Diabetes research and clinical practice最新文献

Background: Total contact cast (TCC) is the 'reference-standard' for off-loading plantar diabetic foot ulcers (DFU). Practical limitations, associated complications, and lack of patient acceptability, limits its widespread use. Posterior slab cast (PSC) may provide an alternate way of off-loading the foot that might be more acceptable, and better tolerated, by people with DFU.

Aim: To compare wound healing and foot related outcomes in people with plantar DFU using TCC or PSC for off-loading the foot.

Method: This was a parallel-group, open-label, single-centre randomized controlled trial. Ninety-nine adults with Type 2 diabetes (T2D) with a single neuropathic Wagner grade 2 or 3 plantar DFU were randomly assigned to receive either a PSC (n = 48) or a TCC (n = 51) for off-loading the foot. The primary endpoint was wound healing rate at 6 months. Secondary endpoints included reduction in ulcer surface area at 4 weeks, wound healing rate at 3 months, and patient satisfaction with either off-loading strategy.

Results: The wound healing rate of DFU at 6 months among subjects using PSC (72.9%) was significantly greater than that seen among those using TCC (49%) [HR: 1.3 (1.03-1.73) (P = 0.024)]. Similarly, the wound healing rate at 3 months was also greater among subjects using PSC (50%) as compared to those on TCC (25.5%) (P = 0.011). The percentage reduction of ulcer surface area at 4 weeks from baseline was significantly higher among subjects using PSC (63.2 ± 15.5%) as compared to those using TCC (55.6 ± 18.9%) (P = 0.040). Patient satisfaction, assessed using the Likert scale, was significantly better among subjects using PSC when compared to those using TCC (4.0 ± 1.2 vs 2.5 ± 1.1 respectively, P < 0.001) CONCLUSION: Compared to TCC, PSC was more effective in healing neuropathic plantar DFUs, likely due to its less cumbersome application technique and providing easier access for wound monitoring and intervention when required. Further studies are needed to validate these results.

Hypoglycemia unawareness is characterized by a reduction in autonomic and neuroglycopenic signals of hypoglycemia; therefore, it is hardly perceivable. Glucagon-like peptide-1 (GLP-1) plays a critical role in glucose metabolism. Experimental model of recurrent hypoglycemia in type 1 diabetes mellitus suggests that increased intestinal GLP-1 expression is associated with impaired counterregulatory responses. However, whether incretin-based drugs or elevated intestinal GLP-1 produce similar impairments, in patients with type 1 and 2 diabetes mellitus and preexisting hypoglycemia-associated autonomic failure, remain incompletely understood. Clinical applications of incretin-based therapies might require caution, especially in sensitive patients, because of GLP-1-mediated disruption of hypoglycemic counterregulation. The impaired counterregulatory response to hypoglycemia could be because of GLP-1's actions, such as glucagon suppression, reduced sympathoadrenal signaling, modulatory effects on brain signaling during hypoglycemia, delayed gastric emptying, and among others. These factors might collectively contribute to abrogation of counterregulatory mechanisms to hypoglycemia, particularly when GLP-1 is overactive. This impairment should be carefully considered when managing patients with diabetes, especially hypoglycemic-sensitive individuals utilizing incretin-based medications chronically or when these medications are combined with insulin or sulfonylureas. This review brings together the complex role of GLP-1 in disrupting hypoglycemia counterregulation, the related mechanistic insights, and new therapeutic accountabilities pertaining to incretin-based medications.

Background: Guidelines differ on how often to monitor lipid profiles in adults with type 2 diabetes mellitus (T2DM) without established cardiovascular disease (CVD), and randomized evidence is lacking. This study aimed to optimise lipid monitoring intervals for type-2 diabetes mellitus (T2DM) patients at various LDL-C levels.

Methods: This is a target trial emulation study using territory-wide electronic health records from the Hong Kong Hospital Authority. Adults with T2DM and no prior CVD who had ≥2 lipid panel tests within any 12‑month window during 2009-2012 were enrolled. The index date was the date of the second lipid test. Participants were stratified by baseline LDL‑C (<1.8, 1.8-2.59, ≥2.6 mmol/L). Within each LDL‑C stratum, we emulated a three-arm target trial using a clone-censor-weight (CCW) approach to compare three monitoring strategies: monitoring lipid panels every (1) 2-8 months, (2) 9-15 months, or (3) 16-24 months. Pooled logistic regression was used to estimate hazard ratios (HRs) for all‑cause mortality and major CVD associated with each monitoring strategy. Follow‑up continued until the first occurrence of an outcome, death, or 31 December 2021.

