Blood urea nitrogen/creatinine ratio in heart failure: Systematic review and meta-analysis.

The meta-analysis is to evaluate the predictive value of the blood urea nitrogen / creatinine ratio (BCR) for long-term outcomes in patients with heart failure (HF). PubMed, EMBASE, the Cochrane library, and Web of Science were searched for relevant studies from inception to October 2023. STATA SE 14.0 software was used for statistical analysis. A total of 2036 reports were identified with 14 studies meeting pre-designed inclusion criteria. Three long-term outcomes were investigated. In patients with HF, the increase of BCR level indicated a greater risk of all-cause mortality (HR = 1.67, 95% CI 1.38-2.00; I2 = 90.8%, P = 0.000). The acute HF (AHF) subgroup demonstrated a higher risk of all-cause mortality (HR = 1.79, 95% CI 1.15-2.79; I2 = 93.9%, P = 0.000) as did the non-AHF subgroup (HR = 1.51, 95% CI 1.34-1.71; I2 = 37.1%, P = 0.122). The subgroup (≤ 70 years old) demonstrated a lower risk of all-cause mortality in patients with HF (HR = 1.62, 95% CI 1.35-1.94; I2 = 68.3%, P = 0.004) as did the subgroup (> 70 years old) (HR = 1.67, 95% CI 1.19-2.34; I2 = 88.3%, P = 0.000). In addition, this study did not support the predictive value of BCR in CVD mortality (HR = 1.48, 95% CI 0.91-2.43; I2 = 63%, P = 0.100) and HF hospitalization (HR = 1.28, 95% CI 0.73-2.24; I2 = 77.5%, P = 0.035). Sensitivity analysis showed that all the results were robust. In summary, the results showed that the blood urea nitrogen / creatinine ratio (BCR) had a significant predictive value for all-cause mortality in patients with heart failure and was a fairly promising predictor obviously. Moreover, more studies are needed to further determine the predictive value of BCR in other long-term outcomes such as CVD mortality, HF hospitalization or aborted cardiac arrest.

Improved Dynamic Window Approach for Unmanned Surface Vehicles' Local Path Planning Considering the Impact of Environmental Factors.

The aim of local path planning for unmanned surface vehicles (USVs) is to avoid unknown dynamic or static obstacles. However, current relative studies have not fully considered the impact of ocean environmental factors which significantly increase the control difficulty and collision risk of USVs. Therefore, this work studies two ocean environmental factors, namely, wave and current, given that they both have a significant impact on USVs. Furthermore, we redesign a kinematic model of an USV and the evaluation function of a classical and practical local path planning method based on the dynamic window approach (DWA). As shown by the results of the simulations, the path length was impacted mainly by the intensity of the environmental load and slightly by the direction of the environmental load, but the navigation time was significantly influenced by both. Taking the situation in still water as a benchmark in terms of the intensity and direction of the environmental factors, the maximum change rates of the path length were 8.6% and 0.6%, respectively, but the maximum change rates of the navigating time were 17.9% and 25.6%, separately. In addition, the average calculation time of each cycle was only 0.0418 s, and the longest time did not exceed the simulation time corresponding to a single cycle of 0.1 s. This method has proven to be a good candidate for real-time local path planning of USVs since it systematically considers the impact of waves and currents on the navigation of USVs, and thus ensures that USVs can adjust to the planned path in time and avoid obstacles when navigating in the real ocean environment.