Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy最新文献

Aim: The research examined the correlation between the weight-adjusted waist index (WWI) and periodontal disease, as well as the intermediary influence of triglyceride glucose (TyG) index-related indicators, utilizing a health examination dataset.

Methods: This cross-sectional study included 39,522 subjects from health check-up database of Shanghai Health and Medical Center. The WWI was determined by applying a formula that includes dividing the waist circumference (WC) by the body weight's square root. Periodontitis diagnosis followed the Centers for Disease Control and Prevention and American Academy of Periodontology (CDC/AAP) classification. The correlation between the WWI and periodontitis was investigated through multivariate logistic regression and smoothing curve fitting. Subgroup analysis and interaction tests were also performed to verify the stability of the results. A mediation analysis was conducted to quantify the direct and indirect influences mediated by the TyG-related indicators [TyG, TyG -body mass index (TyG-BMI), TyG -waist-to-height ratio (TyG-WHtR), and TyG-waist circumference (TyG-WC)].

Results: Multivariable logistic regression analysis revealed the positive association of WWI and periodontitis (OR=1.37, 95% CI: 1.30-1.43). Compared to those in the lowest quartile of WWI, participants in the highest quartile exhibited a 82% higher likelihood of periodontitis (OR=1.82, 95% CI: 1.69-1.96). Subgroup analysis and interaction tests revealed that this positive correlation was consistent in gender, BMI, WC, smoking, drinking, hypertension, and dyslipidemia (P for interaction > 0.05), with some variations noted by age and diabetes status (P for interaction<0.05). Mediation analysis showed that the proportions mediated by TyG, TyG-BMI, TyG-WC, and TyG-WHtR on the association of WWI and periodontitis risk were 13.13%, 6.30%, 16.46% and 19.79%, respectively.

Conclusion: A higher WWI in Chinese adults was linked to an increased likelihood of periodontitis, and this correlation could be partially explained by elevated levels of TyG index-related indicators.

Background and aims: Existing research suggests that low muscle mass is independently associated with carotid atherosclerosis, but its relationship with lower extremity arterial atherosclerosis in type 2 diabetes mellitus (T2DM) patients remains unclear. This study aims to investigate the association between low skeletal muscle mass and lower extremity arterial atherosclerosis in T2DM patients, in hopes of providing a scientific basis for early diagnosis and treatment.

Methods: This cross-sectional study recruited a total of 276 patients with T2DM who underwent bioelectrical impedance analysis, lower limb artery ultrasonography, brachial-ankle pulse wave velocity(baPWV) arterial stiffness measurement, and blood tests. An skeletal muscle index (SMI) < 7.0kg/m2 in men and an SMI< 5.7kg/m2 in women were defined as low skeletal muscle mass. Lower limb atherosclerosis was defined as the presence of atherosclerotic plaques in the lower extremity arteries.

Results: In our study of 276 T2DM patients, 224 (81.1%) presented with lower limb atherosclerosis: 194 (70.2%) with simple lower limb arterial plaques, 15 (5.4%) with lower limb arterial stenosis, and 15 (5.4%) with lower limb arterial occlusion. 52 (18.8%) were diagnosed with low skeletal muscle mass. Logistic regression analysis indicated the risk of having overall lower limbs atherosclerosis increased with the prevalence of low skeletal muscle (OR= 6.175,95% CI 1.328-28.711); Patients with a low skeletal muscle mass had a higher prevalence of simple arterial plaque (OR= 6.225,95% CI 1.339-28.935) and arterial occlusion (OR=12.345,95% CI 1.221-124.808); after the adjustment for clinical risk factors. Spearman's analysis showed significant negative correlations between total-P1NP and baPWV (r=-0.166, p=0.008), N-MID and baPWV (r=-0.163, p=0.009), and β-CTX and baPWV (r=-0.141, p=0.024).

Conclusion: Low muscle mass is independently associated with an increased risk of having lower limb atherosclerosis in T2DM patients. And there may be some relationship between BTMs and arteriosclerosis of the lower limb atherosclerosis in T2DM.

Objective: Diabetic foot ulcer (DFU) and related amputation significantly contribute to morbidity rates. The objective of this study was to assess the risk factors correlated with amputation in Chinese patients with DFU.

Methods: A prospective study was implemented on DFU patients at Third Affiliated Hospital of Anhui Medical University from February 2016 to May 2024. Patients were categorized into two groups based on whether they underwent amputation: the amputation group (n = 33) and the non-amputation group (n = 29). A comparative analysis was conducted between two groups, focusing on demographic data, disease characteristics, and laboratory indicators. Binary and multivariate logistic regressions were employed to evaluate the risk factors associated with amputation. Receiver Operating Characteristic curve analysis was used to assess the risk factors in predicting amputation in patients with DFU.

