Background. The relationship between malnutrition and diabetic retinopathy (DR) is still unclear. The purpose of this study is to investigate the relationship between malnutrition and DR in type 2 diabetic patients. Methods. A cross-sectional study was conducted on 612 patients with type 2 diabetes mellitus. Four malnutrition assessment tools: Global Leadership Initiative on Malnutrition (GLIM) criteria, controlling nutritional status (CONUT), nutritional risk index (NRI), and prognostic nutritional index (PNI), were applied to assess the nutritional status of the study population. The association between malnutrition and DR was examined using multivariable logistic regression and ordered logistic regression. Results. The proportion of malnutrition varied from 10.0 to 34.3 in total patients and from 16.3 to 45.1 in DR patients across the assessment tools. DR patients were more likely to be malnourished than patients without DR. The adjusted odds ratios (aOR) and 95 confidence interval (CI) for DR of malnutrition defined by different tools were 1.86 (1.01-3.14) for GLIM criteria, 1.67 (1.04-2.70) for NRI, and 2.24 (1.07-4.69) for PNI. The aOR and 95 CI for the severity of DR of malnutrition defined by different tools were 1.99 (1.12-3.51) for GLIM criteria, 1.65 (1.06-2.58) for NRI, and 2.51 (1.31-4.79) for PNI. Conclusions. Malnutrition was common in DR patients, and it was closely linked to the presence and severity of DR. Diabetic patients with DR should undergo nutritional assessment and early treatment of malnutrition to prevent the onset or progression of DR.

Objective: This study aims to examine the clinical significance of ultrasound evaluation of the gastrocnemius muscle (GM) in identifying sarcopenia in patients with type 2 diabetes (T2D). Methods: One hundred and fifty-three patients with T2D were included in this study. We measured the appendicular skeletal muscle mass index (ASMI), handgrip strength, and 6-meter walking speed. The US-derived muscle thickness (MT), cross-sectional area (CSA), and shear wave ultrasound elastography (SWE) of GM were also measured. We assessed the correlations between clinical indicators and US features. The model for screening sarcopenia was established using stepwise logistic regression. Stepwise linear regression was used to identify a set of variables that jointly estimated ASMI. The model’s ability to identify sarcopenia and low muscle mass was assessed by receiver operating characteristic (ROC) curve analysis. Results: The prevalence of sarcopenia in this study was 24.2%. The CSA, MT and SWE values of the patients with sarcopenia were lower than those of patients without sarcopenia (all p < 0.05). ASMI was positively correlated with CSA (r = 0.56, p < 0.001) and MT (r = 0.39, p < 0.001). Handgrip strength was positively correlated with CSA (r = 0.45, p < 0.001), MT (r = 0.25, p < 0.001), and SWE (r = 0.26, p = 0.002). A diagnostic model for sarcopenia was established with a sensitivity of 81.1%, specificity of 75.0%, and an area under the curve (AUC) of 0.800. The estimated ASMI equation was developed and found to have a positive correlation with actual ASMI (r = 0.70, p < 0.001). It was also effective in diagnosing low muscle mass, with an AUC of 0.787 for males and 0.783 for females. Conclusion: Ultrasonographic assessment of the gastrocnemius muscle was found to be a useful and convenient method for detecting sarcopenia in patients with T2D.

Background. Legumain is related to carotid atherosclerotic plaques and may be a new biomarker of carotid atherosclerosis. However, the association between legumain and peripheral artery disease (PAD) of lower extremity has been less studied. This study is aimed at exploring the potential link between legumain and PAD in patients with type 2 diabetes mellitus (T2DM). Methods. A cross-sectional study was conducted on 483 hospitalized T2DM patients. The serum legumain level was measured by a sandwich enzyme-linked immunosorbent assay. PAD was evaluated by color Doppler sonography. The association between legumain and PAD was tested by logistic regression. The predictive power of legumain for PAD was evaluated with the receiver-operating-characteristic (ROC) curve. Results. Overall, 201 (41.6%) patients suffered from PAD. Patients with PAD had significantly higher serum legumain level than those without PAD [11.9 (6.3, 17.9) μg/L vs. 7.6 (3.2, 14.2) μg/L, ]. Logistic regression showed that a higher serum legumain level was independently associated with a greater risk of PAD in T2DM patients [adjusted odds ratio (aOR): 1.03; 95% confidence interval (CI): 1.01-1.06]. The area under the ROC curve was 0.634 (95% CI, 0.585 to 0.684). Conclusion. High serum legumain level was significantly correlated with an increased risk of PAD in T2DM patients.

