Affiliation:
1. Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine
Abstract
Abstract
To investigate the predictive value of the decision tree model for the recovery of femoral neck fractures after hip arthroplasty in elderly patients. A total of 206 elderly patients with femoral neck fractures who received surgeries in our hospital from January 2019 to June 2020 were recruited as subjects. Six months after the operation, they were divided into a good recovery group (Harris score ≥ 70) and a poor recovery group (Harris score < 70) according to the Harris Hip Score. General data, surgical conditions, and postoperative conditions were observed in the two groups. Python language was utilized to construct the decision tree model for postoperative recovery predictions in elderly patients with femoral neck fractures and its performance was verified. After 6 months of follow-up, 3 cases were excluded and 203 cases were finally included. Among them, 158 cases in the good recovery group accounted for 77.83% and 45 cases in the poor recovery group accounted for 22.17%. There were significant differences in age, Charlson comorbidity index, Mini-Mental State Examination score, MNA-SF, FI-CGA score, postoperative weight-bearing time, and social support rating scale score between the two groups (P < 0.05). There was no significant difference in sex and fracture site between the two groups (P > 0.05). Decision tree analysis exhibited that the MNA-SF score was an important factor affecting the postoperative recovery of hip fractures. The best parameters obtained were used for internal verification of the included subjects, and the results demonstrated that the accuracy rate of the model was 88.18%; the sensitivity was 93.33%; the specificity was 86.71%; the positive predictive value was 66.67%; the negative predictive value was 97.86%. The construction of the decision tree model can better exhibit the factors affecting the postoperative recovery of elderly patients with femoral neck fractures, and nutritional status is the most important factor affecting postoperative recovery.
Publisher
Research Square Platform LLC
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