Results: The incidence of history of amputation, duration of diabetes in the amputation group were significantly increased compared to the non-amputation group (P < 0.05). On the contrary, the red blood cell count, hemoglobin level, and hematocrit in the amputation group were significantly lower compared to the non-amputation group (P < 0.05). Moreover, in the bi-variable logistic regression analysis, the duration of diabetes, duration of DFU, history of amputation, and hemoglobin levels were significantly associated with amputation (P < 0.05). After controlling potential confounding factors in multiple logistic regression analysis, duration of DFU was identified as a determining factor for amputation (P < 0.05). Additionally, the values for the area under curve (AUC) in relation to the duration of diabetes, duration of DFU, history of amputation, and a combined panel in predicting the occurrence of amputation in patients with DFU were 0.890, 0.868, 0.730, and 0.916, respectively.

Conclusion: Our findings indicate that duration of DFU is an independent risk factor for amputation in patients with DFU.

[This corrects the article DOI: 10.2147/DMSO.S450994.].

Purpose: To investigate the relationship between obesity indices and sarcopenia in postmenopausal patients with type 2 diabetes mellitus (T2DM) at different body mass index (BMI) levels.

Patients and methods: This retrospective cross-sectional study included 298 hospitalized postmenopausal women diagnosed with T2DM. We collected demographic, biochemical, and anthropometric data on each subject. Body composition was measured using dual-energy X-ray absorptiometry (DXA), and skeletal muscle mass index (SMI) and body fat percentage (%BF) were calculated. According to BMI stratification, the patients were divided into normal group A (18.5 kg/m²≤BMI < 24 kg/m²), overweight group B (24.0 kg/m²≤BMI < 28 kg/m²), and obesity group C (28.0 kg/m² ≤BMI < 35 kg/m²).

Results: From group A to group C, SMI (5.21±0.56 vs 5.48±0.56 vs 6.03±0.69) increased gradually (P < 0.05). Logistic regression analysis indicated that for each 1-unit increase in BMI, the risk of sarcopenia decreased by 63.2% (OR=0.368, 95% CI 0.215-0.629, P=0.000) in group A. Age (OR=1.077, 95% CI 1.015-1.144, P=0.015) and %BF (OR=1.094, 95% CI 1.010-1.186, P=0.028) increased the risk of sarcopenia by 1.077 and 1.094 times, respectively, in group B. While every 1-unit increase in BMI, the risk of sarcopenia decreased by 35% (OR=0.650, 95% CI 0.430-0.983, P=0.041) in group B. %BF (OR=1.459, 95% CI 1.093-1.949, P=0.010) increased the risk factors of sarcopenia by 1.459 times in group C.

Conclusion: In postmenopausal patients with T2DM, BMI had a protective effect on the occurrence of sarcopenia within a certain range, and with the increase of BMI, the risk of sarcopenia was increasing by increased %BF levels in overweight and obese patients.

Background: Patients with chronic heart failure (CHF) and type 2 diabetes mellitus (DM) are prone to insulin resistance and malnutrition, both of which are significant prognostic factors for CHF. However, the combined effect of the triglyceride-glucose index (TyG index) and prognostic nutritional index (PNI) on the mortality risk in patients with CHF and type 2 DM has not yet been studied.

Methods: We enrolled 3,315 patients with CHF and type 2 DM. We used a multivariate Cox regression model to assess hazard ratios (HRs) with 95% confidence intervals (CIs) for mortality risk based on TyG index and PNI levels. Furthermore, we constructed a novel index, the insulin resistance-nutritional index (IRNI), defined as TyG index/Ln (PNI), and evaluated its prognostic significance.

Results: During follow-up, 1,214 deaths occurred. Participants with a high TyG index and non-high PNI had a significantly higher mortality risk compared to those with a non-high TyG index and high PNI, with an adjusted HR of 1.91 (95% CI, 1.57-2.32). The multivariate Cox regression analysis revealed HRs for all-cause and cardiovascular deaths of 1.93 (95% CI, 1.66-2.26; P < 0.001) and 2.50 (95% CI, 2.05-3.06; P < 0.001), respectively, when comparing the highest and lowest IRNI tertiles. IRNI's predictive power was stronger in groups with higher adapted Diabetes Complications Severity Index scores (P for interaction < 0.05). Additionally, adding IRNI to the baseline risk model significantly improved predictive performance, showing a greater effect compared to the TyG index or PNI.

