Analysis of influencing factors for postoperative prognosis of patients with knee osteoarthritis

Objective: To analyze the influencing factors of postoperative prognosis in patients with knee osteoarthritis (KOA) and to construct and validate a Nomogram prediction model. Methods: = 78) in a ratio of 7:3 by the complete randomization method. Relevant factors influencing postoperative prognosis were screened out through univariate analysis and multivariate logistic regression analysis. A Nomogram prediction model was constructed, and the model was validated and evaluated using the concordance index (C-index), calibration curve, and decision curve analysis (DCA). Results: < 0.05). The receiver operating characteristic curves showed that in the training set and the validation set, the area under the curves of the Nomogram model for predicting poor prognosis after KOA surgery were 0.938 (95% CI: 0.871-1.000) and 0.873 (95% CI: 0.806-0.941), respectively, and the sensitivities and specificities were 0.786, 0.925 and 0.718, 0.933, respectively. The constructed Nomogram prediction model had good discrimination. The calibration curve showed good consistency, and DCA analysis indicated that the model had clinical application value. Conclusion: VAS score, ROM, time to first ambulation after surgery, CRP, erythrocyte sedimentation rate, IL-6, and knee circumference affect the postoperative prognosis of KOA. The constructed Nomogram prediction model has high accuracy and clinical application value.