Sarcopenia as a Little-Recognized Comorbidity of Type II Diabetes Mellitus: A Review of the Diagnosis and Treatment

Construction and evaluation of sarcopenia risk prediction model for patients with diabetes: a study based on the China health and retirement longitudinal study (CHARLS)

PURPOSE

Sarcopenia is a common complication of diabetes. Nevertheless, precise evaluation of sarcopenia risk among patients with diabetes is still a big challenge. The objective of this study was to develop a nomogram model which could serve as a practical tool to diagnose sarcopenia in patients with diabetes.

METHODS

A total of 783 participants with diabetes from China Health and Retirement Longitudinal Study (CHARLS) 2015 were included in this study. After oversampling process, 1,000 samples were randomly divided into the training set and internal validation set. To mitigate the overfitting effect caused by oversampling, data of CHARLS 2011 were utilized as the external validation set. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis were employed to explore predictors. Subsequently, a nomogram was developed based on the 9 selected predictors. The model was assessed by area under receiver operating characteristic (ROC) curves (AUC) for discrimination, calibration curves for calibration, and decision curve analysis (DCA) for clinical efficacy. In addition, machine learning models were constructed to enhance the robustness of our findings and evaluate the importance of the predictors.

RESULTS

9 factors were selected as predictors of sarcopenia for patients with diabetes. The nomogram model exhibited good discrimination in training, internal validation and external validation sets, with AUC of 0.808, 0.811 and 0.794. machine learning models revealed that age and hemoglobin were the most significant predictors. Calibration curves and DCA illustrated excellent calibration and clinical applicability of this model.

CONCLUSION

This comprehensive nomogram presented high clinical predictability, which was a promising tool to evaluate the risk of sarcopenia in patients with diabetes.

A Narrative Review of the Diagnosis and Treatment of Sarcopenia and Malnutrition in Patients with Heart Failure

The prevalence of sarcopenia (loss of muscle strength, mass and function) in individuals with heart failure (HF) stands at a considerable level (approximately 20%), contributing to heightened mortality rates and diminished quality of life. The underlying pathophysiological mechanisms involve the presence of low-grade inflammation and a disturbance of the anabolic-catabolic protein balance. The nutritional assessment of patients with HF is a key aspect, and diverse diagnostic tools are employed based on patient profiles (outpatient, inpatient and nursing home). The Global Leadership Initiative on Malnutrition (GLIM) criteria serves as a consensus for diagnosing malnutrition. Given that edema can impact body mass index (BMI) in patients with HF, alternative body assessment technical methods, such as bioelectrical vector impedance (BiVA), BIA (without vector mode), computer tomography (CT) or clinical ultrasound (US), are useful. Scientific evidence supports the efficacy of both aerobic and resistance physical exercises in ameliorating and preventing muscle wasting associated with HF. Dietary strategies emphasize the importance of protein intake, while certain micronutrients like coenzyme Q10 or intravenous iron may offer benefits. This narrative review aims to present the current understanding of the pathogenesis, diagnosis and treatment of muscle loss in individuals with heart failure and its consequential impact on prognosis.

The associations between the Geriatric Nutritional Risk Index and all-cause, cancer-specific, and cardiovascular mortality in the U.S. population: a large-scale pooled survey

BACKGROUND

Previous studies have reported a close association between the Geriatric Nutritional Risk Index (GNRI) and various conditions. However, the association between the GNRI and mortality remains unclear. To examine the correlation between the GNRI and all-cause, cancer-specific, and cardiovascular mortality, this study was performed.

METHODS

We analyzed elderly participants in the National Health and Nutrition Examination Survey from 2005 to 2016. The GNRI was calculated using body mass index and serum albumin. Kaplan-Meier survival curves were drawn to compare the survival probability between the normal and decreased GNRI groups. Weighted multivariate Cox regression and restricted cubic spline (RCS) models were employed to determine the linear and non-linear associations of the GNRI with all-cause, cancer-specific, and cardiovascular mortality.