Conclusion: IRNI, a novel and composite index reflecting insulin resistance and nutritional status, emerges as a potentially valuable prognostic marker for patients with CHF and type 2 DM.

Purpose: Diabetic peripheral neuropathy (DPN) is a prevalent chronic complication of diabetes which is linked to chronic hyperglycemia and glycemic variability. This study aimed to investigate the association between the glycemia risk index (GRI) and DPN in patients with type 2 diabetes mellitus (T2DM) using continuous glucose monitoring (CGM) data.

Patients and methods: From 2019 to 2023, 862 adults diagnosed with T2DM were enrolled at a tertiary care diabetes center in Ningbo, China. The medical history and laboratory parameters were recorded. Neurophysiological examinations were performed to evaluate DPN. The CGM data were recorded for 14 days, and the GRI was calculated based on these data. Multivariate logistic regression analyses were conducted to assess the odds ratio (OR) for DPN with an increased GRI.

Results: The prevalence of DPN in the ascending GRI quartiles was 41.6%, 47.9%, 49.1%, and 59.5%, respectively (P for trend < 0.001). In the multivariable logistic analysis, the highest GRI quartile exhibited a 63% greater risk of DPN (OR 1.631, 95% CI: 1.071 to 2.484, P = 0.023) than the lowest quartile after adjusted for age, sex, body mass index, diabetes duration, blood pressure, creatinine, urinary albumin-to-creatinine ratio, lipid profile and glycated hemoglobin.

Conclusion: High GRI levels, as measured by CGM, were associated with a greater likelihood of DPN in T2DM patients.

Objective: To investigate the diagnostic value of urinary Wilms' tumour-1 (WT-1) and mu-glutathione S-transferase (Mu-GST) gene expression for detecting kidney injury in type 2 diabetes mellitus (T2DM).

Methods: Patients treated between October 2022 and June 2023 were divided into two groups: a diabetic nephropathy (DN) group (105 patients) and a diabetes mellitus (DM) group (100 patients). Additionally, 100 healthy individuals undergoing routine medical check-ups were selected as the control group. The urinary albumin/creatinine ratio (ACR), as well as urinary WT-1 and Mu-GST expression levels, were measured. The sensitivity and specificity of these markers for predicting renal injury were evaluated.

Results: The levels of ACR, WT-1 and Mu-GST in the DN group were significantly higher than those in the DM and control groups. The ACR in the DM group was also significantly higher than that in the control group (P < 0.05), and WT-1 and Mu-GST gene expression levels demonstrated a positive correlation with ACR (r = 0.391 and 0.342, respectively). The sensitivity and specificity of WT-1 were 74% and 95%, respectively, whereas those of Mu-GST were 70% and 96%, respectively. The combined detection of WT-1 and Mu-GST yielded a sensitivity of 82% and a specificity of 97%.

Conclusion: The levels of WT-1 and Mu-GST gene expression are closely related to T2DM kidney injury, helping to identify the location of kidney injury to some extent, which provides valuable information for the clinical diagnosis and treatment of kidney injury.

Purpose: Gastroesophageal reflux disease (GERD) is a common complication after laparoscopic sleeve gastrectomy (LSG); This study aimed to construct a model that can predict the incidence of GERD after LSG by exploring the correlation between the results of high-resolution esophageal manometry (HREM) and the incidence of GERD after LSG.

Patients and methods: We collected the clinical data of patients who had undergone HREM before bariatric surgery from September 2013 to September 2019 at the bariatric center of our hospital. The Gerd-Q scores during the postoperative follow-up were collected to determine the incidence of GERD. A logistic regression analysis was performed to explore the correlation of the HREM results and general clinical data with the incidence of GERD after LSG.

Results: The percentage of synchronous contractions, lower esophageal sphincter (LES) resting pressure, and history of smoking were correlated with the development of GERD after LSG, with the history of smoking and percentage of synchronous contractions as risk factors and LES resting pressure as a protective factor. The training set showed an area under the ROC curve (AUC) of the nomogram model of 0.847. The validation set showed an AUC of 0.761. The decision and clinical impact curves showed a high clinical value for the prediction model.

Conclusion: The HREM results correlated with the development of GERD after LSG, with the percentage of synchronous contractions and LES resting pressure showing predictive value. Combined with the history of smoking, the predictive model showed a high confidence and clinical value.