Construction and validation of a prognostic nomogram for patients with chronic limb-threatening ischemia based on WIfI classification
Objective To develop and validate a wound-ischemia-foot infection(WIfI)-based nomogram for predicting amputation-free survival(AFS)in patients with chronic limb-threaten-ing ischemia(CLTI)after endovascular treatment within 1 year.Methods A total of 223 CLTI patients who underwent lower extremity endovascular treatment at our hospital between January 2017and January 2023 were included.The dataset was randomly divided into a training set(156 cases)and a validation set(67 cases).The positvive outcome was AFS(161 cases,72.2%).Logistic regression analysis was performed on the training set to identify significant variables associated with AFS,including WIfI grading variables.Subsequently,a binary logis-tic regression model incorporating these variables was constructed and visualized as a nomo-gram.Discrimination,calibration,and clinical applicability of the model were evaluated using receiver operating characteristic(ROC)curve analysis,Hosmer-Lemeshow test(H-L test),cal-ibration curve analysis,and decision curve analysis(DCA),respectively.The net reclassifica-tion improvement index(NRI)and the integrated discrimination improvement(IDI)were calcu-lated to compare the prediction performance of the newly developed model and the WIfI classifi-cation model.Results Gender,fasting blood glucose level,estimated glomerular filtration rate(eGFR),WIfI classification score,and wound etiology were identified as independent fac-tors influencing AFS in CLTI patients within one year after endovascular treatment.Based on these variables,we developed a nomogram that demonstrated good predictive performance in both the training set area under curve(AUC)=0.902[95%CI(0.8 514,0.9 531)],and the validation cohort AUC=0.856[95%CI(0.7 586,0.9 542)].H-L tests indicated satisfactory goodness-of-fit for both sets(training set χ2 value=7.6 399;P=0.4 694;validation set χ2 value=9.2 647;P=0.3 205),while calibration curves confirmed excellent agreement be-tween predicted probabilities from the model and observed outcomes in both sets.The DCA curve demonstrated that the model exhibits substantial clinical net benefits when the threshold probability exceeds 0.25.The two models indicated that with a binary NRI cut value of 0.64,the NRI(classification variable)=0.1 876[95%CI(0.0 904,0.2 849)],with P<0.001.The IDI=0.1 765[95%CI(0.1 226,0.2 303)],with P<0.001.Conclusion The newly developed WIfI-based nomogram model and the original WIfI risk classification model demon-strate superior discrimination,calibration,and clinical applicability in predicting AFS within one year after endovascular treatment of patients with chronic limb-threatening ischemia(CLTI).In contrast,the new model exhibits enhanced accuracy and predictive ability com-pared with the old model,thereby holding potential for clinical implementation in personalized diagnosis and treatment.
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