Hemodialysis(HD)is a crucial renal replacement therapy for patients with end-stage renal disease.Despite improvements in dialysis technology,mortality for maintenance HD(MHD)patients remains high.To improve the qualit...Hemodialysis(HD)is a crucial renal replacement therapy for patients with end-stage renal disease.Despite improvements in dialysis technology,mortality for maintenance HD(MHD)patients remains high.To improve the quality of life among MHD patients,it is necessary to examine the risk factors associated with mortality.In this study,we retrospectively analyzed patients5 conditions at the beginning of dialysis and assessed the risk factors for mortality in MHD patients treated at the Center for Hemodialysis in West China Hospital,Sichuan University,China.The aim of this study was to identify significant risk factors to guide the treatment of MHD patients and targeted early preventions to improve prognosis.展开更多
To the editor： Patients undergoing maintenance hemodialysis （MHD） are more vulnerable to nosocomial infection, with less ability to combat the infection and a greater susceptibility to contaminants in the dialysis ...To the editor： Patients undergoing maintenance hemodialysis （MHD） are more vulnerable to nosocomial infection, with less ability to combat the infection and a greater susceptibility to contaminants in the dialysis environment.展开更多
This study aimed to find out the blood data characteristics of patients and explore the correlation between severe preeclampsia and blood index value.Provide assistance for the early attention direction of severe pree...This study aimed to find out the blood data characteristics of patients and explore the correlation between severe preeclampsia and blood index value.Provide assistance for the early attention direction of severe preeclampsia diagnosis and treatment.19,653 pregnant women presenting to the West China Second University Hospital,Sichuan University from January 2017 to April 2019.After screening,a total of 248 patients,124 severe preeclampsia cases,and 124 controls were selected for this study.Forty-three blood examination variables were obtained from routine blood work,hepatic,renal and coagulation function examination.Light gradient boosting machine(light GBM),decision tree and random forest were used for date diving.We randomly divided 35%of the original data as a testing set to conduct internal validation of the performance of the prediction model.The area under receiver operating characteristic curve(AUC)was used as the main score to compare the three methods.Finally,a binary classification light GBM model based on aspartate aminotransferase,direct bilirubin and activated partial thromboplastin time ratio can predict severe preeclampsia with sensitivity of 88.37%,specificity of 77.27%,AUC of 89.74%and positive predictive value of 65.96%.We believe relevant quantifiable indicators can establish an effective prediction model,which can provide guidance for early detection and prevention of severe preeclampsia.展开更多
基金supported by a grant of Sichuan Medical Association Scientific Research Project(No.2017SHD001).
文摘Hemodialysis(HD)is a crucial renal replacement therapy for patients with end-stage renal disease.Despite improvements in dialysis technology,mortality for maintenance HD(MHD)patients remains high.To improve the quality of life among MHD patients,it is necessary to examine the risk factors associated with mortality.In this study,we retrospectively analyzed patients5 conditions at the beginning of dialysis and assessed the risk factors for mortality in MHD patients treated at the Center for Hemodialysis in West China Hospital,Sichuan University,China.The aim of this study was to identify significant risk factors to guide the treatment of MHD patients and targeted early preventions to improve prognosis.
文摘To the editor： Patients undergoing maintenance hemodialysis （MHD） are more vulnerable to nosocomial infection, with less ability to combat the infection and a greater susceptibility to contaminants in the dialysis environment.
基金National Key R&D Program of China(2018YFC2001800).
文摘This study aimed to find out the blood data characteristics of patients and explore the correlation between severe preeclampsia and blood index value.Provide assistance for the early attention direction of severe preeclampsia diagnosis and treatment.19,653 pregnant women presenting to the West China Second University Hospital,Sichuan University from January 2017 to April 2019.After screening,a total of 248 patients,124 severe preeclampsia cases,and 124 controls were selected for this study.Forty-three blood examination variables were obtained from routine blood work,hepatic,renal and coagulation function examination.Light gradient boosting machine(light GBM),decision tree and random forest were used for date diving.We randomly divided 35%of the original data as a testing set to conduct internal validation of the performance of the prediction model.The area under receiver operating characteristic curve(AUC)was used as the main score to compare the three methods.Finally,a binary classification light GBM model based on aspartate aminotransferase,direct bilirubin and activated partial thromboplastin time ratio can predict severe preeclampsia with sensitivity of 88.37%,specificity of 77.27%,AUC of 89.74%and positive predictive value of 65.96%.We believe relevant quantifiable indicators can establish an effective prediction model,which can provide guidance for early detection and prevention of severe preeclampsia.