RESULTS

A total of 3,276 participants were included in the analysis. The Kaplan-Meier survival curve showed that the decreased GNRI group had a lower survival probability for all-cause mortality and cancer-specific mortality (P < 0.001) but not for cardiovascular mortality (P > 0.05). In the full regression models, the decreased group had a higher risk of all-cause mortality (HR = 1.67, 95% CI = 1.21-2.30, P = 0.002), and cancer-specific mortality (HR = 2.20, 95% CI = 1.32-3.67, P = 0.003) than the normal group. For cardiovascular mortality, no significant association with GNRI (HR = 1.39, 95% CI = 0.60-3.22, P = 0.436) was detected. Notably, the RCS analysis identified a linear downward trend between the GNRI and all-cause, alongside cancer-specific mortalities (all P for overall < 0.05). The time-dependent Receiver Operating Characteristic (ROC) analysis unveiled the predictive power of the GNRI for 5-year all-cause mortality, cancer mortality, and cardiovascular mortality was 0.754, 0.757, and 0.836, respectively, after adjusting for covariates.

CONCLUSIONS

Individuals with a decreased GNRI had increased risks of all-cause, and cancer-specific mortality. There were linear associations of the GNRI with all-cause, and cancer-specific mortality. Nutritional status should be carefully monitored, which may improve the overall prognosis for the general population.

Unraveling the enigma of sarcopenia and sarcopenic obesity in Indian adults with type 2 diabetes - a comparative cross-sectional study

BACKGROUND

Sarcopenia and sarcopenic obesity are growing concerns associated with increasing diabetes incidence, but data from Indian diabetic cohorts are limited. This study examined the prevalence and clinical factors associated with sarcopenia and sarcopenic obesity.

METHODS

In this cross-sectional study, 750 participants aged 35-70 years were recruited by systematic stratification and a fixed quota sampling technique from medical camps and categorized into diabetic (n = 250), nondiabetic (n = 250), and obese nondiabetic (n = 250) groups. The assessments included questionnaires, muscle mass estimation by bioimpedance analysis, and blood tests. Sarcopenia was defined using the Asian Working Group consensus, and sarcopenic obesity was defined as sarcopenia with a BMI ≥ 25 kg/m2. Logistic regression was used to analyze risk factors.

RESULTS

Sarcopenia affected 60% of diabetic patients, 28% of nondiabetic patients, and 38% of nonobese nondiabetic patients (p < 0.001). The prevalence of sarcopenic obesity was 40%, 11%, and 30%, respectively (p < 0.001). Diabetes was associated with 2.3-fold greater odds (95% CI 1.1-4.7) of sarcopenia and 2.4-fold greater odds (1.1-5.0) of sarcopenic obesity after adjustment. A duration greater than 10 years, uncontrolled diabetes, age greater than 65 years, low physical activity, hypertension, and dyslipidemia also independently increased the odds.

CONCLUSION

Indian adults with type 2 diabetes have a high burden of sarcopenia and sarcopenic obesity. Early optimization of diabetes care and lifestyle changes are vital for preserving muscle health.

Albadri A, Patel H, Kadri A, Aouadi K. Identification of dual-target isoxazolidine-isatin hybrids with antidiabetic potential: Design, synthesis, in vitro and multiscale molecular modeling approaches

In the development of novel antidiabetic agents, a novel series of isoxazolidine-isatin hybrids were designed, synthesized, and evaluated as dual α-amylase and α-glucosidase inhibitors. The precise structures of the synthesized scaffolds were characterized using different spectroscopic techniques and elemental analysis. The obtained results were compared to those of the reference drug, acarbose (IC50 = 296.6 ± 0.825 μM for α-amylase & IC50 = 780.4 ± 0.346 μM for α-glucosidase). Among the title compounds, 5d exhibited impressive α-amylase and α-glucosidase inhibitory activity with IC50 values of 30.39 ± 1.52 μM and 65.1 ± 3.11 μM, respectively, followed by 5h (IC50 = 46.65 ± 2.3 μM; IC50 = 85.16 ± 4.25 μM) and 5f (IC50 = 55.71 ± 2.78 μM; IC50 = 106.77 ± 5.31 μM). Mechanistic studies revealed that the most potent derivative 5d bearing the chloro substituent attached to the oxoindolin-3-ylidene core, and acarbose, are a competitive inhibitors of α-amylase and α-glucosidase, respectively. Structure activity relationship (SAR) was examined to guide further structural optimization of the most appropriate substituent(s). Moreover, drug-likeness qualities and ADMET prediction of the most active analogue, 5d was also performed. Subsequently, 5d was subjected to molecular docking and dynamic simulation during the progression of 120 ns analysis to check the essential ligand-receptor patterns, and to estimate its stability. In silico studies were found in good agreement with the in vitro enzymatic inhibitions results. In conclusion, we demonstrated that most potent compound 5d could be exploited as dual potential inhibitor of α-amylase and α-glucosidase for possible management of diabetes.