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成人心血管手术压疮高危预测模型的建立与验证 被引量:13

Development and validation of an intraoperatively acquired pressure ulcer risk prediction model for adults receiving cardiovascular surgery
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摘要 目的建立成人心血管手术患者压疮高危预测模型,并验证模型的应用效果,为减少手术压疮提供参考。方法回顾性调查成人心血管手术患者1 163例,通过Logistic回归分析确定手术压疮高危因素并建立预测模型,通过ROC曲线确定临界值;在443例成人心血管手术患者中验证模型的预测效果。结果成人心血管手术压疮风险预测模型包括术前血红蛋白、前白蛋白、血钠、血钾,术中平均体温、最低平均动脉压,以及患者吸烟频率、高血压史、年龄≥70周岁;绘制ROC曲线后得出Logit P的临界值为-1.259(曲线下面积AUC=0.751)。模型的灵敏度为0.657、特异度为0.793、误诊率和漏诊率分别为0.207和0.343。结论该模型可较好地预测成人心血管手术患者的手术压疮风险。 Objective To develop a risk prediction model for intraoperatively acquired pressure ulcer in adult patients undergoing cardiovascular surgery, and to verify the model. Methods A retrospective study was conducted on 1 163 adult patients undergoing cardiovascular surgery, and risk factors of intraoperatively acquired pressure ulcer were identified by Logistic regression analysis to develop the prediction model, then ROC curve was performed to determine the cut-off point. The model was validated in 443 patients. Results The risk prediction model included hemoglobin, prealbumin, serum sodium and potassium before surgery, mean body temperature and minimum mean arterial pressure during surgery, smoking frequency, hypertension history, and age greater than 70 years. The cut-off point of Logit P was-1.259(AUC=0.751). The sensitivity, specificity, false positive rate and false negative rate of the model were 0.657, 0.793, 0.207 and 0.343, respectively. Conclusion The model can predict intraoperative pressure ulcer development risk in adult patients undergoing cardiovascular surgery.
作者 陈沅 吴蓓雯 钱蒨健 方琼 王维 Chen Yuan;Wu Beiwen;Qian Qianjian;Fang Qiong;Wang Wei(Operating Theater,Ruijin Hospital,Medical College of Shanghai Jiaotong University,Shanghai 200025,China)
出处 《护理学杂志》 CSCD 北大核心 2019年第10期52-54,83,共4页 Journal of Nursing Science
基金 上海交通大学医学院护理科研重点项目(Jyhz1816)
关键词 心血管手术 手术压疮 高危人群 预测模型 ROC曲线 灵敏度 特异度 风险评估 cardiovascular surgery intraoperatively acquired pressure ulcer high risk population prediction model ROC curve sensitivity specificity risk assessment
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