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At present, percutaneous nephrolithotomy has become an option for hospitals increasingly to treat calculus. However, due to the certain risk of percutaneous nephrolithotomy, it may lead to postoperative complications. Analyzing the preoperative factors of septic shock after percutaneous nephrolithotomy can provide guidance for reducing the incidence of septic shock after PCNL. This article establishes a logistic regression model based on preoperative factors, uses statistical methods, and uses the professional statistical software SPSS to create a database and analyze the data. The method of classification data analysis was used to determine various influencing factors including patient factors, stone factor, and preoperative factors and combined B-ultrasound guidance and percutaneous nephrolithotomy to reduce the risk of surgery. The experimental results found that the percutaneous nephroscope laser lithotripsy guided by the smart Internet of Things can effectively perform lithotripsy; in this paper, the preoperative data of different complications are obtained, and the risk of surgery is closely related to the operation time. The operation time exceeds 90 minutes and causes the risk of severe bleeding after PCNL. It is twice the operation time of less than 90 minutes and 5 times the operation time of less than 60 minutes. [ABSTRACT FROM AUTHOR]

Background. Evidence regarding the relationship between body mass index (BMI) and 1-year unplanned readmission was limited. Therefore, the objective of this research is to investigate whether BMI was independently related to 1-year unplanned readmission in Chinese patients with acute myocardial infarction (AMI) after percutaneous transluminal coronary intervention (PCI) after adjusting for other covariates. Methods. The present study was a cohort study. A total of 214 participants with AMI after PCI were involved in a hospital in China from 1st January 2017 to 1st January 2018. The target independent variable and the dependent variable were BMI measured at baseline and 1-year unplanned readmission, respectively. Covariates involved in this study included age, gender, TC, triglyceride, HDL-C, LDL-C, PT, APTT, INR, creatinine, HGB, LVEF, discharge medication, marital status, educational level, COPD, diabetes mellitus, heart failure, history of ischemic stroke, history of hemorrhagic stroke, arrhythmia, and hypertension. Results. The average age of 172 selected participants was 60.2 ± 10.8 years old, and about 68.6% of them was male. The rate of readmission in patients with AMI was 26.14%. The result of fully adjusted binary logistic regression showed BMI was negatively associated with risk of readmission after adjusting confounders (hazard ratio (HR) = 1.1, 95% CI 0.93–1.29). Nonlinear relationship was detected between BMI and 1-year unplanned readmission, whose point was 29.3. The effect sizes and the confidence intervals of the left and right sides of inflection point were 0.9 (0.7–1.2, P for nonlinearity = 0.530) and 2.8 (1.3–5.8, P for nonlinearity = 0.008), respectively. Conclusion. BMI has a nonlinear relationship with 1-year unplanned readmission in patients with myocardial infarction. The 1-year unplanned readmission rate of overweight patients (BMI > 29.3 kg/m2) has increased significantly. Obesity paradox does not exist in terms of readmission of Chinese patients with myocardial infarction after PCI. [ABSTRACT FROM AUTHOR]