Results: For LDL-C < 1.8 mmol/L, extending monitoring intervals to 16-24 months were not associated with higher risks of mortality or CVD risk compared to 2-8 months (HR [95% CI]: mortality: 1.094 [0.948, 1.263]; CVD: 1.002 [0.846, 1.187]). For the group with LDL-C levels of 1.8-2.59 mmol/L, monitoring of the lipid profile every 16-24 months was associated with higher mortality risk compared to monitoring every 2-8 months (HR [95% CI]: 1.154 [1.069, 1.245]). For LDL-C ≥ 2.6 mmol/L, monitoring every 9-15 months was associated with higher risks of mortality and CVD compared to 2-8 months (HR [95% CI]: mortality: 1.263 [1.174, 1.359]; CVD: 1.060 [1.017, 1.105]).

Conclusions: Lipid monitoring frequency in T2DM may be individualized by baseline LDL‑C level, with intervals of approximately 16-24, 9-15, and 2-8 months representing minimum frequencies.

Aims: To determine if tight glycemic control in gestational diabetes mellitus (GDM) reduces adverse outcomes compared to less tight targets.

Methods: In a single-center, open-label randomized controlled trial, 650 women with GDM (singleton pregnancies, 12-31 weeks' gestation) were randomized to tight (fasting < 5.1 mmol/L, 1-h postprandial < 7.0 mmol/L) or less tight (fasting < 5.3 mmol/L, postprandial < 7.8 mmol/L) targets. The primary outcome was the incidence of large-for-gestational-age (LGA) infants. Secondary outcomes included measures of maternal and neonatal health, analyzed by intention-to-treat.

Results: Of 650 enrolled women, 626 (96.3%) completed the trial with primary outcome data. The tight-target group had a lower incidence of LGA (19.2% vs. 26.5%; adjusted relative risk (aRR) 0.61, 95%CI 0.42-0.89; p = 0.010), lower cesarean rates (23% vs. 29.9%; aRR 0.63; p = 0.012), and reduced gestational weight gain (10.1 vs. 10.7 kg; p = 0.006). Insulin use was higher with tight targets (32.6% vs. 21.6%; aRR 1.67; p = 0.005). Serious complications and maternal hypoglycemia rates were low and comparable.

Conclusion: Tight glycemic targets in GDM lower the risk of LGA births, cesarean delivery, and excess maternal weight gain without increasing severe adverse events, though they necessitate more frequent insulin therapy.

Objective: To investigate the diabetes-specific association between non-HDL/HDL cholesterol ratio (NHHR) and urinary albumin-to-creatinine ratio (UACR), and its nonlinear threshold effect in chronic kidney disease (CKD) stages.

Methods: This cross-sectional study included 10,613 U.S. adults(aged 20-70 years, estimated glomerular filtration rate ≥ 30 mL/min/1.73 m²) from NHANES 2015-2020. NHHR was calculated as the difference between total cholesterol and HDL-C divided by HDL-C. To explore the relationship between NHHR and UACR, a multivariable logistic regression model, smoothed curve fitting and subgroup analyses were employed.

Results: Each 1-unit NHHR increase elevated UACR by 4.46 mg/g overall(95% CI: 1.13-7.78, P = 0.009). Crucially, NHHR-UACR association wasexclusive to diabetics(β = 23.56 mg/g, 95% CI: 8.59-38.54, P < 0.001) with no significance in non-diabetics(P for interaction < 0.001). A nonlinear pattern emerged and intensified with declining renal function: Stage 1 showed a linear relationship(P = 0.426), Stage 2 demonstrated marginal nonlinearity(P = 0.031), and Stage 3 displayed a markedly nonlinear relationship(P < 0.001),characterized by an accelerated increase in UACR beyond an NHHR of approximately 3.5. Effect modification was significant by ethnicity (stronger in Non-Hispanic Blacks, P = 0.016) and sex(greater in females, P = 0.048).

Conclusion: NHHR associates with albuminuriaexclusively in diabetesand exhibits anonlinear pattern in CKD stage 3. These findings indicate diabetes-specific renal injury patterns and CKD stage-dependent pathophysiological mechanisms.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation is the most commonly used equation for estimating glomerular filtration rate (GFR) in clinical practice. However, recent studies have questioned the accuracy of this equation in estimating GFR in people with diabetes. We conducted a comprehensive review of existing literature on the role of artificial intelligence and machine learning in estimating GFR and the progression of chronic kidney disease (CKD), specifically in people with diabetes. Artificial intelligence, including machine learning and image-based deep learning algorithms have shown promise in improving the accuracy of GFR estimation. Artificial Neural Networks is the commonly used machine learning algorithm in GFR estimation studies. Other artificial intelligence methods include random forests, support vector machines, and ensemble learning models. Many of the studies included in this review reported that artificial intelligence-based GFR estimation equations exhibit lower bias, as well as higher precision and accuracy. However, these findings are not consistent across all the studies. In addition, currently available studies are limited to smaller sample sizes and majority of the studies are from selected countries or populations. Therefore, before implementing these methods in clinical practice, it is essential to validate them on larger sample sizes and diverse patient populations.