Influencing factors and predictive models of volume overload in maintenance hemodialysis patients
Objective To develop and validate a predictive model for volume overload in patients undergoing maintenance hemodialysis.Methods We conducted a retrospective analysis of 126 patients receiving maintenance hemodialysis at Rugao Traditional Chinese Medicine Hospital from June 2023 to September 2023.Patients were randomly divided into a training set(n=101)and a validation set(n=25)in an 8:2 ratio.Patients with an overload of water(OH)value>2.5 L after one month of maintenance hemodialysis were categorized into the volume overload group,while others were placed in the non-volume overload group.Influencing factors for volume overload in maintenance hemodialysis patients were analyzed,and a predictive model was constructed and validated along with an assessment of its predictive performance.Results The training set included 49 patients with volume overload,and the validation set included 13 patients with volume overload.Multivariate logistic regression analysis indicated that serum albumin(OR=3.564,95%CI:1.467～8.662),residual renal function(OR=5.212,95%CI:2.145～12.667),and dialysis vintage(OR=3.644,95%CI:1.499～8.855)were significant predictors of volume overload in maintenance hemodialysis patients(P<0.05).A nomogram prediction model was established using these predictors,with total scores ranging from 77 to 256,corresponding to risk rates from 0.09 to 0.53.Internal validation of the nomogram model showed a C-index of 0.801(95%CI:0.749～0.819),and the calibration curve was close to the ideal(P>0.05).The receiver operating characteristic(ROC)curve analysis for the training set demonstrated that the sensitivity and specificity of the nomogram model for predicting volume overload were 71.43%and 88.46%,respectively,with an area under the curve(AUC)of 0.851(95%CI:0.769～0.928).The ROC curve analysis for the validation set showed that the sensitivity,specificity,and AUC of the nomogram model for predicting volume overload were 76.92%,83.33%,and 0.867(95%CI:0.781～0.923),respectively.Conclusion Serum albumin,residual renal function,and dialysis vintage are influential factors for volume overload in patients undergoing maintenance hemodialysis.The risk prediction model built on these factors has good predictive efficacy for volume overload risk in this patient population.
Maintenance hemodialysisCapacity overloadInfluencing factorsPrediction model
万方数据
维普