The relationship between obesity and diabetic retinopathy (DR) remains controversial, and the relationship between sarcopenic obesity and DR is still unclear. The purpose of this study is to investigate the relationship between obesity, sarcopenic obesity, and DR in patients with type 2 diabetes mellitus (T2DM). A cross-sectional study was conducted on patients with T2DM. Obesity was assessed by body mass index (BMI), fat mass index (FMI), android fat mass, gynoid fat mass, and visceral adipose tissue (VAT) mass. Sarcopenia was defined according to the criteria of Consensus of the Asian Working Group for Sarcopenia (AWGS 2019). Sarcopenic obesity was defined as the coexistence of sarcopenia and obesity. The association between obesity, sarcopenic obesity, and DR was examined using univariable and multivariable logistic regression models. A total of 367 patients with T2DM (mean age 58.3 years; 57.6% male) were involved in this study. The prevalence of DR was 28.3%. In total patients, significant adverse relationships between obesity and DR were observed when obesity was assessed by BMI (adjusted odds ratio [aOR] 0.54, 95% confidence interval [CI] 0.31 to 0.96, p = 0.036), FMI (aOR 0.49, 95% CI 0.28 to 0.85, p = 0.012), android fat mass (aOR 0.51, 95% CI 0.29 to 0.89, p = 0.019), gynoid fat mass (aOR 0.52, 95% CI 0.30 to 0.91, p = 0.021) or VAT mass (aOR 0.45, 95% CI 0.25 to 0.78, p = 0.005). In patients with T2DM and obesity, the prevalence of sarcopenic obesity was 14.8% (n = 23) when obesity was assessed by BMI, 30.6% (n = 56) when assessed by FMI, 27.9% (n = 51) when assessed by android fat mass, 28.4% (n = 52) when assessed by gynoid fat mass, and 30.6% (n = 56) when assessed by VAT mass. Sarcopenic obesity was associated with DR when obesity was assessed by BMI (aOR 2.61, 95% CI 1.07 to 6.37, p = 0.035), android fat mass (aOR 3.27, 95% CI 1.37 to 7.80, p = 0.007), or VAT mass (aOR 2.50, 95% CI 1.06 to 5.92, p = 0.037). Patients with T2DM showed a substantial inverse relationship between DR and obesity, and sarcopenic obesity was considerably favorably associated with DR. Detection of sarcopenia in patients with T2DM, especially in obese T2DM, is essential to guide clinical intervention in DR.

Background: The association between lipoprotein(a) (Lp(a)) and sarcopenia in T2DM patients of general age is unclear, and whether this association differs by sex remains uncertain. We intend to analyze the association between Lp(a) and sarcopenia in patients with type 2 diabetes mellitus (T2DM) and whether this association differs by sex. Methods: T2DM patients between December 2021 and December 2022 were consecutively enrolled. Sarcopenia was defined according to the criteria of Consensus of the Asian Working Group for Sarcopenia (AWGS) 2019.A multivariable logistic regression model was used to calculate the odds ratio of Lp(a)≥ 30 mg/dL for sarcopenia in total T2DM patients and in all sexes. Restricted cubic splines were also used to evaluate the association between Lp(a) and sarcopenia. Results: Among the 426 patients, the mean age was 58.6 years and 56.3% were males. The prevalence of sarcopenia was 31.7% in total patients, 34.2% in male and 28.5% in female. The percentages of Lp(a)≥ 30 mg/dL were 19.0% in total patients. Compared with patients in Lp(a)< 30 mg/dL group, those in Lp(a)≥ 30 mg/dL group showed an increased risk of sarcopenia (adjusted odds ratio [aOR]: 2.19, 95% CI: 1.09 to 4.39, p = 0.027). Results from restricted cubic splines were robust. When analyzing each sex, there was also a significant association between Lp(a)≥ 30 mg/dL and sarcopenia (male: aOR: 2.59, 95% CI: 1.09 to 6.21, p = 0.032; female: aOR: 2.45, 95% CI: 1.06 to 6.03, p = 0.039). Conclusion: In T2DM patients, elevated Lp(a) was associated with an increased risk of sarcopenia and such an association did not differ by sex. Screening for sarcopenia should be emphasized in T2DM patients with Lp(a)≥ 30 mg/dL, both men and women.

Carotid artery plaque (CAP) and sarcopenia are notable complications in patients with type 2 diabetes mellitus (T2DM). This study aims to explore whether t