Objectives: This study performed a prediction and risk factor analysis of diuretic resistance (DR) in patients with decompensated heart failure during hospitalization. Methods: The data of patients with decompensated heart failure treated in 2010–2018 with DR (n = 3,383) or without DR (n = 15,444) were retrospectively collected from Chinese PLA General Hospital medical records. Statistical analysis of baseline was performed on two groups of people, and the risk factor of DR was analyzed through logic regression. Six machine learning models were built accordingly, and the adjustment of model super parameters was performed by using Bayesian optimization method. Finally, the optimal algorithm was selected according to prediction efficiency. Results: The preliminary analysis of variance showed significant differences in the incidence of DR among patients with lung infection, hyperlipidemia, type 2 diabetes, and kidney disease. There were significant differences in estimated glomerular filtration rate (eGFR) (P < 0.001). In addition, some physical indicators like BMI were different, the laboratory results like mean red blood cell volume or C-reactive protein assay were also significantly different. The optimal classification model indicated that the best cutoff points for risk factors were vein carbon dioxide, 21 mmol/L and 29 mmol/L; total protein, 64 g/L; pro-brain natriuretic peptide (pro-BNP), 7,600 pg/mL; eGFR, 50 mL/(min ∙ 1.73 m 2 ); serum albumin, 33 g/L; hematocrit, 0.32% and 0.56%; red blood cell volume distribution width, 13; and age, 59 years. The optimal area under the curve was 0.9512. The ranked features derived from the model were age, abnormal sodium level, pro-BNP level, serum albumin level, D -dimer level, direct bilirubin level, and eGFR. Conclusions: The DR risk prediction model based on a gradient boosting decision tree created here identified its important risk factors. The model made very accurate predictions using simple indicators and simultaneously calculated cutoff values to help doctors predict the occurrence of DR.

A method for studying the characteristics of electromagnetic railguns exterior ballistic trajectory is present. For electromagnetic railguns high muzzle velocity and wide range,which make it cover the whole near space, an proper atmospheric environment model and an mathematical model of motion are proposed to describe the railguns exterior ballistic trajectory. By comparing the trajectory performance and velocity variation between electromagnetic railgun and conventional gun, railguns advantage in velocity and range as well as its lethality over conventional gun is testified and its potential application value is shown. Results indicate that electomagnetic railgun has the capability to intercept the missile or other type of military targets, and it is critical to get a tradeoff between mass of projectile and muzzle velocity.