BackgroundThe risk of all-cause mortality in patients with heart failure (HF) has been studied previously. Readmission risk of HF patients was rarely explored. Thus, we aimed to explore early warning factors that may influence short-term readmission of HF patients.MethodsThe data of this study came from an HF database in China. It was a retrospective single-center observational study that collected characteristic data on Chinese HF patients by integrating electronic medical records and follow-up outcome data. Eventually, 1,727 patients with HF were finally included in our study.ResultsIn our study, the proportion of HF patients with New York Heart Association (NYHA) class II, III, and IV HF were 17.20%, 52.69%, and 30.11%, respectively. The proportion of patients with readmission within 6 months and readmission within 3 months was 38.33% and 24.20%, respectively. Multivariate logistic regression showed that NYHA class (pIII = 0.028, pIV < 0.001), diabetes (p = 0.002), Cr (p = 0.003), and RDW-SD (p = 0.039) were risk factors for readmission within 6 months of HF patients. NYHA class (pIII = 0.038, pIV < 0.001), CCI (p = 0.033), Cr (p = 0.012), UA (p = 0.042), and Na (p = 0.026) were risk factors for readmission within 3 months of HF patients.ConclusionsOur study implied risk factors of short-term readmission risk in patients with HF, which may provide policy guidance for the prognosis of patients with HF.

The State Grid has proposed to construct a strong smart grid to solve the resource scarcity, environmental pollution and other social problems, which will certainly drive the development of green energy, such as wind energy, solar energy, tidal energy and biomass energy. The study will build a Green Power System Assessment Model (GPSAM) using multivariate statistical analysis to optimize the energy resources of a region and finally to provide reference for the construction of a new plant or the plant expansion to get the balance of environment benefit, economic benefit and social benefit.

BackgroundPrevious studies have shown that estrogen, kidney function, and homocysteine (Hcy) or hyperhomocysteinemia (HHcy) are related to each other. However, the underlying biological mechanisms still remain unclear. We aimed to explore the association between estradiol (E2) and HHcy in the female population, and to further evaluate the mediating role of renal function indicators.MethodsThis unmatched case–control study consisted of 1,044 female participants who were 60.60 ± 12.46 years old. Data on general demographic characteristics, such as age, smoking and drinking status, menopause and so on were collected in a personal interview, and laboratory examinations were performed by well-trained personnel. The mediating effect model was applied to analyze the direct and indirect effects of E2 on Hcy.ResultsThe average levels of Hcy and E2 of the participants were 12.6 μmol/L and 14.95 pg/ml. There were statistical differences in renal indexes blood urea nitrogen (BUN), serum creatinine (Scr), uric acid (UA), glomerular filtration rate (GFR) and E2 between HHcy group and non-HHcy group. The logistic regression models showed that UA was risk factor for HHcy (P <0.001), GFR and E2 were protective factors for HHcy after adjusting for confounding factors (P <0.001). The indirect effects of E2 on Hcy through UA and GFR accounted for 14.63 and 18.29% of the total impacts of E2 on Hcy.ConclusionsThese data indicated that E2 was a protective factor of HHcy, and the effects of E2 on HHcy may be mediated by renal function indicators UA and GFR.