基于决策树的肿瘤患者难免性压疮风险预测模型研究  

Study on risk prediction model of unavoidable pressure ulcers in cancer patients based on decision tree

作　　者：杨青[1] 王国蓉[2] 江宾[2] 张含凤[3] 卢秀英[1] Yang Qing;Wang Guorong;Jiang Bin;Zhang Hanfeng;Lu Xiuying(Anesthesia Medicine Center,Sichuan Cancer Hospital,Chengdu 610041,China)

机构地区：[1]四川省肿瘤医院麻醉医学中心,四川成都610041 [2]四川省肿瘤医院护理部,四川成都610041 [3]四川省肿瘤医院放疗科,四川成都610041

出　　处：《护理学杂志》2019年第13期4-7,共4页Journal of Nursing Science

基　　金：四川省卫生计生委科研课题(16PJ519)

摘　　要：目的评价决策树预测肿瘤患者难免性压疮风险的准确性与合理性,为压疮预防提供依据。方法收集Braden评分高风险肿瘤患者611例的临床病例资料,采用CHAID算法构建肿瘤患者难免性压疮风险预测的决策树模型,并通过ROC曲线下面积、灵敏度和特异度指标比较其与Braden评分的预测效果。结果46例发生难免性压疮,发生率为7.53%。决策树模型包含3层共11个节点,提取6条分类规则,筛选出4类高危人群,即Braden评分≤11分,翻身计划无法落实;Braden评分>11分,皮肤有现存或潜在损伤;Braden评分≤11分,翻身计划可以落实,但存在增加压疮发生风险的特殊情况;Braden评分>11分,皮肤没有现存或潜在损伤,但翻身计划无法落实。决策树模型ROC曲线下面积为0.840;决策树模型的灵敏度为0.848、特异度为0.774。结论决策树模型ROC曲线下面积、灵敏度及特异度均较好,可以用于肿瘤患者难免性压疮高危人群的筛选和管理。Objective To evaluate the accuracy and rationality of decision tree in predicting the risk of unavoidable pressure ulcers for cancer patients, and to provide reference for prevention of pressure ulcers. Methods Clinical data of 611 cancer patients with high Braden scores were collected, and the decision tree model predicting unavoidable pressure ulcers for cancer patients was constructed using the CHAID algorithm, then its prediction effect was compared with that of Braden score according to the area under the ROC curve, sensitivity and specificity. Results Totally, 46 patients (7.53%) developed unavoidable pressure ulcers. The decision tree model included three stratums and eleven nodes. Six classification rules were extracted and four high-risk populations were screened out as follows: Braden score ≤11 points, turning and repositioning plan could not be implemented;Braden score >11 points, existing or potential damage appeared in the skin;Braden score ≤11 points, turning and repositioning plan could be implemented, but special situations increasing risk of pressure ulcers existed;Braden score >11 points, there was no existed or potential damage in the skin, but the turning and repositioning plan could not be implemented. The area under the ROC curve of the decision tree model was 0.840. The sensitivity of the decision tree model was 0.848, and its specificity was 0.774. Conclusion The decision tree model enjoys good area under the ROC curve, sensitivity and specificity, making it suitable to screen and manage cancer patients at high risk of unavoidable pressure ulcers.

关 键 词：肿瘤患者 难免性压疮 BRADEN评分 决策树 预测模型 

分 类 号：R472[医药卫生—护理学]