Diabetes research and clinical practice最新文献

Aim

Methods

Results

Conclusion

Background

Methods

Results

Conclusions

Aim

There is a bidirectional relationship between glucose control and sleep quality and timing in type 1 diabetes (T1D). The aim of the study was to investigate the sleep quality and the glucose metrics in people with T1D at the seasonal clock adjustment.

Methods

This observational study retrospectively compared the continuous glucose monitoring (CGM) derived metrics and sleep quality observed before (Time 0) and after (Time 1) transition in autumn and before (Time 2) and after (Time 3) transition in spring. We included adults with T1D, treated with CGM systems, who completed the Pittsburgh Sleep Quality Index questionnaire. The main outcome measure was the change in glucose monitoring indicator (GMI), time in range (TIR), time above range (TAR) and time below range.

Results

Sixty-two participants showed no changes in sleep quality at time transitions. GMI values increased during both time transitions and the percentage of TIR decreased from Time 0 to Time 1 and from Time 2 to Time 3. The percentage of level 2 TAR increased during the observation.

Conclusions

At similar level of sleep quality, adults with T1D underwent the worsening of most of CGM-derived glucose control metrics during the transition time.

Aims

To determine the prevalence and patterns of diabetes distress, and evaluate the differences in health outcomes between profiles.

Methods

This cross-sectional study included 330 adults with T2DM and overweight/obesity. The participants completed questionnaires on diabetes distress, sleep quality, self-efficacy, depression, anxiety and positive and negative affect. A cluster analysis was performed to identify different patterns of diabetes distress and one-way ANOVA was used to investigate the differences in physical and psychological outcomes between profiles.

Results

30.6% of patients were identified as moderately to highly distressed, with the regimen-related distress found to be the most prominent. The Cluster analysis revealed four distinct clusters: (1) “comprehensively exhausted profile”; (2) “strained profile”; (3) “high internal anguish profile”; (4) “unperturbed profile”. The measures of fasting blood glucose (FBG), glycated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, sleep quality, depression, anxiety, positive and negative affect and self-efficacy differ between clusters.

Conclusions

This study identified important differences that existed in patterns of diabetes distress among people with T2DM and overweight/obesity, and this variation can be utilized to tailor intervention strategies to the particular needs of different subgroups within individuals with T2DM.

Aims

Methods and results

Conclusions

Background

Post‑acute pancreatitis prediabetes/diabetes mellitus (PPDM‑A) is one of the common sequelae of acute pancreatitis (AP). The aim of our study was to build a machine learning (ML)-based prediction model for PPDM-A in hypertriglyceridemic acute pancreatitis (HTGP).

Methods

We retrospectively enrolled 165 patients for our study. Demographic and laboratory data and body composition were collected. Multivariate logistic regression was applied to select features for ML. Support vector machine (SVM), linear discriminant analysis (LDA), and logistic regression (LR) were used to develop prediction models for PPDM-A.

Results

65 patients were diagnosed with PPDM-A, and 100 patients were diagnosed with non-PPDM-A. Of the 84 body composition-related parameters, 15 were significant in discriminating between the PPDM-A and non-PPDM-A groups. Using clinical indicators and body composition parameters to develop ML models, we found that the SVM model presented the best predictive ability, obtaining the best AUC=0.796 in the training cohort, and the LDA and LR model showing an AUC of 0.783 and 0.745, respectively.

Conclusions

The association between body composition and PPDM-A provides insight into the potential pathogenesis of PPDM-A. Our model is feasible for reliably predicting PPDM-A in the early stages of AP and enables early intervention in patients with potential PPDM-A.

Aims

To examine the association of daily PA levels and sedentary behaviour with body composition, estimated insulin sensitivity, and arterial stiffness in adults with type 1 diabetes (T1D).

Methods

Cross-sectional study in adults with T1D (n = 54). PA levels (daily steps, and time in moderate-to-vigorous intensity PA (MVPA)) and sedentary behaviour were measured using accelerometry for 7 days (McRoberts® DynaPort MoveMonitor). Cardiopulmonary exercise test for VO_2max. Anthropometrics were collected, and body composition (total and % of fat mass (FM_tot, FM_%), total and % of lean mass (LM_tot, LM_%), and estimated visceral adipose tissue (VAT)) volume was assessed with dual energy X-ray-absorptiometry (DXA). Estimates of insulin sensitivity were determined (estimated glucose disposal rate (eGDR) and total daily insulin dose). Arterial stiffness was assessed with carotid-femoral pulse wave velocity (cf-PWV (m/s); SphygmoCor®).

