全膝关节置换术后切口愈合不良预测模型的建立与验证
Establishment and Validation of a Model for Predicting Poor Wound Healing after Total Knee Arthroplasty
DOI: 10.12677/jcpm.2025.43377, PDF,   
作者: 周德威*:济宁医学院临床医学院,山东 济宁;李梁涛#:济宁医学院附属医院关节与运动医学科,山东 济宁
关键词: 切口愈合不良并发症列线图预测模型危险因素全膝关节置换术骨性关节炎Poor Wound Healing Complications Nomogram Prediction Model Risk Factors Total Knee Arthroplasty Osteoarthritis
摘要: 目的:分析全膝关节置换(Total knee arthroplasty, TKA)患者术后发生切口愈合不良(Poor wound healing, PWH)的危险因素,建立并验证列线图预测模型。方法:回顾性分析2022年6月至2024年6月于济宁医学院附属医院关节与运动医学科接受TKA治疗的1055例患者的病历资料,按照7:3随机分为实验组(n = 738,其中PWH患者38例,正常患者700例)与验证组(n = 317,其中PWH患者17例,正常患者300例)。收集实验组与验证组患者围手术期的一般资料,对TKA患者术后PWH进行单因素及多因素分析,建立并验证TKA患者术后PWH列线图预测模型。结果:实验组单因素分析结果表明,PWH患者合并2型糖尿病占比、合并高脂血症占比、合并类风湿性关节炎占比、手术时间、术中出血量 ≥ 100 ml占比、引流管放置时间 ≥ 48 h占比、住院时间 ≥ 10天占比高于正常患者,术前血红蛋白水平、术前白蛋白水平低于正常患者,差异有统计学意义(P < 0.05);多因素分析结果表明,手术时间延长以及合并2型糖尿病、合并高脂血症为增加TKA术后PWH的危险因素,术前高水平血红蛋白以及白蛋白为减少TKA术后PWH的保护因素(P < 0.05)。实验组ROC结果显示:AUC为0.885 (95%CI: 0.805~0.911);验证组ROC结果显示:AUC为0.907 (95%CI: 0.857~0.871)。实验组与验证组校准曲线均显示与参考曲线走行一致性良好。经决策曲线评估,实验组与验证组均有较好的临床收益。结论:经分析,合并2型糖尿病、合并高脂血症、手术时间延长为增加PWH发生的危险因素,术前血红蛋白高水平、术前白蛋白高水平为减少PWH发生的保护因素。基于以上危险因素及保护因素构建的列线图预测模型能够有效地评估TKA患者术后发生PWH的风险,且经决策曲线评估有较好的临床收益。
Abstract: Objective: To analyze the risk factors for poor incision healing in patients after total knee arthroplasty and to establish and validate a nomogram prediction model. Methods: We retrospectively reviewed the medical records of 1055 patients undergoing TKA procedures in the Department of Joint and Sports Medicine, Jining Medical University Affiliated Hospital from June 2022 to June 2024, these patients were randomly divided into the experimental group (n = 738, including 38 PWH patients and 700 normal patients) and the validation group (n = 317, including 17 PWH patients and 300 normal patients) in a 7:3 ratio. Collect the general data of patients in the experimental group and the validation group during the perioperative period. Conduct univariate and multivariate analyses on the poor wound healing after total knee arthroplasty. Establish and validate the nomogram prediction model for poor wound healing after total knee arthroplasty in patients. Results: The results of univariate analysis in the experimental group indicated that the proportions of PWH patients with type 2 diabetes, hyperlipidemia, rheumatoid arthritis, operation time, intraoperative blood loss ≥ 100 ml, drainage tube placement time ≥ 48 h, and hospital stay ≥ 10 days were higher than those of normal patients, while the preoperative hemoglobin level and preoperative albumin level were lower than those of normal patients, and the differences were statistically significant (P < 0.05). The results of multivariate analysis indicated that prolonged operation time and the coexistence of type 2 diabetes and hyperlipidemia were risk factors for poor wound healing after total knee arthroplasty, while preoperative high levels of hemoglobin and albumin were protective factors (P < 0.05). The ROC results of the experimental group showed that the AUC was 0.885 (95%CI: 0.805~0.911); the ROC results of the validation group showed that the AUC was 0.907 (95%CI: 0.857~0.871). The calibration curves of the experimental group and the validation group both showed good consistency with the reference curve. Based on the evaluation by the decision curve, both the experimental group and the validation group showed good clinical benefits. Conclusion: For total knee arthroplasty, the predictors of PWH are prolonged surgical duration, Type 2 diabetes mellitus and hyperlipidemia. Preoperatively high-level hemoglobin and albumin levels can be used to predict the protective effects of PWH in total knee arthroplasty. The nomogram prediction model constructed based on the above risk factors and protective factors can effectively assess the risk of PWH in patients undergoing TKA, and it has been evaluated by the decision curve and shown to have relatively good clinical benefits.
文章引用:周德威, 李梁涛. 全膝关节置换术后切口愈合不良预测模型的建立与验证[J]. 临床个性化医学, 2025, 4(3): 520-533. https://doi.org/10.12677/jcpm.2025.43377

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