Are lipid ratios less susceptible to change with systemic inflammation than individual lipid components in patients with rheumatoid arthritis?

Rheumatoid arthritis (RA) associates with excess cardiovascular risk and there is a need to assess that risk. However, individual lipid levels may be influenced by disease activity and drug use, whereas lipid ratios may be more robust. A cross-sectional cohort of 400 consecutive patients was used to establish factors that influenced individual lipid levels and lipid ratios in RA, using multiple regression models. A further longitudinal cohort of 550 patients with RA was used to confirm these findings, using generalized estimating equations. Cross-sectionally, higher C-reactive protein (CRP) levels correlated with lower levels of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol ([HDL-C] P = .015), whereas lipid ratios did not correlate with CRP. The findings were broadly replicated in the longitudinal data. In summary, the effects of inflammation on individual lipid levels may underestimate lipid-associated cardiovascular disease (CVD) risk in RA, thus lipid ratios may be more appropriate for CVD risk stratification in RA.

A fuzzy expected value approach under generalized data envelopment analysis

Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.