Development And External Validation Of A Nomogram For Postoperative Prediction Of 90-day Local Complications In Patients After TKA

BackgroundTotal knee arthroplasty is one of the most successful operations for the treatment of severe end-stage knee disease.It has been identified as a safe and standard treatment,which can greatly restore the function of patients and improve their quality of life.With the rapid increase of domestic surgery demand year by year,the incidence of early postoperative local complications should not be underestimated.Each local complication after total knee arthroplasty will significantly prolong the length of stay,increase medical costs,affect the prognosis,and even lead to disability or death.Predicting and controlling local complications is very important to evaluate surgical results and improve medical quality,and nomogram is a good tool in this regard.The purpose of this study was to construct a nomogram based on preoperative and intraoperative factors to predict local complications within 90 days after total knee arthroplasty and to validate it externally.MethodsThe training set of patients who underwent total knee arthroplasty in our hospital from April 2015 to September 2018 was constructed according to the inclusion and exclusion criteria,and the data of patients who underwent total knee arthroplasty in our hospital from October 2018 to June 2020 were collected as the validating set.The preoperative and intraoperative factors related to the outcome were collected.The outcome variables included four major local complications within 90 days.LASSO regression model,single-factor and multi-factor Logistic regression analysis were used to screen predictors,establish prediction model.A nomogram was used to visualize the model.The model was validated internally by Bootstrap and tested for prospectively external validation.The discrimination,calibration and clinical practicability of the prediction model were evaluated by C index,calibration plot,area under the curve and decision curve analysis.ResultsFive significant predictors were identified and included in the nomogram,which were age-adjusted Charlson Comorbidity Index,operation time,ASA score,tourniquet time and estimated intraoperative blood loss.The model has a good discrimination,with the C index 0.806（95%confidence interval is 0.713-0.900）,and the area under the curve 0.806.The calibration plot shows that the nomogram prediction is in good agreement with the actual observation results.The high C index of 0.780 can still be achieved in the internal verification of Bootstrap.The application of nomogram in the external validation still shows good discrimination（C index,0.773[95%CI 0.6430.903]）and good calibration.The decision curve analysis shows that when the threshold probability is in the range of 2%to 100%,the nomogram is clinically useful.ConclusionWe developed and validated a new nomogram,which can provide individualized prediction of local complications within 90 days after total knee arthroplasty.The verification results show that our model has high differentiation and university accuracy,and its performance is good.This practical tool can help clinicians to make clinical decisions.