Establishment and verification of a Nomogram prediction model for poor postoperative joint functional recovery after elbow fractures
Objective To explore the influencing factors of poor joint functional recovery of elbow joint fractures after surgery and to establish and verify the Nomogram prediction model.Methods From Jun.2019 to Sep.2022,210 patients with elbow fractures in our hospital were retrospectively analyzed,in terms of gender,age,in-jury side,fracture type,AO classification,combination of vascular or nerve injuries,combination of diabetes,fracture to operation time,operation approaches,postoperative complications,and conduction of rehabilitation exercises early after surgery.According to the functional recovery of the elbow joint,patients were divided into good recovery group and poor recovery group.Logistic regression analysis was used to analyze independent influencing factors for poor postoperative elbow joint functional recovery,and based on the results a Nomogram prediction model was construc-ted,whose efficiency was further verified by the C index,receiver operating characteristic(ROC)curve and calibra-tion curve in R software.Results Among the 210 patients,48 have poor joint functional recovery(poor recovery group),accounting for 22.86％.The other 162 cases were included in the good recovery group.Compared with the good recovery group,the poor recovery group showed much higher proportions of patients with an age ≥60 years,open fractures,AO type C fractures,combined vascular injury,combined nerve injury,diabetes history,and postoper-ative complications(all P＜0.05),and less proportion of patients taking early rehabilitation exercises(P＜0.05),which were all confirmed as independent risk factors for poor functional recovery of elbow fractures after surgery by Logistic regression analysis(all P＜0.05).The ROC curve showed that for each risk factor,the area under the curve was＞0.700 and the odds ratio was＞1,indicating a good value of all the factors in predicting poor postoperative el-bow joint functional recovery.Based on the above 8 independent risk factors,the Lasso-Nomogram prediction model was established.The C-index value of the calibration curve was 0.820,and the AUC of the ROC curve training group and test group reached 0.822 and 0.701 respectively,which indicated that the Nomogram model had good discrimi-nation and prediction efficiency.Conclusion A Nomogram prediction model based on 8 independent influencing factors of elbow joint functional recovery after surgery is effective.
Elbow fracturesElbow joint functionInfluencing factorsPrediction model
万方数据
维普
