Diabetes-Metabolism Research and Reviews最新文献

Background and aim: Diabetic neuropathy (DN) is a recognised risk factor for fragility fractures. However, the mechanisms linking DN, bone health, and falling risk remain unclear. We aimed to assess bone health and risk of falls, with their contributing factors, in young elderly patients with type 2 diabetes (T2D) and mild-to-moderate DN.

Methods: We enrolled 144 subjects with T2D, excluding those with severe DN (neuropathy disability score -NDS- ≥ 9) or fracture history. Clinical and biochemical data were collected, including surrogate markers of insulin resistance, such as the triglycerides/HDL (TG/HDL) ratio and triglycerides/glucose (TyG) index. Bone mineral density (BMD) and trabecular bone score (TBS) were evaluated using DXA scans. Falls were self-recorded prospectively over 4 years using diaries.

Results: Subjects with DN (27%) had higher BMI (p = 0.036), fasting blood glucose (p = 0.04), serum triglycerides (p = 0.016), TG/HDL ratio (p = 0.012) and TyG index (p = 0.003) compared with those without DN. After adjustment for gender, age, BMI, HbA1c, TyG index and TG/HDL ratio, subjects with DN showed significantly lower BMD at the femoral neck (0.702 [0.638-0.850] g/cm² vs. 0.789 [0.717-0.860] g/cm², p = 0.015) and total femur (0.890 [0.820-1.055] g/cm² vs. 0.983 [0.889-1.076] g/cm², p = 0.027). No differences were observed in spine BMD or TBS. However, TBS was negatively correlated with the TG/HDL ratio (r = -0.215, p = 0.013) and visceral adipose tissue (r = -0.310, p < 0.001). After 4 years of follow-up, subjects with painful neuropathy at baseline had a higher rate of falls (p = 0.011).

Conclusion: DN is associated with decreased BMD and increased risk of falls. Among factors associated with DN, insulin resistance was also associated with decreased bone quality.

Aims: This study aims to evaluate the predictive performance of clinical characteristics and beta-cell function markers for future insulin requirements in Chinese individuals with type 2 diabetes who were not insulin deficient.

Materials and methods: A prospective cohort of 2421 individuals with type 2 diabetes and fasting plasma C-peptide ≥ 0.25 nmol/L (1996-2012) was followed until 2019 for insulin requirement, defined as insulin initiation or two consecutive HbA1c ≥ 8.5% while on at least two non-insulin glucose-lowering drugs. Cox regression with stepwise selection was used to identify predictors and derive a clinical risk score. Model calibration was assessed using the Hosmer-Lemeshow test, and discrimination using the Harrell's C-index and area under the receiver operating characteristic curve (AUC) at one, five and 10 years.

Results: Over a median follow-up of 10.2 (IQR 4.0-14.1) years, 1143 individuals progressed to insulin requirements. Younger age at diabetes diagnosis, male sex, poorer glycaemic control, kidney complications and greater use of non-insulin glucose-lowering drugs were identified as independent predictors. The clinical risk score demonstrated better discrimination (C-index: 0.729, AUCs: 0.829 at 1 year, 0.792 at 5 years, 0.779 at 10 years) than fasting plasma C-peptide (C-index: 0.532, AUCs: 0.502, 0.553, 0.537), C-peptide-to-glucose ratio (C-index: 0.560, AUCs: 0.660, 0.572, 0.571) and HOMA2-%B (C-index: 0.618, AUCs: 0.734, 0.651, 0.639) (all p < 0.001). Adding fasting plasma C-peptide or HOMA2-%B to the clinical model did not significantly improve its predictive performance.

Conclusions: Clinical characteristics outperformed fasting beta-cell function markers in predicting insulin requirements in non-insulin-deficient type 2 diabetes.

Aims: Diabetic peripheral neuropathy (DPN) often coexists with sudomotor dysfunction, resulting in an increased risk of diabetic foot. This study aimed to explore an efficient method for early diagnosis of DPN by establishing a quantitative Neuropad.

Methods: We recruited 518 patients with type 2 diabetes. Neuropathy Symptoms Score (NSS) combined with Neuropathy Disability Score (NDS) was used to assess distal symmetrical peripheral neuropathy (DSPN). The area under the ROC curve (AUROC), sensitivity, and specificity were used to compare the diagnostic efficacy of quantitative Neuropad (the change rate of the chromatic aberration value per minute) and two types of visual Neuropad (visual Neuropad A: whether the time to complete colour change within 10 min, visual Neuropad B: the time to complete colour change) for DPN.

Results: We did not observe very good diagnostic efficacy of Neuropad (visual Neuropad A and B: 0.59 and 0.64, quantitative Neuropad AUROC: 0.62-0.64) when using standard DSPN diagnostic criteria (NDS 6-12 or NDS 3-5 combined with NSS 5-9). When DPN was assessed by NSS + NDS ≥ 4, visual Neuropad B improved the specificity (AUROC 0.72, 67.00%, specificity 71.70%) by extending the detection time compared with visual Neuropad A (AUROC 0.62, sensitivity 81.80%, specificity 41.70%). Quantitative Neuropad significantly improved the diagnostic effect (AUROC 0.81, sensitivity 80.0%, specificity 76.3%) and reduced the detection time (4 min).

Conclusions: This study provides a new quantitative Neuropad, which has great potential to be an extremely useful diagnostic tool for early screening of sudomotor dysfunction in the clinical practice.