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老年髋部骨折患者术后恐动症风险预测模型构建和验证
作者:谭娅1  张玲1  陈诚2  魏李芳3  罗秀4 
单位:1. 成都医学院 护理学院, 四川 成都 610500;
2. 遂宁市中心医院 疼痛科, 四川 遂宁 629000;
3. 四川大学华西医院 肾脏内科, 四川 成都 610041;
4. 成都医学院 大健康与智能工程学院, 四川 成都 610500
关键词:老年人 髋部骨折 恐动症 影响因素 列线图 预测模型 
分类号:R473
出版年·卷·期(页码):2024·52·第六期(938-945)
摘要:

目的: 构建和内部验证老年髋部骨折患者术后恐动症风险预测模型。方法: 于2022年10月至2023年8月采取便利抽样,选取四川省3家三甲医院符合标准的367例老年髋部骨折患者为研究对象,按7∶3的比例随机分为训练组(257例)和验证组(110例)。中文版恐动症评估简表用于识别恐动症患者,Logisitic回归分析用于识别影响因素及变量筛选,R软件建立恐动症风险预测模型。结果: 在训练组中,Logistic回归分析显示衰弱、疼痛、自我效能、社会支持是导致老年髋部骨折患者术后恐动症发生的独立影响因素;训练组和验证组的ROC曲线下面积分别为0.888和0.914,Youden指数确定的最佳截断值为0.760,P=0.187的校正曲线验证了模型的校正效果。决策曲线表明,当阈值概率为5%~98%时,临床获益更大。结论: 基于衰弱、疼痛、自我效能、社会支持构建老年髋部骨折患者术后恐动症风险预测模型具有良好预测能力,有助于确定恐动症的发生风险,有助于恐动症的筛查和预防。恐动症风险评分大于0.760的患者,应定期进行恐动症的监测并接受个体化的预防干预。

Objective: To construct and internally validate a predictive model for postoperative kinesiophobia in elderly patients with hip fractures. Methods: Convenience sampling was conducted from October 2022 to August 2023, and 367 elderly patients with hip fractures who met the standards from three tertiary hospitals in Sichuan Province were selected as the study subjects. They were randomly divided into a training group (257 cases) and a validation group (110 cases) in a 7∶3 ratio. The tampa scale of kinesiophobia was used to identify patients with kinesiophobia, logistic regression analysis is used to identify influencing factors and variable screening, and R software is used to establish a risk prediction model for kinesiophobia. Results: In the training group, logistic regression analysis showed that frailty, pain, self-efficacy, and social support were independent influencing factors for the occurrence of postoperative kinesiophobia in elderly patients with hip fractures; The areas under the ROC curves of the training group and the validation group were 0.888 and 0.914, respectively. The optimal cutoff value determined by the Youden index was 0.760, and the correction curve with P=0.187 validated the correction effect of the model. The decision curve indicates that clinical benefits are greater when the threshold probability is between 5% and 98%. Conclusion: The postoperative kinesiophobia risk prediction model for elderly hip fracture patients based on frailty, pain, self-efficacy, and social support has good predictive ability, which helps to determine the risk of kinesiophobia and is helpful for screening and prevention of kinesiophobia. Patients with a kinesiophobia risk score greater than 0.760 should undergo regular monitoring of kinesiophobia and receive personalized preventive interventions.

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