Development and validation of a Nomogram model for predicting infection risk after totally implantable venous access ports implantation:a retrospective study
Objective:To develop and validate a Nomogram predictive model for estimating the risk of infection following the implantation of a totally implantable venous access ports(TIVAP).Methods:A retrospective analysis was conducted on 794 patients who underwent TIVAP implantation surgery at Guangzhou First People's Hospital from January 2017 to August 2022.Subjects were randomly divided into a training set(555 cases)and a validation set(239 cases)in a 7∶3 ratio.LASSO regression analysis was initially applied to identify the optimal predictive factors,which were then incorporated into a multifactorial Logistic regression to develop the Nomogram model.The predictive model's discriminative ability,accuracy,and clinical utility were assessed using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DC A).Results:Multifactorial Logistic regression analysis identified age,operation duration,hematological malignancies,and BMI as independent factors affecting infection after TIVAP implantation.Based on these factors,a Nomogram predictive model was constructed.ROC curve analysis revealed AUC values of 0.948(95％CI:0.914-0.982)and 0.935(95％CI:0.876-0.994)for the training and validation sets,respectively,indicating good discriminative ability and predictive accuracy of the model.Conclusion:The TIVAP post-implantation infection risk predictive model developed in this study has practical clinical value.It can assist clinicians in assessing patient infection risks,thus facilitating the formulation of more personalized treatment plans.
万方数据
维普
