Health state utility values of type 2 diabetes mellitus and related complications: a systematic review and meta-regression.

BACKGROUND: This study aimed to synthesize and quantitatively examine Health State Utility Values (HSUVs) for Type 2 Diabetes Mellitus (T2DM) and its complications, providing a robust meta-regression framework for selecting appropriate HSUV estimates. METHOD: We conducted a systematic review to extract HSUVs for T2DM and its complications, encompassing various influencing factors. Relevant literature was sourced from a review spanning 2000-2020, supplemented by literature from PubMed, Embase, and the Web of Science (up to March 2024). Multivariate meta-regression was performed to evaluate the impact of measurement tools, tariffs, health status, and clinical and demographic variables on HSUVs. RESULTS: Our search yielded 118 studies, contributing 1044 HSUVs. The HSUVs for T2DM with complications varied, from 0.65 for cerebrovascular disease to 0.77 for neuropathy. The EQ-5D-3L emerged as the most frequently employed valuation method. HSUV differences across instruments were observed; 15-D had the highest (0.89), while HUI-3 had the lowest (0.70) values. Regression analysis elucidated the significant effects of instrument and tariff choice on HSUVs. Complication-related utility decrement, especially in diabetic foot, was quantified. Age <70 was linked to increased HSUVs, while longer illness duration, hypertension, overweight and obesity correlated with reduced HSUVs. CONCLUSION: Accurate HSUVs are vital for the optimization of T2DM management strategies. This study provided a comprehensive data pool for HSUVs selection, and quantified the influence of various factors on HSUVs, informing analysts and policymakers in understanding the utility variations associated with T2DM and its complications.

Modulating Catalytic Activity and Stability of Atomically Precise Gold Nanoclusters as Peroxidase Mimics via Ligand Engineering.

Metal nanoclusters (NCs), composed of a metal core and protecting ligands, show promising potentials as enzyme mimics for producing fuels, pharmaceuticals, and valuable chemicals, etc. Herein, we explore the critical role of ligands in modulating the peroxidase mimic activity and stability of Au NCs. A series of Au15(SR)13 NCs with various thiolate ligands [SR = N-acetyl-l-cysteine (NAC), 3-mercaptopropionic acid (MPA), or 3-mercapto-2-methylpropanoic acid (MMPA)] are utilized as model catalysts. It is found that Au15(NAC)13 shows higher structural stability than Au15(MMPA)13 and Au15(MPA)13 against external stimuli (e.g., pH, oxidants, and temperature) because of the intramolecular hydrogen bonds. More importantly, detailed enzymatic kinetics data show that the catalytic activity of Au15(NAC)13 is about 4.3 and 2.7 times higher than the catalytic activity of Au15(MMPA)13 and Au15(MPA)13, respectively. Density functional theory (DFT) calculations reveal that the Au atoms on the motif of Au NCs should be the active centers, whereas the superior peroxidase mimic activity of Au15(NAC)13 should originate from the emptier orbitals of Au atoms because of the electron-withdrawing effect of acetyl amino group in NAC. This work demonstrates the ligand-engineered electronic structure and functionality of atomically precise metal NCs, which afford molecular and atomic level insights for artificial enzyme design.

Cation polymer-induced aggregation of water-soluble Au(I)-thiolate complexes and their photoluminescence properties.

Au(I)-thiolate complexes are a new class of aggregation-induced emission (AIE) material. Here we demonstrate a new aggregation strategy of water-soluble Au(I)-thiolate complexes induced by cationic polymers at optimized pH values. The generated AIE shows longer wavelengths than the emission induced by other methods.