Results

Lower 10-years HbA1_c associated moderately with all PA measures. Favourable moderate associations were also found between PA measures and BMI, waist, VAT but not FM and LM. PA measures were favourably associated with a lower total daily insulin dose and higher eGDR. All PA parameters associated moderately with cf-PWV however not independent from traditional risk factors. VO_2max was inversely associated with cf-PWV independent of age, T1D duration and 24-hour mean blood pressure.

Conclusions

Higher levels of PA, lower sedentary behaviour and greater exercise capacity are favourably associated with long-term glycaemic control, body composition, insulin dosage, estimated insulin sensitivity and arterial stiffness in adults with T1D. Therefore, regular PA and limiting sedentary time should be encouraged to improve metabolic and cardiovascular health in this population. Future longitudinal studies should explore mutual interactions and synergistic effects of PA on these outcomes.

Background

Population-based studies of ideal cardiovascular health (CVH) and gestational diabetes mellitus (GDM) are scarce.

Methods

We conducted a cross-sectional analysis of 2007–2018 National Health Examination and Nutrition Survey women aged ≥ 20 years, who had data on Life’s Simple 7 (LS7) metrics and self-reported GDM history. Each LS7 metric was assigned a score of 0 (non-ideal) and 1(ideal) and summed to obtain total ideal CVH scores (0–7). We used logistic regression models to assess associations between LS7 ideal CVH scores (0–7) and GDM history, accounting for socio-demographic factors.

Results

Among 9199 women (mean age: 46 years, 8 % with a GDM history), there was a progressive decrease in the odds of past GDM history across increasing ideal CVH scores. Compared to females with 0–1 ideal CVH scores, females with ideal CVH scores of 3, 4 and 5–7 had an associated 39 % lower [odds ratio: 0.61 (95 % CI: 0.41–0.90)], 50 % lower [0.50 (0.33–0.76)] and 66 % lower [0.34 (0.20–0.56)] odds of past GDM history, respectively. There were notable racial/ethnic and citizenship/nativity differences in these associations.

Conclusions

Women with higher ideal CVH scores had lower odds of GDM history. Our findings underscore the importance of optimizing cardiometabolic health among women with GDM history.

Diabetic foot ulcer (DFU) is a common and serious complication among diabetic patients, and its incidence and difficulty in treatment have placed large burdens on patient health and quality of life. Diabetic foot tissue typically exhibits chronic wounds, ulcers, or necrosis that are difficult to heal, are prone to infection, and, in severe cases, may even lead to amputation. Recent studies have shown that microRNAs (miRNAs) play key roles in the development and healing of DFUs. miRNAs are a class of short noncoding RNA molecules that regulate gene expression to affect cellular functions and physiological processes. miRNAs may be involved in the development of DFUs by regulating cell growth, proliferation, differentiation and apoptosis. miRNAs can also participate in the healing and recovery of DFUs by regulating key steps, such as inflammation, angiogenesis, cell migration and proliferation, tissue repair and matrix remodeling. Therefore, altering the pathological processes of diabetic foot by modulating the expression of miRNAs could improve the recovery and treatment outcomes of patients. This review provides new insights and perspectives for the treatment of DFUs by summarizing the roles of miRNAs in the development and healing of DFUs and the mechanisms.

Aim

Type 2 diabetes (T2D) is a common chronic disease that disproportionally affects groups with a low socioeconomic position (SEP). This study aimed to examine associations between childhood SEP and incident T2D, independent of adult SEP.

Methods

Longitudinal data from The Maastricht Study were used (N=6,727, 55.2 % female, mean (SD) age 58.7(8.7) years). Childhood SEP was determined by asking for the highest completed educational level for the father and mother and childhood income inadequacy. Adult SEP was determined by highest completed educational level, equivalent household income, and occupational position. Incident T2D was self-reported yearly (up to 12 years of follow-up). Associations were studied with Cox regression analyses.

Results

In participants without T2D at baseline, 3.7% reported incident T2D over 8.2 (median) years of follow-up. Incident T2D was most common in people with low childhood and adult SEP and lowest in those with high childhood and adult SEP (1.7 vs. 7.5 per 1,000 person years). The association between childhood SEP and incident T2D was mainly explained by adult SEP, except for childhood income inadequacy which was independently associated with incident T2D.

Conclusion

Socioeconomic inequalities in childhood and adulthood are risk factors for incident T2D. More attention is needed to reduce childhood poverty and improve adult SEP to reduce the T2D risk.