Construction and Validation of the Prediction Model of Urinary System Infection in Patients with Chronic Renal Failure and Maintenance Hemodialysis
Objective To investigate the contributing variables of urinary tract infection in individuals suf-fering from chronic kidney failure and undergoing maintenance hemodialysis,and to develop and verify a risk prediction model.Methods Retrospectively,360 chronic renal failure patients who received MHD in our hospital between January 2021 and 2023 were selected.3 out of 10 subjects were put into the validation set(n=108)and 7 into the modelling set(n=252).The latter were further divided into the infected group(n=37)and non-infected group(n=215)based on whether they had had urinary system infection.Data from the two groups were compared and examined to make a risk prediction model.The ROC curve,deci-sion curve,and internal validation calibration curve in Bootstrap method's were drawn to assess the predic-tion effectiveness of the model,and the case data of the validation set were also analyzed concurrently so as to externally validate the model.Results In MHD patients with chronic renal failure,urinary system infec-tion was related to age,dialysis time,urinary tract intubation,diabetic nephropathy,hypertensive nephropa-thy,and serum albumin(P＜0.05),according to univariate and multivariate logistic regression analysis.The area under the ROC was 0.880,95％CI(0.820～0.940),with the values for the Youden index 0.640,scale of sensitivity and specificity 91.9％and 72.1％,respectively.The decision curve showed the substantial potential clinical benefit and availability of the model.The mean absolute deviation of the internal validation calibration curve in Bootstrap method was 0.894,95％CI(0.817～0.970),with the values for the Youden index as 0.623,scale of sensitivity and specificity 93.8％and 68.5％,respectively.The calibration curve was 0.042,which suggested that the model performed well in terms of external prediction.Conclusions Age,length of dialysis,urinary tract intubation,and other variables all influence the risk of urinary system infection in MHD patients with chronic renal failure.The risk prediction model based on each independent risk factor performs well in terms of prediction,and can offer nursing guidance for the prevention of urina-ry tract infection in these patients.
chronic renal failuremaintenance hemodialysisurinary system infectionrisk factorprediction
万方数据
维普
