1. We found that increased FPG variability was associated with a greater risk of osteoporotic fractures in people with diabetes than in those without diabetes (47% vs. 32%).

Conclusion

Increased FPG variability was an independent predictor of incident osteoporotic fracture, especially in individuals older than 50 years old, nonobese individuals, diabetes patients, and individuals with positive FPG-SD variability.

Validation of the clinical consensus recommendations on the management of fracture risk in postmenopausal women with type 2 diabetes

BACKGROUND AND AIMS

Bone fragility is recognized as a complication of type 2 diabetes (T2D). However, the fracture risk in T2D is underestimated using the classical assessment tools. An expert panel suggested the diagnostic approaches for the detection of T2D patients worthy of bone-active treatment. The aim of the study was to apply these algorithms to a cohort of T2D women to validate them in clinical practice.

METHODS AND RESULTS

The presence of T2D-specific fracture risk factors (T2D ≥ 10 years, ≥1 T2D complications, insulin or thiazolidinedione use, poor glycaemic control) was assessed at baseline in 107 postmenopausal T2D women. In all patients at baseline and in 34 patients after a median follow-up of 60.2 months we retrospectively evaluated bone mineral density and clinical and morphometric vertebral fractures. No patient was treated with bone-active drug. Following the protocols, 34 (31.8%) and 73 (68.2%) patients would have been pharmacologically and conservatively treated, respectively. Among 49 patients without both clinical fractures and major T2D-related risk factors, who would have been, therefore, conservatively followed-up without vertebral fracture assessment, only one showed a prevalent vertebral fracture (sensitivity 90%, negative predictive value 98%). The two patients who experienced an incident fracture would have been pharmacologically treated at baseline.

CONCLUSIONS

The clinical consensus recommendations showed a very good sensitivity in identifying T2D postmenopausal women at high fracture risk. Among those with treatment indication as many as 13% of patients experienced an incident fracture, and, conversely, among those without treatment indication no incident fractures were observed.

The interplay between diabetes mellitus and menopause: clinical implications

The menopausal transition is an impactful period in women's lives, when the risk of cardiovascular disease is accelerated. Similarly, diabetes mellitus profoundly impacts cardiovascular risk. However, the interplay between menopause and diabetes mellitus has not been adequately studied. The menopausal transition is accompanied by metabolic changes that predispose to diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), as menopause results in increased risk of upper body adipose tissue accumulation and increased incidence of insulin resistance. Equally, diabetes mellitus can affect ovarian ageing, potentially causing women with type 1 diabetes mellitus and early-onset T2DM to experience menopause earlier than women without diabetes mellitus. Earlier age at menopause has been associated with a higher risk of T2DM later in life. Menopausal hormone therapy can reduce the risk of T2DM and improve glycaemic control in women with pre-existing diabetes mellitus; however, there is not enough evidence to support the administration of menopausal hormone therapy for diabetes mellitus prevention or control. This Review critically appraises studies published within the past few years on the interaction between diabetes mellitus and menopause and addresses all clinically relevant issues, such as the effect of menopause on the development of T2DM, and the management of both menopause and diabetes mellitus.

Major osteoporosis fracture prediction in type 2 diabetes: a derivation and comparison study

The widely recommended fracture prediction tool FRAX was developed based on and for the general population. Although several adjusted FRAX methods were suggested for type 2 diabetes (T2DM), they still need to be evaluated in T2DM cohort.

INTRODUCTION

This study was undertaken to develop a prediction model for Chinese diabetes fracture risk (CDFR) and compare its performance with those of FRAX.

METHODS

In this retrospective cohort study, 1730 patients with T2DM were enrolled from 2009.08 to 2013.07. Major osteoporotic fractures (MOFs) during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Multivariate Cox regression with backward stepwise selection was used to fit the model. The performances of the CDFR model, FRAX, and adjusted FRAX were compared in the aspects of discrimination and calibration.

RESULTS

6.3% of participants experienced MOF during a median follow-up of 10 years. The final model (CDFR) included 8 predictors: age, gender, previous fracture, insulin use, diabetic peripheral neuropathy (DPN), total cholesterol, triglycerides, and apolipoprotein A. This model had a C statistic of 0.803 (95%CI 0.761-0.844) and calibration χ² of 4.63 (p = 0.86). The unadjusted FRAX underestimated the MOF risk (calibration χ² 134.5, p < 0.001; observed/predicted ratio 2.62, 95%CI 2.17-3.08), and there was still significant underestimation after diabetes adjustments. Comparing FRAX, the CDFR had a higher AUC, lower calibration χ², and better reclassification of MOF.

CONCLUSION

The CDFR model has good performance in 10-year MOF risk prediction in T2DM, especially in patients with insulin use or DPN. Future work is needed to validate our model in external cohort(s).

Fracture prediction tools in diabetes

PURPOSE OF REVIEW

Type 1 (T1D) and 2 diabetes (T2D) are associated with increased risk of fracture independent of bone mineral density (BMD). Fracture risk prediction tools can identify individuals at highest risk, and therefore, most likely to benefit from antifracture therapy. This review summarizes recent advances in fracture prediction tools as applied to individuals with diabetes.

RECENT FINDINGS

The Fracture Risk Assessment (FRAX) tool, Garvan Fracture Risk Calculator (FRC), and QFracture tool are validated tools for fracture risk prediction. FRAX is most widely used internationally, and considers T1D (but not T2D) under secondary osteoporosis disorders. FRAX underestimates fracture risk in both T1D and T2D. Trabecular bone score and other adjustments for T2D-associated risk improve FRAX-based estimations. Similar adjustments for T1D are not identified. Garvan FRC does not incorporate diabetes as an input but does includes falls. Garvan FRC slightly underestimates osteoporotic fracture risk in women with diabetes. QFracture incorporates both T1D and T2D and falls as input variables, but has not been directly validated in individuals with diabetes.

SUMMARY

Further research is needed to validate and compare available fracture prediction tools and their performance in individuals with diabetes.

Evaluation of Quality and Bone Microstructure Alterations in Patients with Type 2 Diabetes: A Narrative Review

Bone fragility is a common complication in subjects with type 2 diabetes mellitus (T2DM). However, traditional techniques for the evaluation of bone fragility, such as dual-energy X-ray absorptiometry (DXA), do not perform well in this population. Moreover, the Fracture Risk Assessment Tool (FRAX) usually underestimates fracture risk in T2DM. Importantly, novel technologies for the assessment of one microarchitecture in patients with T2DM, such as the trabecular bone score (TBS), high-resolution peripheral quantitative computed tomography (HR-pQCT), and microindentation, are emerging. Furthermore, different serum and urine bone biomarkers may also be useful for the evaluation of bone quality in T2DM. Hence, in this article, we summarize the limitations of conventional tools for the evaluation of bone fragility and review the current evidence on novel approaches for the assessment of quality and bone microstructure alterations in patients with T2DM.